diff --git a/docs/lattice_gauge/lattice_gauge.ipynb b/docs/lattice_gauge/lattice_gauge.ipynb
new file mode 100644
index 00000000..28b4c89a
--- /dev/null
+++ b/docs/lattice_gauge/lattice_gauge.ipynb
@@ -0,0 +1,1901 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "213b4271",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path\n",
+    "sys.path.append('/Users/tylerac/Documents/VS_Code_Projects/ReCirq Stuff/ReCirq')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f81ba0e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['/Library/Frameworks/Python.framework/Versions/3.11/lib/python311.zip',\n",
+       " '/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11',\n",
+       " '/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/lib-dynload',\n",
+       " '',\n",
+       " '/Users/tylerac/Documents/VS_Code_Projects/ReCirq Stuff/.venv/lib/python3.11/site-packages',\n",
+       " '/Users/tylerac/Documents/VS_Code_Projects/ReCirq Stuff',\n",
+       " '/Users/tylerac/Documents/VS_Code_Projects/ReCirq Stuff/',\n",
+       " '/Users/tylerac/Documents/VS_Code_Projects/ReCirq Stuff/ReCirq']"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sys.path"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6af072a8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cirq\n",
+    "from matplotlib.colors import LinearSegmentedColormap#, ListedColormap\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib\n",
+    "from matplotlib import ticker\n",
+    "import numpy as np\n",
+    "from matplotlib import colormaps\n",
+    "import qsimcirq\n",
+    "from scipy.optimize import minimize_scalar\n",
+    "import sympy\n",
+    "\n",
+    "import recirq.lattice_gauge.lattice_gauge_experiment as lgt\n",
+    "from recirq.lattice_gauge.lattice_gauge_grid import LGTGrid\n",
+    "import recirq.toric_code.toric_code_plotter as tc_plot\n",
+    "import recirq.toric_code.toric_code_plaquettes as tc_plaq\n",
+    "import recirq.toric_code.toric_code_rectangle as tcr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6cbbedb7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Notebook Parameters\n",
+    "\n",
+    "reps = 1_000\n",
+    "\n",
+    "number_of_gauge_qubits = 17\n",
+    "\n",
+    "plt.rcParams['figure.dpi'] = 72\n",
+    "plt.rcParams['font.size'] = 12\n",
+    "plt.rcParams['lines.markersize'] = 8\n",
+    "plt.rcParams['lines.markeredgecolor'] = 'k'\n",
+    "plt.rcParams['lines.markeredgewidth'] = 0.7\n",
+    "plt.rcParams['xtick.direction'] = 'in'\n",
+    "plt.rcParams['ytick.direction'] = 'in'\n",
+    "plt.rcParams['xtick.bottom'] = True\n",
+    "plt.rcParams['xtick.top'] = True\n",
+    "plt.rcParams['ytick.left'] = True\n",
+    "plt.rcParams['ytick.right'] = True\n",
+    "plt.rcParams['xtick.labelbottom'] = True\n",
+    "plt.rcParams['ytick.labelleft'] = True\n",
+    "\n",
+    "WALA_INITIAL = np.array([0, 0.35746251, 0.14352941, 1])\n",
+    "TORIC_INITIAL = 'steelblue'\n",
+    "POLARIZED_INITIAL = \"#fbbc04\"\n",
+    "BREAKING_BOTTOM = '#67cd85ff'\n",
+    "BREAKING_TOP = '#e6a304ff'\n",
+    "BREAKING_VAC = 'k'\n",
+    "\n",
+    "cmap1 = LinearSegmentedColormap.from_list(\"1\", ['darkred', 'salmon'],gamma=1.0)\n",
+    "cmap2 = LinearSegmentedColormap.from_list(\"2\", ['salmon','lightgrey'],gamma=1.0)\n",
+    "cmap3 = LinearSegmentedColormap.from_list(\"3\", ['lightgrey','lightsteelblue'],gamma=1.0)\n",
+    "cmap4 = LinearSegmentedColormap.from_list(\"4\", ['lightsteelblue','steelblue'],gamma=1.0)\n",
+    "color_list = [cmap1(i) for i in np.arange(0,1,1/375)]+ [cmap2(i) for i in np.arange(0,1,1/250)]  + [cmap3(i) for i in np.arange(0,1,1/30)] + [cmap4(i) for i in np.arange(0,1,1/95)]\n",
+    "charge_cmap = LinearSegmentedColormap.from_list(\"Charge\", color_list,gamma=1)\n",
+    "charge_cmap_r = LinearSegmentedColormap.from_list(\"Charge_r\", color_list[::-1],gamma=1)\n",
+    "\n",
+    "he_list = [0,0.3,0.6,0.8,2.0]\n",
+    "blues_cmap = matplotlib.colors.LinearSegmentedColormap.from_list(\n",
+    "    \"Blues\", [(0.0,'k'),(0.5,'steelblue'), (1.0,(0.9*0.6901960784313725, 0.9*0.7686274509803922, 1.0*0.8705882352941177, 1.0))]\n",
+    ")\n",
+    "blues_cmap_r = matplotlib.colors.LinearSegmentedColormap.from_list(\n",
+    "    \"Blues_r\", [(1.0,'k'),(0.5,'steelblue'), (0.0,(0.9*0.6901960784313725, 0.9*0.7686274509803922, 1.0*0.8705882352941177, 1.0))][::-1]\n",
+    ")\n",
+    "blues_color_list = [blues_cmap(i) for i in np.arange(1,-0.01,-1/(max(len(he_list)-1,1)))]\n",
+    "\n",
+    "colors_greens1 = ['white', '#009468ff']\n",
+    "colors_greens2 = [\"#bdc1c6\",'#009468ff']\n",
+    "colors_greens3 = ['#009468ff','black']\n",
+    "cmap_greens1 = LinearSegmentedColormap.from_list(\"1\", colors_greens1,gamma=3.5)\n",
+    "cmap_greens2 = LinearSegmentedColormap.from_list(\"mycmap\", colors_greens3,gamma=0.8)\n",
+    "color_list = ([cmap_greens1(i) for i in np.arange(0,1,1/10240)] + [cmap_greens2(i) for i in np.arange(0,1,1/12500)])\n",
+    "cmap_green = LinearSegmentedColormap.from_list(\"mycmap\", color_list,gamma=1)\n",
+    "cmap_green_r = LinearSegmentedColormap.from_list(\"mycmap\", color_list[::-1],gamma=1)\n",
+    "\n",
+    "colors = ['darkred', 'salmon']\n",
+    "cmap1 = LinearSegmentedColormap.from_list(\"mycmap\", colors,gamma=4.0)\n",
+    "colors = ['salmon','lightgrey']\n",
+    "cmap2 = LinearSegmentedColormap.from_list(\"mycmap\", colors,gamma=1.0)\n",
+    "colors = ['lightgrey','lightsteelblue']\n",
+    "cmap3 = LinearSegmentedColormap.from_list(\"mycmap\", colors,gamma=1.0)\n",
+    "colors = ['lightsteelblue','steelblue']\n",
+    "cmap4 = LinearSegmentedColormap.from_list(\"mycmap\", colors,gamma=0.5)\n",
+    "color_list = [cmap1(i) for i in np.arange(0,1,1/1500)]+ [cmap2(i) for i in np.arange(0,1,1/300)]  + [cmap3(i) for i in np.arange(0,1,1/300)] + [cmap4(i) for i in np.arange(0,1,1/1500)]\n",
+    "diff_cmap = LinearSegmentedColormap.from_list(\"mycmap\", color_list,gamma=1)\n",
+    "diff_cmap_r = LinearSegmentedColormap.from_list(\"mycmap\", color_list[::-1],gamma=1)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "bbc3fd0a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Notebook Functions\n",
+    "\n",
+    "def mean_field_energy(theta, Lx=5, Ly=5, Je=1., Jm=1., he=0.0):\n",
+    "    energy = - Je * Lx * Ly\\\n",
+    "             - Jm * (Lx-1) * (Ly-1) * np.sin(theta)\\\n",
+    "             - he * (2 * (Lx-1) + 2 * (Ly-1)) * np.cos(theta)\\\n",
+    "             - he * (2 * Lx * Ly - 3 * Lx - 3 * Ly + 4) * np.cos(theta)**2\n",
+    "    return energy\n",
+    "\n",
+    "def bitstring_to_expectation_value(\n",
+    "        bitstrings:np.ndarray\n",
+    ")->np.ndarray:\n",
+    "    return -2 * bitstrings + 1\n",
+    "\n",
+    "def energy_from_measurements(\n",
+    "        hamiltonian_coefs:dict,\n",
+    "        z_basis_results:np.ndarray,\n",
+    "        x_basis_results:np.ndarray\n",
+    ") -> float:\n",
+    "    return (-hamiltonian_coefs['Je'] * np.sum(np.mean(bitstring_to_expectation_value(lgt.plaquette_bitstrings(z_basis_results,grid)),axis=0))\n",
+    "            -hamiltonian_coefs['Jm'] * np.sum(np.mean(bitstring_to_expectation_value(lgt.x_plaquette_bitstrings(x_basis_results,grid)),axis=0))\n",
+    "            -hamiltonian_coefs['he'] * np.sum(np.mean(bitstring_to_expectation_value(z_basis_results),axis=0))\n",
+    "            -hamiltonian_coefs['lambda'] * np.sum(np.mean(bitstring_to_expectation_value(x_basis_results),axis=0))\n",
+    "            )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4110f55",
+   "metadata": {},
+   "source": [
+    "### Motivation and background\n",
+    "\n",
+    "This ReCirq tutorial is based on experiments done on Google's quantum processor, the results of which can be found on [arXiv](https://arxiv.org/abs/2409.17142).\n",
+    "\n",
+    "Gauge theories are a fundamental way to describe nature. From the quantum description of electromagnetic phenomena (dubbed quantum electrodynamics) to the theories that explain the fundamental particles explored at the Large Hadron Collider in Switzerland, gauge theories are ubiquitous throughout physics. While studies of gauge theories began analytically (pen and paper), soon the continuous theories were discretized and physicists began studying \"lattice gauge theories,\" which are advantageous for numerical simulations. However, certain lattice gauge theories have proven intractable for classical computers because of the exponential cost to simulate larger systems. This provides a unique opportunity for today's emerging quantum computers to simulate results beyond the capabilities of classical processors. Along those lines, researchers have used superconducting qubits, arrays of neutral atoms, and trapped ions to simulate one dimensional lattice gauge theories. These experiments have shown the ability for quantum processors to capture the expected behavior in small, spatially limited systems. In our work, we extend the state-of-the-art by pushing the quantum simulation of gauge theories to two spatial dimensions. Specifically, we study the dynamics of a 2D grid of superconducting qubits under a Trotterized time evolution described by a $\\mathbb{Z}_2$ lattice gauge theory with Hamiltonian:\n",
+    "\n",
+    "$$\\mathcal{H}=-J_E\\sum_{v}\\hspace{-0.6mm}A_v -J_M\\sum_{p} \\hspace{-0.6mm}B_p-h_E\\sum_{\\text{links}}\\hspace{-0.6mm}Z_l-\\lambda\\sum_{\\text{links}}\\hspace{-0.6mm}X_l$$\n",
+    "\n",
+    "$$A_v=\\prod_{i \\in v} Z_i$$\n",
+    "\n",
+    "$$B_p=\\prod_{i \\in p} X_i.$$\n",
+    "\n",
+    "As depicted in the schematic below, the $A_v$ operators correspond to electric \"charges\" that can exist on a vertex $v$. The $B_p$ operators correspond to magnetic excitations, that are defined on the dual lattice of plaquettes, indexed by $p$. The $h_E$ term represents the energy associated with the \"electric field\", while $\\lambda$ controls the coupling between electric charges."
+   ]
+  },
+  {
+   "attachments": {
+    "image-2.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "aebd7ee0",
+   "metadata": {},
+   "source": [
+    "![image-2.png](attachment:image-2.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b2a074d",
+   "metadata": {},
+   "source": [
+    "After first preparing a low energy state, we excite the system by pair-creating charges connected by a string of gauge flux. Based on the value of $h_E$, the theory will be in a confined or a deconfined regime. We see this transition by tracking the Hamiltonian evolution of charges and the average separation of an initialized pair. Then we turn to exploring the dynamics of a string of gauge flux connecting two charges that are \"pinned\" to the boundary of the grid. The string displays behavior that shows the transition from a deconfined, to a weakly and finally to a strongly confined regime as $h_E$ is increased. Finally, by initiating a string across the grid, but then measuring the pair-creation of additional charges, we observe evidence of string breaking in the confined regime as the coupling parameter, $\\lambda$, is tuned."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "629aac46",
+   "metadata": {},
+   "source": [
+    "### Prepare a low energy initial state: WALA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c9e5c8e1",
+   "metadata": {},
+   "source": [
+    "We start by preparing a low-energy state, on top of which we will pair-create charges. Our approach is to use a \"Weight Adjustable Loop Ansatz\" (WALA), which is equivalent to the mean-field ground state of the dual Ising model when $\\lambda = 0$. The ansatz only has one tunable parameter, $\\theta$. Since an expression for the mean-field Ising model is known exactly, the variational parameters for the WALA initial state can be efficiently classically calculated for any system size. In the limit of $h_E \\rightarrow 0$, the WALA reduces to the ground state of the toric code, previously explored in [ReCirq](https://quantumai.google/cirq/experiments/toric_code/toric_code_ground_state). As shown below, we choose a system size that has a 4x3 grid of charge sites, which corresponds to 17 gauge qubits.\n",
+    "\n",
+    "Note that in the experiment on quantum hardware, we use an additional 18 ancilla qubits to facilitate the Trotterization on the square grid of qubits with nearest-neighbor connectivity. However, to perform a Cirq simulation of these circuits, I will use a modified Trotter evolution that is not limited by the device connectivity and only uses the minimal number of physical qubits, at the cost of more gate layers."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97b5d107",
+   "metadata": {},
+   "source": [
+    "We start by initializing a `grid` object that serves to keep track of the qubits."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "3ec38233",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Lx = 4\n",
+    "Ly = 3\n",
+    "\n",
+    "grid = LGTGrid(origin_qubit = cirq.GridQubit(0,0),orientation_vector = (1,1), rows = Lx-1, cols = Ly-1, flip_rowcol = False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f841a5a",
+   "metadata": {},
+   "source": [
+    "This is visualized below where the grey diamonds correspond to the gauge qubits and the possible sites for charge excitations are shown in blue:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "f6175473",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "code = tcr.ToricCodeRectangle(origin_qubit=cirq.GridQubit(0,0), row_vector=(1,1), rows=grid.cols, cols=grid.rows)\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "tc_plot.ToricCodePlotter(z_cmap = charge_cmap, x_cmap = matplotlib.colormaps['binary']).plot_expectation_values(tc_plaq.ToricCodePlaquettes(\n",
+    "                code,\n",
+    "                x_plaquettes = np.zeros((code.rows,code.cols))-1,\n",
+    "                z_plaquettes = np.zeros((code.rows+1,code.cols+1))+1\n",
+    "            ),patch_kwargs={'linewidth':0.025},ax = ax)\n",
+    "\n",
+    "lgt.plot_qubit_polarization_values(\n",
+    "            ax = ax,\n",
+    "            grid = LGTGrid(origin_qubit = cirq.GridQubit(0,0),orientation_vector = (1,1), rows = grid.cols, cols = grid.rows, flip_rowcol = False),\n",
+    "            qubit_polarization_data=np.zeros(17),\n",
+    "            ancilla_states_data=np.zeros(18),\n",
+    "            plot_physical_qubits=True,\n",
+    "            plot_ancillas = False,\n",
+    "            qubit_colormap=matplotlib.colormaps['binary']\n",
+    "        )\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e6b8e7c1",
+   "metadata": {},
+   "source": [
+    "Next, we populate a dictionary with the optimal WALA angle, $\\theta$, for each $h_E$:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "88c9f682",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he_list = np.around(np.linspace(0,3,31),2)\n",
+    "\n",
+    "angles = {}\n",
+    "for he in he_list:\n",
+    "    fun = lambda theta: mean_field_energy(theta, Lx=Lx+1, Ly=Ly+1, he=he)\n",
+    "    res = minimize_scalar(fun, bracket=(0, np.pi/2))\n",
+    "    angles[np.around(he,2)]= res.x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c76734c",
+   "metadata": {},
+   "source": [
+    "and then use those angles to define the circuits to create the WALA state:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "a2247fcf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"overflow: auto; white-space: pre;\">                            ┌──┐           ┌──┐           ┌──┐\n",
+       "(-1, 0): ───Ry(theta)─────────@──────────────@───────────────────────\n",
+       "                              │              │\n",
+       "(-1, 2): ───Ry(theta)────────@┼─────────────@┼───────────────────────\n",
+       "                             ││             ││\n",
+       "(0, -1): ───────────────H────┼@────H────────┼┼─────────────@─────────\n",
+       "                             │              ││             │\n",
+       "(0, 1): ────────────────H────@─────H───H────┼@────H────────┼─────────\n",
+       "                                            │              │\n",
+       "(0, 3): ───────────────────────────────H────@─────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(1, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───\n",
+       "                             │              │               │\n",
+       "(1, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───\n",
+       "                             ││             ││\n",
+       "(2, -1): ───────────────H────@┼────H────────┼┼─────────────@─────────\n",
+       "                              │             ││             │\n",
+       "(2, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────\n",
+       "                                             │             │\n",
+       "(2, 3): ───────────────────────────────H─────@────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(3, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───\n",
+       "                             │              │               │\n",
+       "(3, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───\n",
+       "                             ││             ││\n",
+       "(4, -1): ───────────────H────@┼────H────────┼┼─────────────@─────────\n",
+       "                              │             ││             │\n",
+       "(4, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────\n",
+       "                                             │             │\n",
+       "(4, 3): ───────────────────────────────H─────@────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(5, 0): ──────────────────────────────────────────────H────@┼────H───\n",
+       "                                                            │\n",
+       "(5, 2): ──────────────────────────────────────────────H─────@────H───\n",
+       "                            └──┘           └──┘           └──┘</pre>"
+      ],
+      "text/plain": [
+       "                            ┌──┐           ┌──┐           ┌──┐\n",
+       "(-1, 0): ───Ry(theta)─────────@──────────────@───────────────────────\n",
+       "                              │              │\n",
+       "(-1, 2): ───Ry(theta)────────@┼─────────────@┼───────────────────────\n",
+       "                             ││             ││\n",
+       "(0, -1): ───────────────H────┼@────H────────┼┼─────────────@─────────\n",
+       "                             │              ││             │\n",
+       "(0, 1): ────────────────H────@─────H───H────┼@────H────────┼─────────\n",
+       "                                            │              │\n",
+       "(0, 3): ───────────────────────────────H────@─────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(1, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───\n",
+       "                             │              │               │\n",
+       "(1, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───\n",
+       "                             ││             ││\n",
+       "(2, -1): ───────────────H────@┼────H────────┼┼─────────────@─────────\n",
+       "                              │             ││             │\n",
+       "(2, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────\n",
+       "                                             │             │\n",
+       "(2, 3): ───────────────────────────────H─────@────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(3, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───\n",
+       "                             │              │               │\n",
+       "(3, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───\n",
+       "                             ││             ││\n",
+       "(4, -1): ───────────────H────@┼────H────────┼┼─────────────@─────────\n",
+       "                              │             ││             │\n",
+       "(4, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────\n",
+       "                                             │             │\n",
+       "(4, 3): ───────────────────────────────H─────@────H────────┼@────────\n",
+       "                                                           ││\n",
+       "(5, 0): ──────────────────────────────────────────────H────@┼────H───\n",
+       "                                                            │\n",
+       "(5, 2): ──────────────────────────────────────────────H─────@────H───\n",
+       "                            └──┘           └──┘           └──┘"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cirq.Circuit.from_moments(*lgt.variational_ground_state_minimal_qubits(grid,sympy.Symbol('theta')))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0af624ee",
+   "metadata": {},
+   "source": [
+    "Adding measurements in the Z and X bases, we populate lists of circuits for many values of $h_E$ to simulate the energy of the WALA state and compare this to the energy of the trivial product state where all qubits are in the $\\ket{0}$ state."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "b51f1408",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wala_circuits_z=[]\n",
+    "wala_circuits_x=[]\n",
+    "\n",
+    "for he in he_list:\n",
+    "    wala_circuits_z.append(cirq.Circuit.from_moments(*lgt.variational_ground_state_minimal_qubits(grid,angles[he]))+cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\"))\n",
+    "    wala_circuits_x.append(cirq.Circuit.from_moments(*lgt.variational_ground_state_minimal_qubits(grid,angles[he]))+cirq.H.on_each(grid.physical_qubits)+cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\"))\n",
+    "\n",
+    "polarized_circuit_z = cirq.Circuit.from_moments(cirq.Moment(cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\")))\n",
+    "polarized_circuit_x = cirq.Circuit.from_moments(cirq.Moment(cirq.H.on_each(grid.physical_qubits)),cirq.Moment(cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\")))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5756ed6",
+   "metadata": {},
+   "source": [
+    "Let's simulate these circuits using qsim. Since we're simulating a few 10s of circuits with 17 qubits, this should take less that 1 second."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "0cdcec41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "simulator = qsimcirq.QSimSimulator()\n",
+    "\n",
+    "results_wala_z = simulator.run_batch(wala_circuits_z,repetitions=reps)\n",
+    "results_wala_x = simulator.run_batch(wala_circuits_x,repetitions=reps)\n",
+    "\n",
+    "results_polarized_z = simulator.run(polarized_circuit_z,repetitions = reps)\n",
+    "results_polarized_x = simulator.run(polarized_circuit_x,repetitions = reps)\n",
+    "\n",
+    "results_wala_combined = {}\n",
+    "for idx,he in enumerate(he_list):\n",
+    "    results_wala_combined[('basis_z',f'he_{np.around(he,2)}')] = results_wala_z[idx][0]\n",
+    "    results_wala_combined[('basis_x',f'he_{np.around(he,2)}')] = results_wala_x[idx][0]\n",
+    "\n",
+    "results_polarized = {}\n",
+    "results_polarized['basis_z'] = results_polarized_z\n",
+    "results_polarized['basis_x'] = results_polarized_x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "530fe2e1",
+   "metadata": {},
+   "source": [
+    "Now, we can take these measurements, which correspond to the initial states with different values of $h_E$, and calculate the energy based on the Hamiltonian, $\\mathcal{H}$:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "272f2aa9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wala_energies_dict = {}\n",
+    "toric_code_energies_dict = {}\n",
+    "polarized_energies_dict = {}\n",
+    "for idx, he in enumerate(he_list):\n",
+    "    energy = energy_from_measurements(\n",
+    "        hamiltonian_coefs = {'Je':1,'Jm':1,'he':he,'lambda':0.25},\n",
+    "        z_basis_results = results_wala_combined[('basis_z',f'he_{np.around(he,2)}')].measurements['measure_all'],\n",
+    "        x_basis_results = results_wala_combined[('basis_x',f'he_{np.around(he,2)}')].measurements['measure_all']\n",
+    "    )\n",
+    "\n",
+    "    wala_energies_dict[he] = energy\n",
+    "\n",
+    "    energy = energy_from_measurements(\n",
+    "        hamiltonian_coefs = {'Je':1,'Jm':1,'he':he,'lambda':0.25},\n",
+    "        z_basis_results = results_wala_combined[('basis_z',f'he_{0.0}')].measurements['measure_all'],\n",
+    "        x_basis_results = results_wala_combined[('basis_x',f'he_{0.0}')].measurements['measure_all']\n",
+    "    )\n",
+    "\n",
+    "    toric_code_energies_dict[he] = energy\n",
+    "\n",
+    "    energy = energy_from_measurements(\n",
+    "        hamiltonian_coefs = {'Je':1,'Jm':1,'he':he,'lambda':0.25},\n",
+    "        z_basis_results = results_polarized['basis_z'].measurements['measure_all'],\n",
+    "        x_basis_results = results_polarized['basis_x'].measurements['measure_all']\n",
+    "    )\n",
+    "\n",
+    "    polarized_energies_dict[he] = energy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f42e302",
+   "metadata": {},
+   "source": [
+    "Plot the energies!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "845546bd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots()\n",
+    "\n",
+    "ax.plot(wala_energies_dict.keys(),np.array(list(wala_energies_dict.values()))/((number_of_gauge_qubits+1)/2), marker = \"o\", color = WALA_INITIAL, label='WALA')\n",
+    "ax.plot(toric_code_energies_dict.keys(),np.array(list(toric_code_energies_dict.values()))/((number_of_gauge_qubits+1)/2), marker = \"o\", color = TORIC_INITIAL, label='toric code')\n",
+    "ax.plot(polarized_energies_dict.keys(),np.array(list(polarized_energies_dict.values()))/((number_of_gauge_qubits+1)/2),marker='o', color= POLARIZED_INITIAL, label = 'polarized')\n",
+    "\n",
+    "ax.set_xlabel(\"$h_E$\")\n",
+    "ax.set_ylabel(\"Energy error per unit cell\")\n",
+    "ax.set_xbound(-0.05,1.05)\n",
+    "ax.set_ybound(-3.5,-1.25)\n",
+    "ax.legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "022dec20",
+   "metadata": {},
+   "source": [
+    "We can see that the WALA state yields an energy as low or lower than the two limiting cases of the toric code and polarized states across the entire range of $h_E$. The next step is to pair-create charge excitations on top of the WALA state with X gates and measure the Trotterized dynamics."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "89307a79",
+   "metadata": {},
+   "source": [
+    "### Dynamics of Charges"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c05f8dab",
+   "metadata": {},
+   "source": [
+    "By applying a single X gate on qubit `cirq.GridQubit(2,1)`, we excite two charges next to each other in the center of the grid. By then simulating their Hamiltonian evolution, the dynamics reveal a fingerprint of the confinement.\n",
+    "\n",
+    "We choose $h_E$ values between 0 (fully deconfined) and 2.0 (strongly confined) to simulate the dynamics. $J_E = J_M = 1$ and $\\lambda = 0.25$ are held constant. For the Trotterized simulation, we find that at time step of $dt=0.3$ does not accumulate significant trotter error over the simulated 10 trotter steps.\n",
+    "\n",
+    "A circuit with a single Trotter step now looks like:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "f19dcaf8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"overflow: auto; white-space: pre;\">                            ┌──┐           ┌──┐           ┌──┐               ┌──┐           ┌──┐                                               ┌──┐           ┌──┐\n",
+       "(-1, 0): ───Ry(theta)─────────@──────────────@───────────────────────────H────@─────H──────────────────────────────Rz(-2*dt)──────────────────────────────H────@─────H───H───@───H───────@───────────────────────────────────────────────@───────H───@───H───H───────────────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────────────────────────────────────────────────────────────────────────────────────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M(&#x27;measure_all&#x27;)───\n",
+       "                              │              │                                │                                                                                │             │           │                                               │           │                           │           │                       │           │                                                                                                                                             │\n",
+       "(-1, 2): ───Ry(theta)────────@┼─────────────@┼───────────────────────────H────┼@────H──────────────────────────────Rz(-2*dt)──────────────────────────────H────┼@────H───────┼───────H───@───H───────────────Rz(-2*dt)───────────────H───@───H───────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────────────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(0, -1): ───────────────H────┼@────H────────┼┼─────────────@──────────────────@┼────────H────@─────H───────────────Rz(-2*dt)───────────────H────@─────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              ││             │                   │             │                                                  │               │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(0, 1): ────────────────H────@─────H───H────┼@────H────────┼───────────────────┼─────────────┼──────────────────────────────────────────────────┼───────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                            │              │                   │             │                                                  │               │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(0, 3): ───────────────────────────────H────@─────H────────┼@──────────────────@────────H────┼@────H───────────────Rz(-2*dt)───────────────H────┼@────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(1, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───────H────@─────H────────@┼─────────────────────────────────────────────────@┼────────H────@─────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              │               │                 │               │                                                  │             │             │                       │                       │                       │                           │           │                       │           │                       │                                                                       │                                             │\n",
+       "(1, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───────H────┼@────H─────────@──────────────────────────────────────────────────@────────H────┼@────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(2, -1): ───────────────H────@┼────H────────┼┼─────────────@──────────────────@┼────────H─────@────H───────────────Rz(-2*dt)───────────────H─────@────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                              │             ││             │                   │              │                                                  │              │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(2, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────X─────────┼──────────────┼──────────────────────────────────────────────────┼──────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                             │             │                   │              │                                                  │              │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(2, 3): ───────────────────────────────H─────@────H────────┼@──────────────────@────────H────@┼────H───────────────Rz(-2*dt)───────────────H────@┼────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(3, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───────H────@─────H────────┼@─────────────────────────────────────────────────┼@────────H────@─────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              │               │                 │              │                                                  │              │             │                       │                       │                       │                           │           │                       │           │                       │                                                                       │                                             │\n",
+       "(3, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───────H────┼@────H────────@──────────────────────────────────────────────────@─────────H────┼@────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(4, -1): ───────────────H────@┼────H────────┼┼─────────────@──────────────────@┼────────H─────@────H───────────────Rz(-2*dt)───────────────H─────@────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                              │             ││             │                   │              │                                                  │              │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(4, 1): ────────────────H─────@────H───H────@┼────H────────┼───────────────────┼──────────────┼──────────────────────────────────────────────────┼──────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                             │             │                   │              │                                                  │              │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(4, 3): ───────────────────────────────H─────@────H────────┼@──────────────────@────────H────@┼────H───────────────Rz(-2*dt)───────────────H────@┼────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(5, 0): ──────────────────────────────────────────────H────@┼────H───────────────────────────┼@─────────────────────────────────────────────────┼@───────────────────────────────────────@───────────┼───────────────────────┼───────────@───────────────────H───────@───────────────────────────────────────────────────────────────────────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                            │                                │                                                  │                                                    │                       │                                                                                                                           │                                                                       │                                             │\n",
+       "(5, 2): ──────────────────────────────────────────────H─────@────H───────────────────────────@──────────────────────────────────────────────────@────────────────────────────────────────────────────@───────────────────────@───────────────────────────────H───────────────────────────────────────────────────────────────────────────────────────────@───────────────────────────────────────────────────────────────────────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                            └──┘           └──┘           └──┘               └──┘           └──┘                                               └──┘           └──┘</pre>"
+      ],
+      "text/plain": [
+       "                            ┌──┐           ┌──┐           ┌──┐               ┌──┐           ┌──┐                                               ┌──┐           ┌──┐\n",
+       "(-1, 0): ───Ry(theta)─────────@──────────────@───────────────────────────H────@─────H──────────────────────────────Rz(-2*dt)──────────────────────────────H────@─────H───H───@───H───────@───────────────────────────────────────────────@───────H───@───H───H───────────────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────────────────────────────────────────────────────────────────────────────────────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M('measure_all')───\n",
+       "                              │              │                                │                                                                                │             │           │                                               │           │                           │           │                       │           │                                                                                                                                             │\n",
+       "(-1, 2): ───Ry(theta)────────@┼─────────────@┼───────────────────────────H────┼@────H──────────────────────────────Rz(-2*dt)──────────────────────────────H────┼@────H───────┼───────H───@───H───────────────Rz(-2*dt)───────────────H───@───H───────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────────────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(0, -1): ───────────────H────┼@────H────────┼┼─────────────@──────────────────@┼────────H────@─────H───────────────Rz(-2*dt)───────────────H────@─────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              ││             │                   │             │                                                  │               │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(0, 1): ────────────────H────@─────H───H────┼@────H────────┼───────────────────┼─────────────┼──────────────────────────────────────────────────┼───────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                            │              │                   │             │                                                  │               │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(0, 3): ───────────────────────────────H────@─────H────────┼@──────────────────@────────H────┼@────H───────────────Rz(-2*dt)───────────────H────┼@────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(1, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───────H────@─────H────────@┼─────────────────────────────────────────────────@┼────────H────@─────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              │               │                 │               │                                                  │             │             │                       │                       │                       │                           │           │                       │           │                       │                                                                       │                                             │\n",
+       "(1, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───────H────┼@────H─────────@──────────────────────────────────────────────────@────────H────┼@────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(2, -1): ───────────────H────@┼────H────────┼┼─────────────@──────────────────@┼────────H─────@────H───────────────Rz(-2*dt)───────────────H─────@────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                              │             ││             │                   │              │                                                  │              │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(2, 1): ────────────────H─────@────H───H────@┼────H────────┼─────────X─────────┼──────────────┼──────────────────────────────────────────────────┼──────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                             │             │                   │              │                                                  │              │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(2, 3): ───────────────────────────────H─────@────H────────┼@──────────────────@────────H────@┼────H───────────────Rz(-2*dt)───────────────H────@┼────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(3, 0): ────Ry(theta)────────@──────────────@─────────H────@┼────H───────H────@─────H────────┼@─────────────────────────────────────────────────┼@────────H────@─────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             │              │               │                 │              │                                                  │              │             │                       │                       │                       │                           │           │                       │           │                       │                                                                       │                                             │\n",
+       "(3, 2): ────Ry(theta)────────┼@─────────────┼@────────H─────@────H───────H────┼@────H────────@──────────────────────────────────────────────────@─────────H────┼@────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                             ││             ││                                ││                                                                               ││            │                                                                       │                           │           │                       │           │                                   │           │                       │           │                                                         │\n",
+       "(4, -1): ───────────────H────@┼────H────────┼┼─────────────@──────────────────@┼────────H─────@────H───────────────Rz(-2*dt)───────────────H─────@────H────────@┼────────────┼───────────────────────────────────────────────────────────────────────┼───────H───H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                              │             ││             │                   │              │                                                  │              │            │                                                                       │               │                       │                       │                       │                       │           │                       │           │                                                         │\n",
+       "(4, 1): ────────────────H─────@────H───H────@┼────H────────┼───────────────────┼──────────────┼──────────────────────────────────────────────────┼──────────────┼────────────@───────H───@───H───H───@───H───Rz(-2*dt)───H───@───H───H───@───H───────@───────H───────┼───────────────────────@───────────────────────@───────────────────────┼───────H───@───H───────@───────────┼───────────────────────┼───────────@───────H───@───H───H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                             │             │                   │              │                                                  │              │                        │           │                       │           │                           │                                                                       │           │                       │                       │                       │                                             │\n",
+       "(4, 3): ───────────────────────────────H─────@────H────────┼@──────────────────@────────H────@┼────H───────────────Rz(-2*dt)───────────────H────@┼────H─────────@────────────────────────┼───────────┼───────────────────────┼───────────┼───────────────────H───────┼───────────────────────────────────────────────────────────────────────┼───────────┼───────────────────────@───────────────────────@───────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                           ││                                ││                                                 ││                                       │           │                       │           │                           │                                                                       │           │                                                                       │                                             │\n",
+       "(5, 0): ──────────────────────────────────────────────H────@┼────H───────────────────────────┼@─────────────────────────────────────────────────┼@───────────────────────────────────────@───────────┼───────────────────────┼───────────@───────────────────H───────@───────────────────────────────────────────────────────────────────────@───────────┼───────────────────────────────────────────────────────────────────────┼───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                                                            │                                │                                                  │                                                    │                       │                                                                                                                           │                                                                       │                                             │\n",
+       "(5, 2): ──────────────────────────────────────────────H─────@────H───────────────────────────@──────────────────────────────────────────────────@────────────────────────────────────────────────────@───────────────────────@───────────────────────────────H───────────────────────────────────────────────────────────────────────────────────────────@───────────────────────────────────────────────────────────────────────@───────H───Rz(-2*dt*he)───Rx(-2*dt*lambda)───M──────────────────\n",
+       "                            └──┘           └──┘           └──┘               └──┘           └──┘                                               └──┘           └──┘"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "excitation = cirq.Moment(cirq.X.on(cirq.GridQubit(2,1)))\n",
+    "\n",
+    "cirq.Circuit.from_moments(\n",
+    "    *lgt.variational_ground_state_minimal_qubits(grid,sympy.Symbol('theta')),\n",
+    "    excitation,\n",
+    "    *lgt.trotter_step_minimal_qubits(grid,sympy.Symbol('dt'),sympy.Symbol('lambda'),sympy.Symbol('he')),\n",
+    "    cirq.Moment(cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\"))\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b5891922",
+   "metadata": {},
+   "source": [
+    "Let's populate a list of circuits to simulate:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "e4aec731",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he_list = [0,0.3,0.6,0.8,2.0]\n",
+    "dt = 0.3\n",
+    "coupling = 0.25\n",
+    "trotter_steps = np.arange(10)\n",
+    "\n",
+    "excitation = cirq.Moment(cirq.X.on(cirq.GridQubit(2,1)))\n",
+    "\n",
+    "time_evolution_circuits = []\n",
+    "\n",
+    "for he in he_list:\n",
+    "    for step in trotter_steps:\n",
+    "        time_evolution_circuits.append(cirq.Circuit.from_moments(\n",
+    "            *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "            excitation,\n",
+    "            *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he)*step,\n",
+    "            cirq.Moment(cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\"))\n",
+    "        ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b31c4627",
+   "metadata": {},
+   "source": [
+    "and run the simulations. Now that we're simulating deeper circuits for many Trotter steps, this may take a few seconds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "5b1af32b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_charge_dynamics = simulator.run_batch(time_evolution_circuits,repetitions=reps)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad8e4713",
+   "metadata": {},
+   "source": [
+    "Now we will calculate the charge operator for each vertex, $v$. Then, by post-selecting on bitstrings that only have two charge excitations ($A_v = -1$ on two vertices and $+1$ for all others), we calculate the average distances between charges for each set of parameter values and number of trotter steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "a3824a60",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "counter = 0\n",
+    "\n",
+    "trotter_steps = np.arange(10)\n",
+    "\n",
+    "occupations = {}\n",
+    "separations = {}\n",
+    "separations_sdom = {}\n",
+    "\n",
+    "for he in he_list:\n",
+    "    separations[he] = []\n",
+    "    separations_sdom[he] = []\n",
+    "    for step in trotter_steps:\n",
+    "        occupations[(he,step)] = []\n",
+    "        res = results_charge_dynamics[counter][0].measurements['measure_all']\n",
+    "        charge_occupations = lgt.plaquette_bitstrings(res,grid)\n",
+    "        charge_excitation_number = np.sum(charge_occupations,axis = 1)\n",
+    "        post_selected_charge_occupations = charge_occupations[np.nonzero(charge_excitation_number==2)[0],:]\n",
+    "        charge_separation = lgt.excitation_sep_plaquette_input(\n",
+    "            post_selected_charge_occupations,\n",
+    "            grid.rows+1,\n",
+    "            grid.cols+1\n",
+    "        )\n",
+    "        \n",
+    "        occupations[(he,step)] = np.mean(charge_occupations, axis = 0)\n",
+    "        separations[he].append(np.mean(charge_separation))\n",
+    "        separations_sdom[he].append(np.nanstd(charge_separation)/np.sqrt(len(charge_separation)))\n",
+    "\n",
+    "        counter += 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28ae7fbb",
+   "metadata": {},
+   "source": [
+    "To start to explore this data, we will plot heatmaps of $\\langle A_v \\rangle$ for each charge site for the deconfined ($h_E = 0$) and the confined ($h_E = 2.0$) cases for times $t \\in \\{0, 1.5,2.7\\}$. Notice that the charges tend to separate much faster in the deconfined regime."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "80377772",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAErCAYAAAAokrM1AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAAL79JREFUeJzt3Ql0XVW9+PHfvZmHm3me07RNMzSdC6VFKFBoGVT0j09loT70KYroUuS5BBwYnF26cHjA07/CWv59KgqKdKKF0lIKHdOmbdIh8zzP83T/63fKyUvSJL1N7j5n//b+fdfKanOb3tzc3Hyyzz77nONwu91u4DiO40jmtPsBcBzHcfOPEec4jiMcI85xHEc4RpzjOI5wjDjHcRzhGHGO4zjCMeIcx3GEY8Q5juMIx4gL7g9/+AOcPn3aK/f1xz/+EU6cOAHe7jOf+QzccsstV/y4G2+8ET73uc/N63P89Kc/heXLl4NOefq8ctxCYsQF1tnZCV/4whcgMDDwsn9rbW2F2NhY8Pf3h+HhYY/ur6ioCH72s595/XE+88wz8NJLL028j/AgQN4Mf/msXLkSZGvHjh3G4woICICMjAz4+c9/ftX3MdvzNf15pdaBAwfgQx/6EKSnp4PD4YCnn376iv/ne9/7nvGx099KS0stecw6xogL7F//+hcsXboUlixZctm/ffOb34QvfvGLMDIyAmfOnPHo/u6++27Yvn27x+h7Wnh4OERGRoLIZET82LFjBlLbtm2DkydPGgA9+uij8Nxzz5F5XkXW29sLubm58JOf/AQSEhI8/n/4y7ChoWHKW2ZmptDHqnV47hROTHfffbf78ccfv+z2Q4cOuXNyctwjIyPuxMRE9+9+9zuP7m98fNz4+B07dsz6MXv37nX7+fm5+/r6jPcHBgbcAQEB7o0bN058zOuvv258TE9Pj/H+pz/9affNN9888Xd8WUx+27dvn/FvN9xwg/uzn/2s+8knn3THx8e7IyMj3ffdd9/E/cwW/rvD4XD//ve/d99zzz1ul8vljouLcz/33HNuO/vEJz7h3rBhw5TbvvGNb7jT09M9vo+5nq/Jz6v5/N1///3uxx57zB0bG+sODw93P/roo+6xsTH3E088YTwnMTExxm3T++Uvf+nOzs42vpeLFy92P/3008brx6rwOXnqqaeu+HHf/e533VlZWZY8Ju5SPBIXVH9/P+zevdsYPU9ubGwMvvSlLxlzxL6+vsY8safz3LhZiiPHl19+edaPue6668DpdMLbb79tvP/OO++Ay+WCo0ePQl9fn3Hbm2++CevWrYPQ0NAZpwCuv/56+NjHPjYxisL7NPvb3/4G7e3t8NZbb8Gf//xneO211+DHP/7xnI+7sLAQBwvw61//Gu69915j1It/fvnLX554TJ70gx/8wHjMc73hx3gaPjdbt26dchu+X1VVBbW1tR7dx5Wer+nh84dbXwcPHjSmbvDx3nHHHcaoF79nOF2Gt+3cuXPi/+AWAt7+wx/+EEpKSozP+fzzz8MTTzxh2XN1NeFzl5KSYrzhVs6hQ4eEfB7u/d7HnPNyL7/88owjumeeecZ96623Trz/8MMPu6+99lqP73f37t3GiA1Hb7OFI75HHnnE+DuO6nD0hyP/nTt3GretX79+yhbC9BEj/h1vm+l+CwoKptz2wAMPXPHx49fs7+/vvnjx4sRtJ0+eNEatNTU1xvsvvPCC8XWtWLFi4u3AgQNT7qetrc24j7ne8GM8DbdGnn/++Sm3nTlzxnhcR44c8fh+Znu+ZhqJ49c1udzcXHd+fv6U2/A5xtcFhltUQUFBE987sxdffNEYyc+Wt58rT0fi27dvd//pT38yvr/4/bv33nvdTqfT2PrjxORrYs55fz4cR1iTa2xsNEZPuMPIDEfizz77LIyPjxsj6Cu1efNmY/R6+PBh2LBhw6wfg5/fHHU/9NBDxs5V/DuOEo8fPw4/+tGP5vV1rVixYsr7SUlJxhbHXOGWxq233gqLFy+euK2srAyCg4ON/4+dOnXKGHHifoLZioqKMt4oN/35w7nm6fPN+H5zc7Px97Nnz8LAwAB89KMfNbbEJm/RDQ4OQktLi7GDXJbn6vbbb5/yPm6l4Mgctzy3bNli+ePRIZ5OEdSiRYugoqJiym0PP/ywMRWBP8g4lYJv999/vzH1cu7cuQnMNm3aNPF/KisrjR2CiDzW1NRk/FDjzqPZuummm4wpjOrqagNsfB/fEPH9+/eDn5/fnJv8c4WraSaHsJiPbS7Ep38+vK2goGDiFxeuvFm1atWc9+PtKYLExETjF+vk8Pk1/01E+NxPf/5mus18Ts0/cZULTkOZb7hs9eLFi7NCbed0yvRwsIGvY05MPBIXFM6FP/XUU9Dd3Q1hYWHGHPKrr74K7733HoSEhEx8HM6PrlmzxkAXVwIsW7bM+OE0w9Hpt7/97Qns/vGPf8A111wzJzL47zjyfvLJJ42VMTiyw9H5xz/+cWM+HUHFJXVzQY0jPW+Eo0Wcx50ONCK+evXqifcRpc9//vMTXyfOmT/yyCNT/s8DDzxgzD3P1dWMPjdu3GhsRXznO9+ZuG3Xrl3Gkjqcz/U0bz5f08vLyzO+l+Xl5ZeNcufK28/VQsLvdWpqqiWfS8cYcUHhDx+OlnEdMm4KP/jgg/CVr3zFAHZ6aWlpxgsd4UJcIyIijM1kXEuOI/QXXnhh4mNfeeUV+MhHPnJFVBCoF1980fhhNn9g8/PzjQOG8BfDXOFysH379hlTHrhMDt+mjxY9DUfYo6OjU8DG8OvF5wXDnYG48xU/dq68PUXwta99zfiF9thjj8F9991nTFH96le/gl/84hdXdT/efL6mhyNmXPaIbzhCxzXp+HziLz38xT/bTmVvPFe4s9Vc343LWnGrBbcC8DGZU2O4sxrfzC3Jr3/963DnnXcar30cwPz2t7+FPXv2wD//+c8FPRZu9ng6RfBoHNFFFBCq6SNLMxx9T16hgiNyHL3iCHHyCgScisH59OkrXmYKR974w47TKGb49+m3zRRO+8TExBjTPjjfiqs45htCk5ycDHFxcRO31dXVGdMWJuw4hZSTkwNWhyt0cMsGV9jg14rP9/e///2JX3wY/gJFPOeaDvDm8zVTuCWGK1kQRPwcON2Gr6m5ptS8tY4et6DwDV+/v/nNb4y/Tz5qFwca58+fn3gfP+5Tn/qU8f3E/SD4b3v37oW77rpL6GPVOQfu3bT7QajakSNHjJETjqrnmr6Y3uOPP278nwsXLhgjPDMcWeMPM6KnUngwCX69uPNLthD2v//978ZzjvswOE62+FUpeKSHm9Y4Epm+UuVKUzGf/OQnjbXEk8NRvSejcGohkLjPADe7J89NX81RgqLCUTqOQBlwTtZ4JM5xHEc4nhPnOI4jHCPOcRxHOEac4ziOcIw4x3Ec4RhxjuM4wjHiHMdxhGPEOY7jCMeIcxzHEY4R5ziOIxwjznEcRzhGnOM4jnCMOMdxHOEYcY7jOMIx4hzHcYRjxDmO4wjHiHMcxxGOEec4jiMcI85xHEc4RpzjOI5wjDjHcRzhGHGO4zjCMeIcx3GE87X7AXByNTo2Dm3dg9DdPwI9fcPQ3T8MPQMjMDI6ftnHhgT6QliwP7iC/SEs2A8iQgMgLMTflsdNqd7BEWjuHICO3iHo7B0y/uzqG4axcfeUj/NxOoznNDLUHyJDAiDSFQBxEcEQHMA/ttz/5nC73VNfOZx2IdANbX1Q19oHTZ0DMD4Nk6spNMgPkqJDIDkmxECHuxT+Mqxo7Ibyxh5o6RqY9/04ACA+MhgyE1yQmRAGoYF+Xn2cHL0YcY1r6uiHsvpuaO7ohwW4PWs4YkyLC4Ws5HAI8PMBHbdqztd2wrnaTmPrRkRxEUGQkxoJS5LCwelE4jndYsQ1DEfcF2o6jc14K8JpgYwEFyxNiYAgDaYChkfHoKS6A4oq22FgaNSSz4lbQCsyoyE7JQJ8fXhXl04x4pqE3+aall44X9MJPf0jtjwGHCimxbsgOzUCQhScBhgaGYPTlW1wtqodhkYu34dgRUH+PrA8Mxry0qLAz5cx1yFGXINw51lhaSt09Fgz8r5SuNmPkOOoUZUpgIt1nfDeuSYYGB4DGcK58uty4yEjPszuh8IJjhFXfIdlcVU7lNd3g4zfZJwCWLk4xpjXpfwL8uDZBqhv7wcZS48LhetyE8AVxKuGVI0RV7Tall4oKm+DQUlGhnOVEhsCBYuiIdDfl9ROy8KyVjhV0bag1TxW5OvjgNWLY6EgI1qZLR/uf2PEFdypduJiK9S39gGlcP52zZJYSIoJAdnDlSZ7T9Yaa7spFRMWCDevTIbwEF76qVKMuEK1dw/CkXPN0G/RiggRLUoKM3bM4YoWGcOdljj3Pf3AHEq/LDflJRpLEjk1YsQVCZcMIjAqfDfDQ/xh/bI440hQmVaeHDhdDxVNPaBCS5PDYWNuIq9gUSBGnHiIy7HzzdDUMf+jAGWdx12ZFWMsSZThoKg3TtVB74A9SzNFFRHiD7esSoEoV6DdD4VbQIw44XBlxLtnG6VZ1iaiRYlhsCIrGhwOe6ZX8KCdg8UNSmzhzBROW91YkARZiTy9QjWtER8YHoWa1l6obumFvqFR8Pd1GpuX/j5O8PfzAT8fJ8SFB0FqTCjIFp7rBOe/qc7NXk3xkUGwflm8pZv++GNx+HwzFFW0gQ6tWxoHq7JiQLZauwehrr3XOHhqZGzcWDaLf+IOfF+nE1KiQ4yfTzwRm65phXhlcw8cvths/Fnd2muciMiTL94V5AfLkiMgNyUSclIiITPOZetSrdK6LmP5oE7hPPmGvARLzuCHywffPFUHlYrMf3saHnx1fV6ira/thvY+OFfXOfHW1uPZOWfCg/0NzPGtID0KlqdHgy4pjzjOGb9zrhH2nKqF0sZu7x3anBYFd6xJh9zUSLAq/FadKm8zDt7RsUB/H9iQmyD07Ii4smf38Wpo6RJzwirZwzNQblmVYukJyxo6+mHniWo4XtYCXf3eWbYZFx4Em/OT4AN5SQbwKqcs4i3dA/Dq0So4UNwgdMnd0qRw+PD6DFi3OA5Ejw6PlDRBo2I7MOczh7tuWZyBjbdr7xmEXcdqjPN961xEqD9sXZMmfIqirLELXjtWBcfKWoTtc/BxOmBtVizcviYNshLUnPdXEvHdJ2vgj/svwuCIdTv8cG7ug+vS4fqcRK+fRQ7PhHfobCO5g0tEtnxRNCxJ9t4PZW1rL+wprJ3x4he6bvXctjrVOHe5tyuqaoPXjlZBcW0HWJXDAbB1ZSrcszEL/H3VOi2yUog3dfbDc7uL4UyNdS+O6UW7AuAzm7Ph2qXxXluBgoBTOHye6soV1VegyLJyBfdF/W5vifGnXSVEBMF/bMmF7OQIUCVlELdj9D1XNy1Phn+/KRsCFzC32NjeD4dL6B4daNXKlWty4ue99YNHX+qyAsXOlSvbj1XBS++WweiY/a9lhwPg1hWp8PFNi5U42EkJxP/nYCm8/F4FyFZiZDB89Y7lkJUQNq8TWB0938yjQw+KDguA6/Ku/ujDA2fq4VxNp7DHpVIrF0XD+uyr37ps7x2E53cXw1kbt45na2VmNHz1jgLykJNHXFbAzXydDvi3jVnwwfUZ4PRws7+mudc4CpP0N8bicMXKpnzPIMeX/P7T9XChrsuSx6ZKBZnRcO0yzyE/VtpsTJ/0Dsp7Lp+VCkBOGnHZAZ9cXmokPHR7PkRf4RDnqqYeOH6hxbLHpdqqCoQcD9SarXG3G94qqofSegZ8PuWnRxnnJ7/Sst4/7r8A+87UA4VWEoecLOJ/eacM/vZuOVAK16s+/n9WQ0bczOcDqWzsNk4jyy3soKBNyxNnXOeM5/3eV1QHZQ16rrP3VrlpkcaZEGeqZ2AYfvzKSVt3Xs4X8q/ftYLk+dZJ/uo5U90OfycGOIYHMjzx12NQNsNBR+UNDLg3wmWYbxc1zAj4GydrGXAvVFzdYZzRcXp44e2nXzpBDnDsZEUbbD9RBRQjhziuPnl2dzHZ+eL+oTHoHrh8vfcg4XOAy9bI6OUrlHCFj8onCrO6mQ6gw1G4t464tKOX362A+nZaF1Mhifj/O3ARmrtoHrWIOza/emc+rMq8fLlWbkYULEtVZ+2qXeEpEa4vSLrsdpzv3LY2DRIEHLyiW2mxobBldeoMt7vgWx9dZVykmWIjY+Pw33uKjf0mlCKFeHFNB+wurAHKgF+XPftOIYbcO4DjBZhniiH3HuCzXXkpnTjkpQ3dsOtENVCKFOLP76E5jeIJ4GYMuRjAzRhycYCrAvnf3i2Hzr4hoBIZxIsq26C+vR9UBtyMIRcDuBlDLg5wFSAfHh2H/WdpLI8khfieolrQAXAzhlwM4GYMuTjAVYB835l6MnPjJBDHTZujpS3aAG7GkIsB3IwhFwc4dchbuwfhdBWNc+qQQPzN0/WkTgLlDcDNGHIxgJsx5OIApw75m6frgEJEEKfxZHobcDOGXAzgZgy5OMApQ15Y3kZiB6f0iOOT2ERkXbgIwM0YcjGAmzHk4gCnCvm42w3lXrqko9aI45XodQfcTHfIRQFuxpCLA5wq5DVt8vsjPeJVrQSeRAsA1x1y0YCb6Qy5aMApQl5NwR+QvOoWuU+mYyXgukJuFeA6Q24V4NQgr2mV/1wq0iNeJfF0ih2A6wa51YDrCLnVgFOCvLGjX/qLZ0uPeGOnnEdp2gm4LpDbBbhOkNsFOBXIx91uaOmWe2GF9Ijb9eKSHXDVIbcbcB0gtxtwKpD7SGgQKcT9fOZ/tXjVAVcVclkAVxlyWQCnALmfj9xMyv3o3v8BkiUZAVcNctkAVxFy2QCXHXI/iQyaKbkfHQD4S/IEygy4KpDLCrhKkMsKuMyQ+/nKNRswPTmElBxxCoBTh1x2wFWAXHbAZYXcn6dTFlaQv6+tn58S4FQhpwI4ZcipAC4b5AG+TnBK/pxJj/jixHDbPjdFwKlBTg1wipBTA1wmyBcl2OePMojnptgDEWXAqUBOFXBKkFMFXBbIlyXL+/NDBnF8Eq1+/akAuOyQUwecAuTUAZcB8mWM+MILDvCDtFiXZZ9PJcBlhVwVwGWGXBXA7YTcx+mwdTpXGcStnFJREXDZIFcNcBkhVw1wuyDPjHdBgJ/cywsJIR4p/HOoDLgskKsKuEyQqwq4HZAvSxbvjjaIr8yMgTCBP/g6AG435KoDLgPkqgNuJeQOANi4jIYHJBDHTZptq9OE3LdOgNsFuS6A2wm5LoBbBfmKzGhIjQkFCpFAHNu6MhUCvTw/pSPgVkOuG+B2QK4b4FZAftfaDKASGcQRgZsLkr12fzoDbhXkugJuJeS6Ai4S8iWJ4ZBNYGkhOcSxO9ekg68XXqwMuHjIdQfcCsh1B1wU5HetTQdKkUI8JiwQNuYsDF4GXDzkDLh4yBlwMZAnR4XA6qxYoBQpxLG712eCr8/8XrgMuHjIGXDxkDPg4iC/+9pMoBY5xJOjQ+De65dc9f9jwMVDzoCLh5wBFwf5tUvjjTdqkUMcu3NtOhSkR3n88Qy4eMgZcPGQM+DiII92BcK/35wNFCOJOPblbfkeHQDEgIuHnAEXDzkDLg5yhwPgi7flQkgAzdcvWcQjQwPggdty5/wYBlw85Ay4eMgZcLGQ37U2A5ZZcGoPUZFFHFu3OA62rEiZ8d8YcPGQM+DiIWfAxUK+KD4MPrqB3s5MZRDHPn3jUmNZ0OQYcPGQM+DiIWfAxUIe4OcDD27LAx8nbQZpP/r3vxH/+eEVEBZ86RvEgIuHnAEXDzkDLhZyH6cDHtyaB/ER9p86eKE53G63GxSosrkHnnrpOHz2lmUMuKCKK9uhqqmHARfUyOg47DxWDf6+TgZcUFUtPfDjV07CfTcshQ3Z9JYTKo041j80CsEBvnY/DKUbHRsHXx/yG3BSP78Oh4MB5/REnOM4Trd4SMVxHEc4RpzjOI5wjDjnceMjIzBQesHuh6F0w02NMNrRbvfD4AilDOLF1R3w7Paz8G5Jk90PRVnA637+Q6j63qPQe+qE3Q9HWcBrnnocqp/+NkMuqOrmHvjzWxfhyDl1nFAC8XM1HbD/dL3x95PlrQy5IMB7TxwD98gw1P70Bwy5IMBH29tgpKGeIRcE+KHiRsClHGUN3XDsQjOoEHnEL9R1wltFlwA3Y8jFAG7GkIsD3IwhFwe42cW6LjhxsQWoRxrx0vouePNUHcy0RpIhFwO4GUMuDnAzhlwc4GbnazvhZFkrUI4s4uWN3fDGydoZvzFmDLkYwM0YcnGAmzHk4gA3K6nugFPldCEniXh9Wx/sKayFcQ8OU2LIxQBuxpCLA9yMIRcHuFlxVQdcqO0EipFDvLN3CHYdr4FxTwR/P4ZcDOBmDLk4wM0YcnGAm50obYG61j6gFinEB4dHYcfRahgaGbvq/8uQiwHcjCEXB7gZQy4OcAw//lBxA3T0DAKlyCA+NjYOu47VQFf/8LzvgyEXA7gZQy4OcDOGXAzgZqNjbthfVA/9gyNAJTKI7yuqh4aO/gXfD0MuBnAzhlwc4GYMuRjAzQaGx4zjTvDUwBQigfjRC81wsb7La/fHkIsB3IwhFwe4GUMuBnCzzt5h4/7GCZzkVXrEcR3nMQEL8hlyMYCbMeTiADdjyC/lbcAnr4KjcDCQ1Ijjk/jW+4fTi0hnyEUCbqY75CIBN9Md8mpBgE8+qvN8TQfInLSId/Zd/VLC+aQj5FYArjvkVgCuO+SiATcrLG2F2tZekDWnrJeo2n28Zl5LCeeTTpBbCbiukFsJuK6QWwU4hp/ivZIm6B2Qc8WKlIjjN6e9Z8jSz6kD5HYArhvkdgCuG+RWAm6GK1WMHZ2CZwaUQLysoQvOVtszB6Uy5HYCrgvkdgKuC+R2AG7W1j0IRRX2fW9JIN7dP3zZaWWtTkXIZQBcdchlAFx1yO0EfPLJshra5Do0XxrEx8bdsLewFoYlWGCvEuQyAa4q5DIBrirkMgBuhjYMDI2CLEmD+PGLLdDUOQCypALkMgKuGuQyAq4a5DIBjuGCi/ckurybFIh39A5BoYQnZqcMucyAqwK5zICrArlsgJs1tvdDVVMPyJAUiB84Uy/t4a0UIacAOHXIKQBOHXJZAZ986trhUWuWQUuNOB5WX9+28BNbiYwS5JQApwo5JcCpQi474Njg8BgUlbfpjTjOLb1b0ggUogA5RcCpQU4RcGqQUwDcrLSuy1h6qC3ih883Gad9pJLMkFMGnArklAGnAjklwDF8mMcuNIOWiOMhrCXV9K5pJyPkKgAuO+QqAC475NQAN8Ojy2tbevVDHDGUdWcmJchVAlxWyFUCXFbIqQJuVmzTUea2IY4L5fHIJ8rJALmKgMsGuYqAywY5dcAxnBdv9MKVx8ggfqqiDUYlPJEMJchVBlwWyFUGXBbIVQDcrLiyXQ/Eh0fG4GyVHJtwVCHXAXC7IdcBcLshVwlwDI84t2OliuWIVzb3SHF+FKqQ6wS4XZDrBLhdkKsGuFlFYzcoj3hZg/VfpCqQ6wi41ZDrCLjVkKsKOGbHKhVLER8ZHYMaG5fiUIZcZ8CtglxnwK2CXGXAMTzupaVrQF3Eq5p7jVPOqpwIyBlw8ZAz4OIhVx1wM6sHqpYiXtGk5lSKSMgZcPGQM+DiIdcFcDumVCxFvLXL3nMMUIOcARcPOQMuHnKdAMf6BkeNVXjKIT42Ng5d/cOgUwuBnAEXDzkDLh5y3QA3s9I6yxDv7BvW7hs5X8gZcPGQM+DiIdcVcKyrT0HE23uHrPpUpCFnwMVDzoCLh1xnwLFuFRHv0WwqZT6QM+DiIWfAxUOuO+DmWVqVQ1zxlYULhpwBFw85Ay4ecgb8Um7jTOOaXJ5NR8hPznBR6Ppf/5wB9yLkQ7XVU24f6+1hwL0Iec33vwPusdEptze09zHgNsSIW1xooB9kJoRddnvklm3gCAiw5TGpVsjyAvBPSJxym0+oC8JvuMm2x6RaEbdsBYeP75TbYsKCICYs0LbHpGuMuMWAf/DaDAgP8b/s30LyCyD1P7/NkC+w0NVrIeXhb4HD1++yf4u555MQffc9tjwulYr71Gchcuudl93u5+uEGwqSITacIVcS8QA/vX9fzAW4GUMuDnAzhlwM4GYM+aX8fX3AqiyTNTJUX5g8AdyMIRcHuBlDLgZwM4YcIMyDn3VyiEdpivjVAG7GkIsD3IwhFwO4me6QhwcriHhwoB8E+Fm3iUEVcDOGXBzgZgy5GMDNdIY8XMWRuG6j8YUAbsaQiwPcjCEXA7jOkPs4HRASNP/XpNSIJ8eEgA55A3Azhlwc4GYMuRjAdYU8LiIInA6HmohnJV6+Plq1vAm4GUMuDnAzhlwM4DpCnhobaunns3Y6xRUIERbOFakAuBlDLg5wM4ZcDOA6Qe5wAKSojDi2SNHRuEjAzXSHXCTgZrpDLgpwXSCPiwiyfAGH5YhnzXDIOfWsAFx3yK0AXHfIRQOuA+RpsS7LP6fliMeEB0FiVDCokpWA6wq5lYDrCrlVgKsMub+vE9LjNUAcW50VAypkB+C6QW4H4LpBbjXgqkK+NCXC+Jq0QDwtzkX+bGd2Aq4L5HYCrgvkdgGuGuS+Pg7ITomw5XPbdlaq1YvpjsZlAFx1yGUAXHXI7QZcJcgXJ4WDv01HpNuG+KKEMJInxZIJcFUhlwlwVSGXBXAVIPdxOmBZaqRtn982xB0OB1yXEw+UkhFw1SCXEXDVIJcNcOqQ56RFQlDA1AtkWJmtJ/nGuXEckVNIZsDNqEMuM+CqQC4r4FQhdwX5QW66faNwzPYrNWzKS7Blj65qgFOHnALg1CGXHXCKkK9dGgc+Tnv9sl3PkEA/WL80DmSNEuBUIacEOFXIqQBOCfL0OBckSHDMi+2IY/kZUVIuOaQIODXIKQJODXJqgFOA3M/XCaskWWEnBeJ42sbNBUnGXl5Zogw4FcgpA04FcqqAyw756sWxtu7MlA5x83D8DZKsVlEBcNkhVwFw2SGnDriskGfEu6Q6kZ80iGPLM6Ih04ZzD6gKuKyQqwS4rJCrArhskLuC/IydmTIlFeLY5hXJEGrhpY1UB1w2yFUEXDbIVQNcFsidTgdszEuUbjWdXI8GwDgX75ZVKWD19LjKgMsCucqAywK5qoDLAPmqrBiIdMmxNSs14lhCZDCsz7ZuflwHwO2GXAfA7YZcdcDthDwlJsQ4S6GMSYm4+VtvaXK48M+jE+B2Qa4T4HZBrgvgdkAeGRoAG3ITQNakRRy7sSBJ6AUkdATcash1BNxqyHUD3ErIgwN84QMFSeDrIy+VTrnPDuaErWtShVxcWWfArYJcZ8CtglxXwK2A3NfHYQCOkMuc1Ihjgf6+cPu6NAj04rl6GXDxkDPg4iHXHXCRkDscYKxEoXC6bOkRx8JDAmDr2lSvHNHJgIuHnAEXDzkDLhby1YtjISk6BChEAnEsMSrEODR/ITHg4iFnwMVDzoCLhTw7JULalSikEceWJEfAuqWx8/q/DLh4yBlw8ZAz4GIhT44JkebEVkoijq1dEgfZV7n0kAEXDzkDLh5yBlws5JGhAXBdboJx1TFKkUMcu6EgCZI9nK9iwMVDzoCLh5wBFwt5SKD8Swlni94jfn/p4ba1aVdcQ86Ai4ecARcPOQMuFvLgAF+4aWWK9EsJlULc/AbdsS4N4iODZvx3Blw85Ay4eMgZcLGQB/n7wE0r7TvpntaIY36+PnDHunSIC58KOQMuHnIGXDzkDLhYyAMR8FUp4Aqm7QRpxM2zHt55TfrE5d0YcPGQM+DiIWfAxUIe4HdpBB5GHHDM4Xa73aBAg8Oj8OapOtiYm8iAC6rvTBF07NkJyQ99nQEXVOtLfwIfVxgDLqiR0XF4t6QRCjKjIYLA0ZhaIc5xHKdj5KdTOI7jdI4R5ziOIxwjznEcRzhlEB93u2FnYTX0D43a/VCUrbt/GE6Vt9r9MJSurKELalt77X4YSrersBr6BkdAlZRB/Hd7S+DFfRfghy8XMuSCAN95tAqOX2yBoxea7X44ygKOK6x2H69hyAX17K6z8H/fOA8/eLnQWNGmQkog/td3yuDN0/XG3y82dDHkggDvG7z0nJ6uaGPIBQGOa8XGxt0MuSDA3zxzyYkL9V3ws1eLjC146pFH/GxNO7xypGLKbQy5OMDNGHIxgJsx5OIANztV2Qb/OloF1CONeO/gCPzXzrNTXvxmDLk4wM0YcjGAmzHk4gA3+/PBUihv6gbKkUb8t3tKoK13aNZ/Z8jFAW7GkIsB3IwhFwc4Njruhme2n4ahkTGgGlnE952pg8MXr4wHQy4OcDOGXAzgZgy5GMDN6tv74YV954FqJBFv6MAn/YLHH8+QiwPcjCEXA7gZQy4GcLO9RXVwxINBoYyRQ3x0bBx+tePMVW/+MOTiADdjyMUAbsaQiwHc7LnXi6F9julZWSOH+Ftn6+e9I4IhFwe4GUMuBnAzhlwM4FjPwAj85WApUIsU4rim87VjC1sSxJCLA9yMIRcDuBlD7n3AzQ6UNEB7zyBQihTiOGfV2Dmw4PthyMUBbsaQiwHcjCH3PuDY6Jgbtp+oBkqRQvzVo5Veuy+GXBzgZgy5GMDNGPJLeQtwsz2nakmdW4UM4qer2qC8qcer96kz5KIBN9MZcpGAm+kO+bNeBhwbGB6D3SdrgUpkEH9V0OGxOkJuFeA6Q24F4LpDLgJwsx0nqmF4lMYBQCQQr2nthdPV7cLuXyfIrQZcR8itBFxXyEUCjnX1D8PBkkagEAnE8UQ1otMBcrsA1wlyOwDXDXLRgFvpjjaIl9R1WvJ5VIbcbsB1gNxOwHWB3CrAsZJaa9zRAvHzFiGuKuSyAK4y5DIArjrkVgKOdfQNGaf4kD3pEa9u7TVOOWtlKkEuG+AqQi4T4KpCbjXgZiW1HSB70iNu15OoAuSyAq4S5DICrhrkdgGOFTPiC++chVMpKkEuO+AqQC4z4KpAbifgGI/EvVBL18IPs9cNciqAU4acAuDUIbcbcKylS/7zqEiP+PDouN0PgRTk1ACnCDklwKlCLgPgGH6LRyQwiDTisjyBFCCnCjglyCkCTg1yWQA3k/3ITekRHx6T5wmUGXLqgFOAnDLgVCCXDXBsZEyOgSRZxGUZicsMuSqAywy5CoDLDrmMgMsypUsacRmfQJkgVw1wGSFXCXBZIZcVcIynUxZYSIAvyJgMkKsKuEyQqwi4bJDLDDgWHOAHMic94qmxoSBrdkKuOuAyQK4y4LJALjvgriA/iAoNAJmTHvG0GHkRtwtyXQC3E3IdALcbctkBp+APxogTg1w3wO2AXCfA7YKcAuBYusQzAWQQTyWAuFWQ6wq4lZDrCLjVkFMBHEuLcYHsSY94clQI+Po4QHfIdQfcCsh1BtwqyCkBjqXHyT+IlB5xXx8nrFkUC1QSATkDLh5yBlw85NQAjw0LhEXxYSB70iOO3VyQDJTyJuQMuHjIGXDxkFMDHLulIBmcDvlnAUggXpAeDfHhQaAb5Ay4eMgZcPGQUwTcx+mAzfk0Bo8kEMduWk7jCfUW5Ay4eMgZcPGQUwQcW5MVC5GSrw8nh/gNeYnGb0cdIGfAxUPOgIuHnCrg2BZCU7hkEI8ICYDbVqYCxa4GcgZcPOQMuHjIKQO+LDkCVmbGAJXIII7928YsiI+gNTd+NZAz4OIhZ8DFQ04ZcH9fJ3zxtlygFCnEA/x84IFbc4HepMqVIWfAxUPOgIuHnDLg2Mc3LYakqBCgFCnEsZyUSLiV6LSKCfmuwhrj7+OTNDl8rokB9yLkzZ2Xrs06OumE/m+faWDAvQT5/tP1MD4+9ck8VdlGGvClSeFwx5o0oBY5xLFPXL+Y7LTKzcuT4cPXZBh/n7wG9QPLkyA6LNDGR6ZOG/MSIO791wceLGa2dW0a+PmSfMlLVaC/D2xbmwbOaQsNVmREw+e35ADB9QcQ4OeEL92WR2Jd+PQcbjfNsUlz1wA89dJxaOmW/2rUGL427l6fCR/bmDXrxwyNjMHrx6tJXGFbxvDHb1N+IixJjpj1Y3CEvuNolZQXG6FQUIAv3Lk+fc7ld4fONcKzu4thcETuiylMngf/1kdWQX5aFFCMLOKUII8ODYAHt+VDbmqkR1cRef14zcR0AOf5L8kP5CdBVlL4FT+2pQshrzZ+aXKeF/w+4BEerJ9u7OyHZ147DaWN3SBz/sQBJ484BcivWRIH/7ElB0IDPb86yAhCfqIGmjoYck8Bv7EgGTITPD/PRWv3oDEiHxxmyD0pJBABz4DwEH+P/8/Y+Dj89VA5/ONwBUybPpcifwUAVwJxE/Lv//0ENEk0eg3084FPb86GzflJ875A9N7CGmho7/f6Y1MpnMO8cUUSZMzjREXtPYOw/UgVDDDkV7y6zR3r0yEs2HPAJ1dS2wG/3HHG+MUpS8H+vvDIh1eQB1wZxDGcf/uft0vh9ZM1YPcXlJUQBg/dng8JEcELXgXwztkGKK3v8tpjUylccnrzqhRIiJz/89wzMAy7jtVAR++QVx+bKuEO4ttWpxpz4Qupb3AE/ntPCRw63wR2tyozBr5waw5Eu9RYSKAM4pN/6z/3erEto/LEiGC4c20a3JCXNGVVxEIrLGuBwtJWr92fCuGocMvq1KvavJ+t4ZEx2HOyFupa+7zy2FQpM8EFmwuSvfpaPlHeCq8croBzdZ1gx0XXP7M5G26c59axrCmHOIY7rP7yThnsPlljjGZFh+cc/tC6dFi3JE7YEiU8UOXgmQZLvh7Zi48MgptXpkCg/8JGh5PDNc8HixvgXI31uMjYikXRcE12vLD7P1/XCf84UgnHy1os2XJetzgWPndLjvQXPZ5PSiJu1tU/DPvP1sMbp+uEjMwL0qPgg+syLJtXa+rohzcKa8ks3RJRVmIYbMpPEnYytFPlrXD4vLUXZZYpHINcn5cIyzxYSeWNalp74Z9HK+GdkkYY9fIAxRXkZ2wV48msqB2FeTUpjfjkiqra4I2iOjhe3gKjY/P7kl2BfpCdHAE5KRHGOc7tuP4nHp6PSxDxT91alRUDqxaLv8pTRWO3cXi+bls9uFrjllUpkGLD6xp3Mp+oaIWS2k4oru2Y905QB57AKiUCthSkwLVL47U4uEsbxM3wMOz6jn5jBFDV0mP8Wd3SC/3Do+Dv6wN+Pk7jG48vaPwzNiwIcgy4I6W5aDNOF+GIvLFDj5UrOEWFB/Es9mANuLfCdfq7j1drs3IFR614RKss59Bu6R6AkpoOKK7thJq2XuPgLFyxNTI2Zvwd3/Dau6nRoZAWEwrpsS5Iiw01fkZxZZhOaYe4KumycsVYgbIyBRKiFrbSZz7psnLFWytQOHtixIlXVNEKxy+2KHlipyhXAGxekeKVFSgLWbmyr6geqpp7QMWWJIcbc+DeXIHCWRsjrkC4w/OtojqlzoKIO9bWZ8dJg8uZynY4fL5JmXlynDbEE4UtneM8MxyNGHFFwnlyXIJIfcSI+yJw/ns+R2CKrrV7AN4orDNWPVEu2hVgHCSFV8vi6MeIK1ZxdTscPd9McsQYGx5kHELvCrJv+sSTE5QdPNtIdl9EXlokXJsTDz5OObZwuIXHiCtYW/egMSpv65HnXBVXWn1SsCgaVi6Kuewc1bJ2oa4T3i1pInMmRDwD4aa8BCm3cLiFxYgrGl41qKS6A05cbIGRSVe3kS1cdXJdToJHpzeVrcHhUePAoPO1nVIfvJOXFgVrl8YaS2g59WLEFa9/cMS49FtFU490V4dZnx1v6dpvUTW298PbZxukW4qI01PX5ydATBjNq2BxnsWIaxJe2PbIuSbo7LN3pxzOlmSnRMLqJbHGGnBVwnOvnK5sg8KyVtuvGhTk7wNrlsRCTmokOAheboy7uhhxjcJvNa5eOVXeZsybWxkeXYfL2fIzoiE0yPMLZFALd3wWV3cYF2u2+mhPvPBIQWY0LEuNkGZpJic+RlzjkTme7En01YNwySCu+c7LiIIgL551kMLpHXCuHH9h9g6OCP1ceDAU7hRekhROZscw570Ycc3DEXllUzdUNvVAl5emWvAMg3gSpYx4F6TFhYKfxjvUcJqltq3POKkWPsfeWs2Ch8hnxruMS9IlRQXztInGMeLcRLhjrrKxG+rb+6Czd9hjcNAPvEhDdFggpMe5DMB1OHvcfEDH5xZ3MuMJtjp7hzxez4/TUXhyqvjIYMiMD4OEyCCGmzNixLlZGxgaNWDv7BuC4ZGpO+vQDzwoJyLUH8JDAoSd31vl8Eevu3/EwByf4+mg47x2RIi/gbdrnte35NSPEec4jiMcb/NyHMcRjhHnOI4jHCPOcRxHOEac4ziOcIw4x3Ec4RhxjuM4wjHiHMdxhGPEOY7jCMeIcxzHEY4R5ziOIxwjznEcRzhGnOM4jnCMOMdxHOEYcY7jOMIx4hzHcYRjxDmO4wjHiHMcxxGOEec4jiMcI85xHEc4RpzjOI5wjDjHcRzhGHGO4zjCMeIcx3GEY8Q5juMIx4hzHMcB3f4/NTiGy3wnsXAAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAABDCAYAAACROQIsAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAACHhJREFUeJzt3WtIFN0fB/Dv7loaVhqkVFBZYVkS2Y0K7EUkCBlFBlH6orAXYkEvigjCwi5Q0OXFv3pRECkYPPBEN9OUii4I3bPSMqzIoihJzCS1NHf/nOPexp1ZR591V/d8PzA4c+bMmTOz6/ntnDOza3E4HA4QEZGyrKGuABERhRYDARGR4hgIiIgUx0BARKQ4BgIiIsUxEBARKY6BgIhIcQwERESKYyCgsHfu3DlUV1cHpKzi4mI8e/YsIGURDRYMBBTWmpubkZubi6ioKJ91jY2NiIuLw/Dhw9HR0WGqvJcvX+Lo0aMDUFOi0GEgoLBWUlKC6dOnIzEx0Wfdrl27kJeXh87OTtTU1Jgqb82aNSgtLTUdOIiGAgYCCmuXLl2SjXdP9+/fl9PevXsxfvx4VFVVmSpv8eLFiI6Oxq1btwagtkShwUBAYautrQ0VFRU+gaCrqwtbtmzBkSNHEBERgdmzZ5vu97dYLFi9ejUuXrw4QLUmCj4GAgpbIgiIMYB58+Zp0k+dOoX4+HhkZGTI5b4EAkEElqtXr8Jutwe8zkShwEBAYT0+4GrsXb59+4Z9+/bh+PHj7jQRCMQgsNmGfdmyZWhtbcXDhw8DXmeiUGAgoLA1depUfPjwQZO2Y8cONDU1Yc6cObJbSEw5OTmyG+nNmzcyz4sXL5Camurepr6+HikpKe5A0dDQgPb2diQkJAT5iIgGRsQAlUsUcqIL58CBA2hpacHo0aNx584d2aXz4MEDOeDrIu4amj9/vhwwnjVrFpKSkvD27Vv3+oKCAuzZswdWa/fnpsuXL2PRokVykJkoHDAQUNhKTk6Wn9rLysqwdu1abN26Fdu2bZONeE+TJk2S4wTZ2dmIjIxEbGwsvn//Lp81EFcKhYWFmjuRMjMzg3w0RAOHgYDC/qpANNyfPn3C169fsXPnTt184irAe8BYXBnU1tbixIkTckzBRXQr3bt3D2fOnAlK/YmCwcLfLKZw9ujRI6SlpclP9+KTvln5+flym7q6Oty+fdudXlRUJAeaxTgCUbjgFQGFtYULFyImJgY3b970uYOot26lrKwsVFZWmnpAjWgo4xUBEZHiePsoEZHiGAiIiBT3n8cIxibOR2dbi/t7WCzOdItzxpXiWnbNe3K6lj0LFk1+r5zOfGI/utuKvO79uspw7r9nHXSWu8vr7inTHoc2zZvFsGfNK90niyfBuTu9TM4ko3RRH711furjtcriZ53PjjTrepyLXuuvXec5nYGqp9F5dmi31TkGM+u0h6C/nSfVa85fPQ1fJu3x+dTEb7UN6m28M+chGbwO7t0Zv64OPxXyOSeGxRi995zlG1fPz3tdrPLT421U/x4vuP+3Wm/Hbvz/r9nWsJj+nRchOT0d5eXlCGogEEEgdev/5LzNakGEtfvfz2a16i575xNpshJyvg/b2ay65ehtp93Wk89mcSDC2n029eZtlu6nSG1WByKcrbWYFw2/u/HXnbcbr3Mua+ftBuU43+gOu8lyDPL6K6cfdfNbb/gp0/lUrifdXL2N6ubeph/nVLccrwbE1Yj0nBfb2O2ecjxFOnS3czdG3ut6lmv3zWe0/+4q6JTpdzv9vEbbeV5C/3XR37/+OTTev35eM8ekl9dcvT3nUDefQ/98m359/WzX++urPYdmzoXreLzX/dPYiL5i1xARkeIYCIiIFMdAQESkOAYCIiLFMRAQESmOgYCISHEMBEREimMgICJSHAMBEZHiGAiIiBTHQEBEpDgGAiIixTEQEBEp7j8Hgo7Wn1DJvxcuhLoKRESGxG9tBz8QOH+LQBUXGAiIaBBr5NdQExFR0H+8Pjk5GSNGjIBKl11xcXGhrgYRka729na8evUKQQ0EREQ0tLFriIhIcQwERESKYyAgIlIcAwERkeICEghOnjyJBQsWIDIyEps2bUI4+PPnDzZv3ozJkydj1KhRSElJwfXr133yHTp0CLt378br16/lORgzZoyc0tLSZBoRUbDU1NQgPT0dY8eOhcViGZhAUFBQIKeeJkyYgPz8fOTk5GAo0juuv3//YuLEibh79y5+/vyJgwcPYt26daivr9fkKy0txYoVK+Q5EA+bNTU1yQc6Vq1ahfXr1wf5SIhIZcOGDZPt1NmzZ/u0XUQgdp6ZmSn/PnnyBJ8/f0Y4iI6O1gSHlStXYsqUKXj69CkSEhJk2o8fP1BXV4clS5bAZrMhNjZWpos7csXyu3fvQlZ/IlLPjBkz5NTXticggUAFDQ0NstEXD9C5VFRUYPny5bLRdxHB4NevX7Db7di/f3+IaktEZB4DgQmdnZ3Izs7Gxo0bkZSU5NMt5K25uRmtra0oKiqS4wtERINdr08Wiy6RyspKOf/792/5NyoqSv5NTU3FtWvX3HnFOIHoGiosLMRgZ/a4xCf7rKwstLS04MqVK7IPzpUuxgWqq6t1v3JCrBfptbW1iI+PD+KREZEqzp8/j9zcXDm/dOlS9w0tomsoMTFRdlMH5IrAu6F39ZnrDRgPNWaOS5xEceeQ6BYqKytzBwHh8ePH8hO/0fcOiUDQ1taGL1++MBAQ0YAQPRViGhS3j4o7bMSn6q6uLjmJeZE21OXl5clP9CUlJT5frCcCQ0ZGhnv5xo0bqKqqkscvrh62b98ubyOdOXNmCGpORCpyOByy/e3o6JDLYl7cCh+UQCBurRQN5eHDh1FcXCznRdpQ9vHjR5w+fRrPnz/HuHHjMHLkSDmJSzG98QExNrBhwwbExMRg2rRpeP/+PcrLy93dTUREwWi3RPvruqlFzIu7iHrDbx/tB9FVNHfuXNnt05eHNoiIBiN+xUQ/iAfMjh07xiBARGGBVwRERIrjFQERkeIYCIiIFMdAQESkOAYCIiLFMRAQESmOgYCICGr7P6pi6/KM2zLEAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for he in [0,2.0]:\n",
+    "        for step in [0,5,9]:\n",
+    "            tc_plot.ToricCodePlotter(z_cmap = charge_cmap, x_cmap = matplotlib.colormaps['binary']).plot_expectation_values(tc_plaq.ToricCodePlaquettes(\n",
+    "                code,\n",
+    "                x_plaquettes = np.zeros((grid.cols,grid.rows))-1,\n",
+    "                z_plaquettes = {(p%(grid.cols+1),p//(grid.cols + 1),):bitstring_to_expectation_value(occupations[(he,step)][p]) for p in range((grid.rows+1)*(grid.cols+1))}\n",
+    "            ))\n",
+    "\n",
+    "            title_text = rf'$ \\langle A_v \\rangle $ with $h_E =$ {he}, time = {np.around(dt * step,3)}'\n",
+    "\n",
+    "            plt.title(title_text)\n",
+    "\n",
+    "f,ax = plt.subplots()\n",
+    "ax.set_aspect(0.1)\n",
+    "\n",
+    "norm = matplotlib.colors.Normalize(vmin=-1, vmax=1)\n",
+    "\n",
+    "matplotlib.colorbar.ColorbarBase(\n",
+    "    ax, cmap=charge_cmap_r, norm=norm, orientation='horizontal'\n",
+    ")\n",
+    "\n",
+    "ax.set_xticks([-1,-2/3,1],labels=['+1','+2/3','-1'])\n",
+    "ax.set_xticks([],minor=True)\n",
+    "ax.tick_params(right=False,labelright=False)\n",
+    "ax.set_title(r'$ \\langle A_v \\rangle $')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c15671ff",
+   "metadata": {},
+   "source": [
+    "Next we can plot how the separation between charges evolves for many different values of $h_E$ ($h_E \\in \\{0,0.3,0.6,0.8,2.0\\}$). These results show a clear transition from deconfined to confined dynamics as $h_E$ is increased."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "9a77f2a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "for idx, he in enumerate(he_list):\n",
+    "    ax.errorbar(x = np.arange(len(separations[he]))*dt, y = separations[he],yerr = separations_sdom[he],marker='o',color = blues_color_list[idx])\n",
+    "\n",
+    "ax.set_xlabel('Time')\n",
+    "ax.set_ylabel('Charge separation (Manhattan metric)')\n",
+    "\n",
+    "plt.show()\n",
+    "\n",
+    "fig,ax = plt.subplots()\n",
+    "ax.set_aspect(0.1)\n",
+    "\n",
+    "bounds = [-0.05]+[np.mean(he_list[i:i+2]) for i in range(len(he_list)-1)]+[1.7]\n",
+    "norm = matplotlib.colors.BoundaryNorm(bounds, blues_cmap_r.N)\n",
+    "\n",
+    "matplotlib.colorbar.ColorbarBase(\n",
+    "    ax, cmap=blues_cmap_r, norm=norm, orientation='horizontal'\n",
+    ")\n",
+    "\n",
+    "ax.set_xticks([np.mean(bounds[i:i+2]) for i in range(len(bounds)-1)],he_list)\n",
+    "ax.set_xticks([],minor=True)\n",
+    "ax.tick_params(top=True,bottom=False,labeltop=True,labelbottom=False)\n",
+    "ax.set_title(r'$h_E$')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cbc9a122",
+   "metadata": {},
+   "source": [
+    "### String Fluctations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ffbe1a18",
+   "metadata": {},
+   "source": [
+    "Next we want to focus on the string of gauge flux connecting the charges. We can initialize that string by choosing the X-string we use to excite on top of the WALA state. In the present case, we excite `[cirq.GridQubit(-2,1), cirq.GridQubit(0,1), cirq.GridQubit(1,2), cirq.GridQubit(2,3), cirq.GridQubit(3,2), cirq.GridQubit(4,1), cirq.GridQubit(6,1)]`, which stretches across the entire grid as show in the schematic:"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "75a9b975",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07508b97",
+   "metadata": {},
+   "source": [
+    "This excitation initializes two charges on the extra charge sites to the left and right, connected to the rest of the system by two additional qubits. By not applying the local field terms ($h_E Z_l$ and $\\lambda X_l$) to these qubits, we can keep the charges on their initial sites and monitor the behavior of the string with pinned ends.\n",
+    "\n",
+    "We will monitor the string dynamics by measuring the two-point correlator $\\mathcal{S}_{ZZ}(t)$ defined as:\n",
+    "\n",
+    "$$\\mathcal{S}_{ZZ}(t)=\\Re[\\langle Z(t) Z(0) \\rangle] \\times \\langle Z(0) \\rangle.$$\n",
+    "\n",
+    "Inspired by the implementation of these circuits on the quantum hardware, we utilize an auxiliary qubit to measure the two-time correlator $\\Re[\\langle Z(t) Z(0) \\rangle]$ for each qubit. Then we measure $\\langle Z(0) \\rangle$ to get the second term in the product. Let's make the list of circuits to simulate:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "b901211c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he_list = [0.1,0.6,1.4]\n",
+    "dt = 0.3\n",
+    "coupling = 0.25\n",
+    "trotter_steps = [0,2,4,9]\n",
+    "auxillary_qubit = cirq.NamedQubit('a')\n",
+    "string_excitation_indices = [(-2,1),(0,1),(1,2),(2,3),(3,2),(4,1),(6,1)]\n",
+    "string_excitation_qubits = [cirq.GridQubit(idx1,idx2) for idx1,idx2 in string_excitation_indices]\n",
+    "\n",
+    "time_evolution_circuits = []\n",
+    "\n",
+    "for target_qubit in grid.physical_qubits:\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            time_evolution_circuits.append(cirq.Circuit.from_moments(\n",
+    "                cirq.H.on(auxillary_qubit),\n",
+    "                *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "                cirq.Moment(cirq.X.on_each(string_excitation_qubits)),\n",
+    "                cirq.CZ(auxillary_qubit,target_qubit),\n",
+    "                *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he,extra_z_plaquette_indices=[(0,1),(3,1)])*step,\n",
+    "                cirq.H.on(auxillary_qubit),\n",
+    "                cirq.Moment(cirq.measure(auxillary_qubit,target_qubit, key=\"measure_all\"))\n",
+    "            ))\n",
+    "\n",
+    "initial_state_circuits = []\n",
+    "\n",
+    "for he in he_list:\n",
+    "    initial_state_circuits.append(cirq.Circuit.from_moments(\n",
+    "        *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "        cirq.Moment(cirq.X.on_each(string_excitation_qubits)),\n",
+    "        cirq.Moment(cirq.measure(*sorted(grid.physical_qubits), key=\"measure_all\"))\n",
+    "    ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1ad5a60",
+   "metadata": {},
+   "source": [
+    "We have now expanded to 20 qubits and our observable requires the dynamics to be run separately for every gauge qubit. This means the simulations are a bit more expensive and may take up to one minute. Enjoy a short break while qsim does its work!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "8cabb739",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_string_dynamics = simulator.run_batch(time_evolution_circuits,repetitions=reps)\n",
+    "results_string_initial = simulator.run_batch(initial_state_circuits,repetitions=reps)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b564aef",
+   "metadata": {},
+   "source": [
+    "We can now take those bitstrings and assemble $\\mathcal{S}_{ZZ}$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "e42ffad0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "zz = {}\n",
+    "\n",
+    "counter = 0\n",
+    "for idx,target_qubit in enumerate(grid.physical_qubits):\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            if idx == 0:\n",
+    "                zz[(he,step)] = []\n",
+    "            bitstrings = results_string_dynamics[counter][0].measurements['measure_all']\n",
+    "            zz[(he,step)].append(np.mean(np.sum(bitstrings,axis=1)%2))\n",
+    "            counter+=1\n",
+    "\n",
+    "z0 = {}\n",
+    "z0_sdom = {}\n",
+    "\n",
+    "for idx,he in enumerate(he_list):\n",
+    "    bitstrings = results_string_initial[idx][0].measurements['measure_all']\n",
+    "    z0[he] = np.mean(bitstrings,axis=0)\n",
+    "    z0_sdom[he] = np.std(bitstrings,axis=0)/np.sqrt(np.shape(bitstrings)[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e5495cb2",
+   "metadata": {},
+   "source": [
+    "Using these measurements, let's calculate $\\mathcal{S}_{ZZ}(t)$ and plot it as heatmaps:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "8f58c501",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAErCAYAAAAokrM1AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAAP+VJREFUeJztnQVYVGn7h39iIJhYYOvasXa37toBqKDYiN1dmNiKoiKooGs3oIDdoruu3b22a6JigQh4/td79g8fqDBn4syp574uvm+dOs+cOfOc9/3d78yk4jiOA0EQBKFILKQugCAIgjAcauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWA038THjx8PW1tbpEqVCmvWrJG6HNXToEED9OrVK8Xb9OjRA7///rtZ6pk/fz5+/fVXs2xL6ZjzdSEU3sTDw8MxduxYlCpVCtbW1siWLRuqVauG9evXm3Q7p0+fxpw5c+Dn54fnz5+jQ4cOJn18wjAWL16M7du3J/ybNQ7WQMTgwoULqFChAuTGnj17+LosLS1RqFAhLFy4UPB7p3///siTJw9/38KFC8Pf31+vbSe3v79/XZTG/PnzUbNmTdjY2CBr1qyoU6cO9u3bl+zt2X5ng7vv/8qUKQM5kQYy4+XLl6hSpQqKFy+OpUuXokiRIvyBeeTIEaRJY9py7969CwsLC9jb2xv1OF+/fkW6dOlMVpfWyZIli9m2xZp4nz59ICfOnTvHH5OjRo3C5s2b+cFGv379+AEN+//k+PTpE+rVq4e8efPy9ytYsCA/OImLi1Pc6yIGR44cQc+ePVG1alV+X65cuRKtWrXC8ePHUbt27R9uf/bs2ST7ju3fcuXKoWPHjpAVnMyYMmUKlyFDBi4qKkrU7XTv3p19Z0ySP8bXr1+5sWPHcnny5OHSpk3LlSpVitu4cWOS+9avX5/r2bMnN3HiRM7Ozo6ztbVNdjuRkZFc7969ucyZM3NZs2bl+vfvz40bN44rUqRIwm0OHDjAP6aNjQ1/u3r16nGnT5/+YZtubm5JLps+fTpXsGBBvbbFWLJkCVeiRAnO0tKSK1q0KDdjxgwuJiYm2efAXot+/folPC777+8fV0h98bdzdXXl93H27Nm5TJky8TUnfr3Za/Pbb78l+zodPXqUO3HiBFerVi0uY8aM/F+5cuW4ffv2cfrw8eNHLlWqVNwff/zBOTk58bXkypWLW758OSclLi4uXM2aNZNcNmrUqB/25fdMnjyZv82XL18M3nZy+/v71yXx+8Dd3Z3LmTMnlyVLFm7ChAlcXFwcN23aNH5f5siRg7/se/Q9BsXi119/5UaMGCHotn5+flyaNGm4Z8+ecXJCdk188ODBnLW1NXf58mVRtxMREcEtWrSIS506Nff8+XP+L/7Nki1bNm7btm3c7du3uZkzZ/Jv9EOHDiU5eFnj6Nu3L3f9+nXuypUrKT4fdjAHBwdzt27d4psfa4aJG2BQUBC3detW/vpr167xzZA19PDwcL2apJBtsZNkgQIF+G3ev3+f2717N5c/f37+hJQcw4YN49+kO3fu5G7evMmNHDmSb3iGNnF23169enE3btzgQkJC+Mdm24gncbNgr1PdunU5Z2fnhNcpOjqa3z/Dhw/n7ty5w/+x5xMWFsbpA7s9a1KVKlXin9u9e/f4x2Rv1E+fPun1WOw4YYOPlP7YbYTAXh/WBBPDjj9W65MnT5K9X5kyZbjOnTvzJ282uGBNkh3Pnz9/Fvw8ktvfyTVxdnyNGTOGf6+sWrWKr7FZs2bc6NGj+cvWrFnDX7Znzx6jjkFT7t942MmGHZ+TJk3ihFC5cmXO0dGRkxuya+LsjV28eHH+hS9ZsiQ/6jt8+HCS27BmUb58+YQ/NmqOf+OldN33rF69mm/i8bCDPV26dJyPj0+S2zk4OHANGzZMcvAWK1aMPwhSgm2TPd7KlSuTXF69evUfRseJYY/LRrwbNmwQ3CSFbIs9PysrK27v3r1JbrN27Vp+FJXcc2CjJTYK+f6ANrSJs8tiY2MTLluxYgW/jfjX6Ptmwf6bXRbP27dvk4wQDWXx4sX8Prt7927CZZcuXUrSLFkTYifGxMfUz04Wb9684R8npT92GyGwGSDbJ4lhJ3dW15kzZ5K9X/r06fn9yBr52bNn+ZM5a46dOnXSY6/8uL/j+VkTZ/sjMaVLl+bKli2b5DI2S2InfkOPQVPv38THJ9tmSifGeNj+ZPtf39meOZBdJs5k5q1bt3DmzBkcPnwYwcHBWL58OYYPH54gd1iWFc+zZ89Qq1YtXk5myJAhxet08c8///D5NssVE1O/fn3Mnj07yWWVK1fm83Qhj1ejRo0klzO5EhoamvDvBw8eYPLkyTh16hRevXqFb9++ITIyEo8ePdJZsz7bun79OqKiotCuXTte0MTDcr8vX77g9evXyJkzZ5L737t3D9HR0fx+TAyTQrt27YIhMEmdOnXqhH+zPJJtg22LZY66YGKKrXBp2rQpGjVqxL8+jo6OKFGihN55eJMmTVC0aNGEy1gNLC9lYpBx+fJlTJ06lZeFKcHkO/uTEnbcZM+eHatXr0batGn5y9gx4eTkBG9vb1HqK1++fJJ/29nZ8X/fX8aOa0OPQTH2r6+vL2bNmoWQkBDky5dP5+1XrFjBS2J2vMgNWa5OYS9u9erVMWHCBF7qtGzZkj8wv+f9+/do1qwZ+vbtC1dXV8HXmQIhJ4V4Eh+sP4PJlcePH8PHxwd///03Ll26hFy5cvFvwHjYCeP7r36PiYnRa1vsTc5gKwzYNuL/rl69ykteY94kQuszFWzFxfnz59G4cWNeTJUtW5Z/o+nbxL8/ObHL2Ikk/gR95coVVKxYUedjsYaQMWPGFP/YbYSQO3duvHjx4gfhH39dSvdjCwLiGzgjfiWFPgMCfUi8rfjj72eXxR97hh6Dpty/np6eGD16NN/AhSyZ/PDhAy+KmQDX9V6WAtmNxH8GO3OzppYYNnJjBp+tO2ZrvYVelxJsRMaWZYWFhfFNIZ74JqEv7PHYqhU2wi5dunTC5axRx/PmzRvcuHGDX1LGRpaMp0+fJoxc4mHPn80svm84+myLvaHTp0+P+/fvo0WLFoKeA1sdxB73r7/+SrK06s8//9Srvp9Z//jROHtstt/Ztn4G2/7PVliw14T9jRgxgl+1wWZc7KQtBDbqu3nz5g8NmtVcqVKlhH+z5sLevPFNvXPnznwD+B62fWdn5xS3KfQkyWYm+/fv52dn8bClcGy1SUqjxrp16+Lo0aOIjY1NWMl1+/bthOVyQkluf5sCQ45BU+7fyZMnw8vLi3+/sRmcEDZs2MAPqMQYDKquiXft2pV/I7PRFTtY2fIoNuJiTXTLli0Jt2Nnc/ZmYh/SWbRoUZLHSOk6XbBp9JAhQzBp0iR+SsemigEBAXykc/DgQYNG66ypTJw4ka+HjZLWrl3LN4/4KSOLBth/s+fJnjtr6mPGjIGVlVWSx2IjBjalZyMY1nhYXSdOnODXuwrdFhutsNkN+2MjCvaY7A3PGtXFixcxd+7cnz4H9gaKf1wWWaxatYpvDolPrLrqSwx7jgMHDsTQoUP5NzPb36z25GY3bBrLmhOLOtgyt3fv3vGxWevWrZE/f37+5MG2lbj5suWp7I9Fcz+DjbDZc098n/gmzqb6DHb8ZcqUib+tLkw53WfRIZshuLu78+8JNhtlcQhrPik9P7Ykcdu2bRgwYAB/YmP1s8u6devGH2dC+X5/s7/vR9eGYsgxaKr9O2zYMH62xkbV7DiOn+2w91r88smf7Vd2HwcHB/74lyWcjPDy8uLNOFutwIRToUKFeEt+7ty5JLdj9p2JxnhrLvQ6XWJTnyWG30u85Ihf9sdWZDCJwuobOnRoEvlz7NgxXv4wKcWkbkBAAC8NmcVPXBe7X/xSrgEDBvBW/WdLDFPaFsPf358XUmx7TKBWq1aN8/X1TfE59OnTh1+JwP7YNr5fYiikvsRLDONXAbFVPmxfsm0kJ9DYqhF2XLAVCOyQ3bRpE79KIG/evPxxkjt3bn61C1tZEQ/bdykd3mwZIbt/Yp4+fcrf58KFC/y/mXxr1aoVJwW7du3ijwn2/NhKjgULFiS5Prnnx1axVKlShX9t2b7/fnUKO+bZ/R48eJDstr/f3yktMfz+ffAzKdq0aVNethpzDJoCfLd0Mv4vcb3f79dTp07x/068Ok1upGL/AwUxffp0BAUF8aPzzJkzC75OTjAZx0ZGgYGBit0Wk31smsmEqlqZN28eL9rYJ/3UAosT2LHAhK2pPzxHSIOiXsWHDx/yByHLBhOvIGHTHDblSe46li9KBZsmsik6WyXCcjX21QFsqrp3715Fb0sLsEZ37NixJFEay6a/X32hJNiKIibQqYGrB0W9kkzOpDRxkOOkguV+y5Yt47N2lteXLFkSO3bs4FfOKHlbWmDjxo1QG8nJZkK5KC5OIQiCIGS+TpwgCIIQBjVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQEycIglAw1MQJgiAUDDVxgiAIBUNNnCAIQsFQE5eQz58/Izo6WuoyVM27d+/AcZzUZaiWb9++ISIiQuoyNA01cYkICwtDoV8Ko2Llyrh//77U5agO1rjnzpuHnDlzoku3boiKipK6JNXx4cMH2Ds4wNbODn7+/lKXo1moiUvQXJZ4e8OhXVv0mOmOqo7NUa1Gdezfv1/q0lQ1w3Hu2AF+69fAPWg17r15gRq1a+HJkydSl6Yabt++jSrVquJbZivM37ERs+bNRZ9+ffH161epS9McqTiaa5qNL1++oHffvjh55m8MXDILtgXy8ZffOnsRK0ZNwajhIzB2zBikSpVK6lIVy4MHD9CyTWvYFCkA54nDkS69JX/iPLxmK8I2BiJg6zbUr19f6jIVTUhICFzd3OAyciCadGjLXxb58ROWjJqIbx+jsCMoCLlz55a6TM1ATdxMsFFgGwcHWNtlh+uMCbC0tkpy/ZvnL7FsmDvKFiuJdWvWIEOGDJLVqlQOHDiATl274PeenVCvk+MPJ8Obf53FBvfZmDxxEoYOGUInSwPyb4/p07FsxXKMWjofJSqW++H6AB9/HN66AzsCg1CjRg3JatUS1MTNlH87dXBGoy5OaO7WOdnm8TU6GhumeeLl7fvYFRKCX375xey1KhF2CM+bPx/zFnii25yJKF61QrK3DX/yDKtGTEbtKtWx0s8PVlZJT6ZE8vl35y5d8OD5U76BZ8uVM9nbnjl8DMvGe2D2rNno07u3WevUItTERYTtWu+lSzHVYxp6zZmMX+tUF3Sfw5sCsXv5GmxYtx7NmjUzS61Kzr+7u7ri0q3rcF04Ddnscum8T3RkFLZM9UTUi3CE7gxGgQIFzFKrUrl16xbaONijWJUK6DlpDNKmS6vzPk/vP8S8fiPQ5LffsHSJN9KlS2eWWrUINXEx8+8+fXDy7Okk+bdQ4nPykcOGY9zYsTT1/wlsVU8r+zbIVrQgnNyH8fm3UPiT5dqtCNsQiO1btqJBgwai1qpUgoOD0bNXryT5t1D4nHz0JHz7EEk5uYhQE5cg/xZKfE5epmgJPifPmDGjyWtVcv7t0qUzGrt1/mn+LRQ+J584B5PdJ1JO/l2+Pc3DAyv8/TDSe94P+bc+jxOfkwcFBKJmzZomr1XrUBM3McePH+fz79+6OqeYfwuF5eTrp3ni1e37CA0ORpEiRaBl4td/z1+4QGf+LZTwp8+xavgk1K5SDSv9/DWfk7P8u1Pnznj08hmff9vkzGH0Y549fBy+46dh1sxZ6Nunj0nqJP6DmriJ139Pm+4hOP/W57EpJzcs/xYKn5NPW4Co5681nZOz/Lu1fRuUqFYJrhNHC8q/hRKfkzdu1Ag+3kspJzcR1MRNnH8P8p6NXPnzirIdLefkxuTfQtF6Tv5f/u2GTiMHobGe+bdQKCc3PdTEZZJ/C0WLObmp8m+haC0nN1X+rc/2KCc3HdTEZZR/C0UrObkY+bdQtJKTi5F/C4VyctNATVxm+bc+NRzZHIRdy1arMicXM/8WitpzcjHzb6FQTm481MRlmn8L5fa5S1g+crKqcvL4/Ds7y78nDkNaS9Pn31rPyc2RfwuFcnLjoCYu4/xbKG9fvILv0AmqyMkTvv/ErRPquYiff2stJzd3/i0UyskNh5q4zPNvofDfu+LhiZe3lJmTx+ffniz/njsJxaqUh9xQek4uZf4tFMrJ9YeauAA2btqIwUOHSpZ/G5KT79uzF1WqVIFS6NqjO05dOCdZ/m1ITn7q5J+wtraGEggPD0fN2rUkzb/1zcnb2Ttggaen1OXIHvpRCAF8+vQZadKkgXUmeX89LJsdZMiSmZ+asuxeSbCf+EqfwRrpLOUtttKkTQvrLJnw6eNHfj8rhbi4OERGRiJjlsxInSY15Ex6KytYZbBGxHv62TchUBMXAJvW+S1bDu+BYxEWGAo5Ehcbi22eSxHqvRJHDx9BnTp1oCR2BgahWZ0GWNBpAJ7cugs58iH8LXz6jEK691G4cO68otyDra0tX/OTKzcxu89QfPrwAXLk+pkLGNu2C7p2cOEjK0I3FKfouSSrVZs2+KVqObiMG4Y0MpmSfnz3Hn6jJsPGMgMCtm1D9uzZoVS2bNmC/oMGwnHMQFRt8TvkwsOrN7F61FT0dnXDdA8PWFgoc/wTExODYSOGI3TPboxZthAFisnDnbA2tG/DNmxf6o/1a9eiefPmUpekGKiJ68n79+/h8v9yqJ/XDGTNKW3DfHzrLnyGjIeLUwfMnTOHj32UzpUrV9Da3h4lG9RA66G9kVri53Rqxx6ELvbHH/4r4ejoCDWwevVqjBw9Cn1nTETNpr9JLuX9Js/C0xt3ELIzGEWLFpW0HqVBTdwAWBY6ZdpUrPD3x4BFM1CkfFlJ6vh790FsnuXFf0jCxcUFauLt27do38EZrz5/QPd5k5Axaxaz1xAXE4ug+T54dPYydoWEolSpUlATZ8+ehUNbR9R1aImOw/pLMrsIf/4SngNHoWSRoli3Zq2iIiq5oMw5ocSwg336NA/4+S6TJCf/Pv9WWwNnZMuWDQf37Uez2vWxwKW/2XPy7/NvtTVwRtWqVf/LyS/fkCQnj8+/uzh3ROD2AGrgBkIjcYXl5GrKv+Wak6sl/5ZrTk75t2mhJq6gnFyN+bfccnI15t9yyskp/zY91MQVkpOrOf+WQ06u9vxbDjk55d/ioO55ogpyci3k31Ln5FrIv6XOySn/Fg8aics4J9di/m3unFxr+be5c3LKv8WHmrhMc3It59/mysm1nH+bIyen/Ns8UBOXYU5O+be4OTnl3+Ln5JR/mw+aO8ooJ6f8W/ycnPJv8XNyyr/NC43EZZKTU/4tfk5O+be4OTnl39JATVwGOTnl3+Ln5JR/i5uTU/4tHdTEJc7JXz99Tvm3iDl5l1njccBvA+XfIubk7Dc6FwweQ/m3VLAmTpifHTt2cFmz2XD5CxXkLl26JHU5qiM2NpYbOWoUlzZdWq5pi+ZcRESE1CWpjhcvXnC16tbhLNOn52bOmsV9+/ZN6pI0CY3EJeTly5dInz49smQx/zf0aYV79+6hcOHClH+LmJM/ffqU38eENFATJwiCUDA0PCEIglAwqmrir1694pc5EeJNnZk0JMTj06dP/A8aE+IRHh7O/3C0WlBNEw8ICOB/DNbbx0fqUlQJOzl26+mKPPny4tq1a1KXo0oiIiJQ8tcyqFyjOqKioqQuR5WcPHkSdrlzY+z4cVALqmjirKn06tsHbaaPxOSpUxAWFiZ1Sapjqc9ShBw5gOh6pdGkZQu8e/dO6pJUt/TUsYMTXufJiEdpotHdrSfNKk3Mv//+i7ZO7dHSfRDWbdqILVu3Qg0ovomzZtLSvg3qDOyCEo1qobH7ALRzdsKTJ0+kLk01nDhxAmMnuiOyVWWgwi94kzsD7Nu3U9WUVGrGT3THmfu38PX3cohqURG7TxyF1+JFUpelGqKjo9HawQG/OjZBueYNYT9rDPoN6M9/OEzpKLqJsybSvkMH2FUti9LNGvCXFa5eEWXbNkVrB3t8+fJF6hIVD1s+1qatI6KalAds/vsQx9d6pXH+8V2MUdGUVEoCAwPh7bcckY7VgNQWQLo0iGxfHROnTcWxY8ekLk/xcByHPv37ITZLetTs1o6/zK7EL2g41BWt7Nso3vMouolPmOiOR+9eoc6ALkkur9LZHnHZMvIRC01JDYedBJu2aomPv+YDfrH73xUWFohsXhHLVq/Ctm3bpCxR8dy4cQPd3Hoiql11IGP6/11hkxFRbSrDoX07PH78WMoSFY+vry8OnTiO5u6DkCpVqoTLyzatj/y1KqFdB2dFzyotlCwyV61di6ZTh/7wPdLshfptXD8cPfUniU4DYSc/1969cD/uI+Kq/uR7MKwtEdWyElz79CbRaYTIbNKyOSIblgby/uQLz4rkxqcqhfgTKYlOw0Wm+5RJcJg9FumsrX64vsGArvj3w1tFi04LJYvMFjNGIIPNzz/tmM4qPVrMINFprMj80rg8Oyv+/EZ2NoisW5JEp5EiExV/SfZ2cTVLkOg0UmQ2dx+MbPlz//Q2FmlSo7XHCEWLTgsli0y7kin/ZJRNPjsSncaKzHQ6vlGxTAESnUaKzBRJlYpEp5Eis2ityine1jprZkWLTkU1cdYknDp2TCIydUGi03iRqQtedD66q+gpqaQiUxeJROfx48fNUaLqRKYulCw6LZQmMh+8efGDyNQFiU4jRaYumOhsQaLTKJGpi/8Xnfbt25LoNFBk6kKpotNCaSKz2bRhev8gbmLRuWTpUtFqVLXI1IW1JSJJdBonMnXBRGdlEp3GiExdxIvOMePGQilYqEVk6iJedLIfZCDRaaDI1EWC6GxOovMnItPBub1OkakLEp0pi0zH9u1SFJm6iBed6zdvUozotFCTyNQFiU4TiExd8KIzI4nOn4jMsw9u6xaZuiDRmaLILNe2qU6RqQuliU4LtYlMXZDoNF5k6oJEp5EiUxckOo0WmWoSnRZqFJm6INFppMjUBYlO40WmLkh0Gi0y1SI6LdQoMnVBovN/IvNB3CfDRKYuSHTyIrMxE5mNyhgmMnVBohNMZE6cMtlgkSlEdD77+E7WotNCrSJTF1oXnfEiM6pxOcNFpi40LDrjRWY4E5kVxPv9SS2LzniR2cx9kMEiU4jobDVtuKxFp4WaRaYutCo6TSoydaFR0WkykamH6Fy0ZDG0gilFptJFp4UsRWYV04lMXWhNdIohMnXxta62RKfJRaYQ0dmuOtynTtGE6BRDZCpZdFrIUmQONK3I1IVWRKdoIlMXqbUjOkUTmbrIph3RKZbIVKrotNCCyNSFFkSn6CJTFxoQnaKLTF1oQHSKLTKVKDottCIytS46zSIyNSw6zSUytSw6zSEylSg6ZdHE/1i9GnkqlhZdZAoRncV+r4UlPuobjc/38kJkxULii0xdlMqPd18isXfvXqiJ+/fv48TRY/haq4S0hTDRWbs4Ardu42cGamL79u3IYJsDRWpWkrQO66yZUb5dc9l8YlYWTdx9wgR8/OcJbh46KWkdj89fxf0jf8Nz7jyojTX+K2H1523g/WdJ60h78iYqlCgFZ2dnqImiRYti0JDBsA49D8R9k66QmFhYh5zHjNkzYWNjAzXRt29fZLJIizObgyWt49W9Rzi7YQeWLZXHr4bJoolnz54du4JDcGLxGry6+1CSGt6/eIV9Ht7YumkzChUqBLXRqFEjTHOfBOtdF/g3uiTcfAKbx+8QGrQTaczsPczBwnmeqJC7ENIelSjz5zik33sJjavVxrjR8slsTYWVlRV2B4fgwpZduH/mkiQ1RH34hJ3j52LJosWoVEnaGYGsmjijfPny8F3qg90TFyDq/UezbjvmSzT2uC+E+7hx+P3336FWRo0ciWa16iL9oav8G96svIqA9fEb2L9rD3LkyAE1kjp1aoQG7kD2h++AK+YfjFicuYt8URbYtHadWVdtmJMCBQogYOs27PFYgnfPXpp129/i4rBrqhecHdqhW9eukAuyaeKMTi4u6OLcEfunLcG3WPMs4WHy58h8P9SqWBmjRoyEmmFv7PWr16JAnCUsLtwz34ajvvIzAD+fZahQoQLUTLZs2fgTlfWha8BzM8rbBy+R8e97OMC2bW0NNdOgQQNMcp+I4PHz+AGYuTjhvxk50ljBa8ECyAlZNXHG/LlzYWeVCX/5bTbL9i5u343Yf99g9cpVqh29JIa9wQ/s3oOMFx4Bj16Jv8FvHKz3XULPTl3QuXNnaIFy5cph5fLlsA46DUSaoclEfIZV8FkEbNmKwoWlWxljToYPHYo6Vaph/2xfs6zCuXnkT9w7fAo7AgJlFwXKromzHcR21JOT50UXnUxkXtwUit0hIaofvSSmYMGC2LE9AFb7LokuOpnILGebH16e8hq9iI1LRxf06tIN1jvPiis6mcgMPI1J48ajcePG0ApswPWH/0rEvnwnuuhkIvOQpz9CdwYjZ86ckBuya+LmEp1qF5myEJ0qF5mSi06Vi0w5iM4oGYpMRTTxeNHp471UFNGpFZEpqejkReZNVYtMqUWnFkSmlKLzm0xFpmKaOKNzp07o7NTBpKJTSyJTMtGZIDJ9VS8yJROdD14ig0ZEplSi84RMRaaimjjDc948k4pOrYlMs4tODYpMs4vO/xeZgRoSmeYWnTdlLDIV18QTi85bh/406rG0KjLNKTrT/nlLkyLTbKKTicygM5oTmeYUna9kLjIV18QTi86wxasNFp1aF5lmEZ1MZD56q1mRKbrojBeZVWtpUmSaQ3RGKUBkKrKJGys6Y6JJZOolOg8bIDpJZOonOq/qPxghkSmu6PwWF4fdUxfJXmQqtokbKjpZPnZ0vj+JTH1EZ6yeopNEpv6i86CeopNEpt6iM2TCfL1EJxOZ2dOkl73IVHQTTyI6/bcIFpkxT8NJZOorOi8+FiY6SWQaJDpXrVghXHSSyBRddN5UkMhUfBNPEJ0nzukUnSQyDRedOwWKThKZhtGxQ0f07tpdt+gkkWkQqVKlwio/f0GiU2kiU/FNPF50sh2ekugkkWkcDRs21C06SWQaxYK581MWnfEis0pNEpkiic4oBYpMVTRxBstemejcM2kBoj4kFZ0kMs0gOl+/J5Epsui0OPsP8n5OhY0kMkURnd8UKjJV08TjRWen9kx0evMvCINEphlEJy8yz5PIFFN0PnyJDKf+wcE9e5EhQwYpS1St6DyhUJGpqiaeIDrTZ8Rffv+JThKZIovOeJHpQiJTNNHJROZOEpliis6bChaZ35OKU8FPYr958wYVKleCXc3yuH/4FM6fOUs5uIk5evQoWrZ1QEyhnKiSyQ4njhxT/MEvN4aNGgH/XYHAlxhMHDAE48eMk7okVREVFYVqtWrCqmhe3DlyCkcOHlJsDq66Js64fPkyWjvY8x+9pRxcHBZ6eWHFHyvx59HjlIOLQFxcHJrbt+Z/4HjLug00kxSBx48f4/emTTBxgruic3BVNnGCIAgtovhMnCAIQstQEycIglAw1MQlloVXrlyRugzVEhsbi02bNuHdOzP+6rzGePHiBbZv345v30T8HVEiRaiJSySwRo8dg5ZObVGjXh2sW7dO6pJUR3h4OOo0agC3kUNQpkJ5XLsm0u9capi///4bpSuUQ7ch/dG8TWt8/Gjan1EkhEFN3MxERESgUbMm8N25BVF9GyOqewP0HzMCAwYP4keOhPFcvHiRb9wXUn/ClwHN8LxqAVSvUxvbtm+TujTVsMLPD42aN8W7puXwZVALHH/3CGUrVcCdO3ekLk1z0OoUM3L9+nU0adkc4QWy4GuTCkDq/z+HRkXDOvA0ytjkxu4dyvwSHrmwYeMG9B04AJHNKgC/JvqswLM3sN5+Cv17uGHu7Dn8R94J/fn69Su/f7ftCUWkS20gZ5aE61KduYMMR69j09r1aN26taR1aglq4mYiICAA3Xu7IfL3ckClX368wbdvSHvkGrLeeol9obtU8SEEc8JmMUNHDMeabZsR6VQTsLP58Uafv/Any8r5iyB4eyC/HpsQzvPnz/l17HeiIxDVtjqQPt2PN3r0Clbb/sKoQUMwdfIUWFjQZF9sqImbIf8eN2E8fP5YiagOtYC82VO+w9VHsNpzAcuXLEW3bt3MVabi8+9WbR1w9c2/iHSoBlhbJn/juG9Id+gKsj+K4L9OoGzZsuYsVdH5dwuHNvhYvgBiG5QFLFL4INKHSFhv/Qt1SpZDwOYtyJQpkzlL1RzUxEXOv+2d2uHc47uIbF8DyGgl7I4v3sF62yl0a98B3l6L6OPtOvLvZq1b4l3xXIhpyJqLwJHfxfuwPnQVq/394ezkLHaZis+/h48djag2VYHS+YXdKTYOlnsuwPZVFA7u3ovixYuLXaZmoSYuev6dFV+blP9f/i2UqGhYBZ5GWcrJk2XDhg3oO2gAIptXBMoW1P8Bnr2B1fZTGEA5uY78OwSRLnWS5N9CYTm59dHr2Ew5uWhQExcz/25cDqj4k/xbKJSTG55/C4Xl5EGnUTkf5eR6599CoZxcVKiJS5l/C4Vy8h/z7/B/EemoI/8WSkJO/g4Hdu/VfE6uV/4tFJaTb/sLdUr8ioDNWyknNyHUxE2ef//z//l3etNugHJyw/NvoVx6AOuDVzSdkyfk3/ZVgVIC82+hUE4uCtTE5ZB/C0XDObnR+bdQNJqTmyL/Fgrl5KaFmrhc8m+haCwnN2n+LRSN5eQmzb+FQjm5yaAmLrf8WyhXH8F670UsW+yt2pxclPxbKBrJyUXJv4VCOblJoCYux/xbKC8j+A9VqDEn/1/+bYuYhmVMn38LRcU5uaj5t1AoJzcaauJyzb+Fwr53JegMymS1U01Ozuffgwf+9/0nYubfGs3JzZl/C4VycsOhJi7n/FtjOXmS/Nu5JmAroyxaJTm5JPm3UCgnNwhq4krIv4Vy7RGs9ygzJ0+Sf7etBliZMf/WSE4uaf4tFMrJ9YaauADGTBiHJWtWIdq1kXT5t1BeRiCN/wFsWb8B7dq2g1Io8WsZ3LeOQ2yrKtLl30I5cweWBy/j2dN/kS1bNiiBBw8eoFiJ4ohzrpP0K3rlSGwc0m77E1Wy5cNfR49LXY3skfm7RR60beMA6zggzfl7gJzPeTGxSP/nbRQuXBjVqlaDkujn1htp7zwHHryErHnzAdbnH6Cds5OiRom2trZo0rwZrE/dBd5/hqy59RRpHr1G3x49pa5EEdBIXCDPnj1Dszat8E/sR0Q5VAUs00JWvPvEf6KzabXa2LBmLaytraHE3xx1cGqPT9WL4FvNEkAqmU337/wLq5BzmDdjJgYOGIhUcqtPB+yt7jFjBuYuWogo5hwK2UJWfOOQ5sgVZLn2DHtDQlG1alWpK1IE1MT1IDo6Gr369UHQwX2IZNl4jsyQBfdewCroNKaOd8foUaMU11wS8+jRIzRp1QKPLePwpWUlIJ0Mlk1yHFKfuIlMFx8iNGgn6tSpAyWzZ88edOjSCZ/rlwZXvbg8Tpb//2nk0ply8qus2MyBEAY1cQPwXeaLUePHI8qhClAin3SFcBwsTt1GxlN3sWNbABo1agQ1EBUVhS6uPbDvVNh/n9K0yShdMdEx/Oi7iEVGfuVP3rx5oQb++ecfNG7ZHM+zpUN0q8pAGgmXTbLPO2w+ic6O7eGzeAnSppXZLFfmUBM3kD///BOt2zrgY8WCiK1X2vyjGZZ/h55H/igLHNi1B4UKyVxW6Qk7LBcsXIjJMzwQxT6tWSS3NPn3tlNw+L0p/ljhD0tLGa6YMQL26/RsRH782sX/ZpZZMpi/iGuPYBV6DksXLkLPnpSBGwI1cSXm5CrIv2Wfkys8/5Z9Tk75t8mgJq60nFxF+bcsc3KV5d+yzMkp/zYp1MSVkpOrNP+WVU6u0vxbVjk55d8mh5q4EnJyleffssjJVZ5/yyInp/xbFKiJyz0n11D+LVlOrpH8W7KcnPJvUaEmLuecXIP5t1lzco3m32bNySn/Fh1q4nLMyTWef5slJ9d4/m2WnJzyb7NATVxuOTnl3+Ln5JR/i5+TU/5tNqiJyyknp/xb/Jyc8m9xc3LKv80ONXG55OSUf4ubk1P+LX5OTvm3JFATlzonp/xb/Jyc8m/xc3LKvyWDmriUOXmFAkjz9jPl32Lm5L+VhfXf/1D+LWZOXrEgrA5dpfxbIqiJS5iTO3RwQsH8BbB25SrKv0XKydlvoo4ZPoLybxFz8rUbN2Dr+g2Uf0sENXGCIAgFQz/PRhAEoWCoiRMEQSgY1TTx2NhYrF69Gp8/y/xHYBXM48ePERQUJHUZqubkyZM4d+6c1GWoFo7jsGnTJrx69QpqQTVNfNToURg6bBhc3dz4F4owLZGRkWjZuhW6u/bA+vXrpS5HlVy6dAltHOzRrEVz3Lt3T+pyVMlCLy/06d8Pbdu3R0xMDNSAKpo4aypBwcHYELYf12/dhKenp9QlqQp2UnR16wm7YoUxa+tqDBsxHBcuXJC6LFXx5s0b2Ds6wHXyGDgOcENrB3uaVZqYI0eOYPbcOZgZtA7RqYHhI0dADSi+ibNmMmz4cMz6wxc5bHNhxiofzF/giQMHDkhdmmrwXLAAl29cR5/p7ihYohh6T5vAN5zXr19LXZpqosB2Tk6o3KQharVsgqZdnJG3ZDF+1kOzStPw8OFDdHDpiH7zpyFX/rzoO38qgneFYs3atVA6im7irIk4ODpixJxp+KVkCf4y27x5MMV3Ebp07YoHDx5IXaLiOXjwIObNn4fRPp6wTJ+ev6xW899Rq1UztHN24hsQYRxjxozBx7hodBw5kP83W8/ec9pYXLtzG3PmzpW6PFVEga3t7dHCrQvK1KjCX5YhcyYMWTqXH40r3UEotomz5tHe2RkN7FugYavmSa6rWKs6Og/uizb2NCU1BnYS7NSlC4Ytmo2ceZN+O2DH4f3xJdU3jBg5UrL61MDGjRuxNSgAgxfOROrU//ua13SWlhixdB4WLvLCvn37JK1R+VGgG7IVyoem3TsmuS5f0V/QY+pYOLR1VLTotFCyyIy1AHqP/Xmu1d6tOwqUKkai04jRC5NsDn174NcaP34SjzWcYQtnYUdoMIlOI0Tm4KFDMMJnPjJlzfLD9dlz22LIolno0q0riU4jROaFq5fh6jHup5/YrdakIaq1aqJo0WmhZJE5yWdhktFLYtgLNmrOdBKdRorMVj06JXu7jFkyY4zvAhKdRorMQiWLJ3u70lUrkeg0UmQO9p4DS6v/osCf0W5wb0WLTgulisyZq3yR+Sejl8SwF45Ep3EiU9f3jTDR2WvqeBKdRohMXTDRmadEURKdBorMnN9Fgd9jkTq1okWnopp4eHg4LzKHz56KIqX+E5m6INFpvMjURe0WjVGzVVMSnQaKTF2wE6mbxzhedM6dN0/0+tQoMnWhZNFpoSyR6cSLzEatW+h1XxKdxotMXbgMH4BoEp0Gi0xdxIvOBV4LsX//flFrVKvI1IVSRaeFkkTmV3DJikxdJIjOnj1pSmqAyNQFa0hDF85CUEgw1q1bJ0qNaheZuuBFp9dMdO7ahURnMixYuDBFkamLeNHp2K6dYkSnhZJE5uQURKYuEkTn7VskOg0UmbpgonPsMhKdyUWB7CSpS2TqonS1ynDo35NEZzIic868uTpFpi6Y6PyaJpViRKeFokSmTVajHotEZ/Ii89L1a4JEpi7oE53Jf6ahStNGgkSmLpp17UCi0wiRqYt40bkzVBmi00JtIlOI6Jzs60Wi8zuRyZYKChWZuiDR+RORGStcZOqCROfPRWZzPUSmENE5dOkcRYhOCzWKTF1UqlWDRKeRIlOI6PwCEp0JItNLP5EpRHQO956redHJJRKZzfQUmbrIV6yIIkSnhVpFpi60LjqNFZm64D/R6aVt0WmsyNRFjjx2mhedC4wUmWoQnRZqFZm60LLoNJXI1IWWRaepRKYutCw6TSUylS46ZdfEL168aDKRqQutik5TikxdaFF0mlpk6kKLotOUIlPpotNCbqMXewcHk4pMXWhNdIohMnWhNdFpapEpWHTevqUJ0SmGyFSy6LSQnchs09zkIlMXWhGdYopMXWhFdIolMgWJTg18olNMkalU0WkhO5E5Tpo3udpFp9giUxdaEJ1ii0xdaEF0ii0ylSg6ZdHEt27dKrrI1Ed0Llq0CGqjd58+ootMfUTnlStXoCbev39vFpGpj+iMjo6GmggLCzOLyBQqOkePGQM5IIsm/vTff5E9Zw5YZ8wgaR3p0lvCNl8ePHn6BGqD7WO7ggUkGb0kJkv2bEhracl/n7aa+PLlCz5+/ISc+fJIXQpyFyqA169eq84/vHjxAtaZMvKDASmxSJ0aOQvklU2fkEUTHz5sGHLnyAXvqbMkrWOD93J8fPUGs2ZKW4cYbNqwAQc3B+Lc0ROS1RAbE4MFg8fArUcPNGzYEGrC1tYWq1etgtfgsXj3OlyyOl48egLfMVMRFBCADBmkHRSZGmdnZzRu0Aj+46fj27dvktVxYuce3Dh5Giv9/CEHZNHELSwssGnjRlwM+wu7twZIUsOpw8ewc81G7NyxA+nNtGrDnOTNmxeB27dj6dgpePbgkSQ1rJ29EHbZcmC6x3SoEQcHB/Rxc8PiIeMQ89X8eWnU50gsGDAa06ZMQd26daFGfH18EPf+M0JWrJFk+w+u38KWeUuwKzgENjY2kAOyaOKMrFmzIiQ4GMunz8PNS+bNS58+eIhZw8Zi+7ZtfLNTK7Vr18YMj+mY238EIj+ZdxXO4YBgXDt5Gls3bZbMe5iDaVOnIX+u3Fg3a6FZt8tk/PJx01C3Rk0MHGiepY1SYGlpiZ1BQQjbFoyLx06addsf3r6D95DxWLFsOcqWLQu5IJsmzihdujT8/fwwqdcgvDXTlPTzp09w7zkAHtOmoU6dOlA7/fv1Q8O69eAzZorZVuHcvXId6+cuRmhwCH+yVjNsVrl540bcPXMBh7fvNNt2g/3XIvLVW6xYvlxy7yE2efLkQeD2AKycMBPPzTSrjI2Jhc/wiejWpQucnJwgJ2TVxBlt27aFa48emNJ3CJ+higlrYnOGj0PdWrUxoH9/aAH2Bl/m44svbyMQuGyV6NuLCH8Dz4Gj4b9iBX+S1gJZsmThT1hbPJfi7uVrom/vUthfOLBuK0J27lRlFPgzatWqhVkzZ2LxoHGIMsOscqvnUthmtsGsGTMhN2TXxBnTPTxga5NddNHJROaHl+F8zqb20cuPU9IdOLAxQFTRGS8yXbt3Q7t27aAlSpYsiT9Wii8640VmwLbtyJcvH7REv7598Xv9BqKLTiYyr4WdwrYtW2QZBcqyiZtDdKpdZMpBdKpdZEotOrUgMqUWnQ9kKDIV0cTFFp1aEZlSis4jgSGaEJlSiU4WBa4Y76F6kSml6PwgU5GpmCYulujUmsiUQnT+JzIXaUJkSiU6mcj8/PKNJkSmFKIzVsYiU1FN3NSiU4siUx/RGeC70mQi02+5dkSmPqLzzqWrRj+eFkWmPqIz8tMnox9vy3xv2YpMxTVxU4pOrYpMoaLz4CbjPtGpZZEpVHQuGjLOKNGpZZEpWHSOM050MpF5/cTfshWZimziphCdWheZ5hCdWheZYotOEpm68fXxwbcPkQaLTiWITEU2cWNFJ4lM8UUniUxxRSeJTPFF5weFiEzFNnFDRSeJTPFFJ4lM8UUniUxxRWesgkSmopu4vqKTRKbhojP63XtBovN/n8j0I5Gpp+jcusBHkOgkkSm+6Nwy3xt2WbIpQmQqvonrIzp5kfnqDZb5+tLoRQTRGS8ye/bozp9cCf1E5yr/lTpFJ4lM40Rn4wYNdYrOeJG5dbMyo0BFNnEhojNBZAYF8U2JMGRKmrLoXDvbixeZHtM8zF6fFkQniUzj8Vm6NEXRqUSR+T2pOAX/oOSNGzdQt149zNuwEqUqlEsiMvu36YDgHTsoBzcS32XLMH/RQswOWJfkl5eOBIUidPlqnD97jnJwI2AjxFZt2gA2GeE2dWzC5extuWTYBBTKbou1a9bQTNIInj17hspVq6DrlNGo2KBOEpE51aknliz0UlwOrviReEqik0Sm+KKTF5lzvEhkiig6mcj89CIcfitWUAMXQXTGKlhk/gCnAia4u3OValbnjj26yTVq1Zxz7dmT+/btm9RlqYYvX75wVatX47qMHMStPXOEs8ublwsMDJS6LFVx8+ZNLluO7NysgLXcxD+WcrnsbLknT55IXZaqWLZ8OVegaBFu5fkjXIvuLlzjpk252NhYTukoOk5JMiVt3Rp37t+DTeYsOBkWRjm4CFPSSlWqIH2mDOjs5IyZCrT4cmfnzp3oM6A/4mJieZdDObjp6dW7Nw6FHQNi43Dx3HnF5uCJUUUTZ0RERGDipEkYP24cfaBHJP7++2+E7trFR1VKtPhKYIWfHzJlyohOLp2kLkWVREdHY/yECejp6qqoD/RoookTBEFoEUWLTYIgCK1DTZwgCELBUBOXiC9fvmD4iBHw8vIy26/Oa40HDx7AxcUFYWFhUpeiWnbt2oXOXbvixYsXUpeiWaiJS8DTp09Rp15dXLp9A/5rV6ODS0d8/iz+L3ZriYMHD6JGzZrIlN0G7Z2c4O3tTSdLE68Im+YxDT379MIbLhqVqlTG6dOnpS5Lm0i9xlFrhIWFcbZ2dlyf8aO4o09vc/v/ucI1c3Lkyvz6K3f//n2py1M87PMB8+fP52ztbLnte0K4Z58juL+uXuRKly3Dde/RnYuKipK6RMXz4cMHrlWbNlypSuU5n7Dd3KbbZ7gRPvM5mxzZOf+VK6UuT3PQSNxMsFGgj48PHNu1xQjPGeg0qA//STxLq/QY6zUHjZzsUa16dRw4cEDqUhVLZGQkOnXqhPWbNiL06EHUrl+Pv7zQL4URcuQA3n38gDp16+DJkydSl6pY7ty5g8rVqiLaKg3GrfWBjW1O/vIqv9fHhHXL4DF7Jvr274evX79KXapmoCZupvzbtacrFvl4Y/GOzaje8L/mEg9r5u3cumHiMi906dYV8+bNo6m/Afl3zVo1EQsOOw7uRb4CBZJcb50hA5at/QPN7NvwJ0vKyfUnNDQUNWvXQv1ObeHqMQ5p06VLcn3eIoUwZesqXLx7C/UbNqSc3ExQEzdT/v04/BWWBG9BvsIFk71thZrVsDR0G9Zs2kA5uQH5d/vOLli8cjmsrKx+ejt2shw4YigWLvehnNyA/Nutb28MWToXjTo4Jntb60wZMXTpXOSrVIZycjNBH/YRkRMnTsDJ2Rn2rl3gMrC34C8yio76Aq/xU/Dk1j8IDQ5G4cKFRa9VibBDd8GCBfBc4Imlf/gnxCdCeHj/AXq5dEHVKlWwfNly+rGFZPj48SM6demCe08fYdCiWQnxiRDOHTqO1VPmYN6cuejl5iZqnVqGRuJmzL+FQjm54fm3UCgnNzz/Fgrl5OaBmriZ82+hUE5ueP4tFMrJDc+/hUI5ufhQE5co/xYK5eTJ5N9dOqWYfwuFcnLD82+hUE4uLpSJS5x/C4Xl5IsmTMXjm3c1mZMnzr99Vq9ErXqm/5pWrefkxuTfQqGc3PTQSFzi/FufnHzMwtn4zdke1WvU0FROniT/PnZIlAau9Zzc2PxbKJSTmx5q4jLIv4XCTg5te3aDu+9CzeTkCfl3KvyXf+fPL+r2tJiTmyr/Fgrl5KaFmriM8m99cnKf0O1Yu3mjqnPyJPm3/zKj82+haCUnFyP/Fgrl5KaDMnEZ5t9az8nNkX9rPSc3R/4tFMrJjYNG4jLMv7Wck5sr/9ZyTm6u/FsolJMbBzVxmebfWszJzZ1/azEnN3f+LRTKyQ2HmrjM82+t5ORS5d9aycmlzL+FQjm5YVAmLoBBgwdj76EDWLE3SDYjl+QIf/ESPRq2xJJFi+Dq6gql8EuRImjSqgWmzJ4BuRMSuAP9urni5cuXyJUrF5TAzZs3Ubp0abiv8UGZmlUhZ1hLWj52Kj7/+xrnz56VuhzZQyNxAcyYPh3FfymCMS498fZ1OOTK/Zu3MaxdF/Ry64muXbtCSQQFBmJ/6G7McJ+MuLg4yJXtGzfDfcRoBAQEKKaBM0qVKgX/lSvhM3ISLxLlSszXr1g9eQ5e3nmALZs2SV2OIqCRuB7T0clTpmDV6j8w1W8JSlYoBzlxNGQPvCdOx5LFi9G5c2cokTdv3sC5gzPiwMF3zR+wyWYDuRATEwOP8e44dvAIgnfuRJkyZaBEzpw5A4e2jqjl0BKOg9xgYSGfcdzbl6/gPWQCShT6BRvWrUOmTJmkLkkRyOcVlDnsYGcjcp8l3pjQrS/2bg2CHGCjVv9Znlg9xwuHDh5UbANnZM+eHfv37UeVCpXQsl4j3Lh6DXIg/NVruLR2xLOHT3Du7FnFNnBGtWrVcOHcefx78ToWDxqLyI+fIAdun7+Mqc5u6NLeGTuDgqiB6wGNxA3gxo0baGNvjwp1a6L/lHFIkzatJHV8eBeBWYNHwRIWCNi2HTly5IBa2LRpE4YMHYoZC+bBvn1byeq4fOEienfqhm5du8LDwwOpU6eGGmDL+IYMG4o9B/ZjiPdcfnWIFLD2c3hLEHYuXYl1a9aiZcuWktShZKiJG0hERARcOnfCy7dvMGn5ImTLmcPs+ffkXoPQ3tER8+fNR5o0aaA2Ll26BMe2bdHCvjXGe0wxewNl+bfHhElYsXw52rVrBzWyctUqjB47Bj09xvPrtc2df6+fvgCPr97EruAQFCtWzKzbVwvUxBWYk6sh/5ZzTq6W/FvOOTnl36aDMnEF5eRqyr8Nyclb1G2I61euiro9NeXfcs3JKf82LdTETUDbtm1xIiwMAb4r+RFybEyMKPn3hG598PTGHZw/dw4VK1aEVmBRkaenJ2bNnImOrR2xc3ugaPl3i3qN0KBuPf6TjVmzZoVWsLOzw/GjR1GpeClM6+CGf+89NPk22KT/0OZAeA8ZhzUrV2Giu7ukX1uhFihOUUBOfu/GLUzpPVjV+bc+ObmDoyNaOrTBuGmTTbYvtJB/S5mTU/4tHtTEZZ6Tayn/1jcnj+VYTr4K2bJnM/ixtJZ/S5GTU/4tLhSnyDQnZ/m338z5msq/9c3Jq1b8bz25oTm5FvNvc+fklH+LDzVxGebk8fn3vzfvai7/NldOruX82xw5OeXf5oPiFJnl5JR/i5+TU/4tbk5O+bd5oSYuo5yc8m9xc3LKv8XPySn/Nj8Up8ggJ6f8W/ycnPJv8XNyyr8lgo3ECfNx/fp1rkjRolw7167coYfXuZBrZ7jqDepy9Rs24F6/fi11eapg48aNXPYcOTjfNau4Z58juL0njnL58ufnJkyYwMXGxkpdnuKJjo7m+vbvx+UvUpibv2cbt/HWaa7n1LFcthzZuV27dkldnuagOEXCnPx5+Gu8efWa8m8Rc/JylSrgr7CTlH+LmJMXr1QeEU+fU/4tEdTEJczJvRYtQr68edGhQwepy1FtTj579mz+F44oPhEvJw/cEYSJE9wpPpEIauIEQRAKhsQmQRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRAKhpo4QRCEgqEmThAEoWCoiRMEQSgYauIEQRBQLv8HuM4VKb00iR0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "szz = {}\n",
+    "\n",
+    "map = np.array([5,10,15,2,7,12,17,4,9,14,1,6,11,16,3,8,13,])-1\n",
+    "\n",
+    "for he in he_list:\n",
+    "    for step in trotter_steps:\n",
+    "        szz[(he,step)] = bitstring_to_expectation_value(np.array(zz[(he,step)]))*bitstring_to_expectation_value(np.array(z0[he]))\n",
+    "        lgt.plot_qubit_polarization_values(\n",
+    "            grid = LGTGrid(origin_qubit = cirq.GridQubit(0,0),orientation_vector = (1,1), rows = grid.cols, cols = grid.rows, flip_rowcol = False),\n",
+    "            qubit_polarization_data=[szz[(he,step)][i] for i in map],\n",
+    "            ancilla_states_data=np.zeros(18),\n",
+    "            plot_physical_qubits=True,\n",
+    "            plot_ancillas = False,\n",
+    "            qubit_colormap=cmap_green\n",
+    "        )\n",
+    "\n",
+    "        title_text = r'$S_{ZZ}$ for gauge qubits. '+  f'$h_E =$ {he}, time = {np.around(dt * step,3)}'\n",
+    "\n",
+    "        plt.title(title_text)\n",
+    "        plt.ylim(grid.cols, -1)\n",
+    "\n",
+    "        plt.show()\n",
+    "\n",
+    "f,ax = plt.subplots()\n",
+    "ax.set_aspect(0.1)\n",
+    "\n",
+    "norm = matplotlib.colors.Normalize(vmin=-1, vmax=1)\n",
+    "\n",
+    "matplotlib.colorbar.ColorbarBase(\n",
+    "    ax, cmap=cmap_green, norm=norm, orientation='horizontal'\n",
+    ")\n",
+    "\n",
+    "ax.set_xticks([-1,0,1],labels=['+1','0','-1'])\n",
+    "ax.set_xticks([],minor=True)\n",
+    "ax.tick_params(right=False,labelright=False)\n",
+    "ax.set_title(r'$S_{ZZ}(t)$')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7ef945ca",
+   "metadata": {},
+   "source": [
+    "We see the coherent dynamics of the string in the confined phase ($h_E = 1.4$). In this case, the string mainly stays on the top qubits where it can undergo \"breathing\" type quantum vibrations without changing it's length on the lattice. However, in a more weakly confined regime ($h_E = 0.6$), the string evidently explores more modes of oscillation and is able to \"flop\" down to the bottom qubits. For $h_E=0.1$, there is no clear string excitation, even at the initial time. This is consistent with the deconfined phase.\n",
+    "\n",
+    "To clearly quantitatively see these behaviors, we simulate a denser time sampling for just the top (Q1) and bottom (Q2) qubits in the center, as indicated below."
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "60727930",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b67ba7e1",
+   "metadata": {},
+   "source": [
+    "So let's construct the circuit as before but with more time steps and only simulate $\\mathcal{S}_{ZZ}(t)$ for these two qubits."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "a2732a58",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he_list = [0.1,0.6,1.4]\n",
+    "trotter_steps = np.arange(10)\n",
+    "target_list = [grid.physical_qubits[9],grid.physical_qubits[7]]\n",
+    "\n",
+    "time_evolution_circuits = []\n",
+    "\n",
+    "for target_qubit in target_list:\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            time_evolution_circuits.append(cirq.Circuit.from_moments(\n",
+    "                cirq.H.on(auxillary_qubit),\n",
+    "                *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "                cirq.Moment(cirq.X.on_each(string_excitation_qubits)),\n",
+    "                cirq.CZ(auxillary_qubit,target_qubit),\n",
+    "                *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he,extra_z_plaquette_indices=[(0,1),(3,1)])*step,\n",
+    "                cirq.H.on(auxillary_qubit),\n",
+    "                cirq.Moment(cirq.measure(auxillary_qubit,target_qubit, key=\"measure_all\"))\n",
+    "            ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a0a113b2",
+   "metadata": {},
+   "source": [
+    "Now let's simulate it and calculate $\\mathcal{S}_{ZZ}(t)$! (This should take <1 minute)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "9e3fc15a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_string_dynamics = simulator.run_batch(time_evolution_circuits,repetitions=reps)\n",
+    "\n",
+    "zz_fine = {}\n",
+    "zz_fine_sdom = {}\n",
+    "\n",
+    "for target in target_list:\n",
+    "        for he in he_list:\n",
+    "             zz_fine[(target,he)] = []\n",
+    "             zz_fine_sdom[(target,he)] = []\n",
+    "\n",
+    "counter = 0\n",
+    "for idx, target in enumerate(target_list):\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            bitstrings = results_string_dynamics[counter][0].measurements['measure_all']\n",
+    "            zz_fine[(target,he)].append(np.mean(np.sum(bitstrings,axis=1)%2))\n",
+    "            zz_fine_sdom[(target,he)].append(np.std(np.sum(bitstrings,axis=1)%2)/np.sqrt(np.shape(bitstrings)[0]))\n",
+    "            counter+=1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "7cb5f32f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAa4AAAFNCAYAAABYJYu2AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAAVS1JREFUeJztnQV4FNfXxk/cXSBBggaKBS9WrBQpViDYh0uhlLa0pUUqSKF/qNAWK4XiVgrBiltxKy7BoSRoiBL3+Z5zw253k81mk2ySnd339zyT3ZGdzOzM3nfOueeeYyZJkkQAAACATDAv6QMAAAAA8gOECwAAgKyAcAEAAJAVEC4AAACyAsIFAABAVkC4AAAAyAoIFwAAAFkB4QIAACArIFwmTnx8PJUpU4bOnTundbvRo0fT+PHjddrn5MmTqVSpUmRmZkYrV64kQ6V169Y0cuRIrdsMHTqU2rVrV2zHJFcM7Zob2nUrzPdjaOdiEHDmDGDYhIeHSxMmTJCqV68u2dnZSW5ublKjRo2k1atXF3rfX331ldStWze1ZbNmzZLq1Kmjtuzx48eSvb29dP/+fa37O3PmDGdikbZt2yY9e/ZMSkxMlAyVVq1aSSNGjNC6TUxMjBQVFaWcf/PNN6UhQ4botP/nz59LH3zwgeTn5ydZWVlJnp6eUs+ePaVLly6pbXf06FFxDcqXLy++uxkzZkhyoqSvuaZrkv26yeH7ye3eMqRzMRRgcRk4YWFhVK9ePTp//jwtWLCAbty4Qfv376fAwECytLQs1L6Tk5Np0aJFwppS5cyZM9S4cWO1ZWyVvfnmm/Trr79q3efdu3fJ3NycunfvTqVLlyY7O7sCHVtqaioZAi4uLuTm5pbvzz169IgaNmxIp06dEt/xvXv3aNeuXWRtbU1NmjShvXv3qlm9NWrUoO+//158Z3JDX9fcEK6bIX4/hnQuBkNJKyfQztSpUyUHBwcpKSlJ7/veunWrsKLS0tLEfEZGhpjn20IxWVtbK9cvX75cKl26dK7746dF1c8qbq/U1FRp4sSJkq+vr7A8XnvtNWndunU5rJ/hw4cLC5D/R6lSpXL9P/xdvPfee5Kzs7Pk6uoq3k+aNEmqXLmyVmuKLRm2flS3GTZsmDg2Dw8PycnJSXr33XfVvms+J34Szu38Dh8+rPEYu3btKs7h5cuXOdZ16tRJrNP05M3Hp6vFtX//fnEObIHzd9GyZUvp7NmzatscP35catasmeTo6CgmtqT37t1bqH3qcs11+f5Vt/vmm2/Ed8L/d9CgQVJcXJzadgsWLBD3Dd+PXl5ewnLVdk1Ur1t+7kFdjiU72vad2/ejy/eouLeyn0urV7+VL7/8UnwXLi4u0hdffCF+v9OnT5e8vb2Fdc/LsjNv3jypWrVqko2NjVSlShVp5syZyt+3nIBwGTgffvihEJMrV67ofd8ff/yx1Lx5c+V8ZmamdPPmTfGj2blzp3BrvHjxQrk+ODhYrLtx44bG/bFL45dffpEsLCzEZ3liPvvsM8nd3V3auHGjdPv2benbb7+VzMzMpIMHD6r9GLlhHT16tPg/V69e1Xrc/INl1wsf7/jx44XoFES4+HMjR44U5/TXX3+J/fL+Fag2Gnx+b7zxhtSnTx/l+aWkpOQ4PnbrmJub5ypAx44dE9/j9u3bCyVcW7Zskf7880/p1q1b0vXr18X5cmMbEREh1nODxPOffPKJdOfOHTHxZ/j/F3Sful7z/AgXN7z8nfO13Ldvn/h//ACjYMqUKeLhbf78+eL+uXDhgmhwtV2T7I29rvdgXseiCW37zu370fQ95nZvaRIuZ2dn0X3A/2/ZsmXifurYsaP0+eefi2UrV64Uy3bv3q32EMzuaL7GDx48kHbt2iWVK1cuz/MzRCBcBg43qP7+/uIm5D4uti4OHTqktg03EAEBAcqJn/wsLS2l+Ph4reu6d+8ufiiq8L650eX12WHrQSFqubFixQrxI1WQkJAgnpIXLlyott0777wjtWnTRu3HWLVqVfHUqA0+Ln5aXLJkidryBg0aFEi4eD49PV25bPHixWL/ivPP3mjo0sfFFgp/T9xAaCIyMlKs//777wslXNnh744t0LVr1yoFVJtVWJB96nLN8ytc2ftT+R5v0qSJeM/XwdbWVvrhhx9y/f+aronqdcvPPajtWDShy741fT+6nkf2c1EcZ0BAgNo2NWrUkGrVqqW2jM+FH+oUx8n943v27FHbZtWqVUKs5Qb6uAyc1157jW7duiX6nQYNGkQXL14UfU2ffvqpcpulS5fS5cuXxbR7926ysrKiJUuWkIODg9Z1SUlJZGtrq/b/Ll26RNWqVRPrs6PYlj+nK9y3w/1VLVu2VFveqlUrCg4OVlvWoEED0Regjfv371NKSgo1a9ZMbXmLFi2oIHBfnoWFhXK+efPmYv/8f4oavhaF4d9//xX3RJUqVcjZ2VlML1++pJCQELGe+0U4arJDhw7UqVMnmj17Nt2+fbtQ+ywKAgIC1OZ9fX1F3y7D9wj3xbZv377A+8/PPajtWAq7b30SkO04ue+sTp06OZa9ePFCvOdj4d9tr169yNHRUTlx/zZf3/DwcJITEC4ZwCG0r7/+On3xxRd09uxZ6ty5M61YsSLHdnwDduzYUdyMw4YNy3Odl5cXRUVF5RCu+vXrazwOxbb8uaJAk1gWFBbA7KXm0tLSqDioWrWq+P/Xr1/XuF7RoPn7+xfq/3Tp0oVCQ0Np4cKF4sGGH068vb3VAlt+//13unDhAr311lt09OhRqlWrFi1evLhQ+9T3988BK9nv98zMTCoJDOlY8vPQY2ZmpnGZ4tgVr5s2bVI+yPJ07do1ETzi7u5OcgLCJUP4yYkbE1XYSuCoJR6bxGNGdFnHApX9qZBv5rp162r8v3yTs3XCUY66wk/uNjY2dOzYMbXlikY0v1SuXFk0Lhytp8rJkyfV5vn7efr0qdoytlazw+PXMjIylPO8Xz5e/j+a4P+tur0m2NLhhwuOAo2Njc2xftasWeJJnsWkoERGRooI00mTJgmLiqMS2SJWPGGrwt8zW+h79uyhESNGCIu7sPvMC12//7xQHANH0uZGXtdE3/dgUe1bl3uroNSsWVN8jw8ePBDHnH1S9TrIgcLFU4MihV023IByA1e2bFl69uyZeILmH8WGDRuU2/HT1IABA8QAx19++UVtH9rWsfuIBxVz6Ha5cuXEsvT0dLpz5w49efJE3OgeHh7K7Y8cOSJccuw+0hV7e3v66KOP6OuvvxaWGrs4goKCaPv27XTgwIECWWXvvfceffXVV+Kc2K25bNky4QJTFXMesDlmzBjxhMlCy//z+PHj5OrqmqOxHjt2LI0bN078qPk42SrNzfqrWLEiHT58WLgSOUyZJ00uP7ZYmjZtSm3btqWZM2eKhuP58+f0888/099//0379u1Tfo7D4dnlxLBlw9vxAwS7crhRyU0c+fvk+4HvET6PCRMmqIVa8z55fdeuXcX1ZSHh7yA3i1qXfeqKrt9/XvB3wPfotGnTxHHwb4Ef3NjtrXgI03RNivIeLKp963pvFQT+HtljwxNbYnx9+LfOD6PsZfnuu+9IVpR0JxvInZ9//llEGnGkG3cAV6hQQQRTnD9/Xm27MWPGiI5gTRFu2tYxrVu3FlFQCoKCgkQHOkdFvf3222oRh/z/169fr/WYNXVE5ycUWRc4jHzUqFEisoonDmHPHg7P/3PcuHHKcOH3339f+vrrrzWGwyuiwjiqkY9BNUw9e8c4D8Dma8JRbnkFPvAA5LFjx4pILv5OeHv+Dji6TxXeR/ZQaJ74+LRx5MgR0QHPwSQcwMPXjr8Djh5jnj59KvXo0UMqU6aMuH98fHxEBCVHsBV0n/m55nl9/7oGcfC9x5F5fDx8/3C4d2BgoNZrUphweG3Hoom89q1rcEZu95am4IwR2Y5TU2BHhw4dpAEDBqgt+/3330VgB19fDrpp3Lix9Ouvv0pyA8Ilc3jMSd26dTWOF9K2TgGHRvMPLq9sBxwizVFLqhF4hgQ3rKrCZYhwNCZHyMkx/BgAQ8KM/5S01QcKxsOHD4V7wc/PT80Fwy407oDPbR27qVThPg+OpmN3Vm6sWbNGRDhyNghDhF1Ja9euVbrcDBV2lx06dIgGDx5MlSpVKunDAUCWQLiAUSAX4QIAFB4IFwAAAFmBcHgAAACyAsIFAABAVmAc1ys8PT2pQoUKBf48p0wpqowShoqpnTPO17jB+Rpe8FlERITGdRCuV7Bocc2rgsLRdoX5vBwxtXPG+Ro3OF/DQlsEM1yFAAAAZAWECwAAgKyAcOmJUaNGkalhaueM8zVucL7yAeO4ZOLvBQAAU6KhljYZFhcAAABZAeECAAAgKwxWuLgIH5uKXKRt6NChWrflGkdcpprrRA0fPlwUTlQdC9CmTRtRN6d69ep08ODBYjh6AAAAJidcXCGWiwWyEGmDM53Pnj1bZNwOCQkRxQCnTp2qXN+/f39RyI6L4n377bcUGBgoBt4BAACQJwYrXD179qR33nlHrQKvJlatWiXKkXNJDq7gypVIV65cKdZxJV8uFz59+nRRPbVXr15Uu3Zt2rx5czGdBQAAAJMRLl0JDg4W5bIV8PuwsDBhYfE6rnnk5OSktp6XAwAAkCeyF674+HhycXFRzivex8XF5VinWM/rssPuQ+5TU0xcXBEAAEDxwe2uog3W1qUj+1yFjo6OFBsbq5xXvGcrK/s6xXpVC0wBJ5vEOC4AACjZQdGKgdFGnauQ+7auXLminOf3XJ6e+8Z4HQdrqFpYvF5biXoAAACGjcEKV3p6OiUnJ1NGRoaY+D0vy87gwYNp2bJldOPGDYqJiaGZM2cqw+f9/f2pbt26IjiDP79161a6evWqCNIAAAAgTwxWuFiAOBKQQ93Xrl0r3vOy0NBQ4QLkV6Zjx440YcIEMVarfPny5OfnJ4RKwYYNG4QLkCMOJ02aREFBQQZdgwYAAIB2kKvwFchVCAAAhgNyFQIAADAaIFwAAABkBYQLAACArIBwAQAAkBUQLgAAALICwgUAAEBWQLgAAADICggXAAAAWQHhAgAAICsgXAAAAGQFhAsAAICsgHABAACQFRAuAAAAsgLCBQAAQFZAuAAAAMgKCBcAAABZAeECAAAgKyBcAAAAZAWECwAAgKyAcAEAAJAVEC4AAACywmCFKyoqinr06EEODg7k5+dH69ev17hdp06dyNHRUTlZW1tT7dq1lesrVKhAdnZ2yvXt27cvxrMAAACgbyzJQBk7dqwQobCwMLp8+TJ17tyZAgICqGbNmmrb7dmzR22+devW1LZtW7VlO3bsoHbt2hXLcQMAADBBiyshIYE2b95MM2bMEFZSixYtqFu3brRmzRqtn3v48CEdP36cBg8eXGzHCgAAoHgxSOG6c+cOWVpakr+/v3IZW1vBwcFaP7d69Wp64403hHtQlQEDBpCXl5dwE165cqXIjhsAAICJCld8fDw5OzurLXNxcaG4uLg8hWvo0KFqy9atWycssZCQEGrTpg116NCBYmJicnw2PDycGjZsqJyWLFmip7MBAACgC9zuKtpgbpNl1cfF7sHY2Fi1ZTzv5OSU62dOnDhBz58/p8DAQLXlzZs3V76fPHkyrVq1SrgTu3btqrYdW2Tnz5/X2zkAAADIH6NGjRITw+IlK4uLXYTp6el09+5d5TJ28WUPzFCFBalnz55C9LRhZmZGkiTp9XgBAAAUHwYpXBwCzyI0ZcoUEahx8uRJ2r59Ow0aNEjj9klJSbRx48YcbsLQ0FDx2dTUVEpOTqYffviBIiIi1KwwAAAA8sIghYv59ddfhSB5e3tT//79adGiRcLiYjdfdqtq27Zt5OrqKvqwVOE+sTFjxpCbmxuVKVOG9u7dK8LnPTw8ivlsAAAA6AszCX4zpT8VfVwAAGD4bbLBWlwAAACAJiBcAAAAZAWECwAAgKyAcAEAAJAVEC4AAACyAsIFAABAVkC4AAAAyAoIFwAAAFkB4QIAACArIFwAAABkBYQLAACArIBwAQAAkBUQLgAAALICwgUAAEBWQLgAAADICggXAAAAWQHhAgAAICsgXAAAAGQFhAsAAICsgHABAACQFQYrXFFRUdSjRw9ycHAgPz8/Wr9+vcbtpk2bRlZWVuTo6KicHjx4oFx/+fJlatCgAdnb24tXngcAACBfDFa4xo4dS9bW1hQWFkbr1q2jMWPGUHBwsMZt+/btS/Hx8cqpUqVKYnlqaip1796dBg4cSNHR0TRkyBAxz8sBAADIE4MUroSEBNq8eTPNmDFDWFAtWrSgbt260Zo1a/K1nyNHjlB6ejp9/PHHZGNjQx999BFJkkR///13kR07AAAAExSuO3fukKWlJfn7+yuXBQQE5Gpx7dixg9zd3almzZq0aNEi5XLevk6dOmRmZqZcxvO57QcAAIDhY0kGCLv7nJ2d1Za5uLhQXFxcjm379OlDo0aNolKlStHZs2epV69e5OrqSv379xf74c/psp/w8HBq2LChcp73yRMAAIDiYcmSJWJStMmyEi52D8bGxqot43knJ6cc29aoUUP5vlmzZjRu3DgKCgoSwpWf/Xh5edH58+f1eh4AAAB0R9VgUDUkZOEqZBch903dvXtXuezKlSvCFZgX7BbkfiyGt7969apynuF5XfYDAADAMDFI4eIQ+J49e9KUKVNEoMbJkydp+/btNGjQoBzb8nKOGGRx+ueff2jevHkicpBp3bo1WVhYiGUpKSm0YMECsbxt27bFfk4AAACMWLiYX3/9lZKSksjb21u4/Tjogi2l48ePCxeggg0bNlCVKlWE+2/w4ME0ceJEEfbOcDj9tm3baPXq1aLfa/ny5WKelwMAAJAnZpKqH82EYX8q+rgAAMDw22SDtbgAAAAATUC4AAAAyAoIFwAAAFkB4QIAACArIFwAAABkBYQLAACArIBwAQAAkBUQLgAAALICwgUAAEBWQLgAAADICggXAAAAWQHhAgAAICsgXAAAAGQFhAsAAICsgHABAACQFRAuAAAAsgLCBQAAQFZAuAAAAOiFzMxM+nPjJqpQ9w0qW7MJtXizo5jn5frEUq97AwAAYJJkZmZS34FD6XaMBVV6+wOysnOktKR4+nblbtq8fSdtWLOCzM31YyvB4gIAkKk/wcv1eAyJTUGbhWj5NA0UosXwK8/fijYX6/WFwQpXVFQU9ejRgxwcHMjPz4/Wr1+vcbsffviBatWqRU5OTlSxYkUxr0qFChXIzs6OHB0dxdS+fftiOgMAgD6e4PmJnZ/ga/b7mqxfHybm+w0aVuxiYWjHU9IkpKTRwxdxdPZuGO04H0JTf1hInnU7atyWly9cssL4XYVjx44la2trCgsLo8uXL1Pnzp0pICCAatasqbadJEm0evVqqlOnDt2/f18IU7ly5ahfv37KbXbs2EHt2rUrgbMAAOjjCV6B8gn+dJBY37dPb5M9HobFkv/vxP/No/S0NKpQ2pU+HD2Cegf2KpRbLlOSKDo+hcJeJtELDVN4bBLFJ6erfSYqNpH8Xlla2eHvKToxiYxauBISEmjz5s10/fp1YSW1aNGCunXrRmvWrKHZs2erbTthwgTl+2rVqlH37t3p5MmTasIFACjZhjA3ktMyRAMZFZ9MUfEp4n3WfArNnzWfKnQam+sT/LjpP9P6B05kbm5G5mZmZPHqlQ/TwtyczM1IuU59/X/baV7+anvVz5ub0dLvFlD5Du/nejyz5i6mCvVakr2NFdlbW5KDjSXZ2ViSvY0lWVmYG1SfUnJaBoWzCMVqFqaI2GRKz5TUPsPn4+1iJ6Za5d2z3jvbkbdr1us7R+aL/69wE6rCy53s7YxbuO7cuUOWlpbk7++vXMbW1tGjR7V+jq2v48eP0+jRo9WWDxgwQFzkevXqCVci7wsAUDSd6/y0HpuYSpFxKRSdkJJDmJSvCSmUmKL+1M6w4Lg62FBKaqrGRpDh5fZWZvR2g/KUmSmJ/5n1yuchUcar+Qy1df+9ZrzaTrEsLTOTMtP++5xiP2LbV6/xiclaj+dJRCxN2XBe83oLcyFgYrL+T9D4ffblDlq2sbO2FEKblwV489Qmmvf7amrYskOWGMUmqwnTy8TUHN+5u5OtEKDqZdzIu0aWQHm7ZC3j9w62VlqvOz/g8L2iejwKIi7vpS9HDSOjFq74+HhydnZWW+bi4kJxcXFaPzdt2jTx4xs27L8vaN26dVS/fn0hanPnzqUOHTrQrVu3yNXVVe2z4eHh1LBhQ+X8qFGjxASAqZCXK2z9hk3UtmMXIUZRcVnCoxAlhSDxFJOQKhr67HAD7OZoQ+6ONlSptDM1fPU+a5ktuTlkzTvbW4vGucXOH7U+wZf1dKHRb9Wg4qLFVjetx1PJx43mDm9GiSkZlJiSRomp6ZSUkk4JKelCoJNSs17FlJpOUXHJ9PjVMt4uJV23PjJbKwshYseXzyX/rh9q3MarXieaNXcu1X3hJeZtrCyolIsdebnYUZXSzkrLSbHM08mWLAtpFbJVzg84fK+wBap48GHRqu6WSX165xS07CxZskRMijZZVsLF7sHY2Fi1ZTzPARi5sWDBAtHXxRaXjY2Ncnnz5s2V7ydPnkyrVq0S23Tt2lXt815eXnT+vOanJQBMgfmLl5Hn65qfirkhGj9zLtW9r95osxvNzdFaKTpVSrsIIVIIlBCmV+tsrfPX3BTnE7xejuf9kcJaKSjpGZlKsVOIm6rQKQQu4dX7U5Sh1QJ0s7egBSNbCHFysrMiM7MsS62oYGucrXJ+AOJADO7TYvcgXycWLV3+v6rBoGpIyEK42EWYnp5Od+/epapVq4plV65cyRGYoWD58uWi7+vYsWNUtmxZrfvmL4+tLwBMHY4Ku/P0Jd16EiOme0+jKUBLQ+hkY06fdQtQEyUnuyzrqCjQxxO8nI6HLR5nO2sx6cLmn120WoDerk5U1ceFihMWLw5QKeogFYMULg6B79mzJ02ZMoWWLl0qogq3b99Op06dyrEtuwK/+OILOnz4MFWqVEltXWhoKD169IgaNWokXIjz58+niIgINSsMAFOAn+Y5dPnW0yyRuv0khh5FxJPiEa6shwM52ttqbQh9PZzprQDtD4aG9gRvzMfzoYFZpMWJmWSg5geP4xo+fDgdOHCAPDw8hEX1f//3f8LN16lTJ9EPxvDYrcePH6u5BwcOHEi//fYbBQcHU//+/UWYvK2tLdWtW5e+++47jSYoL4OrEBgD/JPmMGYWJxYqfr337KWyD8XF3pqql3EVUzVfV/L3dRWuJB5Im1tD+Ox0EH059O1iD/cGuZOZmSnGj/HgXk0W4J9rVxa7mOoTbW2ywQpXcQPhAnIlPjmNbr8SKIVYcYAEY21pLvqdhEixWPm6UilXO40NGrvn/WvVIwuf2lSuaXdlQ/jo9HbKfHaN7gRfJgsLixI4Q5DX8IWFS1ZQ3CsLcGwJWYDF2SYbpKsQAFMhv+Om2OX3L7v8nkTT7SfcPxVNjyITlOvLeThQo8reWSJVxpUqejvpHC22des2ati4A3mUrkhH9i+h1NQUsra2oXZte1LEcx/asmUr9S7mfiVgGH1KhgYsrlfA4gIlOW5Kk6vnj9XLKTw2JSt4QuHye/6SUl+5/FwdrIUFlSVSblTN1yXPsTaaj0Oil/Fp9M47PajPiP+RvaP6UBQmMT6W/lz2Ba1eu5HsbS3ExOOMLHiUbhF/R5s3b6Ef5y4Vwu7hZk/vjhhCvXr1LJIB0cBwgMUFgMzGTV059ie1GDaNnKs2Ubr8OEKsS0M/IVZsTfE4nPy4g1igYhPSKCaOp1SKjs16ZdHix9eYuCSNosXw8pdxSXT43Au15TZW5mSnImSK92LelgfN8qsFWVmaF0i0Bg8dQWlmnjR4zHfiGFhAg3aupb927qZVK5ZCvEwUCBcABjhuqkyjzvRo/yL6ctxIIVQV8uHy48G/cQnpQpRiYtMoml9fCZRqHlgnB0tydbKm8qXtxesaV3shDLlZXN7uDtStla8YYJuUnEGJyelZr6/mX8YnUVJKhtr/UGBlaZaVCcLOQilmqsKWJXaWYjuFGLOlxaLVsed/aZb42Hh+z5aFYj1cl6YJhAuAEiIuIZlKaxk35WhtRl0a+OX6efbyxyemUzRbULGprwQqjV7GpYk0RQoc7VmgrKiMtz25OVmRq7M1uTpakWU2K2jMqKHCmlEVCgVH96+hUSOHkIerDXloOSc+ppS0zFfCllPckpLTKTyaUz1lUAbnXcoGux4VYvbTvKU08L3vNP6fVu0H0dLlX0O4TBQIFwDFDDfuh649oRdxqeShZdwUj6tSbJ+QpCpQWa9sQaWrNP4OdhbCcvLxtCU3J+ssgXKy0tlNx/1G7IJja4aFQeGaY9GyoSgKDOyV5z7YWrK1thCTm2avo/Kc0tIlNWFLfCVsivnklDStrsvEpBSdzgsYHxAuAIqRJ1EJNG/3Nbr8byRVbdCSHp35iyq1+b8c23EIev2yFWnH0afCzacqUHY2LApW5O/nRG6vxIkFy9qqcP093F/E/UbsgmNrJikphezsbGjk8MFCtPQZXs37srbiiY9f8zY/u2t3XSamEO0+/pTKlLKnMt525OFiLfsQcKAbiCp8BaIKQVGSlpFJQacf0Prjd0Vf1Yg3q9PcL8ZSdJIlJdi4kE+jt5VRhc/O7SaHlJdsdtGMH1e+sp6ssl6drMjG2jTGUm3aFERBO89qdF3u3ryQGtavRa/VfYsiX6YqBd3X247KetuRr5cd2dqYxvdkrCCqEIAS5MbjaJq78xo9DI+jFtVLU4+GlSk+LoMiopPog8lL6PzpvWrjplq37UmNmnWilb+MoU7NfchU0ea6tDWLognjhggLi12LT8IT6UlYEj0OS6T7j7Ky6ni52QhLjIXMw81GJAQGxgGEC4AiIiE5jZb/fYt2XQgV9aV61a9C9mRD565Gi8S0NtZWlJwYT42bvy0mVbiBZjedKaPqupwzbxKlpaaSp7tDDtclB3JUKeckJo6ojIxOoccvkujJiyS6fDtGTBy2r7DGOEiFPwPkC4QLAD3D44/2X3pCy/6+SXHJaVTV051ql/ImZwsrKlfaXky+nrZklzxSaxQfN9CmDosXRw7qGj3IVpWXu62Y6lV3o+TUDHr6SsR4+vdJVpYRdxfrLBErZU/ebI3lM8P9nhPPxGunFqZrEZckEC4A9ACHnz+PSKbr/0ZT0Ll7FBodR262thRYtyI1qOpJ5UrZk4erevCAPqL4gHY4urFSWUcxcXd+1MvUV9ZYIl2795Ku3n0pBnf7eNlS2VdBHg52aBYNHQRnvALBGSC/JKdkiD6VR6+mG88j6VpYVtXWzvX8aGCrKuTsYK1TSqM585bl6goDRUNqWiY9Dc8SscdhSSIcn+EAGIWIlXK3VUtrhRRUxQeyw+sAhMu0KIirh38qPMD30fMsoXoRlTWOKDE9lc4/eUZPXyZQw0pe9GHnWlTa1b7Ijh3oH8W15QcRdimGRSYTj+G2tDAjH6+svjEfTxsaO/Y9kc2jZfuBSgv52P61ZE2RSEGlZxBVCEAhXIBhEckUylbV80SRqYLhMUM1KjvRmX+f0d6bj0SNq8k961GrGj6wlGQIXzMeE8dT7aqulJaeSc+ENZYkXIt87c+f2kNJmR7UpTdSUJU0EC5gUmR39fyswdXznwswy43EGR44CpD7QWpXdRH9VcGPo2jBnquiYOPb9cvT8LbVRTFGYBxwtpHyPg5iYmssNj6Nlv+yk/qNnKVxe6SgMmDh4pL3y5Yto+rVqxfdEQFQRGjLNr55606aNPUnevIimcKjUkRJex7QWrGMozIKkHP7RcUn09zdV+nojWdU3tOR5gxpSrXKu5f0qYEitsZcnKzJTMrQmoIqMjqB7obEifsFg5+Llnw5ZMPDw6l///70999/qy0fOHCgvo8LAL2jmm1c0QApXD2pZh70+/INIvFrQDVX6trSl/p2KEfN63qK7OnmFma0+2IovbvoKJ26HUaDW/nTwndbQLRMCFtba/GgowlebmZuRScuR9CGvaG05+QzuvEgVuSYBCUsXGXLlqV9+/bRlClTaPny5crlT548KYJDA0C//L5slehU18Sbbw+mO5f3ULfWZcT4H083G2VfVWh4HH226jTN3XWNKpVypt9Gv0EDWlYla0s8VZsS7FLmQAxN8BCGzz8eQV1b+VJtfxeRzePstUjauP8R7Tz2lK7djRHuRlBCfVze3t60f/9+GjRoEN29e5dmzdLs8wXAUOBBqA8exVNEdKJWV09KSlbOOwWp6Rn0x4l7tPHkfVFL6tOudah9QFkEX5goeY274/4tvjc8XW2owWvuIjlyyLNECnmaQOdvRIuJkyP7+TiIid/jXioGi8vaOmtMir29PQUFBVF6ejr17t2bkpOTSd9ERUVRjx49yMHBgfz8/Gj9+vUat+OO04kTJ5KHh4eY+L1qhP/ly5epQYMG4pj5leeB8cP3AEeEHTn/gv7cF0pnr0eRpaWVVlePaoqlKw8jaczi47T++D1qVdOXlo5pRR3qlkNDY8IoUlD17tKE1vw2iRb8byT9tfZrMb965bIc9wZn7A/wdxVWfO+3ylLjWu5kbWUhUlBtP/KENh96TOeCo+hFVLJamwXyptDjuH777Tf66KOPKDVV/Wm1sHBfGnemczAIi03nzp3p1KlTVLNmTbXtFi9eTD/99BMdOnRI3DhvvfWWOJ733ntPHFPVqlXp448/pvfff19sO2fOHGEpKkRYAcZxGQfxiWl0NzSe7obGUUJShshRV6mcI/mXd6RD+3fkmm2cn6K5AerQuRv9fvAm7b/ymHzc7OnDt2tRg0peJXIuwDhhN2Lo8wRhjXHIPY8X40AgPx978vN1oNIetvlOQWWM6G0Acm5RhWFhYVSqVCnSFwkJCeTm5kbXr18nf39/sYxdk2XKlKHZs2erbdusWTMaOnQojRo1Sszz8f3+++905swZ4dIcNmwYPX78WPk0VL58eVqyZAl17NhRbT8QLvnCARUhz7Miup6GZ1n/vl62VNXPSQRWKEre84PQkGEjKYXcc7h6rCmKho7/hpYcuEnxyWkU2KQS/V/LqmRrhX4sUHSkpGXQ4+dJFPIsQYwX43uZH7Y4MpFFjO9jxf1rarkTG+prALIiqpCtlrZt2yqXjx8/ntau1dxpWRDu3LlDlpaWStFiAgIC6OjRozm2DQ4OFutUt+NlinV16tRRM+F5npdnFy4gPzjv3J3QONF/xeXiuQJw3WquVLW8IznaW2l09axYtoQ+nzCJvvzsHSIzc7KxNBMuadcG79IP269Q9TKuNK5zbRGEAUBRY2NlQZXLOYopPT1TuLdZxEKfJdK9R/Eicwenn/Lztady3vZkla1YaKYO4xKNEcv8RhVu2LCBevbsSQ8fPqThw4cXSVRhfHw8OTurNxwuLi4UFxencVtep7odL2NDMvs6bfthUWaFV8AWnMKKA4b1hPrv4wThCoyISSX+bZYv7UD+fo4iNY+2mkv8I+8/eDjdjrGg+sNmKws3HvpnF6We+obmLlhIXRtVFIONAShueJwgW1k8ZSVtTqKHTxOFW/Hh0wRxX7IF5ufjICwyriCd27hEDiKRYwoq9obxpGiTZRVV6OjoSLGx6p3oPO/k5JTntvyel7GVlZ/9eHl5wVVooPBDyPPIZOEK5B8y/6g5Ios7u/lJlTOA68KmoM1CtHya/pfdgMWrUqu+9PTUJkoJuUAWr1cqwjMBQDdYpLhuGE9NJQ8xKJ4tsZCnnNElgvj57O7Vg5RCHvR2T+NJQaVqMKgaErKIKmQXIe+bhVHBlStXcgRmMLyM12najl+vXr2qFrHD85r2AwwPHrx55U6MiL7ae/I5hT5PpCrlHcXg4O6ty1DNyi46ixYzf/Ey8qyr2UXsVa8TLVyyQo9HD4B+YC9CKQ9balzLgwLfKps1VqyqC+3fvZladxikJQXVajJWtArXs2fP1ERp7969yvds0fzwww/05ptv0oULF/R6UBwCz+5IHujMgRonT56k7du3CysvO4MHDxZRheyufPr0qeh/42ANpnXr1mRhYUHz5s2jlJQUWrBggViu2j8HDIvMTEmMezlw5jlt2v+ILt6MJgdbS3qjvif161CemgV4qg0Ozg8JSSnCwtIEL49LTNLDGQBQdKiOE7OzlrSOS4yLTxa/J5MTrgEDBqiNn4qIiKDPP/9chJYr3Gocdv7o0SO9H9ivv/5KSUlJwjXJASGLFi0SltLx48eFC1DB6NGjqWvXrlS7dm2qVauWCJvnZQoLcdu2bbR69WpydXUV2T54PnsoPCh6OOpJEfmkCR6syWNa/twfSn+fe0GRManiqbLXm2VFpBSXZec+gMJgb2sj+rQ0wcud7O0KtX8ADCkFVUq6Gf2xN5SOnn9BDx5zAFNWvTFjQGs4vLu7O927d0+8Mt26dROuNhYJjvDjnIXa/JByAuHwRYO2wnsZmSRKqXOgBde2YiOKM6/7+zmJIn76HMuSKUnU79Pv6dK1YNGnlZ1np4Poy6FvU98+vfX2P4F+7p+NGzfSu+++SxkZGeLhlaOY+/TpI7vAA32zaVOQ1nGJrZvXozqN2ouSLMmpmeL3xS5HHiLCwR3ODlbGOY6Lx1JFR0eL95GRkWKs1rlz56hevXq0cuVK2rRpE+3atYuMAQhX0WZjVy28d3T/WoqPeUp9R8ygTMmMXBytRAg7W1V2tkUzbmrt0Tu0+shtSjy7imLJSfR1KaIKIy7vpepumfTn2pUmnxnDkISCj4W7DDi5AEcIK2CPS7t27Wjz5s0mLV6ZWsYlcgoqRTYPfmiLiE4RfcQsYlwwU1HpmR8Uy/nYk5ebjdaIXFkJF39w6dKlVLduXSFS7CbkMHiGs1JwKibuBzMGIFzF+0S4Y+MCqle3Jo0a/n/k7V6wPitdOXXrOU3fdIHeqlOWPulSi4I2bxGBGNynxe7BsaOGUZ9XeeZMGUMSCg7OWrNmDX344Yeinzs7fEycaKBfv35kymS+8mjMmbeM0lJTydPdgUYOH0yBgb1yvZ/jEtKUIsbRuqwANtbmWSJWmiMZ7UQ9MtkK17p162j69Omiz4j7hzp06CACIRTC5enpmSPcXK5AuPTPm+27UM8h32rsQOYnQ87ztm/PX0V6DA9fxNHHK05SeU8n+nFIE2R01wKP0WRLS1W0VAOm/ve//1H79u1F3zMHbeX2qm2drtuytZcXnHsUv9nCZc7gfq8nYUn0KCyRHoclUWpaphgb6eNpp3QpOthZyitzBgdnpKWlCdHiwceTJk1SruMd+vgYT3oRUHiyuyTyysaelJRSpMcTm5RK0zaeJztrS5rSuwFEKw84IleTaDFs9YwbNy5f++PsN7a2tmKys7PL8cpdEdmXq76fP3++1kGoHM38xhtvUJs2bUQEcdOmTcVnTdG1O2fOHGFETHF2zpdrlzN3VCrrKCaOQAyLTBYixr/h01cjxeTuYq0UMQ8Xa508E0WdgipPKeXQckV4uSoc3RcYKK/BbUD/pKVn0tPwJCFUqp3AnCjU2dFWWFa5WVyq2dj1TUZmJs3econCXybR94ObkKezbZH9L2NB0Z+dG9zH/csvv+QqNNlfWbgKw19//aVVuEqXLi2GuXz77bc0Y8YMES3cpEkTIWIKIePjMDXX7rvvvkt//vlnvl27HAzF2Wd4alTTnV7Gp4nfNIsYZ7Tnyd7WQggYuxV9NORRLK4UVIXODm8swFWoO4lJ6cqnsmfhySKThbWlOZUpleVeYB+5jbVFnlFPnI29qEb2c4b3oNMP6OMutalTvfJF8j+MiS1btlDfvn1F31JuNGrUiP755x+DcF2q9nGxpXHixAk6fPgwHTlyhC5evCgaUBsbG6WQsVX2+uuvG5WQbdDx+9EHySkZ4jfPQsb5FNMzJJFH0dfLTilkNtZmNGjIcHoQEkFPH/9LKSlJZGNjR75lK1LlCl4iWCQ/4qW37PDGDIQrd/gWiY5N/c8FGJNVwsbR3lLpQtBUikHXqCd98/e1J/TdtsvUtaEffdCplt73b0xwZQcOgODgKw62YgsnMTHRIIIh+P7p1asXHTx4UGOwCIutpvvn5cuXwiPEIsbTpUuXlELGVpiqkPEyObdZF7Qkf+AqHjyGVZM1zBMnZygInMH+eWSSSATMYsblg5jbl/bRmmU/UmTEc0pJ/i+gxsbWgTy8fOinH76lvn375Ov8IFx5AOFSJyvJZ/IrV0GC8ubksFkWKhYsDqfNS3gKEvVUGO4+e0mfrjxF1XxdafbA13UqCWGK8M+ekwtw7ToWhalTp4q+ERam/ApFcfThcFAYW1acfPvTTz8V1qGuxxITE5NDyPj8ufFmIVP0kTVu3NighIwDVUJDQ8UUEhKS4/XBgweF2r+VlZVOLl9tr/x9ZZIVxSeb09wfZ1JU5HNKS8vZd21ja0/+1arR1csXdT4+CJcOQLiIUlIzRGQRW1ZPXiRSWrpEFq/cASxUZUvZkb1tyUQY6UJMQgp9sPSEaNDmj2hOrg6G0wgZEpwejTPe7Ny5U7jSuIZdjRo19CYUcujLUxUyLlSrEDKu76cqZNmz7OhrnBv/Px4bq0mUFO9fvHih9hn+/n19fYVlzHUF+difP3+e6/+oVq2aCNrQNcJT1whQngoiG45OzhQX+1Ln7SFcJiZc+YnoiY3/b0xHmCghnlWNVfitS9uTryd3shu+1ZKWkUmT1p6lu09j6KehzaiKj3o5G5DVWLJIcUPL0cIc3s5uwoK6jIyFqKgopZBxP5kiaTdbFFw8VxHsweH3bJHqMs6Nv19+QMjNWuLX7C5Z/n8KUdL0yoV02UoqiT6u7PcRn192catXrz4lJ+ee79Pe3oESEjRHrWoCwmUiwqUtvZLiB8Uh6+HRKfToWVZwBUcOMVwmJMsF6ECerrqFvBoS83dfo50XQmlSj7rUplaZkj4cg+Pff/8VjRw3utwIc2KBypUrl/RhGSRsCbGQKYI9OM0dw9YXW1maxpjxOm5D+HfDwsQJv/n3mL10kjZh8vDwyNfvLrOAfYBFReXKVejBg/ta1lcWKQR1BcJlAsKVW3qlY/vXkmVmBM2cNY8ev8gao5HyKmTdx9NWaVk5aagYLBd2XwylubuuUe+mlWhku9dK+nAM7r5YuHChGIPJlhVXdGABM+VUSQURMs7NOmbMmBzuu+zixa5GTcLEU1GMMcs0INfuH3/8Iap1aIpM5aERHCjCCdN1BcJlAsKVV3oln7KVqVmrzqKfioWqrDdXUJV/4xX8KIomrD5DdSt60jf9GqF6sQq3b9+mESNGiLJAnTp1osWLF1O5cuVK+rBkC/cZ3blzR+v6W7dukamS+Wpc2b59+9TKYXHfIWdd2rp1a77EVFubLP+WywThZw0OpIiISRElvYPvv6RfFiwTlpYm3nx7MN28uJv6dyxPrRp4U6UyjkYhWuGxSTRj00XydrWjST3qQbRewU+83333HQUEBNCNGzdo1apVIhk2RKtwsDVTmPXGjrm5uXBPrlixQoz5YyHnV57Pr2jlheGGiBlJn1JBhYlzhsUlplO86pTEr2niPUf8qZKQmKI1vRIfnz7LhJQ0nGPtm40XKDktnb4b9Do52cnX1alPrl27RsOGDRPje3r06CHq2nGGCVB4OKhFWzAEu+hMHXNzcxEQUtTj/SBceuhTGjzmO2WfUtDOtfTXzt20asXSXMVLWExpmeqilIcwWVmakaO9lZhKe9qRk70lOdpZikHAPP2xyKHE0isVN/z9cZ/WnWcvaVqfhuTn5USmDie95ihBnrhoKvd7cEo2uQXZGDIc8s6plHILhuB+JVA8QLgKCFtaLFqqfUosGjzP6Yz++DOIOnTqnk2c0pRWFKdMyY8wsWtPWyPElh6LpqY+Ls5UwYN+jYWtZ/+lQ9ee0OBW/tS0WikydbgfYPjw4cLa4sTYnE+QKzcA/cIPohzybijBEKYMgjMKGJzRvmNX6j5oZq4WzvIFE+iDSb+pCRNH7imESDnZ6SZMeVFS6ZWKm4sPIujL9WepabXS9FVgfYMrflec8NiZadOm0Y8//ijcgRx80aVLl5I+LABKtqwJyJ3k5FStfUpW5pnUtrG3UqC4fEBRPw2ye5ItwaXLvxYlQ9g9WJTplYqbp1EJ9O3mi6K21ufdA0xatDipLEcMcpTbyJEjRZg7uwgBMAUgXAXE1tZaa5+Si7Md+fk4FOsxsXhxtvWiyrhekiSlptP0jVkJRaf2aSBqbJki3LfyxRdf0IIFC8QYoQMHDoj+FQBMCXNDTcHCEVFcdZV/nJwMNDf4SbNWrVrk5OREFStWFPOqVKhQQQz84w5UnriCqz7gPiUe3KsJY+tTKmk428cP269QaEQcfdmrPvm6F+8DgaHAQQG1a9cWovXBBx+IPi2IFjBFDFK4xo4dK0ahc8mFdevWiRHrwcHBGrflLjoekc2JM/fu3St+1JzDS5UdO3aIJ1We9u/fr5dj5JB3a4oUgRhsYTH8yvPcp8TuOaAf/jh+j07eei6yYtSvZHpBB1ymg8Ow33rrLfG7OHbsGM2bN088iAFgihicv4VLhHPkzvXr18UPs0WLFtStWzdas2YNzZ49O8f2EyZMUL7nAW/du3cXmQKKehyBKfQpGQKnb4fR6qN36M3aZajn6xXJ1OAM7qNHjxZZwPle52AMUytPD4DBW1zc2cx5rfz9/ZXLOANAbhZXduuLk2NyqQFVOESYE1yym1CR+VmffUr79vxFx47sE688D9HSD6HhcfT9tsvk7+NC4zrXNsrvlaNB2UOgmmmA5zkn3sCBA6lr167k7u5OZ86cEdkwIFoAGKDFxe687KlTXFxcKC4uLs/P8tMoNwScOUABuxrr16+fNWh17lyRM4vziWWPwOLKrxx+qWDUqFFiAiVDfHIaTdt4QURjTunToMijMksyt1v2Mhl8//I6zkLO9/TkyZNz1IUCwBhZsmSJmBRtcq5IxUyrVq143JjGqXnz5tLFixclOzs7tc/8+OOPUpcuXbTud/78+VKFChWkR48ead2uWrVq0l9//ZVjeYMGDQp4RkDfpGdkSl+sOyu9PXOXdD00UjJW/vjjD8nR0VHjb8Hc3Fz67rvvSvoQASgxtLXJxe4q5Po2bP1omnhsCrsIOUno3bt3lZ9h9152958qy5cvF/1f/ORatmxZrf+f3U0Yc23YrDx8m87fD6exnWpRzXLuZKxwdVpNee8YtriCgoKK/ZgAkAMG18fFIfDsPpkyZYoI1OBAi+3bt9OgQYM0bs+uQB7XwuNZKlWqpLaOq4zy5zmPG6fZ51D5iIgIUdUUGCaHrz+hjafuU+cG5ent+uXJmOGUQYVZD4CpYnDCxXBGa05n4+3tLQqPLVq0SGlxcfCFahjwV199JQq9cae2YqzWe++9J9ZxvxiH0ru5uYmy1xwuv2fPHlFpFBge9569pJ93XKWa5dxoTIfcLWxjgYOQtGHqZTIAkE1wBsNRVNu2bdO47o033lBzr3BJ8txgsVOU3QaGTUxCCk3fdIGc7K3p68AGZGVhkM9UeoFd1dwBzRG0ubmuUSYDAJkJFzAt0jMyaWbQRSFePw1tRm6OxlOCRZP7j6NVuTwGDyhmq4u9CCiTAYDuQLhAifPb/ht0LTSKJr5Tl6r6uJCxcunSJVHTib0EXDdr4sSJYjnKZACQPyBcoETZeymUdpwPocCmlaht7TJkjLArkPtpP/nkEzEQniNrOSOMguKoGAuAMWG8HQnA4LnxOJrm775ODSp50vC21clY8wyylcX5N9988026fPmymmgBAPIPhAuUCBGxyTRj0wXycrGjyT3rk4W58bnFLly4ILK2bN26VaRr4ryDqEwMQOGBcIFiJzU9g77ZdEHU2JrWpyE52VmRsbkG58+fT82aNRNjCI8ePSoS5HJuSwBA4cEvCRR7oz5v13W6/TSGJnSvSxW8nciYiImJocDAQProo49EUmd2DWLAOwD6BcEZoEjh1EWbgjbTxP/No/S0NHJ1sifLCk3o09GDqVn10mRMnDt3TkQDPnr0iH788UcRHYjIQAD0D4QLFKlo9R04lG7HWFCltz8gKztHSkuKpyfndtPOpbNoYKsVRuE+U1QeYHegj4+PGJfVpEmTkj4sAIwW+bcawGBhS4tFy6dpoBAthl8rtOxDt6LNxXq5w5W3e/ToIULdO3XqJMZqQbQAKFogXKDImL94GXnW7ahxHS9fuGQFyZmzZ89SvXr1aPfu3WIAMacp43RlAICiBcIFioyEpBSlpZUdXh6XmERydQ2yUPF4LO7D4nI8bHGhPwuA4gHCBYoMBzsb0aelCV7uZC+/MvRRUVHUvXt3Gj9+PHXp0oUuXrxIjRs3LunDAsCkgHCBIqN5u2706J9dGtdFXN5LY0cNIzlx6tQpqlu3riiPw8EYW7ZsESVzAADFC4QLFAnn7r2gK2nlyDYthp6dDlJaXvzK89XdMqlP70CSS3QkFyFt2bKlyObOAsbjtOAaBKBkQDg80Dv/hsXS/zZfoso+rrR5XxDt/Gu7CMSITkwS7sEvRw0ToiWHhp8rZg8ZMkQEYPTq1YuWLl1Krq6uJX1YAJg0EC6gVyLjkunrDefIzsaCpvdtRA621tS3T28xyQ0OuuCs7eHh4bRgwQJ6//33ZSG2ABg7cBUCvZHMuQf/PE9xSWn0Td9G5OlsS3KEXYOzZ8+m1q1bk62tLZ0+fVpkd4doAWAYwOICeiFTkuj7bZfp3vOXNLVPQ6oi04KQbF0NHjxYBGBwOZLff/9dFHcEABgOEC6gF5YfukUnb4fRe+1rUBP/UiRHjh07Rv3796fIyEhR+HH06NGwsgAwQCBcoNDsvhhKm04/oK4N/eidxhXI0N2AGzdupDlz5lBsbKywpjgZ7r1792jatGlUuXJl2rVrlwh7BwAYJuaGOsiT8785ODiQn58frV+/PtdtubGxsrIiR0dH5fTgwQPlei4r0aBBA7K3txevPA/0x8UHEaKKcaMqXjSmQw2DtlBYtHr27EnvvvsunT9/nu7cuSNeBw0aRFOmTBGuQS7+CNECwLAxSOHijnBra2sKCwujdevW0ZgxYyg4ODjX7bmURHx8vHKqVKmSWM5F/DjLwcCBA0UyVA5r5nleDgpPSHgczQy6QH5ejjS5Zz2yMPBM72xpHTp0SNwjqmRkZJCNjQ1169aNnJyMqz4YAMaIwbU0CQkJtHnzZpoxY4awnjgfHDcoa9asyfe+jhw5Qunp6fTxxx+LhokHjXKeub///rtIjt2UiI5PEWHvNlYW9E2/RuRgY/hVjNk9mF20FKSkpNDPP/9c7McEADAC4WL3DWcn8Pf3Vy4LCAjQanHt2LFDZOWuWbOm6FRXwJ+pU6eOmvuK57XtC+RNSloGTdt4nmLiU2h634bk7WInm4hBbXCfFwDA8DE44eIn4uzhxy4uLhQXF6dxe+6XuHnzpmiUOHT5m2++oT/++EO5L/6sLvvizzds2FA5LVmyRK/nZUxh7z9sv0K3n8TQxB71yN/XsLNIJCcn09q1a6l58+YUEhKidVuEvQNQsnC7q2iDtT1oFrtw8aBOtoA0TewWZPdg9idfns+t76FGjRrk6+tLFhYW1KxZMxo3bhwFBQWJdfnZl5eXl+ioV0yjRo3S63kbC6sO36bjN5/RiHbVqXn10mSo3L9/X1QkLlu2rAi+4B8B93VywI8m+F7h6EIAQMnB7a6iDeY22WCEi/uduJ9J08QpdthFyP1Sd+/eVX7mypUrwg2oCyyAvC+GP3P16lXlPMPzuu4LqLPv8iPacPI+dapXjgKbZAXAGBJ832zfvp06duxIVapUETWzWrVqRQcOHKBbt27RqlWr6K233hIipQrPt2vXTgT5AABkgGSA9O3bV+rXr58UHx8vnThxQnJ2dpauX7+ucdtt27ZJUVFRUmZmpnT27FnJ19dXWrlypViXkpIilS9fXvrll1+k5ORkaf78+WKel2enQYMGRX5ecubSv+FSp5m7pElrz0hp6RmSIfHkyRPpm2++kcqWLctPKFKZMmWk6dOnS48fP86xbUZGhvTHH39IjRo1kqpVqyZeeZ7vHwCA4aCtTTZI4YqMjJS6d+8u2dvbS+XKlZPWrVunXHfs2DHJwcFBOc8C5+7uLpZxQzR37ly1fV28eFGqX7++ZGtrK9WrV0/MawLClTuh4XFSz+/3SSN/PSLFJaVKhgALzcGDB6VevXpJlpaWQrDat28vbd26VUpLSyvpwwMAFBJtbbIZ/ylpq88Q4M5A9qsCdV4mptK45ScpMSWd5g1vTqXd7Ev0eHg83sqVK+m3334TEagcTTp8+HCRnondgwAA42+TkfIJ5EpqegZN33helCr5flCTEhMtfrY6d+6cGOqwYcMGESnYtGlTWr16NfXu3VtkcAcAmA4QLpCrWPy04yoFP4qmL3rWo9fKupXIYHQe2sCCdfHiRRERyNlPOJMKj+0DAJgmEC6gkbXH7tLh609paJtq1Kqmb7H+7xs3bghXIFtUL1++pFq1atHChQtFODvGWgEAIFwgB4euPhbC9VZAWerXvHKx/E/OH7l161ZhXR09elTkqgwMDBTWFQ8eNuTkvQAAE8+cAUqWa6FR9PPOa1THz53Gda5daMHgjOzcL9WoUSOqVq2aeOV5Xs5wNosvv/ySypcvT/369aPQ0FBRffjRo0ciwTIPSodoAQBUgcUFlDyJSqBvNp6nUi529HXvBmRlYa6XMiLZM7JzWZG5c+eSh4cH7dmzRyzr3LmzsK46dOhA5gaeZR4AULJAuIAgNimVpvxxTryf0b8ROdtZF1kZEZ4/c+aM6K+aPHmySPPCFhcAAOgChAtQWkYmzdh0gcJeJtHsga+Tr7vmfH76LCPCcHqvmTNn6uV/AQBMB/hkTBwOe5+78xpdDYmiT7vWoVrl3fW2b44I1EZuGf8BAEAbsLhMnD9O3KMDVx/ToJZVqW3tMnoTQ44QfPjwodbtENoOACgIsLhMmCPBT2nVkTv0Zu0yNKBlVb3s8/bt2yLAolevXlS6dGmys9NcZBJlRAAABQXCZaLceBxNP26/QjXLudHHXQof9s5uv4kTJ1Lt2rXpn3/+oXnz5tG9e/eEiKGMCABAn8BVaII8i06kaX+eJ09nW5rapyFZW1oUyi34559/0vjx4+np06c0bNgwmjVrFpUqVUqs37x5s4gu5NpYXMST3YNsabFoYXwWAKAgQLhMjPjkNPr6j38oI1Oimf0bkYt9wcPer1+/Th988IHIdFG/fn0hUk2aNFHbhsdk8cBingAAQB/AVWhCpHPYe9AFYXFN7dOAynqou/DyEy348ccfU926denatWsiryC7B7OLFgAAFAWwuEwEdunN33OdLv8bSZ91C6A6fh4FyoSxZs0amjBhAoWHh4uBw99++63IgAEAAMUFhMtE2HT6Ae299Ij6t6gikufml0uXLgm34KlTp+j111+n3bt3U4MGDYrkWAEAQBtwFZoAx28+o2WHblGrGj40uLV/vj4bFRVF77//vqhGevfuXVq+fLkQL4gWAKCkgMVlRLArb1PQZpq/eBklJKWQg50N9erdjw5FetFrZVxpfLcAMtcxki8jI0OIFOcSjI6OprFjx9I333xDrq6uRX4eAACgDQiXEYlW34FD6XaMBXm+Powc7BwpLSmefg3aRVJ8BK0+sJlsrHQLe+dACxaq8+fP0xtvvEELFiygOnXqFPk5AACAbF2F7J7q0aOHKNXu5+dH69evz3XbTp06iQGtiokLEPIgWAUVKlQQ2RsU69u3b0/GCFtaLFo+TQPJyi4rWpBfK7XqS7Zu3nRgz84898EBFyNHjhR9WI8fP6a1a9eKUHeIFgDAkDBI4eKnfRagsLAwUUyQ6zQFBwdr3JbrOXEGcsXUrFkz6t27t9o2O3bsUK7fv38/GSPsHvSs21HjOu96nWjhkhW5fjY9PZ0WLlwosrWvWrWKPvvsM5G6acCAARgkDAAwOAxOuBISEsRA1hkzZggLiSvgduvWTYRh5wUndT1+/DgNHjyYTA3u01JYWtnh5XGJSRrXnTx5UgRecMQgB1xcvXqVfvjhByTABQAYLAYnXHfu3CFLS0vx9K8gICAgV4tLldWrV4s+GXYPqsKWg5eXl3ATXrlyhYyN5LQMSs0wE31amuDlTvbqyW6fPXsmBJ4fDNg1u2nTJjpw4AC99tprxXTUAABgJMLF7rzsT/suLi461W5i4Ro6dKjaMnY1siUWEhJCbdq0EUlfY2JiNPbvsOWhmJYsWUJyEKzNZx7QkPl/k1XFJvTk3C6N20Vc3ktjRw0T79PS0ujnn3+matWqiRyDX3zxBd28eZMCAwPhFgQAlCjc7iraYG6TDUa4WrduLRpITRM//bN7kJOxqsLzTk5OWvd74sQJev78uWiAVWnevLkIzrC3txeh3RzOze7E7LBFxlF0iomzQshBsJYcuEkVvJ1o1exPKcDbjJ6dDlJaXvzK89XdMqlP70A6fPiwSNPESW75u+Zcg5z5goNgAACgpOF2V9EGc5tsMOHwR44cybOPi4MFeLBr1apZNaLYvVezZk2tn+Oggp49e+YooZEdFkhOfyRHklPTaeeFUNp0+j7FJKRSvYqeNLBlVWXV4vWrltH48Z/R8gWjhGVlZWVFw4cNo08//UQkueUs7exG3b59O3Xt2hUWFgBAlphJBtiKcyPLjerSpUvp8uXL9Pbbb4tsDbmJV1JSkihayFV327Ztq1weGhpKjx49okaNGolxTvPnz6fvv/+ebt26lSO/HpumrPJyFCyGz4+F+9ChQ8LdqoCjM3kwMfcbssXJeQZzK+4IAACGgrY22SAHIP/66680fPhw8vb2FgKzaNEipWixm4/Hbqk2ztu2bRMuQO7DUoX7xTiU/v79+2RrayvcZBw+L5eksCxYOy6E0KZTD+hlYirVr5QlWDXL/SdYCtiayi5aTGpqqhAtFuyPPvqoGI8eAABMyOIqCQzJ4sqPYClgq1Lb8fN6zogBAAByQHYWl6kiBOt8iMjkzoLVoJInDchDsBRkD2jJ73oAAJALEC6ZCxbDWS6ePn2qdRsMKAYAGAsQrhIk6ZVgBSkEq7KXcAnWKOum0+e5/4r7rmbOnEkWFhZkY2NDKSkpObbjSEsOgQcAAGMAwiVDwWJOnz5N7777rsgo0qdPHzGomHM8Hjx4UC1Ag0WrXbt21Ldv3yI6GwAAKF4gXMUsWH+dCxGDh1mwGr4SrNfyIVjcV8Vh7RxpWbZsWZFAuEuXLmId53jk6MKffvpJbMfuQba0WLQwZgsAYCxAuIpRsIJO36fYpLQCCZYi7J+T4XJ/1ocffihchKoZRczNzcUYOJ4AAMBYgXDpueLwh6NHUO/AXkJEElPYJfhQuAQLI1gKodqyZYuojcWvjRs3LrLzAgAAQwbCpeeKw9+u3E0bt/5Fge9/TVvOPhSC1ahKlmBVL+OW7//BSScnTpwoAjFmzZpF48ePF6mcAADAVIFw6aHisGrdK56/emQD3V+4krp0f6dAgsXcuHFDJJzkelmcxmrx4sVUpUoVPZ8FAADID4Mra2IMFYfLvd6FrJ6ep5n9G+dbtDicfdq0aSI9FZcbWbFihYgUhGgBAEAWsLgKSFafVu4Vh9PT0/K9T87DyFYWJwHm4pccHcj5GgEAAPwHLK4CwoEY+ak4rA0ubDl69Ghq2bIlJScni0TAa9euhWgBAIAGIFwFhKMHubJwXhWHtcH5jYOCgui1114TJVw48IKLO3bsqNkFCQAAAMJVYDjknSsLa6s4rA2uE/bOO+9Q7969ycfHR2Ru//HHH1GNGAAA8gB9XAWEx2ltWLNCRBcuXLKCohOThHvwy1HDhGjllqmCizpy1gvOfsHvWazGjRsnamYBAADIG7SWhRSvvn16i0kXrl27JoIvzpw5Q+3bt6fffvuNKlasWOTHCQAAxgRchcUAB1x8+eWXVL9+fbp3754IvNi7dy9ECwAACgAsriLm8OHDImLw7t27NGTIEOEa9PT0LOnDAgAA2QKLq4iIioqiESNGiKwX3Jd14MABWrlyJUQLAAAKCSyuQsC5BLmMyJw5c9TKiHCY+yeffEKRkZEiz+CUKVPI3t6+pA8XAACMAoO0uBYsWEANGzYUFX2HDh2a5/ZcRLF06dJCOIYPH65WBfjhw4fUpk0bIRzVq1cX6ZP0JVo9e/YUxRzPnz9Pd+7cEa+DBg0SWS/Kly9PFy5coNmzZ0O0AADA2IXL19eXvvrqKyFCebFv3z4hDocOHaKQkBB68OABTZ06Vbm+f//+VK9ePWH9fPvttxQYGEjh4eGFPka2tPh/qlYbZtgtyILLFldAQECh/w8AAAAZCBdbMjw418PDI89tV61aJfqSatasSW5ubvT111+LviSGraCLFy/S9OnTyc7Ojnr16kW1a9cWlYILC7sHs4uWArb4fvnll0L/DwAAADIRrvwQHBysZtnw+7CwMGFh8bpKlSqpVQnm9by8sHCfVmHWAwAAMFHhYqvHxcVFOa94HxcXl2OdYj2vyw67D7lfTTFxAUdtcH9aYdYDAABQh9tdRRusrUun2IWrdevWIh2SpqlFixb53p+jo6OadaN4z1ZW9nWK9aoWmAIvLy8RXKGYOMOFNjghLu8/t2Pi6EIAAAC6w+2uog3mNtlghOvIkSMiXFzTdOLEiXzvj/u2rly5opzn96VKlRL9Y7yOgzVULSxez8sLS58+fahdu3Y5xIvneXnfvn0L/T8AAADIxFWYnp4u0iRxhB5P/J6XaWLw4MG0bNkyUeqe61rNnDlTGULv7+8vKglzcAbvY+vWrXT16lURpKGPPIUc5PH7779To0aNqFq1auKV57ds2ZJrkl0AAACFRDJApk6dKvGhqU68jAkJCZEcHBzEq4I5c+ZI3t7ekpOTkzR06FApOTlZue7ff/+VWrVqJdna2kr+/v7SgQMHNP7PBg0aFMOZAQAA0AVtbbIZ/yms+BkD3BnIflUAAACG3SYbpKsQAAAAyA0IFwAAAFkB4QIAACArIFx6Iq8By8aIqZ0zzte4wfnKBwiXnpDzTVBQTO2ccb7GDc5XPkC4AAAAyAqEw7+CKxNXqFChwJ/nvFraUpQYI6Z2zjhf4wbna1hwLcWIiAiN6yBcAAAAZAVchQAAAGQFhAsAAICsgHABAACQFRCufBAVFUU9evQgBwcH8vPzo/Xr12vcjrsNJ06cKEqr8MTv5diVqOv5Tps2jaysrERJF8XE5WTkxoIFC0R+NBsbG2WFgdz4+eefqXTp0qJg6PDhwyklJYWM9XxXrlxJFhYWateXyxPJCb4+I0aMEPcx1+PjqhF79uwx2uubko/zleP1hXDlg7Fjx5K1tTWFhYXRunXraMyYMRQcHKxxfMS2bdtE7S8uo7Jjxw5avHgxGev5Mlx/jCtOK6ZKlSqR3PD19aWvvvpKNFTa2LdvH82ePZsOHTpEISEhQqSnTp1Kxnq+TNOmTdWuLxeElRNcFqlcuXJ09OhRevnypSh/xDX1OHLNGK9vej7OV5bXV6f88kCKj4+XrKyspNu3byuXDRw4UJo4cWKObZs2bSotXrxYOb906VLp9ddfl4z1fLnkzIABAyRj4csvv5SGDBmS6/r+/ftLkydPVs4fPHhQKlWqlGSs57tixQqpefPmkrFRu3ZtKSgoyOivb17nK8frC4tLR+7cuUOWlpaiOKWCgIAAjRYIL+N1eW1nLOfLsFXp7u4uqksvWrSIjBlN15et0sjISDJWLl26JMY68v0wY8aMXAu7ygW+XnyPa6qGbozXN0zL+crx+lqW9AHIBTaf2d+tiouLC8XFxWncltepbsfLuJ9LLpWR83O+7IIYNWoUlSpVis6ePSsqTLu6ulL//v3JGNF0fRn+brhP09ho2bIlXb9+XfSXcKPObmF+qJk8eTLJkbS0NBowYAANGTKEqlevbvTXNy2P85Xj9YXFpSPcYRkbG6u2jOe54zOvbfk9L5OLaOX3fGvUqCH6S7iDt1mzZjRu3DgKCgoiY0XT9WU0fTfGAPdXVqxYkczNzal27do0ZcoU2V7fzMxMGjRokOi75eAUY7++mTqcrxyvL4RLR9iEZvP57t27ymUcfKHJ9OZlvC6v7YzlfLPDAi3HKEpd0XR92dqU49N4QZDr9eVj5kg7dptt3rxZRMIa8/WVdDxfWV7fku5kkxN9+/aV+vXrJwIXTpw4ITk7O0vXr1/Psd2iRYuk6tWrS48fP5aePHki1ahRQywz1vPdtm2bFBUVJWVmZkpnz56VfH19pZUrV0pyIy0tTUpKSpImTZokAlH4PS/Lzp49e0RnfXBwsBQdHS21adNGY9CKsZzv7t27pefPn4v3N2/elGrWrClNmzZNkhujR48WQVJxcXFatzOW6ztax/OV4/WFcOWDyMhIqXv37pK9vb1Urlw5ad26dWL5sWPHJAcHB+V23IB//vnnkpubm5j4PS8z1vNlcXN3dxfLqlWrJs2dO1eSIxwdyc9yqhMvCwkJEefGrwrmzJkjeXt7S05OTtLQoUOl5ORkyVjPd/z48eJc+T6oWLGi9PXXX0upqamSnHj48KE4PxsbG3Fuimnt2rVGeX0f5uN85Xh9kWQXAACArEAfFwAAAFkB4QIAACArIFwAAABkBYQLAACArIBwAQAAkBUQLgAAALICwgWADOHsDoZeMwmAogJJdgEwQDhfnoLExERR7JFzQTJc201u1QYA0CcYgAyAgVOhQgVaunQptWvXrqQPBQCDAK5CAGQqZgcPHhTvp02bRr1796aBAweKDOac4ZtrL82aNYu8vb1FJdz9+/crP8sVcTn5qo+PD5UpU0ZUQc7IyCjBswEgf0C4ADACuJAnl6+Ijo6mevXqUYcOHURJiydPnogyFaNHj1ZuO3ToUFFv6d69e6KAIIsaW3QAyAUIFwBGwBtvvCHEigWJra/w8HCaNGmSKGXRr18/evjwIcXExIgSF7t376ZffvmFHBwchEX2ySef0IYNG0r6FADQGQRnAGAEcL0oBXZ2dqIMuyKYg+cVlX2fPn0qKuKym1ABW2bsTgRALkC4ADAhWKA4QjEiIkJYZwDIEbgKATAh2NJq3749jR8/XpSkZ2vr/v37dPTo0ZI+NAB0BsIFgImxevVqSk1NpRo1apCbmxsFBgbSs2fPSvqwANAZjOMCAAAgK2BxAQAAkBUQLgAAALICwgUAAEBWQLgAAADICggXAAAAWQHhAgAAICsgXAAAAGQFhAsAAICsgHABAAAgOfH/7wrvu9FFJmUAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "markers = ['o','s']\n",
+    "\n",
+    "for idx2, target in enumerate(target_list):\n",
+    "    fig, ax = plt.subplots()\n",
+    "\n",
+    "    for idx,he in enumerate(he_list):\n",
+    "        res = bitstring_to_expectation_value(np.array(zz_fine[(target,he)])) * bitstring_to_expectation_value(z0[he][grid.physical_qubits.index(target)])\n",
+    "        ax.errorbar(x = np.arange(len(res))*dt,y = res, yerr = 2*np.sqrt(np.array(zz_fine_sdom[(target,he)])**2 + np.array(z0_sdom[he][9])**2),color = blues_color_list[2*idx],marker = markers[idx2])\n",
+    "\n",
+    "    ax.set_xlabel(\"Time\")\n",
+    "    ax.set_ylabel(r\"$S_{ZZ}$\")\n",
+    "    ax.set_title(r\"$S_{ZZ}(t)$ \"+f\"for qubit Q{idx2+1} as a function of time\")\n",
+    "    ax.set_ylim(-1.1,1.1)\n",
+    "\n",
+    "    plt.show()\n",
+    "\n",
+    "fig,ax = plt.subplots()\n",
+    "ax.set_aspect(0.1)\n",
+    "\n",
+    "bounds = [-0.05]+[np.mean(he_list[i:i+2]) for i in range(len(he_list)-1)]+[1.7]\n",
+    "norm = matplotlib.colors.BoundaryNorm(bounds, blues_cmap_r.N)\n",
+    "\n",
+    "matplotlib.colorbar.ColorbarBase(\n",
+    "    ax, cmap=blues_cmap_r, norm=norm, orientation='horizontal'\n",
+    ")\n",
+    "\n",
+    "ax.set_xticks([np.mean(bounds[i:i+2]) for i in range(len(bounds)-1)],he_list)\n",
+    "ax.set_xticks([],minor=True)\n",
+    "ax.tick_params(top=True,bottom=False,labeltop=True,labelbottom=False)\n",
+    "ax.set_title(r'$h_E$')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2bbfb370",
+   "metadata": {},
+   "source": [
+    "### String Breaking"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "afb0db77",
+   "metadata": {},
+   "source": [
+    "Lastly, we want to examine the effects of string breaking by looking at the pair creation of charges that occur when the string breaks. To pinpoint the effects of the string on pair creation, we choose the most confining scenario ($h_E = 1.4$) and compare the dynamics of evolving two initials states: (1) just the WALA initial state and (2) the WALA state with the same string excitation that we used to study the string dynamics above. By comparing the effect that $\\lambda$, the string breaking parameter, has in these two experiments, we can identify the interplay between string-breaking and pair creation.\n",
+    "\n",
+    "Let's define the circuits for both initial states:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "4a222df8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he = 1.4\n",
+    "coupling_list = [0,0.25,0.5]\n",
+    "dt = 0.3\n",
+    "trotter_steps = np.arange(10)\n",
+    "string_excitation_indices = [(-2,1),(0,1),(1,2),(2,3),(3,2),(4,1),(6,1)]\n",
+    "string_excitation_qubits = [cirq.GridQubit(idx1,idx2) for idx1,idx2 in string_excitation_indices]\n",
+    "\n",
+    "excited_evolution_circuits = []\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for step in trotter_steps:\n",
+    "        excited_evolution_circuits.append(cirq.Circuit.from_moments(\n",
+    "            *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "            cirq.Moment(cirq.X.on_each(string_excitation_qubits)),\n",
+    "            *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he,extra_z_plaquette_indices=[(0,1),(3,1)])*step,\n",
+    "            cirq.Moment(cirq.measure(grid.physical_qubits, key=\"measure_all\"))\n",
+    "        ))\n",
+    "\n",
+    "wala_evolution_circuits = []\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for step in trotter_steps:\n",
+    "        wala_evolution_circuits.append(cirq.Circuit.from_moments(\n",
+    "                *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "                *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he,extra_z_plaquette_indices=[(0,1),(3,1)])*step,\n",
+    "                cirq.Moment(cirq.measure(grid.physical_qubits, key=\"measure_all\"))\n",
+    "        ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c7cffaf",
+   "metadata": {},
+   "source": [
+    "And simulate the results:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "07b0838c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_excited_evolution = simulator.run_batch(excited_evolution_circuits,repetitions=reps)\n",
+    "results_wala_evolution = simulator.run_batch(wala_evolution_circuits,repetitions=reps)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c3e7c0ef",
+   "metadata": {},
+   "source": [
+    "Now we can calculate the probability that a charge is pair-created at each site as these two initial states evolve in time:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "3105d6de",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "counter = 0\n",
+    "\n",
+    "trotter_steps = np.arange(10)\n",
+    "\n",
+    "occupations_excited = {}\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for step in trotter_steps:\n",
+    "        res_excited = results_excited_evolution[counter][0].measurements['measure_all']\n",
+    "        occupations_excited[(coupling,step)] = lgt.plaquette_bitstrings(res_excited,grid,particle_locs=[(0,1),(3,1)])\n",
+    "\n",
+    "\n",
+    "        counter += 1\n",
+    "\n",
+    "counter = 0\n",
+    "\n",
+    "occupations_wala = {}\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for step in trotter_steps:\n",
+    "        res_wala = results_wala_evolution[counter][0].measurements['measure_all']\n",
+    "        occupations_wala[(coupling,step)] = lgt.plaquette_bitstrings(res_wala,grid)\n",
+    "\n",
+    "        counter += 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2da10dfa",
+   "metadata": {},
+   "source": [
+    "By substracting the expectation value of $A_v$ of the two initials states, we can directly see the effects of the string, which is mostly located on the top qubits. The results, plotted below, show that charges are pair-created when $\\lambda \\neq 0$, but predominantly on the middle and top rows of charge sites where the string is located, with enhanced pair creation as $\\lambda$ increases."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "371760ae",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAErCAYAAAAokrM1AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAAMtlJREFUeJzt3Qd4VFX6x/Ffeq8khEAogdA7KCBFAdeCghQril0RUKwg7FoW1w4qoojK7l9RsKwiggVUEBSRoigoHQIhEEhCeu+Z//Ne9saEQAjJnLnnnPt+nycPZDKZuZkkn5w599w7bg6HwwGO4zhOydyt3gCO4ziu4THiHMdxCseIcxzHKRwjznEcp3CMOMdxnMIx4hzHcQrHiHMcxykcI+7k3n33XezYscMpt7VkyRL8/vvv0DFnPk4qPFa33XYb/va3v531ekOHDsVdd911zrf/6quvwtPTE0OGDEF+fn4Dt5JTMUbciWVnZ+Oee+6Br69vrY+lp6cjMjIS3t7eKC0trdft/fnnn3jppZdgp8dJ18dq3rx5+PTTT6veJ9AJdmdF8H/++efYsGEDvvnmG4hq5cqV6NWrF3x8fNCmTRu88sorZ/2cWbNmwc3NrdZbfHy8sO20U4y4E/vyyy/RoUMHtG/fvtbHZsyYgcmTJ6OsrAw7d+6s1+2NHTsWX3/9db0h0+Fx0vWxCgkJQVhYmLDbDwwMxKhRo9CqVSvjD5qItm7ditGjR2PEiBHYvn27gfM//vEPvPXWW2f9XAI/OTm5xltsbKyQ7bRbjLgTo5EQYXJqmzZtMt6efPJJREdHY9u2bfW6vQEDBiAgIADff/897PA4qfJY0X3Qs4TCwkLj/eLiYuNZxeDBg6uus3r1auM65tRG9ekU+j/dxnvvvVc1Kv3hhx9q3MfTTz+NZs2aITw8HLfccku9pkgqKyvh7+/v1Gmq6tGo+/zzz8fzzz+Pzp07G1/H1KlT8cILL5z1cz08PIyvp/obXcY1PkbcSdEv9LffflsLp4qKCkyZMgVz5swx5iy7d+9e77lb+uWmkc+yZcug++Ok0mM1cOBAuLu746effjLe//nnnxEUFIRff/0VBQUFxmVr1641wKMR8ummVmju+rrrrqsaldJtmi1duhSZmZkG7B9//DG++uorvPjii2fdrtdffx179+4960j8ueeeM7arrje6zqnR13n55ZfXuIzeT0xMRFJSUp33SR+PiYkx3mgkv3HjxrN+PVz9YsSdFMFE87h9+vSpcfkbb7yBpk2b4sorrzTePxeYKMLuiy++MEZZdXW6X7rqVUdCxsfJlY9VY/Pz8zNG/uaon8C+6qqr0K5duyrY6bLhw4efcWqFRul0O+aolN43a926NebOnYtOnTrh0ksvxfXXX481a9bUuU0E6WOPPYZx48YhISGhzpH7pEmTjOmQut7oOqdGf2xoW6tnvk8fO1P9+vUzdmTTdNdHH32EJk2aGH/E6NkK54ToLIZc47v99tsdU6ZMqXFZcnKyIzw83LFz586qyxYtWuTw9/d3VFRU1Ot2S0tLHQEBAY6NGzfWeT26zumqrKys933Vt3/+85905ss63+g69X2cXP1YOaNZs2Y5+vbta/x/wIABjg8++MD4uqZPn+7IyclxeHh4ONauXVt1/VtvvdVx8cUXV71P/6fLTu2iiy5y3HzzzTUu+9e//uWIjY2tc3suu+wyx7hx44zHjx7/zZs3O5ydl5eX4+23365xmXl/v/zyyzndFn2dl1xyiZO30J7xSNxJtW3b1hgBVe+RRx4xnhb37NnTmB6gtzvuuMOYUqCnvdQff/xRYy718OHDxt5/czSZmpqKoqIiY8cQRU/XR44ciR49eqBbt254++23MX36dOM69HnXXHONcRs0iqM5SxrN0ioA82k9fYzmM2l1SNeuXY2RHn1u9blY2ulI2zR+/PjTrvi47777sGfPnjrf6Dr1fZzq81id7XE63WM1c+ZMY+mdGf3/iSeeMEbsffv2Nb7+2bNn19iOxYsXG48tbQc9lmeKRtk0X3/kyBH89ttvxvv0RiPwH3/8EV5eXg1+9lN9VG5OFdX17OL99983pnIWLFiAjh07GitH6ppSaeh0Cu2jSElJqXEZPebmx86lCy64wPgeck7I6r8iukQjEm9vb2MURq1bt84RGBhojIh27NhR9fb777873NzcHEuWLDGuV1xc7GjatGnV7dDobOnSpVXvv/76644LLrig6n362J133ln1flZWVq2ReEJCgnEfmzZtqrrM/Dh9jEaJ27ZtM96/9tprHYsXLzb+T6Op7t27OwoLCx25ubmOuLg4x5w5c4Q+TvV9rM72OJ3usdq+fbujf//+Ve/T/3ft2uVIT0+vGrn369fPER8fX7Vt7du3d5w4ccJ4PyMj44xfR0lJifEsgb4XXbp0qbq+p6en47bbbnMMHz68xvVPHYmPGDHCMWHChNOOUKt/f6mnn37a0bp169NuR2pqqvEM5r333qu6rE+fPo6pU6eecdtpOw8cOFDn2+m+9vHjxzsGDhxY4zJ65nGmbaurSy+9tNZjxDUsT2f8IeBgjOpoBEjraK+++mrce++9uP/++9G/f/9a16VlYDTXe9NNNxmjptDQUKSlpRnro2nUuWjRohorOWie04xGiNOmTTNG31dccQWGDRt22u2heVWatz1dtLSLRrEUjUjNERHtuBozZowxV0vRkjWRj9MNN9xgLCOs72NV1+N0pscqLy/P+ProtU9olN6lSxc888wzxs5DGt3SDjd65kDz2TSKvvbaa405e4pWhtQ1Wh40aJCxwsScP6br07MjOvCIlt/VFX0P1q1bh4MHDxpz5PRGo/dzzXzcaAVL9a+7rhUqtJ11fW1n6qGHHjKeXdDc+80334wtW7YYO1Np/r568+fPN97MZ5sPP/yw8eyRvu+5ubn497//bcyHr1ix4py3gasdT6c4MXqaTpDQDzXt6CFoTxdNdVTfYUewECS0rO6pp56qupymF9avX19jJUdcXJzxub179zamAh544IHT3gcttztT9IfDjJZ5lZeXw4rHiTqXx+pMj9OZHiuKdgrSCg96oz8aNNWxatUq4w8WTTnQH0FaItiQ6HPpsau+A5P+f+plp4umjyIiIgxw6Y8GbU9D1tvTH0OaUqve2RBvaLTaZvny5cZqGboP+j48++yztXaC0h/Zffv2Vb1P31/6I0PTeDR9Rx+jHbUiBgm2rIEjeO40bdmyxREUFGQ89T+XHnvsMcfEiRMdQ4cOrXE57djr0aNHjcuSkpKM6Q6KpksGDRpk/D8sLMx4im9OmXTt2rXG51WfTqn+MZouMXdC0nRKz549jdvPy8szphacPZ0i4nE602NF7d+/3/ia6O3QoUOOFStWOK644grjY4mJiY7g4GDHp59+arxPUy0dOnRwpKWlnXU6heNkiadTnDxSoafFNMowl8nVd4rhxhtvNA6ZPttBMbt27TKmU2idMo2izR2PNBqi0RHdVkMPP6ftp+kU2rFHS8dop2hwcHCDbsuVj1NdBxDRUaG0k5SmKmgKo0WLFli4cKExKqT3L7zwwqrr0kifdnzSCJseX9pJ+MknnzTiK+U48bmR5C64H06RaH0xrU6gVSG0lpfAo3lzjuPkjEfiXI3onCU0n0rzxBMmTGDAOU7yeCTOcRyncLw6heM4TuEYcY7jOIVjxDmO4xSOEec4jlM4RpzjOE7hGHGO4ziFY8Q5juMUjhHnOI5TOEac4zhO4RhxjuM4hWPEOY7jFI4R5ziOUzhGnOM4TuEYcY7jOIVjxDmO4xSOEec4jlM4RpzjOE7hGHGO4ziFY8Q5juMUjhHnOI5TOEac4zhO4Tyt3gBOrkrz85G8eTMyd+9Gxu7dyNyzB5l796IkO7vG9dzc3REcG4smXbogvFMnhHfujKa9exvvc3WXl5SElC1bkLFnDzL2nHyMs/bvR0VJSY3refr5IaxjRzTp3BnhnbsYj230gAEIiIqybNs5+XJzOBwOqzeCs7aSnBwc+uorxH/+ORJXr0ZFcXGDbyu0fXvEjRmDuLFjEdW3r1O3U+VyDh3CgWXLcODzZUj59Veggb929Mez+cBBaD9uLOLGjkNQTIzTt5VTK0bcxhHYfyxYgCNr1qCitNTptx/cpg06jR+PXvfdB7+ICNit8uJi7Fr0Lna+8w5ObNvm/Dtwc0N0//7ofvfd6HzjTXD35CfWdowRt2Hxy5dj6+zZSP3tN5fcn6e/P7rdeSf6PvQQAlu0gO6V5uXhz7ffxu/zXkVBSopL7jO4dWv0feQRdLv9Dnj6+rrkPjk5YsRtkqOyEvs+/hi/zp5tzMFakYe3NzpNmIDzZ8xASJs20K3i7GxsmzcP296Yj5KsLEu2wT8qCn0eeBC9pkyBV0CAJdvAuTZG3Aad2L4da++7D6k0FytBHr6+OP/RR3He9OkG7Dq054MlWP/ooyg8cQIyFNSqFYa+Mhdxo0dbvSmc4BhxzZ/Wb3rqKWPe21FRAdkK7dABw197DS2HDYOq0cqdtVOn4ugP6yBjbUeOxLBX5xnTLZyeMeKatn/pUqyfPh0Fx49D9jpefz0unDPHmApQpfKiImx57jn89srLQnYKO3ufxIDHn0CfBx+Eh5eX1ZvDOTlGXLNoPfeaSZOM5YIq5RMWhksWLkS7q66C7KX9+Qe+vvFGZO3bB5Vq2qcPrljyAcLat7d6UzgnxohrVPKWLfjmlluQe/gwVK3nlCkY/MIL8PTxgYxtf3OB8Qzn1ANzVMk7KAjD33gDncffaPWmcE6KEdekrS+/jE1PPonK8nKoXmTPnhjxgVwjRlp5snri3co9wzlTXW69FcPnvcYrWDSIEVe8wrQ0fHfnnUj89lvolFdgIIa99ho633ST1ZuC45s3Y9WEm5CbmAidotMlXPnRR4jo1t3qTeEaESOucHQU4JdXX438Y8egaz3uuQcXzZ0Ldw8PS+7/z38vxLr779fiGc6Zlnte9n/voON111m9KVwDszXiZfn5yN63F9l796I0N8f4gfbwoTef//3fB4EtWyG0Y0fI1qGvv8Y3N9+MsoIC6F7ryy7DFR98YMznuvLgqJ9mzsRvc1+B9rm5YdC/nka/mTMhW/nHkpC9bx8qioqM/RB0Xh/zX3cvL+N3M6xLF/g2sd9pHWyJeNbuXTiy8mtk7d6N7L17kH/0aL1OROQTFo7Ifv0Q1X8AmvYfgLBu3SwbGVLb5s/HT9OnG9DYpYju3XHV558jqGVL4fdVVliIb269xTg9gZ3qetttuHjBm5YuQ8yJj0fqlk1I3bwZqZs3oSApqV6f5xvZFGGdOyOscxe0GDYMzS8aCrukPeK0nvfwiuU48MFiZDjpJEQ0X9ts8BB0umsiogYMgKuqrKjA+mnTjIN37FhAdDRGLVuGqD59hN0HnetkxdgxSN26FXas5bDhGPnJJ/ANDXXZfeYcPIjdb7+JI998g+I05xzxGtS6DdrfNAFx48fDLyISOqct4vlJSdj91gIkLPsMZbm5wu4nou956DrlXrS87HKIPs/3qgkTcHjVKtg5OnDl8vffR7tRo5x+2+k7d2L56KuQd+QI7BydG37Mii8QEhsr9H7St/2OHW/Mx9FVK4U9q3T38kLLy0eg2+QpiOgt7o+/lWmJ+L73FmHbc8+g3IXzxSHtO6DLpMmIHXe18YPjzGjH5YoxY5D+559OvV1Vo3NqD3nxRfS+/36nnpb3qxuuR6nAP/gq5RcZiauWfY7mAp5pHvthHXbOfx0pP2+AK39mOt89Eb1n/N14sQ2d0grxvMREbJ7+CFI3/mzZNvhHN8d5T/0Lra640mknr/pi7FglDp93dT0mTcJFr7zS6P0Tuq9AaWi0c//yd95Fh2uvdcrtZezYgY3THkKmhYOR4LZtMXDuPET16w9d0gZxY/T97NMoLyyEDMWNvxHnPfW08fS/oSWsWoVVN91kixUoDa3N5ZcbBwZ5BwY26PPXz5hhnP+Eq2PlytPPoN+MGY26mZ0L3sC2F59HpQTnmXFzd0enO+5E38efNFagqZ4WiG+f/SJ2vvYqZCsoti0Gz1+AJj17nvPnHvjsM+MQeh4dnr3mAwdi9BdfnPMSxDWTJ2HHf/4jbLt06vxHZ2Dws8+e8+cVJidjwwNTkfzTeshWzN8uwdD/vKM85MojLivgZjQ/3mPadHSdfK8xAqhP9OIN395xh5Snj5W1Zv36YcxXX8EnJOSs16WdaN9NvBu733vPJdumS30fehgXzp5d7+sfWbUSGx95yLIXyLAL5EojLjvg1YsaOBAD572OgOjmdV5vz5IlWH333bZaA+7Ms/SNXbkSvmFhdS7T/PaO27H3ww9dum261HvqVOPFJuqqvKgQvzz5BA4sWQwVilEccmUR/+PlOdih2NF0vhERuPjDjxHWpetpP04vqLv23nsZ8EaePGvsqlXwa9Kk1sdoamrVrbdg/yefWLJtOu1Qvvj1+af9WHFmBlaPv97SnZcNhXzYovctPYivodXv+b1k0dKkHa/WPRqQseL0dKy+7hpknOYH/M+FC/H9lCkMeCNL++MPLLv00lqXV5SV4esbxzPgTujPt97C6kn31Lq8MCUF344doxzgVNKa1dj1ppoH0SmHOK0+oWWE9TlcXsbK8vKM0cqpGUsIFf2aZItOG3tqtCqiKC3dku3RsYLklFqXFWdmoig9Daq2/aXZyIk/ANVSDvHfn3sG+YoeUefm4WGsVmkxtPZrSl4waxb6/f3vlmyXTgXGxODq1atrXU7nzR7z5ZdoMXiIJdulU7FXXIlRn35a6/LwLl1w6SefwSc8HCpWWVKCnx98QLlnw0ohTifE2f/eIqgMeOtRZ375MYbcOYCHtm172o/TWnKG3DmAe3h7n/bj4V27Kg152m9bsXvh21AppXZsfnHREOQejIeOgFdv06xZ+OX554Vvl50AP/U8NMtHjcKxDT+5ZNvsAnj1MnftwnfXXY2SzEyoloefH8Zt+kWZF+5WZiSevP5HWwBO8YhcHOAUj8jFAq76iLyiqAjxH6uzBFUZxOlUsnYA3IwhFwO4GUMuDnAdIN+/ZIkyc+NKIF504gSOKvYako0B3IwhFwO4GUMuDnDVIS9IOmqcbVGFlED84H8/hkOhc4g4A3AzhlwM4GYMuTjAVYd8/+L3oUJKIK7S/JQzATdjyMUAbsaQiwNcZciTVn9nzALInvSI04OYn5gIuwJuxpCLAdyMIRcHuKqQOyoqjFcfkj3pEacXNLY74GZ2h1wU4GYMuTjAVYU8SwF/pEc8a4/8D6IrALc75KIBN7Mz5KIBVxHyrN27IXvSIy77SNyVgNsVclcBbmfIXQW4apBnSe6PGohLPBK3AnC7Qe5qwO0IuasBVwny3IMHUVFSApmTHvG8wwmQMSsBtwvkVgFuJ8itAlwVyB0VFcg/KvcJ96RH3M3TE7IlA+C6Q2414HaA3GrAVYHczUM+g5RCXLaXTJIJcF0hlwVwnSGXBXAVIPeQzKBTY8QVB1w3yGUDXEfIZQNcdsg9fOUxSE3EfX0hQzIDrgvksgKuE+SyAi4z5B6SGKQu4j7WP4AqAK465LIDrgPksgMuK+QeEhikNOJeQYGW3r9KgKsKuSqAqwy5KoDLBrmnnz/cPTwgc9Ij3qRXb8vuW0XAVYNcNcBVhFw1wGWCPKK3df5og3hU/wGW3K/KgKsCuaqAqwS5qoDLAnnUgAsge9IjHnl+P7i5u3YzdQBcdshVB1wFyFUHXAbIowZYM4jUCnHv4GCEdu7isvvTCXBZIdcFcJkh1wVwKyF39/JC5HnnQfakR5xq6qK/hjoCLhvkugEuI+S6AW4V5E169DR2bMqeEoi7Yl5KZ8BlgVxXwGWCXFfArYA8SoH5cGUQbz50GHzCmwi7fTsAbjXkugMuA+S6A+5SyN3c0Paaa6BCSiDu6eeHjnfcIeS27QS4VZDbBXArIbcL4K6CPObivyGsU2eokBKIUx1vux2e/s6dn7Ij4K6G3G6AWwG53QB3BeTdpt4PVVIGcZ/QMMTdOMFpt2dnwF0FuV0BdyXkdgVcJOSR5/dDVL/+UCVlEKc6T5xoLPtpbAy4eMjtDrgrILc74KIg737vfVAppRAPaN4CbUaPadRtMODiIWfAxUPOgIuBPLRDR7S87HKolFKIU13vux/uDfzBZcDFQ86Ai4ecARcHeY+HH4FqKYd4SFwces/8xzl/HgMuHnIGXDzkDLg4yNuMHoPYRj7TtyI3h8PhgIJ9f+MNSF7/Y72uy4CfW5tmzcIvzz9/Tp/DgNe/0vx8LB81Csc2/HROn8eA17/MXbvw3XVXoyQzs17XD4iJwVVr1sE7JASqpdxI3Gzg3Hn1OgCIARc/ImfAxY/IGXBxI3I3d3cMef0NJQFXGnG/qCgMmPNSnddhwMVDzoCLh5wBFwt5t6n3K3OIvVaIU7QXuf2EW077MQZcPOQMuHjIGXCxkEf06o1e0x6Fyik7J25WXlSElSMuQ278garLGHDxc+QMuPg5cgZc7By5p38ARq1Zi+DYWKic0iNx87wqQ//vHfg0OTk/zoCLH5Ez4OJH5Ay42BG5m6cnLlzwpvKAazESN8vctRPfj78B/Z59jgEXOCLfvXgxAy54RE4vhMKAixuRr77hOvR7+hnEjhkLHdIGcao0Lw/eQUFWb4bWlRUUwCsgwOrN0Lby4mLj2aSHE04vwdkjrRDnOI6zW8rPiXMcx9k5RpzjOE7hGHGu3lWWliJ39y6rN0PrCpOSUJKebvVmcAqlDeK73n0XbwQFYOMTj1u9KdoCvuuJmdg+dRIyf9ls9eZoC/hv90403hhyMcUv+wwLQoKwbqpa5wzXHvE9ixfjh/vvAxwObJv7CkMuCPCMjRtQWVqCnX+fzpALArzkRCoKjyQy5IIA/+722+CoqMDud9/Bjw8/BB1SHvF9H3+EdfdONgA3Y8jFAP7XZQy5KMCrLmPIhQFutnPh29gwQ+1D7pVH/MBnS/H9PRPhqKys9TGGXAzgf32MIRcFeNXHGHJhgJv98cZ8bHz8Maicsogf/GIF1tx5x2m/MWYMuRjA/7oOQy4K8KrrMOTCADfb9upcbH5qFlRNyYN9jv+8AStGjTSgqU+9H3oYA59+Rvh22Qnw6rl7+6Db83MQ3m+A8G2zE+DV82/VGn3fWAifiAjh22YnwKs35KWX0WPSZKiWcohnHziApRcPq/crdpgx5GIAN2PIxQFuxpCLA5yi0x1c8fEnaDNiBFRKKcSLMzKwdPhQ5Bw82KDPZ8jFAG7GkIsD3IwhFwO4GZ0XaOx3axDZsydUSZk58YqSEqwcf32DAad4jlwc4Cdvg+fIRQJu3AbPkQsD3DzB29fXXI38Y8egSsogvnbyJCRv3Njo22HIxQD+120x5KIAr7othlwI4GYFyccNyMvy86FCSiD+y7PPYP8n/3Xa7THkYgD/6zYZclGAV90mQy4EcLP0HX/i29tuRaWTbs/WiO/76EP8+vxzTr9dhlwM4H/dNkMuCvCq22bIhQBulvjNKmx4dDpkT2rE6TUH1947Rdjt2xlykYD/dR/2hlwk4FX3YXPI4wUBbrbj7beMA4JkTtrVKdnx8cZKlHNdStiQ7LZqxRWA233ViisAt/uqFdGAm7m5u2PER/9F7JVXQsakRJxeomrpRRciY9dOl92nXSB3NeB2hNzVgNsRclcBbuYdEoLrf96E4DZtIFtSTqdsmDnDpYDbZWrFKsDtNLViFeB2mlpxNeBUaU4Ovrv9VlSUlUG2pEM8fvnn2PWff1ty3zpDbiXgdoHcSsDtArkVgJul/vortkh4jhWpplNyExPx34EDjL96Vqbb1IoMgOs+tSID4LpPrVgJeFVubhi5bDlaX3IJZEmakTg9TfnutlssB1y3EblsgOs4IpcNcB1H5FIATjkc+H7iXShISYEsSYP41heeN56uyJIOkMsIuG6Qywi4bpBLA/j/KkpLM17HQJakQDxz3178/srLkC2VIZcZcF0glxlwXSCXDXCzo9+vwf5PP4EMSYH4+oceRKWEe31VhVwFwFWHXAXAVYdcVsDNfp45EyUSTP9ajvjeDz/AsfXrIXMqQa4S4KpCrhLgqkIuO+BUYWqKFK8IZOnqlOKsLHzYp5cxx6RCsq9aURFw1VatqAi4aqtWVAC8+tGcV6/7EVF9+8KWI/Et/3pKGcBlH5GrDrgKI3LVAVdhRK4S4BS9SPuPDz4AK7MM8bykJOxe9C5US0bIdQBcdsh1AFx2yFUD3Cxt2+9I+Oor2A7x7fPmSrszUyXIdQJcVsh1AlxWyFUF3Oy3l+fAVogXpp3A7kWLoHIyQK4j4LJBriPgskGuOuAUHeOS9MM62AbxP+bPR3lREVTPSsh1BlwWyHUGXBbIdQDcbOuc2bAF4qW5udj574XQJSsgtwPgVkNuB8CthlwnwKljP/6I1K1boT3iCSu/NiDXKVdCbifArYLcToBbBblugJvt+/hDaI/4weXLoWOugNyOgLsacjsC7mrIdQWcOrTiC2iNeFl+Po6sWQ1dEwm5nQF3FeR2BtxVkOsMOFWQfBzJmzZBW8QPf/sNKoqLoXMiIGfAxUPOgIuHXHfAzQ6uWK4v4glffQk75EzIGXDxkDPg4iG3C+BWOOdSxNO2b4ddcgbkDLh4yBlw8ZDbCXAq9/BhlGRnQzvEK0pKkHPoEOxUYyBnwMVDzoCLh9xugJtl7t0L7RDPOrDfdt/IhkLOgIuHnAEXD7ldAacy9+yBfoi78C+TypAz4OIhZ8DFQ25nwKmsvRoinptwGHauPpAz4OIhZ8DFQ253wKmchARoh3hlpX2/ofWBnAEXDzkDLh5yBvxkrvz6LX95NjtCvu21ebUu3/PMLAbciZAXJNTciV6Wm8OAOxPy++5BZXl5jcuPfL+GAbcgRtzFBcbEoO3IUbUubz56HNx9fS3ZJt0KO+98+MW0rHGZV3AIml9Z+3HnGlbM2Gvg7ulZ47Lo/gPQrH9/y7bJrjHiLgZ8zMpvENK2ba2PhfU9D91feIUhb2RNBg5G12dehLuXV62PtZs4GbG332XJdulUhwenodX142td7hUYiFHLliN64EBLtsuuuQxxn9BQ2Lm6ADdjyMUBbsaQiwHcjCF3vXcuQzy8Y0fYtfoAbsaQiwPcjCEXA7gZQw6Ed+qsIeKdu8COnQvgZgy5OMDNGHIxgJvZHfLwzhoi7h8VBZ/wcNiphgBuxpCLA9yMIRcDuJmdIQ/r1EnPHZvhLvzCVAbcjCEXB7gZQy4GcDtD7uHri+DYWD0Rjxk6DHbIGYCbMeTiADdjyMUAblfIWwy5EO4eHnoi3m7MGOieMwE3Y8jFAW7GkIsB3I6Qtxsz1qX351LEm3TpitAOHaBrIgA3Y8jFAW7GkIsB3E6Qu3t6ou3Ika69T5feG/2ijNZzNC4ScDO7Qy4ScDO7Qy4KcLtA3nzwEPg2aaI34nFjx0G3XAG43SF3BeB2h1w04HaAPG6c631zOeIRPXogetAg6JIrAbcr5K4E3K6QuwpwnSH3CQ9Hh+uut8e5U/pOexQ6ZAXgdoPcCsDtBrmrAdcV8p6Tpxhfky0Qb33JJYjs1RsqZyXgdoHcSsDtArlVgOsGuVdgILpPmmyvsxj2mTYNqiYD4LpDLgPgukNuNeA6Qd7tzrvgGxZmyX27ORwOhxV37KisxEf9zlPutTdlArx6Wb9txY6ZD6OyuBiqJxPg1Tu48E0kvPsf6JAsgFevLD8fX44bg+SNG6HaEZq37NpjnFrEViNxN3d3DHr+RaiUrIDrNCKXFXCdRuQyAq7yiLzvI9MsA9zyF4WgufF2Y117dJOOgJupDrnMgOsCuayAqwp5SFwc+jz8iL1f2WfI7JfgFRQEmVMBcNUhVwFw1SGXHXAVIb9o7qvw8PGxN+IB0dHo//gTkDWVAFcVcpUAVxVyVQBXCfL2116HlsOGW70Z1u3YrF5lRQU+vXAI0v/YDplSEXDVdnaqCLhqOztVA1yFnZ3eISG46fftls6FSzMSp+i0jRe/+ZblT0t0AlyFEbnqgKswIlcZcJlH5INfnC0F4NIgbh6OP/DZ5yBDOgAuO+Q6AC475KoDLivkHW4Yj84TboYsSTGdUr2V429AwpdfWHb/OgEu69SKToDLOrWiC+CyTa2Etm+P63762ZLD66UfiZsNX/Amglq2tOS+dQVcphG5roDLNCLXEXAZRuQePj647L3FUgEuJeJ06Ool775nnFzdlekMuCyQ6wy4LJDrCrgMkA989jlj2le2pEOcih4wAP2f/KfL7s8OgFsNuR0Atxpy3QG3EvK2V41GD4tOcKXcnHj11tx9F/Z99KHQ+7AT4FbNkdsJcKvmyO0CuBVz5JG9emPst9/BKyAAMiY14hWlpfjiqpE4vmGDkNu3K+CuhNyugLsScjsC7irIA1u0wDU/rDcOSpQ1KadTzDy8vTHiw4+NPcLOzu6Au2Jqxe6Au2Jqxc6Ai55a8QoMxJVLP5MacOkRp3zDwzFy6TKnvvgoAy4ecgZcPOR2B1wk5G4eHsZKlIju8u3IVA5xKqRdO4z46L9OOaKTARcPOQMuHnIGXCzkQ+a8hNaXXQYVUgJxqvnAgRj+5luNug0GXDzkDLh4yBlwsZD3mHIvuk+8B6qkDOIUvZJ0vwae8ZABFw85Ay4ecgZcLOSxV47E4BfUerEaqVennKk1E+/Gvg8/qPf1GXDxq1YYcPGrVhhwsatWIiVfSqgV4rT08KtxY5D0ww9nvS4DLh5yBlw85Ay4WMiDWrXC1d+vk34livLTKdWXHl7x308RPWhQnddjwMVPrTDg4qdWGHCxUyuB/3NCRcCVRZyipzyjPvsczfr3P+3HGXDxkDPg4iFnwMVCHhDdHGO+XoXgNm2gasoibn6DRi5bjqZ9z6txOQMuHnIGXDzkDLhYyP2bRmH01yuNJcwqpzTilE9ICEYtX4GInr2M9xlw8ZAz4OIhZ8DFQu4XGYnRK1cirEMHqJ6SOzZPV3FGBtbcMxFDZs9hwAXu7Dy+Yhk6P/EUAy5wZ6dXSCgDLnBn5+q77kS/xx9HRLfu0CFtEOc4jrNjyk+ncBzH2TlGnOM4TuEYcY7jOIXTBnGa2i84sBeVZaVWb4q2lRYXI+P4cas3Q+uysnOQm5dv9WZoXVZqCirKy6FL2iCe89sW5G7fisz1axlyQYAf3bsH6UlHkXb0iNWboy3giUeSkHD4CEMuqJRDh3AiMRFJ+/ehsqICOqQF4nk7/0BRQrzx/7LMdIZcEODlpScf08zkZIZcEODms0qGXAzgOelpxv+L8/NxLP6A8VirnvKIl5xIQf6enTUuY8jFAW7GkIsB3IwhFwe4WWFODrJSkqF6SiNeWVqC7F/oDGW1/5oy5OIAN2PIxQBuxpCLA9wsLSkJxQUFUDmlEc/ZugWVRYVn/DhDLg5wM4ZcDOBmDLk4wI0cDiQfjFd6flxZxAsT4lF87Ox4MOTiADdjyMUAbsaQCwK82s/7iSPq/vwqiXh5Xi5yt22t9/UZcnGAmzHkYgA3Y8jFAG6Wk3YCeVmZUDHlEHdUViJ7y89wVJzbOk+GXBzgZgy5GMDNGHIxgJulJiQ0+GffypRDvDDhIMqyMhr0uQy5OMDNGHIxgJsx5GIAp+gAoPSkxn1/rMhduaMy9+9u1G0w5OIAN2PIxQBuxpA7H3Cz3Ix0lCk2GlcK8eKkI6jIz2v07TDk4gA3Y8jFAG7GkDsfcPNxzUpJgUophXjBvl1Ouy2GXBzgZgy5GMDNGPKTOQtws5wTJ5Q6t4oyiJekJqPMyXuP7Qy5aMDN7Ay5SMDN7A55ipMBpyorK5B9IhWqpAzi+XudNwq3O+SuAtzOkLsCcLtDLgJwM5pSqayshAopgXhZTjZKT4ibp7IT5K4G3I6QuxJwu0IuEnCKplPyMtKhQkogXpIi/hzWdoDcKsDtBLkVgNsNctGAmxXk5ECFlEC8NP2ES+5HZ8itBtwOkFsJuF0gdxXgVGFe41fCuSJG3AaQywK4zpDLALjukLsScKqirMz43ZE96REvy8mCw8X46AS5bIDrCLlMgOsKuasBNyvMy4XsSY94aZrrRuG6QS4r4DpBLiPgukFuFeBUkQJTKvIj7sKpFJ0glx1wHSCXGXBdILcScKoolxFvdBUF1v7wqQi5KoCrDLkKgKsOudWAU2WlJZA96RF3SPCKGypBrhrgKkKuEuCqQi4D4GayH/TDiGsEuaqAqwS5ioCrBrlMgJuvYSBzjLgmkKsOuAqQqwy4KpDLBjjFiDe2SnkQlxVyXQCXGXIdAJcdchkBNx8vmZMecZlG4jJCrhvgMkKuE+CyQi4r4BTPiTcyNy9vyJgMkOsKuEyQ6wi4bJDLDDjl4eEBmZMeca+QUMialZDrDrgMkOsMuCyQSw+4pyc8veUcSCqDuKfEiFsFuV0AtxJyOwBuNeSyA055+/lD9qRH3CskDLLnSsjtBrgVkNsJcKsgVwFwysffD7InPeKyj8RdCbldAXcl5HYE3NWQqwI45cMj8cbnGRwCuEu/mcIhtzvgroDczoC7CnKVAKd8/BnxRufm7g7f6BiokgjIGXDxkDPg4iFXDXBPb2/4BgRA9qRHnPJv1x4q5UzIGXDxkDPg4iFXDXAqtGlTuLm5QfaUQNwnKhoeAYGwG+QMuHjIGXDxkKsIONzcEBIRCRVSAnHKv20cVKsxkDPg4iFnwMVDriTgAAJDQ6VfH64c4n5t2tEEOewAOQMuHnIGXDzkqgJuTqWokjIqevj6ISCuA1TsXCBnwMVDzoCLh1xlwP0CAxGgyNJmpRCngrr1Um5u/FwgZ8DFQ86Ai4dcZcDd3N3RrG1bqJRSiLt5eiLk/AuganVBzoCLh5wBFw+5yoBTES1i4O0r/1GayiJO+URGwT+uI1SGvODAvlrnKT5xJJEBdyLkRfn5tU4jmnTsuIVbpU/0c3s06Vit82wX5OQoDbhvYCDCmjWDaimHOBXUvbey0yp+sXEI7NzN+H/1NajRbdspcXSYCkW1iTXmNSn3akf7tm3Tusb7XMPy9PAwHstT11AHhIQgqk0bKDuNEttWiXXhp+bmkP1lK85QeUE+Mn9YjYrCAqiRm4F3ULeeZ7xGRXk5kvbtRXGBKl+TfNEvYkjkmdf3FhQW4lBCIioq5D7Rv6x5enoirm1r+Pr6nvE6uRkZSEk4JP3LmlUHvEWHDgigU3womLKIqwS5u58/QvsNgk/TqLNet6Ki4iTk/5sO4OofPZsJjog46/UKC4tw0IBcvleNkjkvT0+0a9cGvj4+Z70u7eNJPhgv/YDETXHAlUdcBch9Y1ohpG9/uHuf/QffrJIg378PRXl5QrdNm9zcTgLepEm9P6WoqAjxhxjy+ubl5WWMwH3qAbgZ0ZJ+LAmZx+XcF+GmAeBaIF4F+Y9rUFGQL9VKmuBe58E/tmFHmhLkxw7sR2FurtO3TadoDjO6XRyCwsPP+XOLiotx8FAiysvLhWybLnl7e6Fd2zbwaeARjIV5uUg+eFCqHffuHh5o3r698oBrgzhVWV6OvB3bUBh/cuWHlXmFNUHogMHwDAxq1O3QnGJKQgJyM9Kdtm06RS+dRb+I/kHBDb6N0tJSHEo4guKSEqdumy75+/shtk0rYyqlMdH+ntTDCcjLzITVBdAO2Ni28FLksHrbIG5WkpaKnF83WTIq9wgMQmDHLsYpAuipmrOip6QZx4457fZ0yMvXFzEdOsK7jh1s9Y2mVA4nHkVevpxTclYVEhKM1i1bOHVFT352tjG9UpSfZ8nou2mr1nXu+FYx7RCnHDQq37kdBfH7aTjrkpF3QKcu8G3RStgSJRqN04EUGn67zjm/oCC0aN8eHp5eTrtNelyTjiUjIzPLabepck0jI9A8+uw74hsa7e/JSD6OguxsuKLA0DBj+aMqJ7WC3RE3qyguRtHhgyg8dEDIyNw7KhqBnbrCp6lrDhAozMvD8QP7jaemdi24SQSaxcY69ZlO9U6kpeN4cirsXMuY5mgS7prXti0pLERmSrKxLBFOpsiD9ktFRCA0sim8/dQ6CvNc0hrx6pWkJhuYFx9PosP4GnQbbt4+8I6IhHdklHGOcy8LTpJDS7do5UpZcTHsVpMWLYzDokWXnZNrHJ5vk1+Nqjzc3dGmdUsEBbn+QLqy0lJjVE4jdNoR2pidoH5BQQbcgeHhtji4yzaIV99ZWJ6Xg/KcbJRlZ5/8NycLjrIyuHl4GG9wP/kvvXkEBMA7oqkBtxVony4aidPKFbssQaQpKtoRFVKPNeDOig4KSjh81DYrV7y9vNA2tlWdB/G4srKSEuOZZ1FeLkqKiozf25NvDlQ6Tv6ffi68/fyNV6SnFzSmI559/PyMuW87ZTvEdckuK1fcPT3RIq49/IMbvgKlodll5YqzVqBw1sSIK17G8ePG6hVnzyfKEI2uaAmhM1agNGblypGjx5CTq+eznrCwELRs0dwW0w66xohrEE2rHD8YL9XBFM54ZZXIVvKcsCotPcPY4anLrws9rjEtohEeJscUIdfwGHFNonlyOulQfpbaS+RoPpNOYtWQIzBFV1hUhMTEJJQo/sfSz9cXrVvH1OscKJz8MeKalZWagrQjR5QcMdL5nJu3i4OXxLgYJyg7lmy8wISKRTQJN9Z/y/IMh2t8jLiG0ZnjaFROa3BViFYZhEc3N5YQqnI+58ysbBw7nqLMCbRopyVNn9BRmJxeMeKaRt/W7NRUpCclobJSXmj8goKNI+loaZhq0fJDmicn0GUffUc3awoPmy29s0uMuObRzk566TcZTjx06tF0dB6L+pz/W/byCwqMKZbiYrmWIvr7+SEmJtr4l9M3RtwmFeRk40TiEZQWF1m7IW5uxtF0ETExBuS6RL9GtIIl9USa5a8a5OnpgWZRTY1D51WZnuIaHiNuo+hbTatXMo4fc/l8OZ3rhM4eF94sWuodl42N5sjTM7KQlp6O8vIKl79wQ9PIJgbevOPSPjHiNh6Z04FCog/dpyWDoU2jjFcR9/Ry3lkHZa+ystI4I+KJtAyUlZUJvS8fH2/jrIO05ptH3vaLEbd5tJIlLysT+ZmZxsm1nDXqphPvB4WFIzAszHbnsqge/Xrl5eUbJ9Wioz6dtZqFXrA4JCQIoSHBCAwIYLxtHCPOVUVTLAQ6vSQcnXSIXi2pXtGJiHx84BMQYJy3OTA01NZw1zmdlV9ggE4v1kznZKnvrx9Nj9CIOzDA31gmGODvz3BzRow4d8bKy8pQUlSI0qIiVJwyv0t+ePn4GksD6dwmos7vrXP0q0cn2SLMS0pKUVlZ81fR3d3NeGFiP18feGv4Ygacc2LEOY7jFI6HTxzHcQrHiHMcxykcI85xHKdwjDjHcZzCMeIcx3EKx4hzHMcpHCPOcRyncIw4x3GcwjHiHMdxCseIcxzHKRwjznEcp3CMOMdxnMIx4hzHcQrHiHMcxykcI85xHKdwjDjHcZzCMeIcx3EKx4hzHMcpHCPOcRyncIw4x3GcwjHiHMdxCseIcxzHKRwjznEcp3CMOMdxnMIx4hzHcVC3/wfPx7Dn6C//cQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAABDCAYAAACROQIsAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAALEwAACxMBAJqcGAAACLtJREFUeJzt3VtIFF8cB/DfrGaZeaHSoAsSkRY+2MXqT/kQRZgUhVGRiFER9JeCiB6iCBEqMIjoQbQrPVgS9TcSfKigKCLoYlSUFSZdyC6mSJbmbXbmzzmzM3v24ua2m7vT+X5i89znrOn8ds5cUnRd1wkAAKTliPQEAAAgshAIAAAkh0AAACA5BAIAAMkhEAAASA6BAABAcggEAACSQyAAAJAcAgFAAF1dXTRp0iR6+PBhwHbbtm2j3bt3D9u8AMIJgQBsr729nfbs2UMzZ86k0aNH09ixY2n+/PlUXV0d8tiHDx+mnJwcmjdvnlVWXl5O2dnZHu1KS0vp+PHj9ObNm5C3CTDcEAjA1lpbW2n27NnU0NBAFRUV9OLFC7p+/TqtXbuWYmNjQxq7t7eXqqqq+Kd90b1793igEbGjhqVLl1JlZWVI2wSIBAXPGgI7KysroyNHjvCjglGjRoV17CtXrlBRURF1dnbyoKJpGiUmJtLPnz+tNnFxcdTd3c3rz549S/v27aPPnz+HdR4AfxqOCMDWOjo6iH2WaWpqCvvYt2/f5kcb5pGFoij06NEjnq6vr+c7/JaWFqt+wYIF9OXLF3r58mXY5wLwJ4V27AwQYSUlJXTt2jW+Zj9jxgxavHgxrVu3jpYsWWK12bp1K186MrW1tdHXr1/p27dvtHPnzkHr3r59y5d8TCwQfPr0iRwOB99OQkKCx1wmT57Mv7LzBOx8BYBdIBCArbEd7qtXr+jBgwd048YNqqur4ydtd+3aRUePHuVtTp8+bbVnO/KFCxfSyZMn+Y48UF1PTw8lJyd7bO/x48eUmZnpEwQYc2mK9QOwEywNge2xT+psWYatz9+/f59WrFjB1+u9sbX+5cuX85O/mzdv/mVdamoqX3ryDgRz5szxOw+zLesHYCcIBPDXYZ/I09LSPMr6+vpo9erVfEln7969Q6pjO/zGxkaPtk+ePKFZs2b53e6zZ88oJiaGn1cAsBMsDYFtFRcX07Rp02jZsmV8fZ6dvD116hQ/yXvhwgWrHbvah139M2HCBDp27JjHGIHq8vPz+U1iHz58oClTpvAyVVX5iemPHz/ypaBx48ZZ7W/dukW5ubmUlJT0x987QDjhiABsa+7cuXTz5k0qKCigjIwMKiws5HcCs+Uhdh+BaceOHXzZht1gxk70igLVsfMP7ChBvDHt0KFD/D4FFhg2btxolbMrl2pqanzuOQCwA9xHAH+1AwcO0OXLl/lRgvcn9UB1pjt37tCGDRuoubmZ4uPjB93OxYsX+Xhs6YgtDwHYCQIB/LXevXtHU6dOpfT0dEpJSbHK2TLQiRMnBq1jl6OK2FVEixYtoqysrEG3xY4a2BEEexwFgN0gEAAASA7nCAAAJIdAAAAguZAvHx0/fS4N/PwedD/FJ6ME12ewNkNp5DOen05DKxrC2GJGCX5MZYjvO0Bjv/2FwsFmFWDaPkXG992zVOzvXSP+Oymum8IYh/e8AszTyLtWNv28dX/v271do59PH7ZSaq6W6jopJKTFOnLlzaF0jRSrytVPHMe7n9DXWp3VdeJ/XHndp4590Xz6GV/c/YwyYXzjL/e79tfOK231C5A3BxWSrrx3u6HVDaV+MFY/LHRTVl4eXb16dXgDAQsC//x7zGdnYPxyu9sZVZ67Xs8dhVAn9vPqI/7C8z5eOwCzuTme5xysSq/5CVu36nzDhPn+3NvwnadY57s93/dotRPz5lhe3xtWzF+DfG9YXnz/HtsQ2vKdrbANhzCow2v7HmMKaYdrfHEH7k4bdQ4hb+7gedrB8kZBjEPhrxExxsHp6LhYYRu6a1xdmJsrzcZnO1Ux70ob78noa+TdaVbO5+baY3iMr2nkUAfIoapGP54eMOpUlRxOd51DqFNYndDPTCtiXzPtGsPq63TSQL+RdqoqqaqT1AFXXqxzajxv1mlOjd/TYLbTnE5yqk4jr2lWmrVzOlV+vwTPa7pVp2saL3fXaby9ldY00jXje6PpLO0eg6XNwKHpnnnWxx2kjLR33p12ByaeN4OLq9zar5ttjYwV/FxZn0DgLzAEChZ6kIFEDK7R5kJ7e9B9sDQEACA5BAIAAMkhEAAASA6BAABAcggEAACSQyAAAJAcAgEAgOQQCAAAJIdAAAAgOQQCAADJIRAAAEgOgQAAQHIIBAAAkgs5EPR3d4ZnJgARdum//yI9BYCQtbW1RSAQ/Mb/RQAQjS7V1kZ6CgAha8djqAEAYNj/8/qsrCyKj48PZQiAqDmkTk1NjfQ0AELS09NDjY2NwxsIAADA3rA0BAAgOQQCAADJIRAAAEgOgQAAQHJhCQQVFRWUk5NDI0eOpE2bNoVjSIBh09HRQQUFBZSQkEDp6elUU1MT6SkB/Jbnz59TXl4ejR8/nhRF+TOBoKysjL+8TZw4kfbv309btmwJZjiAqLB9+3aKi4uj1tZWOn/+PJWUlAR9+R1ANBgxYgStX7+ezpw5E1S/2HBsfM2aNfxrQ0MDtbS0hGNIgGHR3d1NtbW1/JPUmDFjKDc3l1atWkXV1dVUXl4e6ekBBCUzM5O/mpubg+qHcwQgtaamJoqNjaWMjAyrLDs7G0cEIBUEApBaV1cXJSUleZQlJyfTjx8/IjYngKgLBCtXrqSUlBT+YofK7GXmWR2AnbHloO/fPR+cyPKJiYkRmxPAULFzWuxnmL3y8/Ppd/3yHEF9fb2VNk8U+zthDGBHbElIVVV6/fo1TZ8+nZc9ffqUP0MLINoVFRXxV1QsDbFfpN7eXnI6nfzF0qwMINqxS0bZxQ6lpaX8xPHdu3eprq6OiouLIz01gKCxR8ex/W9/fz/Ps3RfX9/wBIKDBw/yJ5CyZaNz587xNCsDsIPKykr+xMa0tDQqLCykqqoqHBGALb1//57vf82fX5ZmVxH9Cp4+CgAgOVw1BAAgOQQCAADJIRAAAEgOgQAAQHIIBAAAkkMgAACQHAIBAIDkEAgAAEhu/wNv9ZO7tBwetQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "code = tcr.ToricCodeRectangle(origin_qubit=cirq.GridQubit(0,0), row_vector=(1,1), rows=grid.cols, cols=grid.rows)\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    tc_plot.ToricCodePlotter(z_cmap = diff_cmap, x_cmap = matplotlib.colormaps['binary']).plot_expectation_values(tc_plaq.ToricCodePlaquettes(\n",
+    "        code,\n",
+    "        x_plaquettes = np.zeros((2,3))-1,\n",
+    "        z_plaquettes = {(grid.cols - p%(grid.cols+1),p//(grid.cols + 1)):bitstring_to_expectation_value(np.mean(occupations_excited[(coupling,9)],axis=0)[p])-bitstring_to_expectation_value(np.mean(occupations_wala[(coupling,9)],axis=0)[p]) for p in range((grid.rows+1)*(grid.cols+1))}\n",
+    "    ))\n",
+    "    \n",
+    "    title_text = r'$\\langle A_v \\rangle_{\\mathrm{string}} - \\langle A_v \\rangle_{\\mathrm{vac}} $ with $\\lambda = $' + f\"{coupling}\"\n",
+    "\n",
+    "    plt.title(title_text)\n",
+    "\n",
+    "    plt.show()\n",
+    "\n",
+    "f,ax = plt.subplots()\n",
+    "ax.set_aspect(0.1)\n",
+    "\n",
+    "norm = matplotlib.colors.Normalize(vmin=-1, vmax=1)\n",
+    "\n",
+    "matplotlib.colorbar.ColorbarBase(\n",
+    "    ax, cmap=diff_cmap_r, norm=norm, orientation='horizontal'\n",
+    ")\n",
+    "\n",
+    "ax.set_xticks([-1,0,1],labels=['+1','0','-1'])\n",
+    "ax.set_xticks([],minor=True)\n",
+    "ax.tick_params(right=False,labelright=False)\n",
+    "ax.set_title(r'$S_{ZZ}(t)$')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "253d4a55",
+   "metadata": {},
+   "source": [
+    "To show this quantitatively, we plot the probability of observing a charge as a function of time when $\\lambda \\in \\{0,0.25,0.5\\}$ for three different charge sites:\n",
+    "\n",
+    "(1) $A_{\\mathrm{vac}}$ on the top/bottom of WALA initial state (black)\n",
+    "\n",
+    "(2) $A_1$ on the top of the initial state with a string excitation (yellow)\n",
+    "\n",
+    "(3) $A_3$ on the bottom of the initial state with the string excitation (mint)\n",
+    "\n",
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "be00db3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "coupling = 0\n",
+    "marker_dict = {0:'P',0.25:'X',0.5:'p'}\n",
+    "\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "\n",
+    "    fig, ax = plt.subplots()\n",
+    "\n",
+    "    mark = marker_dict[coupling]\n",
+    "    ms = 12\n",
+    "\n",
+    "    res = [np.mean(occupations_wala[(coupling,p)],axis=0)[5] for p in range(len(trotter_steps))]\n",
+    "    sdom = [np.std(occupations_wala[(coupling,p)],axis=0)[5]/np.sqrt(np.shape(occupations_wala[(coupling,p)])[0]) for p in range(len(trotter_steps))]\n",
+    "    ax.errorbar(x = np.arange(len(res))* dt, y = res,yerr = sdom, color = BREAKING_VAC, marker = mark, markersize = ms, label = \"$A_{\\mathrm{vac}}$\")\n",
+    "    \n",
+    "    res = [np.mean(occupations_excited[(coupling,p)],axis=0)[5] for p in range(len(trotter_steps))]\n",
+    "    sdom = [np.std(occupations_excited[(coupling,p)],axis=0)[5]/np.sqrt(np.shape(occupations_excited[(coupling,p)])[0]) for p in range(len(trotter_steps))]\n",
+    "    ax.errorbar(x = np.arange(len(res))* dt, y = res,yerr = sdom, color = BREAKING_TOP, marker = mark, markersize = ms, label = \"$A_1$\")\n",
+    "    \n",
+    "    res = [np.mean(occupations_excited[(coupling,p)],axis=0)[3] for p in range(len(trotter_steps))]\n",
+    "    sdom = [np.std(occupations_excited[(coupling,p)],axis=0)[3]/np.sqrt(np.shape(occupations_excited[(coupling,p)])[0]) for p in range(len(trotter_steps))]\n",
+    "    ax.errorbar(x = np.arange(len(res))* dt, y = res,yerr = sdom, color = BREAKING_BOTTOM, marker = mark, markersize = ms, label = \"$A_2$\")\n",
+    "\n",
+    "    \n",
+    "\n",
+    "    \n",
+    "\n",
+    "    ax.set_xlabel('Time')\n",
+    "    ax.set_ylabel(r'$P(A_v)$')\n",
+    "    ax.set_title(f'Probability of charge excitation with $\\lambda = {coupling}$')\n",
+    "\n",
+    "    ax.set_ylim(-0.02,0.45)\n",
+    "\n",
+    "    ax.legend()\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c563f243",
+   "metadata": {},
+   "source": [
+    "Finally, we want to explore the dependence on the confinement parameter, $h_E$. We naively expect a resonance in pair creation near $h_E = 2,$ when the energy \"cost\" of creating two charges is equal to the energy \"gained\" by shorting the gauge string by one link. We will compare the probability of finding a charge on site $A_1$ at time $t=2$, once the probability of pair creation has saturated.\n",
+    "\n",
+    "Let's define the circuits:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "f876333f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "he_list = np.around(np.arange(1,3.1,0.4),2)\n",
+    "coupling_list = [0,0.25,0.5]\n",
+    "dt = 0.2\n",
+    "trotter_steps = [10]\n",
+    "string_excitation_indices = [(-2,1),(0,1),(1,2),(2,3),(3,2),(4,1),(6,1)]\n",
+    "string_excitation_qubits = [cirq.GridQubit(idx1,idx2) for idx1,idx2 in string_excitation_indices]\n",
+    "\n",
+    "resonance_circuits = []\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            resonance_circuits.append(cirq.Circuit.from_moments(\n",
+    "                *lgt.variational_ground_state_minimal_qubits(grid,angles[he]),\n",
+    "                cirq.Moment(cirq.X.on_each(string_excitation_qubits)),\n",
+    "                *lgt.trotter_step_minimal_qubits(grid,dt,coupling,he,extra_z_plaquette_indices=[(0,1),(3,1)])*step,\n",
+    "                cirq.Moment(cirq.measure(grid.physical_qubits, key=\"measure_all\"))\n",
+    "            ))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6753effd",
+   "metadata": {},
+   "source": [
+    "and simulate them:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "d9cde0f6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_resonance = simulator.run_batch(resonance_circuits,repetitions=reps)\n",
+    "\n",
+    "counter = 0\n",
+    "\n",
+    "occupations_resonance = {}\n",
+    "occupations_resonance_sdom = {}\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    for he in he_list:\n",
+    "        for step in trotter_steps:\n",
+    "            res = results_resonance[counter][0].measurements['measure_all']\n",
+    "            occupations_resonance[(coupling,he,step)] = lgt.plaquette_bitstrings(res,grid,particle_locs=[(0,1),(3,1)])\n",
+    "\n",
+    "            counter += 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7b371a0",
+   "metadata": {},
+   "source": [
+    "Now when looking at the plotted results, we see that indeed there is a resonance-like feature near $h_E = 2$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "29879cae",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "marker_dict = {0:'P',0.25:'X',0.5:'p'}\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "for coupling in coupling_list:\n",
+    "    res = [np.mean(occupations_resonance[(coupling,he,10)],axis=0)[5] for he in he_list]\n",
+    "    sdom = [np.std(occupations_resonance[(coupling,he,10)],axis=0)[5]/np.sqrt(np.shape(occupations_resonance[(coupling,he,10)])[0]) for he in he_list]\n",
+    "    ax.errorbar(x = he_list, y = res, yerr = sdom, markersize = 12, color = '#e6a304ff',marker = marker_dict[coupling], label = f\"$\\lambda = {coupling}$\")\n",
+    "\n",
+    "ax.set_xlabel(r'$h_E$')\n",
+    "ax.set_ylabel(r'$P(A_v)$')\n",
+    "ax.legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d819ded5",
+   "metadata": {},
+   "source": [
+    "Congratulations, you've made it to the end of this tutorial! To explore the details of the formulation of this experiment and the results from the quantum processor, please refer to the [paper and its supplement](https://arxiv.org/abs/2409.17142)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/recirq/lattice_gauge/lattice_gauge_experiment.py b/recirq/lattice_gauge/lattice_gauge_experiment.py
new file mode 100644
index 00000000..7a09cbfc
--- /dev/null
+++ b/recirq/lattice_gauge/lattice_gauge_experiment.py
@@ -0,0 +1,849 @@
+# Copyright 2025 Google
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from collections.abc import Sequence
+from typing import Any
+
+import cirq
+from matplotlib import colormaps
+import matplotlib.patches as mpatches
+import matplotlib.pyplot as plt
+import numpy as np
+import sympy
+
+from .lattice_gauge_grid import QubitNeighbor, LGTGrid
+
+def variational_ground_state_minimal_qubits_cols(
+    grid: LGTGrid, x_ancillary_qubits_in_cols: list[set[cirq.GridQubit]], theta: float
+) -> list[cirq.Moment]:
+    """Moments to prepare the state from the toric code variational ansatz for two columns.
+
+    Instead of applying a unitary on each plaquette that creates an equal superpostion of all spins up
+    and all spins down (the Hadamard), this creates a weighted superposition of
+    cos(theta) |0000> + sin(theta) |1111>, based on the variational parameter theta.
+
+    Args:
+        grid: grid of qubits to be used
+        x_ancillary_qubits_in_cols: list of sets of x-plaquette ancillary qubits. The zeroth entry should
+            be the ancillary qubits of the left column of x-plaquettes and the first entry should be for
+            the right column.
+        theta: dictionary where the key:value is he:theta
+    """
+
+    x_ancillary_qubits_all = x_ancillary_qubits_in_cols[0].union(x_ancillary_qubits_in_cols[1])
+
+    return [
+        cirq.Moment(cirq.Ry(rads=theta).on_each(grid.u_set(x_ancillary_qubits_all))),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(x_ancillary_qubits_all, QubitNeighbor.U, QubitNeighbor.L)),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(x_ancillary_qubits_all, QubitNeighbor.U, QubitNeighbor.R)),
+        *cirq.Circuit.zip(
+            cirq.Circuit.from_moments(
+                *cnot_on_layer(
+                    pairs_list=grid.ancillary_to_pair(x_ancillary_qubits_in_cols[0], QubitNeighbor.L, QubitNeighbor.D)
+                )
+            ),
+            cirq.Circuit.from_moments(
+                *cnot_on_layer(
+                    pairs_list=grid.ancillary_to_pair(x_ancillary_qubits_in_cols[1], QubitNeighbor.R, QubitNeighbor.D)
+                )
+            ),
+        ).moments,
+    ]
+
+
+def variational_ground_state_minimal_qubits(
+    grid: LGTGrid, theta: float, extra_x_plaquette_indices: list[tuple[int, int]] = []
+) -> list[cirq.Moment]:
+    """Moments to prepare the state from the toric code variation ansatz.
+
+    Instead of applying a unitary on each plaquette that creates an equal superpostion of all spins up
+    and all spins down (the Hadamard), this creates a weighted superposition of
+    cos(theta) |0000> + sin(theta) |1111>, based on the variation parameter theta.
+
+    Args:
+        grid: grid of qubits to be used
+        theta: dictionary where the key:value is he:theta
+        extra_x_plaquette_indices: list of (row,col) of extra x plaquettes to prepare the ground state for.
+    """
+    extra_ancilla_qubits = {}
+    for col in range(grid.cols):
+        extra_ancilla_qubits[col] = []
+        for p in extra_x_plaquette_indices:
+            if p[1] == col:
+                extra_ancilla_qubits[col].append(grid.x_plaquette_to_x_ancilla(p[0], p[1]))
+
+    moments = []
+
+    if (grid.cols / 2).is_integer():
+        for col in range(int(grid.cols / 2), grid.cols):
+            moments = moments + variational_ground_state_minimal_qubits_cols(
+                grid,
+                [
+                    grid.x_ancillary_qubits_by_col[grid.cols - col - 1].union(
+                        extra_ancilla_qubits[grid.cols - col - 1]
+                    ),
+                    grid.x_ancillary_qubits_by_col[col].union(extra_ancilla_qubits[col]),
+                ],
+                theta=theta,
+            )
+    else:
+        moments = moments + variational_ground_state_minimal_qubits_cols(
+            grid,
+            [
+                grid.x_ancillary_qubits_by_col[int(grid.cols / 2 - 0.5)].union(
+                    extra_ancilla_qubits[int(grid.cols / 2 - 0.5)]
+                ),
+                {},
+            ],
+            theta=theta,
+        )
+        for col in range(1, int(grid.cols / 2 + 0.5)):
+            moments = moments + variational_ground_state_minimal_qubits_cols(
+                grid,
+                [
+                    grid.x_ancillary_qubits_by_col[int(grid.cols / 2 - 0.5 - col)].union(
+                        extra_ancilla_qubits[int(grid.cols / 2 - 0.5 - col)]
+                    ),
+                    grid.x_ancillary_qubits_by_col[int(grid.cols / 2 - 0.5 + col)].union(
+                        extra_ancilla_qubits[int(grid.cols / 2 - 0.5 + col)]
+                    ),
+                ],
+                theta=theta,
+            )
+
+    return moments
+
+def trotter_even_zcol_entangle_minimal_qubits(
+    grid: LGTGrid, extra_z_plaquette_indices: list[tuple[int, int]] = []
+) -> list[cirq.Moment]:
+    """Portion of Trotter step acting on the even columns of Z-plaquettes.
+
+    Computing with minimal qubits necceitates that the connectivity of the qubits is not consistent
+    with the square nearest neighbor lattice. This is used for simulation purposes. It also means
+    that the Trotterization must be sequentially applied to the even and odd colums of the Z- and
+    X-plaquettes respectively.
+
+    Args:
+        grid: grid of qubits to be used.
+        extra_plaquette_indices: Can specify extra plaquettes to include in the Trotterization.
+            By default all 4 qubits around the extra plaquettes will be included.
+    """
+    extra_even_qubits = []
+    for p in extra_z_plaquette_indices:
+        if p[1] % 2 == 0:
+            extra_even_qubits.append(grid.z_plaquette_to_z_ancilla(p[0], p[1]))
+    extra_z_plaquette_ancillary_qubit = set(extra_even_qubits)
+
+    return [
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                grid.z_ancillary_l_side_qubits
+                - grid.z_ancillary_dl_corner_qubits
+                - extra_z_plaquette_ancillary_qubit,
+                QubitNeighbor.D,
+                QubitNeighbor.R,
+            ).union(
+                grid.ancillary_to_pair(
+                    (
+                        grid.z_even_col_ancillary_qubits
+                        - grid.z_ancillary_l_side_qubits
+                        - grid.z_ancillary_d_side_qubits
+                    ).union(extra_z_plaquette_ancillary_qubit),
+                    QubitNeighbor.D,
+                    QubitNeighbor.L,
+                )
+            )
+        ),
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                grid.z_ancillary_l_side_qubits
+                - grid.z_ancillary_ul_corner_qubits
+                - grid.z_ancillary_dl_corner_qubits
+                - extra_z_plaquette_ancillary_qubit,
+                QubitNeighbor.R,
+                QubitNeighbor.U,
+            )
+            .union(
+                grid.ancillary_to_pair(
+                    grid.z_ancillary_dl_corner_qubits - extra_z_plaquette_ancillary_qubit, QubitNeighbor.R, QubitNeighbor.U
+                )
+            )
+            .union(
+                grid.ancillary_to_pair(
+                    (
+                        grid.z_even_col_ancillary_qubits
+                        - grid.z_ancillary_l_side_qubits
+                        - grid.z_ancillary_u_side_qubits
+                    ).union(extra_z_plaquette_ancillary_qubit),
+                    QubitNeighbor.L,
+                    QubitNeighbor.U,
+                )
+            )
+            .union(
+                grid.ancillary_to_pair(
+                    grid.z_ancillary_u_side_qubits.intersection(grid.z_even_col_ancillary_qubits)
+                    - grid.z_ancillary_l_side_qubits
+                    - grid.z_ancillary_r_side_qubits
+                    - extra_z_plaquette_ancillary_qubit,
+                    QubitNeighbor.L,
+                    QubitNeighbor.R,
+                )
+            )
+        ),
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                (
+                    grid.z_even_col_ancillary_qubits
+                    - grid.z_ancillary_l_side_qubits
+                    - grid.z_ancillary_u_side_qubits
+                    - grid.z_ancillary_r_side_qubits
+                ).union(extra_z_plaquette_ancillary_qubit),
+                QubitNeighbor.R,
+                QubitNeighbor.U,
+            )
+        ),
+    ]
+
+
+def trotter_odd_zcol_entangle_minimal_qubits(
+    grid: LGTGrid, extra_z_plaquette_indices: list[tuple[int, int]] = []
+) -> list[cirq.Moment]:
+    """Portion of Trotter step acting on the odd columns of Z-plaquettes.
+
+    Computing with minimal qubits necceitates that the connectivity of the qubits is not consistent
+    with the square nearest neighbor lattice. This is used for simulation purposes. It also means
+    that the Trotterization must be sequentially applied to the even and odd colums of the Z- and
+    X-plaquettes respectively.
+
+    Args:
+        grid: grid of qubits to be used.
+        extra_plaquette_indices: Can specify extra plaquettes to include in the Trotterization.
+            By default all 4 qubits around the extra plaquettes will be included.
+    """
+    extra_odd_qubits = []
+    for p in extra_z_plaquette_indices:
+        if p[1] % 2 == 1:
+            extra_odd_qubits.append(grid.z_plaquette_to_z_ancilla(p[0], p[1]))
+    extra_z_plaquette_ancillary_qubit = set(extra_odd_qubits)
+
+    return [
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                (grid.z_odd_col_ancillary_qubits - grid.z_ancillary_d_side_qubits).union(
+                    extra_z_plaquette_ancillary_qubit
+                ),
+                QubitNeighbor.D,
+                QubitNeighbor.L,
+            )
+        ),
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                (
+                    grid.z_odd_col_ancillary_qubits
+                    - grid.z_ancillary_u_side_qubits
+                    - grid.z_ancillary_dr_corner_qubits
+                ).union(extra_z_plaquette_ancillary_qubit),
+                QubitNeighbor.L,
+                QubitNeighbor.U,
+            )
+            .union(
+                grid.ancillary_to_pair(
+                    grid.z_ancillary_u_side_qubits.intersection(grid.z_odd_col_ancillary_qubits)
+                    - grid.z_ancillary_r_side_qubits
+                    - extra_z_plaquette_ancillary_qubit,
+                    QubitNeighbor.L,
+                    QubitNeighbor.R,
+                )
+            )
+            .union(
+                grid.ancillary_to_pair(
+                    grid.z_ancillary_dr_corner_qubits.intersection(grid.z_odd_col_ancillary_qubits)
+                    - extra_z_plaquette_ancillary_qubit,
+                    QubitNeighbor.U,
+                    QubitNeighbor.L,
+                )
+            )
+        ),
+        *cnot_on_layer(
+            pairs_list=grid.ancillary_to_pair(
+                (
+                    grid.z_odd_col_ancillary_qubits
+                    - grid.z_ancillary_u_side_qubits
+                    - grid.z_ancillary_r_side_qubits
+                ).union(extra_z_plaquette_ancillary_qubit),
+                QubitNeighbor.R,
+                QubitNeighbor.U,
+            )
+        ),
+    ]
+
+def trotter_even_xcol_entangle_minimal_qubits(
+    grid: LGTGrid, extra_plaquette_indices: list[tuple[int, int]] = []
+) ->list[cirq.Moment]:
+    """Portion of Trotter step acting on the even columns of X-plaquettes.
+
+    Computing with minimal qubits necceitates that the connectivity of the qubits is not consistent
+    with the square nearest neighbor lattice. This is used for simulation purposes. It also means
+    that the Trotterization must be sequentially applied to the even and odd colums of the Z- and
+    X-plaquettes respectively.
+
+    Args:
+        grid: grid of qubits to be used.
+        extra_plaquette_indices: Can specify extra plaquettes to include in the Trotterization.
+            By default all 4 qubits around the extra plaquettes will be included.
+    """
+
+    extra_even_plaquette_indices = []
+    for p in extra_plaquette_indices:
+        if p[1] % 2 == 0:
+            extra_even_plaquette_indices.append(p)
+
+    ancilla_qubits = grid.x_even_col_ancillary_qubits.union(
+        {grid.x_plaquette_to_x_ancilla(p[0], p[1]) for p in extra_even_plaquette_indices}
+    )
+
+    return [
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.D, QubitNeighbor.L)),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.L, QubitNeighbor.U)),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.R, QubitNeighbor.U)),
+    ]
+
+
+def trotter_odd_xcol_entangle_minimal_qubits(
+    grid: LGTGrid, extra_plaquette_indices: list[tuple[int, int]] = []
+) -> list[cirq.Moment]:
+    """Portion of Trotter step acting on the odd columns of X-plaquettes.
+
+    Computing with minimal qubits necceitates that the connectivity of the qubits is not consistent
+    with the square nearest neighbor lattice. This is used for simulation purposes. It also means
+    that the Trotterization must be sequentially applied to the even and odd colums of the Z- and
+    X-plaquettes respectively.
+
+    Args:
+        grid: grid of qubits to be used.
+        extra_plaquette_indices: Can specify extra plaquettes to include in the Trotterization.
+            By default all 4 qubits around the extra plaquettes will be included.
+    """
+
+    extra_odd_plaquette_indices = []
+    for p in extra_plaquette_indices:
+        if p[1] % 2 == 1:
+            extra_odd_plaquette_indices.append(p)
+
+    ancilla_qubits = grid.x_odd_col_ancillary_qubits.union(
+        {grid.x_plaquette_to_x_ancilla(p[0], p[1]) for p in extra_odd_plaquette_indices}
+    )
+
+    return [
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.D, QubitNeighbor.L)),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.L, QubitNeighbor.U)),
+        *cnot_on_layer(pairs_list=grid.ancillary_to_pair(ancilla_qubits, QubitNeighbor.R, QubitNeighbor.U)),
+    ]
+
+def trotter_step_minimal_qubits(
+    grid: LGTGrid,
+    dt: sympy.Symbol,
+    coupling: sympy.Symbol,
+    he: sympy.Symbol,
+    je: sympy.Symbol = 1,
+    jm: sympy.Symbol = 1,
+    extra_z_plaquette_indices: list[tuple[int, int]] = [],
+    extra_x_plaquette_indices: list[tuple[int, int]] = [],
+) -> list[cirq.Moment]:
+    """Generate moments to simulate a full Trotter step of the lattice gauge theory Hamiltonian.
+
+    Hamiltonian can be seen at, for example, https://arxiv.org/abs/0912.3272 equation (1.2)
+    We set je = jm = 1 and hx = -coupling and hz = -he.
+
+    Args:
+        grid: Representation of set of qubits.
+        dt: trotter time step.
+        coupling: sigma x field strength.
+        he: sigma z field strength.
+        je: vertex strength
+        jm: plaquette strength
+    """
+    extra_z_plaquette_ancillary_qubits = {
+        grid.z_plaquette_to_z_ancilla(plaquette_indices[0], plaquette_indices[1])
+        for plaquette_indices in extra_z_plaquette_indices
+    }
+
+    extra_x_plaquette_ancillary_qubits = {
+        grid.x_plaquette_to_x_ancilla(p[0], p[1]) for p in extra_x_plaquette_indices
+    }
+    extra_x_plaquette_even_col_ancillary_qubits = set([])
+    extra_x_plaquette_odd_col_ancillary_qubits = set([])
+
+    for p in extra_x_plaquette_indices:
+        if p[1] % 2 == 0:
+            extra_x_plaquette_even_col_ancillary_qubits.add(
+                grid.x_plaquette_to_x_ancilla(p[0], p[1])
+            )
+        else:
+            extra_x_plaquette_odd_col_ancillary_qubits.add(
+                grid.x_plaquette_to_x_ancilla(p[0], p[1])
+            )
+
+    extended_physical_qubits = sorted(
+        grid.u_set(grid.x_ancillary_qubits.union(extra_x_plaquette_ancillary_qubits))
+        .union(grid.r_set(grid.x_ancillary_qubits.union(extra_x_plaquette_ancillary_qubits)))
+        .union(grid.d_set(grid.x_ancillary_qubits.union(extra_x_plaquette_ancillary_qubits)))
+        .union(grid.l_set(grid.x_ancillary_qubits.union(extra_x_plaquette_ancillary_qubits)))
+    )
+
+    return [
+        *trotter_even_zcol_entangle_minimal_qubits(grid, extra_z_plaquette_indices),
+        cirq.Moment(
+            cirq.rz(-2 * je * dt).on_each(
+                grid.u_set(
+                    (grid.z_even_col_ancillary_qubits - grid.z_ancillary_u_side_qubits).union(
+                        extra_z_plaquette_ancillary_qubits.intersection(
+                            grid.z_even_col_ancillary_qubits
+                        )
+                    )
+                )
+            ),
+            cirq.rz(-2 * je * dt).on_each(
+                grid.r_set(
+                    grid.z_ancillary_u_side_qubits.intersection(grid.z_even_col_ancillary_qubits)
+                    - grid.z_ancillary_ur_corner_qubits
+                    - extra_z_plaquette_ancillary_qubits
+                )
+            ),
+            cirq.rz(-2 * je * dt).on_each(
+                grid.l_set(
+                    grid.z_ancillary_ur_corner_qubits.intersection(grid.z_even_col_ancillary_qubits)
+                    - extra_z_plaquette_ancillary_qubits
+                )
+            ),
+        ),
+        *trotter_even_zcol_entangle_minimal_qubits(grid, extra_z_plaquette_indices)[::-1],
+        *trotter_odd_zcol_entangle_minimal_qubits(grid, extra_z_plaquette_indices),
+        cirq.Moment(
+            cirq.rz(-2 * je * dt).on_each(
+                grid.u_set(
+                    (
+                        grid.z_odd_col_ancillary_qubits
+                        - grid.z_ancillary_u_side_qubits
+                        - grid.z_ancillary_dr_corner_qubits
+                    ).union(
+                        extra_z_plaquette_ancillary_qubits.intersection(
+                            grid.z_odd_col_ancillary_qubits
+                        )
+                    )
+                )
+            ),
+            cirq.rz(-2 * je * dt).on_each(
+                grid.r_set(
+                    grid.z_ancillary_u_side_qubits.intersection(grid.z_odd_col_ancillary_qubits)
+                    - grid.z_ancillary_r_side_qubits
+                    - extra_z_plaquette_ancillary_qubits
+                )
+            ),
+            cirq.rz(-2 * je * dt).on_each(
+                grid.l_set(
+                    grid.z_ancillary_ur_corner_qubits.union(
+                        grid.z_ancillary_dr_corner_qubits
+                    ).intersection(grid.z_odd_col_ancillary_qubits)
+                    - extra_z_plaquette_ancillary_qubits
+                )
+            ),
+        ),
+        *trotter_odd_zcol_entangle_minimal_qubits(grid, extra_z_plaquette_indices)[::-1],
+        cirq.Moment(cirq.H.on_each(extended_physical_qubits)),
+        *trotter_even_xcol_entangle_minimal_qubits(
+            grid, extra_plaquette_indices=extra_x_plaquette_indices
+        ),
+        cirq.Moment(
+            cirq.rz(-2 * jm * dt).on_each(
+                grid.u_set(
+                    grid.x_even_col_ancillary_qubits.union(
+                        extra_x_plaquette_even_col_ancillary_qubits
+                    )
+                )
+            )
+        ),
+        *trotter_even_xcol_entangle_minimal_qubits(
+            grid, extra_plaquette_indices=extra_x_plaquette_indices
+        )[::-1],
+        *trotter_odd_xcol_entangle_minimal_qubits(
+            grid, extra_plaquette_indices=extra_x_plaquette_indices
+        ),
+        cirq.Moment(
+            cirq.rz(-2 * jm * dt).on_each(
+                grid.u_set(
+                    grid.x_odd_col_ancillary_qubits.union(
+                        extra_x_plaquette_odd_col_ancillary_qubits
+                    )
+                )
+            )
+        ),
+        *trotter_odd_xcol_entangle_minimal_qubits(
+            grid, extra_plaquette_indices=extra_x_plaquette_indices
+        )[::-1],
+        cirq.Moment(cirq.H.on_each(extended_physical_qubits)),
+        cirq.Moment(cirq.rz(-2 * he * dt).on_each(grid.physical_qubits)),
+        cirq.Moment(cirq.rx(-2 * coupling * dt).on_each(grid.physical_qubits)),
+    ]
+
+def plaquette_bitstrings(
+    data: np.array, grid: LGTGrid, particle_locs: list[tuple[int, int]] = []
+) -> np.ndarray:
+    """Converts Z basis qubit bitstring to a bitstring in the Z stabilizers of the toric code.
+
+    Outputs the bitstring for the Z stabilizers where 0 corresponds to <ZZZZ>=1
+    and -1 to <ZZZZ>=-1.
+
+    Args:
+        data: array where the 0 axis indexes the shot and the 1 axis indexes the
+            qubits.
+        grid: representation of set of qubits.
+        particle_locs: Flips the value of the plaquette bitstrings for the plaquettes indicated
+            here, for applications with the particle_inject Hamiltonian quench.
+    """
+    plaquette_bitstrings = np.zeros((np.shape(data)[0], (grid.rows + 1) * (grid.cols + 1)))
+    for row in range(grid.rows + 1):
+        for col in range(grid.cols + 1):
+            if (row, col) not in particle_locs:
+                p = col + (grid.cols + 1) * row
+                plaquette_bitstrings[:, p] = (
+                    np.sum(
+                        data[
+                            :,
+                            list(
+                                grid.z_plaquette_to_physical_qubit_indices(
+                                    p // (grid.cols + 1), p % (grid.cols + 1)
+                                )
+                            ),
+                        ],
+                        axis=1,
+                    )
+                    % 2
+                )
+            else:
+                p = col + (grid.cols + 1) * row
+                plaquette_bitstrings[:, p] = (
+                    np.sum(
+                        data[
+                            :,
+                            list(
+                                grid.z_plaquette_to_physical_qubit_indices(
+                                    p // (grid.cols + 1), p % (grid.cols + 1)
+                                )
+                            ),
+                        ],
+                        axis=1,
+                    )
+                    + 1
+                ) % 2
+
+    return plaquette_bitstrings
+
+
+def x_plaquette_bitstrings(data: np.array, grid: LGTGrid) -> np.ndarray:
+    """Coverts X basis qubit bitstring to a bitstring  in the X stabilizers of the toric code.
+
+    Outputes the bitstring of the X stabilizers where 0 corresponds to <XXXX>=1
+    and 1 to <XXXX>=-1
+
+    Args:
+        data: array where the 0 axis indexes the shot and the 1 axis indexes the
+            qubits.
+        grid: representation of set of qubits.
+    """
+    plaquette_bitstrings = np.zeros((np.shape(data)[0], (grid.rows) * (grid.cols)))
+    for row in range(grid.rows):
+        for col in range(grid.cols):
+            p = col + (grid.cols) * row
+            plaquette_bitstrings[:, p] = (
+                np.sum(
+                    data[
+                        :,
+                        list(
+                            grid.x_plaquette_to_physical_qubit_indices(
+                                p // (grid.cols), p % (grid.cols)
+                            )
+                        ),
+                    ],
+                    axis=1,
+                )
+                % 2
+            )
+
+    return plaquette_bitstrings
+
+def cnot_on_layer(
+    pairs_list: Sequence[tuple[cirq.GridQubit, cirq.GridQubit]],
+    depolarization_probability: float | dict | None = None,
+) -> Sequence[cirq.Moment]:
+    """Outputs a list of moments for CNOT between two lists, in terms of CZ gates.
+
+    Args:
+        pairs_list: list of pairs of qubits with the first qubit in each pair being the control qubit and the second
+            qubit being the target
+        depolarization_probability: parameter to a 2 qubit depolarization channel after the CZ gate. This may also be a
+            dictionary that maps specific depolarization probability to specific pairs of qubits.
+    """
+    if depolarization_probability is None:
+        return [
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+            cirq.Moment(cirq.CZ.on(qc, qt) for qc, qt in pairs_list),
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+        ]
+    elif type(depolarization_probability) == float:
+        return [
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+            cirq.Moment(cirq.CZ.on(qc, qt) for qc, qt in pairs_list),
+            cirq.Moment(
+                cirq.depolarize(depolarization_probability, 2).on(pair[0], pair[1])
+                for pair in pairs_list
+            ),
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+        ]
+    elif type(depolarization_probability) == dict:
+        # make sure there is a error for every pair.
+        assert set(pairs_list).intersection(set(depolarization_probability.keys())) == set(
+            pairs_list
+        )
+
+        return [
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+            cirq.Moment(cirq.CZ.on(qc, qt) for qc, qt in pairs_list),
+            cirq.Moment(
+                cirq.depolarize(depolarization_probability[pair], 2).on(pair[0], pair[1])
+                for pair in pairs_list
+            ),
+            cirq.Moment(cirq.H.on_each(pair[1] for pair in pairs_list)),
+        ]
+    
+def excitation_sep_plaquette_input(
+    plaq_data: np.ndarray, plaq_rows: int = 3, plaq_cols: int = 2
+) -> np.ndarray:
+    """Computes the distance between two charge excitations based on a Manhattan metric.
+
+    Args:
+        plaq_data: array where the 0 axis indexes the shot and the 1 axis indexes the Z-plaquette.
+            The values correspond to the Z-plaquette expectation values.
+        plaq_rows: number of rows in the grid of Z-plaquettes.
+        plaq_cols: number of columns in the grid of Z-plaquettes.
+    """
+    mat1 = np.zeros((plaq_rows * plaq_cols, plaq_rows * plaq_cols))
+    mat1[:] = np.arange(np.shape(mat1)[1]) % plaq_cols
+    mat1 = np.transpose(mat1)
+
+    mat2 = np.zeros((plaq_rows * plaq_cols, plaq_rows * plaq_cols))
+    mat2[:] = np.arange(np.shape(mat2)[1]) % plaq_cols
+
+    mat3 = np.zeros((plaq_rows * plaq_cols, plaq_rows * plaq_cols))
+    mat3[:] = np.arange(np.shape(mat3)[1]) // plaq_cols
+    mat3 = np.transpose(mat3)
+
+    mat4 = np.zeros((plaq_rows * plaq_cols, plaq_rows * plaq_cols))
+    mat4[:] = np.arange(np.shape(mat4)[1]) // plaq_cols
+
+    distance_metric = (abs(mat1 - mat2) + abs(mat3 - mat4)) / 2
+
+    distances = np.einsum("ij,jl,il->i", plaq_data, distance_metric, plaq_data)
+
+    return distances
+
+def plot_qubit_polarization_values(
+    grid:LGTGrid,
+    qubit_polarization_data: np.ndarray,
+    ancilla_states_data:np.ndarray,
+    ax: plt.Axes | None = None,
+    qubit_kwargs: dict[str, Any] | None = None,
+    set_axis_off: bool = True,
+    force_equal_aspect: bool = True,
+    qubit_colormap=colormaps.get_cmap("Oranges"),
+    ancilla_colormap = colormaps.get_cmap("Oranges"),
+    plot_physical_qubits: bool | list[list[tuple[int]]] = False,
+    plot_ancillas: bool | list[list[tuple[int]]] = False,
+) -> plt.Axes:
+    """Plot toric code plaquette expectation values as colored tiles.
+    If round_edges = True, boundary Z-plaquettes are rounded off with
+    edges corresponding to stabilizers, otherwise all four quibts of
+    the boundary plaquettes are shown."""
+
+    if qubit_kwargs is None:
+        qubit_kwargs = {"edgecolor": "k", "linewidth": 1.0}
+
+    rows = grid.rows
+    cols = grid.cols
+
+    # Set up axis
+    if ax is None:
+        _fig, ax = plt.subplots()
+    if set_axis_off:  # Remove axis frame
+        ax.set_axis_off()
+    if force_equal_aspect:
+        ax.set_aspect("equal")
+    ax.set_xlim(-1, cols)
+    ax.set_ylim(rows, -1.5)
+
+    ax.set_xticks(range(cols))
+    ax.set_yticks(range(rows))
+
+    qubit_order = []
+    for row in range(grid.rows+1):
+        for col in range(grid.cols):
+            qubit_order.append(*grid.u_set({grid.x_plaquette_to_x_ancilla(row,col)}))
+    for row in range(1,grid.rows+1):
+        for col in range(grid.cols+1):
+            qubit_order.append(*grid.u_set({grid.z_plaquette_to_z_ancilla(row,col)}))
+    qubit_order
+
+    pols_shuffled = np.array([qubit_polarization_data[np.nonzero(np.array(grid.physical_qubits) == qubit)[0][0]] for qubit in qubit_order])
+
+    if plot_physical_qubits is True:
+        # Plot X plaquette top qubits
+        qubit_index = 0
+        for row in range(grid.rows + 1):
+            for col in range(grid.cols):
+                ax.add_patch(
+                    get_qubit_patch_rect(
+                        pols_shuffled,
+                        qubit_index,
+                        row,
+                        col,
+                        x_basis=True,
+                        qubit_colormap=qubit_colormap,
+                        **qubit_kwargs,
+                    )
+                )
+
+                qubit_index += 1
+
+        # Plot Z plaquette bottom qubits
+        for row, col in grid.z_plaquette_indices:
+            if row != grid.rows:
+                ax.add_patch(
+                    get_qubit_patch_rect(
+                        pols_shuffled,
+                        qubit_index,
+                        row,
+                        col,
+                        x_basis=False,
+                        qubit_colormap=qubit_colormap,
+                        **qubit_kwargs,
+                    )
+                )
+
+                qubit_index += 1
+
+    elif type(plot_physical_qubits) == list:
+        # Plot X plaquette top qubits
+        for row, col in plot_physical_qubits[0]:
+            qubit_index = (row) * grid.cols + col
+            ax.add_patch(
+                get_qubit_patch_rect(
+                    qubit_polarization_data,
+                    qubit_index,
+                    row,
+                    col,
+                    x_basis=True,
+                    qubit_colormap=qubit_colormap,
+                    **qubit_kwargs,
+                )
+            )
+
+        # Plot Z plaquette bottom qubits
+        for row, col in plot_physical_qubits[1]:
+            qubit_index = (
+                (data.code.rows + 1) * (data.code.cols + 1) + (row) * (data.code.cols + 1) + col
+            )
+
+            ax.add_patch(
+                get_qubit_patch_rect(
+                    qubit_polarization_data,
+                    qubit_index,
+                    row,
+                    col,
+                    x_basis=False,
+                    round_edges=round_edges,
+                    qubit_colormap=qubit_colormap,
+                    **qubit_kwargs,
+                )
+            )
+            
+    if plot_ancillas is True:
+        for row, col in grid.z_plaquette_indices:
+            qubit_index = (2*grid.cols+1)*row+col
+            ax.add_patch(
+                get_ancilla_patch(data = ancilla_states_data, qubit_index = qubit_index,row=row, col=col, x_basis=False, ancilla_cmap = ancilla_colormap, **qubit_kwargs)
+            )
+        for row, col in grid.x_plaquette_indices:
+            qubit_index = (2*grid.cols+1)*row+3+col
+            ax.add_patch(
+                get_ancilla_patch(data = ancilla_states_data, qubit_index = qubit_index,row=row, col=col, x_basis=True, ancilla_cmap = ancilla_colormap, **qubit_kwargs)
+                )
+
+    elif type(plot_ancillas) == list:
+        for row, col in plot_ancillas[0]:
+            ax.add_patch(
+                get_ancilla_patch(row=row, col=col, x_basis=False, **qubit_kwargs)
+            )
+        for row, col in plot_ancillas[1]:
+            ax.add_patch(get_ancilla_patch(row=row, col=col, x_basis=True, **qubit_kwargs))
+    return ax
+
+def get_qubit_patch_rect(
+    data: np.array,
+    qubit_index: int,
+    row: int,
+    col: int,
+    x_basis: bool,
+    qubit_colormap=colormaps.get_cmap("Oranges"),
+    **kwargs,
+) -> mpatches.Patch:
+    """Generate a single patch polygon for a plaquette."""
+    if not x_basis:  # z basis, includes special boundary cases
+        coordinates = [
+            (col - 0.5 + 0.2, row),
+            (col - 0.5, row + 0.25),
+            (col - 0.5 - 0.2, row),
+            (col - 0.5, row - 0.25),
+        ]
+
+    else:  # x basis
+        coordinates = [
+            (col + 0.25, row - 0.5),
+            (col, row - 0.5 + 0.2),
+            (col - 0.25, row - 0.5),
+            (col, row - 0.5 - 0.2),
+        ]
+
+    color = qubit_colormap((data[qubit_index] - 1)/(-2))
+
+    return mpatches.Polygon(coordinates, closed=True, facecolor=color, **kwargs)
+
+def get_ancilla_patch(
+        data:np.ndarray,
+        qubit_index,
+        row: int,
+        col: int,
+        x_basis: bool,
+        ancilla_cmap,
+        **kwargs
+    ) -> mpatches.Patch:
+    """Generate a single patch polygon for a plaquette."""
+    if not x_basis:
+        coordinates = (col - 0.5, row - 0.5)
+
+    else:  # x basis
+        coordinates = (col, row)
+
+    color = ancilla_cmap(data[qubit_index])
+
+    return mpatches.Circle(coordinates, radius=0.146, facecolor=color, **kwargs)
\ No newline at end of file
diff --git a/recirq/lattice_gauge/lattice_gauge_experiment_test.py b/recirq/lattice_gauge/lattice_gauge_experiment_test.py
new file mode 100644
index 00000000..6b6cca6a
--- /dev/null
+++ b/recirq/lattice_gauge/lattice_gauge_experiment_test.py
@@ -0,0 +1,135 @@
+# Copyright 2025 Google
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import cirq
+
+import numpy as np
+import matplotlib.pyplot as plt
+from .lattice_gauge_experiment import plot_qubit_polarization_values, variational_ground_state_minimal_qubits, trotter_step_minimal_qubits
+from .lattice_gauge_grid import LGTGrid
+
+def test_plot_qubit_polarization_values():
+    # Create a mock LGTGrid
+    grid = LGTGrid(
+        origin_qubit=cirq.GridQubit(0, 0),
+        orientation_vector=(1, 1),
+        rows=3,
+        cols=3
+    )
+
+    # Mock data for qubit polarization and ancilla states
+    qubit_polarization_data = np.random.rand(len(grid.physical_qubits))
+    ancilla_states_data = np.random.rand(len(grid.physical_qubits))
+
+    # Create a matplotlib axis
+    fig, ax = plt.subplots()
+
+    # Call the function to test
+    plot_qubit_polarization_values(
+        grid=grid,
+        qubit_polarization_data=qubit_polarization_data,
+        ancilla_states_data=ancilla_states_data,
+        ax=ax,
+        plot_physical_qubits=True
+    )
+
+    # Assert that the axis has been modified
+    assert ax.has_data(), "The axis should have data after plotting."
+
+    # Close the plot to avoid resource warnings
+    plt.close(fig)
+
+def test_variational_ground_state_minimal_qubits():
+    # Define grid parameters
+    lx, ly = 4, 3  # Grid dimensions
+    grid = LGTGrid(
+        origin_qubit=cirq.GridQubit(0, 0),
+        orientation_vector=(1, 1),
+        rows=lx - 1,
+        cols=ly - 1,
+        flip_rowcol=False
+    )
+
+    # Define Hamiltonian coefficients
+    hamiltonian_coefs = {'Je': np.random.random(), 'Jm': np.random.random(), 'he':np.random.random(), 'lambda': np.random.random()}
+
+    # Define thetas to test
+    thetas = [0, np.pi / 2]
+
+    # Initialize simulator
+    simulator = cirq.Simulator()
+
+    # Loop over thetas and compute energy
+    # Note the correspondence between he and theta in this test is not physical
+    for theta in thetas:
+        # Create the circuit for the given theta
+        circuit = cirq.Circuit.from_moments(
+            *variational_ground_state_minimal_qubits(grid, theta)
+        )
+        
+        observable = cirq.PauliSum()
+        for row in range(lx):
+            for col in range(ly):
+                observable += cirq.PauliString(hamiltonian_coefs['Je'],cirq.Z.on_each(grid.z_plaquette_to_physical_qubits(row, col).values()))
+        for row in range(lx-1):
+            for col in range(ly-1):
+                observable += cirq.PauliString(hamiltonian_coefs['Jm'],cirq.X.on_each(grid.x_plaquette_to_physical_qubits(row, col).values()))
+        for qubit in grid.physical_qubits:
+            observable += cirq.PauliString(hamiltonian_coefs['he'],cirq.Z(qubit))
+            observable += cirq.PauliString(hamiltonian_coefs['lambda'],cirq.X(qubit))
+
+        # Simulate the expectation values
+        results = simulator.simulate_expectation_values(circuit,[observable])
+
+        if theta == np.pi:
+            assert np.isclose(results[0], lx*ly*hamiltonian_coefs['Je']+(lx-1)*(ly-1)*hamiltonian_coefs['Jm'], atol=1e-2), (
+            f"Error of energy of WALA initial state when theta = {theta}"
+            )
+        elif theta == 0:
+            assert np.isclose(results[0], lx*ly*hamiltonian_coefs['Je']+len(grid.physical_qubits)*hamiltonian_coefs['he'], atol=1e-2), (
+            f"Error of energy of WALA initial state when theta = {theta}"
+            )
+
+def test_trotter_step_minimal_qubits():
+    # Define grid parameters
+    lx, ly = 3, 2  # Grid dimensions
+    grid = LGTGrid(
+        origin_qubit=cirq.GridQubit(0, 0),
+        orientation_vector=(1, 1),
+        rows=lx - 1,
+        cols=ly - 1,
+        flip_rowcol=False
+    )
+
+    # Define Hamiltonian coefficients
+    hamiltonian_coefs = {'Je': 1, 'Jm': 1, 'he':0.4, 'lambda': 0.5}
+    dt = 0.3
+
+    observable = cirq.PauliSum()
+
+    #Going to test that, under these parameters, the average probability of particle creation from the
+    #WALA state after 20 Trotter steps is consistent with the expected value of 0.9019627769788106.
+    for row in range(lx):
+        for col in range(ly):
+            observable += cirq.PauliString(1/6,cirq.Z.on_each(grid.z_plaquette_to_physical_qubits(row, col).values()))
+
+    circuit = cirq.Circuit.from_moments(
+        *variational_ground_state_minimal_qubits(grid, 0.625),
+        *trotter_step_minimal_qubits(grid, dt, hamiltonian_coefs['lambda'], hamiltonian_coefs['he'], hamiltonian_coefs['Je'], hamiltonian_coefs['Jm'])*20,
+    )
+
+    simulator = cirq.Simulator()
+    results = simulator.simulate_expectation_values(circuit,[observable])
+
+    assert np.isclose(results[0], (0.9019627769788106+0j), atol=1e-4), ("Error in Trotterization circuit.")
diff --git a/recirq/lattice_gauge/lattice_gauge_grid.py b/recirq/lattice_gauge/lattice_gauge_grid.py
new file mode 100644
index 00000000..2f8d9e13
--- /dev/null
+++ b/recirq/lattice_gauge/lattice_gauge_grid.py
@@ -0,0 +1,377 @@
+# Copyright 2025 Google
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from collections.abc import Iterator
+from enum import Enum
+
+import cirq
+import numpy as np
+
+class QubitNeighbor(Enum):
+    """Enum for the neighbors of a qubit in a grid.
+
+    The neighbors are defined as follows:
+    - A: The qubit itself
+    - U: Up
+    - R: Right
+    - D: Down
+    - L: Left
+    """
+    A = "a"
+    U = "u"
+    R = "r"
+    D = "d"
+    L = "l"
+
+class LGTGrid:
+    """Representation of rectangular grid of qubits for lattice gauge theory experiments.
+
+    This grid of qubits is analagous to the X-type/Z-type Toric Code with the boundary chosen
+    such that all boundary stabilizers are Z-type. The origin_qubit is chosen to be an ancillary
+    qubit for an X-type plaquette closest to a corner. The other qubits are chosen based on the
+    orientation vector, which is drawn from the origin_qubit away from the corner to the adjacent
+    'bulk' ancillary qubit for a Z-type plaquette.
+    """
+
+    def __init__(
+        self,
+        origin_qubit: cirq.GridQubit,
+        orientation_vector: tuple[int, int],
+        rows: int,
+        cols: int,
+        flip_rowcol: bool = False,
+    ):
+        """
+
+        Args:
+            origin_qubit: ancillary qubit for an X-type plaquette closest to a corner
+            orientation_vector: vector drawn from origin_qubit to the ancillary qubit of the adjacent 'bulk'
+                Z-type plaquette
+            rows: number of rows of X-type stabilizers
+            cols: number of columns of X-type stabilizers
+            flip_rowcol: chooses whether to transpose row and columns code
+        """
+        if np.any(np.abs(orientation_vector) != np.array([1, 1])):
+            raise ValueError(
+                f"Inconsistent orientation_vector={orientation_vector}: must be (±1, ±1)"
+            )
+
+        if rows < 1 or cols < 1:
+            raise ValueError(f"rows ({rows}) and cols ({cols}) must both be at least 1")
+
+        self.origin_qubit = origin_qubit
+        self.orientation_vector = orientation_vector
+        self.row_vector = np.array([2 * orientation_vector[0], 0], dtype=int)
+        self.col_vector = np.array([0, 2 * orientation_vector[1]], dtype=int)
+        self.rows = rows
+        self.cols = cols
+        self.flip_rowcol = flip_rowcol
+
+    @property
+    def physical_qubits(self) -> set[cirq.GridQubit]:
+        """Set of physical gauge qubits at the corners of Z and X plaquettes."""
+        return sorted(
+            self.u_set(self.x_ancillary_qubits)
+            .union(self.r_set(self.x_ancillary_qubits))
+            .union(self.d_set(self.x_ancillary_qubits))
+            .union(self.l_set(self.x_ancillary_qubits))
+        )
+    
+    @property
+    def x_ancillary_qubits(self) -> set[cirq.GridQubit]:
+        return {self.x_plaquette_to_x_ancilla(row, col) for row, col in self.x_plaquette_indices}
+    
+    @property
+    def z_ancillary_l_side_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(row, 0) for row in range(0, self.rows + 1)}
+    
+    @property
+    def z_ancillary_dl_corner_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(self.rows, 0)}
+    
+    @property
+    def z_even_col_ancillary_qubits(self) -> set[cirq.GridQubit]:
+        return {
+            self.z_plaquette_to_z_ancilla(row, col)
+            for row, col in self.z_plaquette_even_col_indices
+        }
+    
+    @property
+    def z_ancillary_d_side_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(self.rows, col) for col in range(0, self.cols + 1)}
+    
+    @property
+    def z_ancillary_ul_corner_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(0, 0)}
+    
+    @property
+    def z_ancillary_u_side_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(0, col) for col in range(0, self.cols + 1)}
+    
+    @property
+    def z_ancillary_r_side_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(row, self.cols) for row in range(0, self.rows + 1)}
+
+    @property
+    def z_ancillary_ur_corner_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(0, self.cols)}
+    
+    @property
+    def z_odd_col_ancillary_qubits(self) -> set[cirq.GridQubit]:
+        return {
+            self.z_plaquette_to_z_ancilla(row, col) for row, col in self.z_plaquette_odd_col_indices
+        }
+    
+    @property
+    def x_ancillary_qubits_by_col(self) -> list[set[cirq.GridQubit]]:
+        return [
+            {self.x_plaquette_to_x_ancilla(row, col) for row in range(self.rows)}
+            for col in range(self.cols)
+        ]
+    
+    @property
+    def z_ancillary_dr_corner_qubits(self) -> set[cirq.GridQubit]:
+        return {self.z_plaquette_to_z_ancilla(self.rows, self.cols)}
+    
+    @property
+    def x_even_col_ancillary_qubits(self) -> set[cirq.GridQubit]:
+        return {
+            self.x_plaquette_to_x_ancilla(row, col)
+            for row, col in self.x_plaquette_even_col_indices
+        }
+    
+    @property
+    def x_odd_col_ancillary_qubits(self) -> set[cirq.GridQubit]:
+        return {
+            self.x_plaquette_to_x_ancilla(row, col) for row, col in self.x_plaquette_odd_col_indices
+        }
+    
+    @property
+    def x_plaquette_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows):
+            for col in range(self.cols):
+                yield row, col
+
+    @property
+    def z_plaquette_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows + 1):
+            for col in range(self.cols + 1):
+                yield row, col
+
+    @property
+    def z_plaquette_even_col_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows + 1):
+            for col in range(0, self.cols + 1, 2):
+                yield row, col
+
+    @property
+    def z_plaquette_odd_col_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows + 1):
+            for col in range(1, self.cols + 1, 2):
+                yield row, col
+
+    @property
+    def x_plaquette_even_col_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows):
+            for col in range(0, self.cols, 2):
+                yield row, col
+
+    @property
+    def x_plaquette_odd_col_indices(self) -> Iterator[tuple[int, int]]:
+        for row in range(self.rows):
+            for col in range(1, self.cols, 2):
+                yield row, col
+    
+    def q_displaced(self, qubit: cirq.GridQubit, displacement: np.ndarray) -> cirq.GridQubit:
+        """Helper to return a `GridQubit` displaced by a fixed x/y.
+
+        Args:
+            displacement: numpy array with row/column displacement.
+
+        Returns:
+            `cirq.GridQubit` that is displaced by a fixed amount of rows/columns
+        """
+        if self.flip_rowcol is False:
+            return qubit + (int(round(displacement[0])), int(round(displacement[1])))
+        else:
+            return qubit + (int(round(displacement[1])), int(round(displacement[0])))
+        
+    def u_set(self, qubit_set: set[cirq.GridQubit]) -> set[cirq.GridQubit]:
+        """Ouputs a set of qubits translated up from the input set."""
+        return {self.q_displaced(qubit, -self.row_vector / 2) for qubit in qubit_set}
+
+    def r_set(self, qubit_set: set[cirq.GridQubit]) -> set[cirq.GridQubit]:
+        """Ouputs a set of qubits translated right from the input set."""
+        return {self.q_displaced(qubit, self.col_vector / 2) for qubit in qubit_set}
+
+    def d_set(self, qubit_set: set[cirq.GridQubit]) -> set[cirq.GridQubit]:
+        """Ouputs a set of qubits translated down from the input set."""
+        return {self.q_displaced(qubit, self.row_vector / 2) for qubit in qubit_set}
+
+    def l_set(self, qubit_set: set[cirq.GridQubit]) -> set[cirq.GridQubit]:
+        """Ouputs a set of qubits translated left from the input set."""
+        return {self.q_displaced(qubit, -self.col_vector / 2) for qubit in qubit_set}
+    
+    def ancillary_to_pair(
+        self, a_set: set[cirq.GridQubit], qubit1_relationship: QubitNeighbor, qubit2_relationship: QubitNeighbor
+    ) -> set[tuple[cirq.GridQubit, cirq.GridQubit]]:
+        """Generates a pair of qubits for each qubit in a_set based on nearest neighbor
+        relationships.
+
+        Args:
+            a_set: set of input qubits, usually ancillary qubits of a set of plaquettes.
+            qubit1_relationship: either A, U, R, D, or L. indicated that the first qubit in each pair will either
+                be qubits in a_set (A), or the qubits that are up (U), right (R), down (D), or left (L) from
+                the qubits in a_set.
+            qubit2_relationship: ... same but the second qubit in each pair.
+        """
+        displacement_dict ={
+            QubitNeighbor.A: 0,
+            QubitNeighbor.U: -self.row_vector / 2,
+            QubitNeighbor.R: self.col_vector / 2,
+            QubitNeighbor.D: self.row_vector / 2,
+            QubitNeighbor.L: -self.col_vector / 2,
+
+        }
+
+        return {
+            (
+                self.q_displaced(qubit, displacement_dict[qubit1_relationship]),
+                self.q_displaced(qubit, displacement_dict[qubit2_relationship])
+            )
+            for qubit in a_set
+        }
+    
+    
+    def z_plaquette_to_physical_qubit_indices(self, row: int, col: int) -> list[int]:
+        """Outputs the indices of all physical qubits within the sorted list of all physical
+        qubits."""
+        return [
+            sorted(list(self.physical_qubits)).index(qubit)
+            for qubit in self.z_plaquette_to_physical_qubits(row, col).values()
+        ]
+    
+    def x_plaquette_to_physical_qubit_indices(self, row: int, col: int) -> list[int]:
+        """Outputs the indices of all physical qubits within the sorted list of all physical
+        qubits."""
+        return [
+            sorted(list(self.physical_qubits)).index(qubit)
+            for qubit in self.x_plaquette_to_physical_qubits(row, col).values()
+        ]
+    
+    def z_plaquette_to_physical_qubits(self, row: int, col: int) -> dict[str : cirq.GridQubit]:
+        """Outputs all the physical qubits that constitute the Z plaquette at indices (row, col).
+
+        Interior Z plaquettes are made up of 4 qubits. While plaquettes on the edge are only comprised
+        of 3 qubits. Corner plaquettes just have 2 qubits.
+        """
+        u_displacement = (
+            (row - 0.5) * self.row_vector + (col - 0.5) * self.col_vector - self.row_vector / 2
+        )
+        r_displacement = (
+            (row - 0.5) * self.row_vector + (col - 0.5) * self.col_vector + self.col_vector / 2
+        )
+        d_displacement = (
+            (row - 0.5) * self.row_vector + (col - 0.5) * self.col_vector + self.row_vector / 2
+        )
+        l_displacement = (
+            (row - 0.5) * self.row_vector + (col - 0.5) * self.col_vector - self.col_vector / 2
+        )
+        if row == 0 and col == 0:
+            return {
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+            }
+        elif row == 0 and col == self.cols:
+            return {
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        elif row == self.rows and col == 0:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+            }
+        elif row == self.rows and col == self.cols:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        elif row == 0:
+            return {
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        elif col == 0:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+            }
+        elif row == self.rows:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        elif col == self.cols:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        else:
+            return {
+                "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+                "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+                "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+                "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+            }
+        
+    def x_plaquette_to_physical_qubits(self, row: int, col: int) -> dict[str : cirq.GridQubit]:
+        """Outputs all the physical qubits that constitute the X plaquette at indices (row, col).
+
+        In current construction, all X plaquettes are on the interior, so thus have 4 qubits.
+        """
+        u_displacement = (row) * self.row_vector + (col) * self.col_vector - self.row_vector / 2
+        r_displacement = (row) * self.row_vector + (col) * self.col_vector + self.col_vector / 2
+        d_displacement = (row) * self.row_vector + (col) * self.col_vector + self.row_vector / 2
+        l_displacement = (row) * self.row_vector + (col) * self.col_vector - self.col_vector / 2
+        return {
+            "u_qubit": self.q_displaced(self.origin_qubit, u_displacement),
+            "r_qubit": self.q_displaced(self.origin_qubit, r_displacement),
+            "d_qubit": self.q_displaced(self.origin_qubit, d_displacement),
+            "l_qubit": self.q_displaced(self.origin_qubit, l_displacement),
+        }
+
+    def x_plaquette_to_x_ancilla(self, row: int, col: int) -> cirq.GridQubit:
+        """This displacement is counting from the upper left X plaquette.
+
+        Args:
+            row: plaquette row, row 0 is on top with increasing rows going down.
+            col: plaquette column, column 0 is on the left and increasing to the left.
+        """
+        displacement = row * self.row_vector + col * self.col_vector
+        return self.q_displaced(self.origin_qubit, displacement)
+    
+    def z_plaquette_to_z_ancilla(self, row: int, col: int) -> cirq.GridQubit:
+        """This displacement is counting from the upper left Z plaquette.
+
+        Args:
+            row: plaquette row, row 0 is on top with increasing rows going down.
+            col: plaquette column, column 0 is on the left and increasing to the left.
+        """
+        displacement = (row - 1 / 2) * self.row_vector + (col - 1 / 2) * self.col_vector
+        return self.q_displaced(self.origin_qubit, displacement)
\ No newline at end of file
diff --git a/recirq/lattice_gauge/lattice_gauge_grid_test.py b/recirq/lattice_gauge/lattice_gauge_grid_test.py
new file mode 100644
index 00000000..f4579d85
--- /dev/null
+++ b/recirq/lattice_gauge/lattice_gauge_grid_test.py
@@ -0,0 +1,70 @@
+# Copyright 2025 Google
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import cirq
+
+import numpy as np
+import matplotlib.pyplot as plt
+from .lattice_gauge_grid import LGTGrid
+
+def test_z_plaquette_to_physical_qubit_indices():
+    # Create a mock LGTGrid
+    grid = LGTGrid(
+        origin_qubit=cirq.GridQubit(0, 0),
+        orientation_vector=(1, 1),
+        rows=3,
+        cols=3
+    )
+
+    # Define a sample plaquette index
+    plaquette_index = (1, 1)
+
+    # Call the function to test
+    physical_qubit_indices = grid.z_plaquette_to_physical_qubit_indices(row = plaquette_index[0], col = plaquette_index[1])
+
+    # Expected result based on the grid structure
+    expected_indices = [4,8,11,7]
+
+    # Assert the result matches the expected indices
+    assert physical_qubit_indices == expected_indices, (
+        f"Expected {expected_indices}, but got {physical_qubit_indices}"
+    )
+
+def test_z_plaquette_to_physical_qubits():
+    # Create a mock LGTGrid
+    grid = LGTGrid(
+        origin_qubit=cirq.GridQubit(0, 0),
+        orientation_vector=(1, 1),
+        rows=3,
+        cols=3
+    )
+
+    # Define a sample plaquette index
+    plaquette_index = (1, 1)
+
+    # Call the function to test
+    physical_qubits = grid.z_plaquette_to_physical_qubits(row=plaquette_index[0], col=plaquette_index[1])
+
+    # Expected result based on the grid structure
+    expected_qubits = {
+        'u_qubit': cirq.GridQubit(0, 1),
+         'r_qubit': cirq.GridQubit(1, 2),
+         'd_qubit': cirq.GridQubit(2, 1),
+         'l_qubit': cirq.GridQubit(1, 0)
+    }
+
+    # Assert the result matches the expected qubits
+    assert physical_qubits == expected_qubits, (
+        f"Expected {expected_qubits}, but got {physical_qubits}"
+    )
\ No newline at end of file