mosaic_sim.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "593e90ad-fd42-43b4-b733-7c16f10b0992",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "0e07b053-f493-4b4e-a766-970c4714d842",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "want_colors = 1 # from input 1=color, 0=b/w\n",
    "seconds = 10 # length of generated gif\n",
    "fps = 12\n",
    "x = 10 # dimension of generated image ( # of tiles in x)\n",
    "y = 11# dimension of generated image ( # of tiles in y)\n",
    "\n",
    "frameAmount = seconds * fps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c907569a-af45-4c59-bae2-7947936a230c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Use AerSimulator\n",
    "from qiskit.providers.aer import AerSimulator\n",
    "\n",
    "backend = AerSimulator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c24b494f-a11e-4596-a501-2bf8cadd768a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f2ba266e110>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Quantum Circuit acting on a quantum register of seven qubits\n",
    "qubits = 7\n",
    "circ = QuantumCircuit(qubits)\n",
    "\n",
    "#always is variable 0-1\n",
    "circ.h(1) #shape\n",
    "circ.h(5) #rot1\n",
    "circ.h(6) #rot2\n",
    "\n",
    "# set q0 to 1 if wants colors\n",
    "if want_colors:\n",
    "    circ.x(0)\n",
    "\n",
    "# Set colors to 0-1 if q0 is 1 (want_colors)\n",
    "circ.ch(0, 2) #colors1 0-1 if q0 is 1\n",
    "circ.ch(0, 3) #colors2 0-1 if q0 is 1\n",
    "\n",
    "# Set b/w-w/b to 0-1 if !want_colors\n",
    "circ.x(0) #invert q0\n",
    "circ.ch(0, 4) #b/w 0-1 if q0 is 1 now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "a029bb9f-31de-4cb5-ade9-f18bf461c40f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 538.33x618.722 with 1 Axes>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circ.draw('mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e22359f2-fa64-4b77-83c5-e5c038933707",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$0.1767766953 |0000000\\rangle+0.1767766953 |0000010\\rangle+0.1767766953 |0000100\\rangle+0.1767766953 |0000110\\rangle+0.1767766953 |0001000\\rangle+0.1767766953 |0001010\\rangle + \\ldots +0.1767766953 |1100110\\rangle+0.1767766953 |1101000\\rangle+0.1767766953 |1101010\\rangle+0.1767766953 |1101100\\rangle+0.1767766953 |1101110\\rangle$$"
      ],
      "text/plain": [
       "<IPython.core.display.Latex object>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.quantum_info import Statevector\n",
    "\n",
    "# Set the intial state of the simulator to the ground state using from_int\n",
    "state = Statevector.from_int(0, 2**qubits)\n",
    "\n",
    "# Evolve the state by the quantum circuit\n",
    "state = state.evolve(circ)\n",
    "\n",
    "# draw using latex\n",
    "state.draw('latex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ad246130-bf1c-4b75-bf93-54645ea1a7b2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# state.draw('qsphere')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "0ed14bab-4a2e-4d68-b625-b9836136ddd7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5WrFihfbs2SOpeqlNSkqq8djZXbt2Vf4R4Unsi5fKsStD5rtHyHTGya9Mfn7ye/ghyW6T7c9/kcNbrmXzi6jk8mJXV0l9JavnfWZRK/8gqcMgyVTHd/hFsVKbK+s3k1F89T1wUYzU5qq6z9+qi9S89fnn83QBAQEKDw9XQIA7j9huWJdddpn8fvlwxpmTXUmuFdqzH8eZEW4AABqC15ZaqbygLl++XCdOnNCJEyf0zTffaMyYMSoqKtKBAwdkNpvVvn37KsvceOON+vLLLysv9yNJ33zzjfbt26dBgwY19CZcEMehQ7K/+bZMSZfL/Otbq003xbWSecRwOXb8T/aPPPdyRTUxmaR2/c4/WmX2K58vOqVhcjWk5nFS2q3nH7G9OEFKu8VLR2l9+D0gSa27S217lr8famUqL79tezZYLEMdOnRI48aN06FDh4yO4rKgoKDKk1z9/PPPdV7O1UIrlV/DvbS0VKWlpRwzCwBodEwObxueqINvvvlGV155pS677LJqx2IdP35cHTp0UEREhJ566imdOnVK06ZN08UXX6yvvvqqwX6Zu/N4woZw7Lq+jeZYwrMVHZWyt0u5GdLpX052ajJJ8ddILdtLgXU/V4xHKjtdvu3Z28uvxVuhZXspJk1q6vox+fXK094DUuN9H5w6IWX/V8rZKZ06/sudJimumxSTIlmaGhrvgjl7TO2QIUO0ePFip0YcL7/c+ROvXahzHVNbwWw2n/fSPxX8/Pz09ttv64477nCq0J65vM127ouAFxYWckwtAKDB+eTHrTt27JBUfddjSWratKnWrl2rqKgoDRs2TPfdd5+uuuoqLV++nE+nPZQ1XErsLfUcJwX+8rdWoFWK6+r9hVaS/APLjxfudtf/b39QSPkIdWMttHAvS6gU30O6eswZrwGr1PZqzy+0vq6uhVaSbDabRo4cqTfeeMPpQluxPAAAjVHjG1JoAOcqtZIUHx+v5cuXN2QkNBA3XbnFY/n69oPXgK+z2Wy69957jY4BAIBb+eTQ4/lKLQAAAADAM/jkSO3atWuNjgAAMECLFi00ffp0tWjRwugoAADATXyy1AIAfFNERIRGjRpldAwAAOBGPrn7MQDANxUUFGj16tUqKCgwOgoAAHATSi0AwGdkZWVp8uTJVa5FDgAAPBulFgAAAADgsSi1AAAAAACPRakFAAAAAHgsSi0AwGdYLBYlJSXJYrEYHQUAALgJl/QBAPiM+Ph4LV261OgYAADAjRipBQAAAAB4LEotAMBn7Nq1SykpKdq1a5fRUQAAgJtQagEAPsPhcKi0tFQOh8PoKAAAwE04praRCjb76dh1fY2OUWfBZj+jI8DLeNp7QOJ9APcKDg5WYWGh29Y3e/77Ol5UrKbWYE0dO6zabXcIDg52y3oAAHAGpbaRMplMsvrx7YHv4j0AX2cymWS1Wt22vsAgiwJLbQoMsshqtVa7DQCAp2L3YwAAAACAx2IYBADgM+Lj47Vs2TLFxsYaHQUAALgJpRYA4DMsFosSEhKMjgEAANyI3Y8BAD4jOztbjz/+uLKzs42OAgAA3IRSCwDwGfn5+VqyZIny8/ONjgIAANyEUgsAAAAA8FiUWgAAAACAx6LUAgAAAAA8FqUWAOAzzGazunTpIrOZX38AAHgLfqsDAHyG3W7Xxo0bZbfbjY4CAADchFILAAAAAPBYlFoAAAAAgMei1AIAAAAAPBalFgDgM8LCwjRo0CCFhYUZHQUAALiJv9EBAABoKDExMXr22WeNjgEAANyIkVoAgM8oKSnRwYMHVVJSYnQUAADgJpRaAIDPyMzMVL9+/ZSZmWl0FAAA4CbsftxIORzSaZvRKeou0E8ymYxOAQDwFg6HQ8XFxUbHcEpwcLBM/DIEgAZHqW2kTtuk6YuMTlF36bdLQbyaAABuUlxcrJCQEKNjOKWwsFBWq9XoGADgc9j9GAAAAADgsSi1AAAAAACPxQ6jAACfkZycrIyMDKNjAAAAN2KkFgAAAADgsSi1AACfsX//fg0bNkz79+83OgoAAHATSi0AwGcUFxdr+/btHnepGAAAUDtKLQAAAADAY1FqAQAAAAAei1ILAAAAAPBYlFoAgM+Ijo5Wenq6oqOjjY4CAADchOvUAgB8RrNmzTR48GCjY8BDhYWFqaCgwOgYAICzUGoBAD7j6NGjWrVqlfr376/w8HCj46ABBAUFKSUlRZ06dVJqaqrCwsJkNpt18uRJ7dmzR5s2bdLmzZt19OjRc64nMjJSa9eu1apVqzRlypQGSg8AqAtKLQDAZ+Tk5GjmzJlKS0uj1Hq5lJQUjRs3TsOHD1dISMh551+zZo3+/ve/a9myZbLZbFWmVRTapKQkJSUlKS8vT7Nmzaqv6AAAJ/nEMbV5eXmaNm2a2rZtK4vFotjYWE2cOFFFRUUaPXq0TCaT5s2bZ3RMAABwgeLi4rR69Wpt375dY8eOrVOhlaS+fftq6dKl+v777zVw4MDK+88stJK0f/9+vffee/WSHQDgGq8fqd22bZv69++v3NxcWa1WtWvXTkeOHNHcuXO1b9++yt2N0tLSjA1aT7J2fa4lT/fW1XfMVqeBD9c4z99GmBSXNlA3Pby8gdMBAOA+DzzwgGbPnl2lyJ44cUIfffSRvv32W23ZskVHjhyRw+FQ06ZNK3dLHjRokNq2bStJuvTSS7V8+XK9+eabmjVrlj788MMqhbZ37946ePCgIdsHAKiZV5favLw8DRo0SLm5uZoyZYpmzJih0NBQSdKzzz6r6dOny9/fXyaTSSkpKQanBQAArjCbzXrppZd0//33V9536NAhzZo1S++8844KCwtrXG7Hjh169913NWXKFPXt21dTp05Vnz59JEl33323hg0bpqCgIEkUWgBozLx69+MHH3xQWVlZmjBhgubMmVNZaCVp2rRpSk1NVVlZmeLi4tS0aVMDkwIAGoLValWPHj1ktVqNjgI3MZlMeuWVV6oU2vnz56t9+/Z66aWXai20Z3I4HPrkk0/Ut29f3XPPPTp+/LgkVRbaQ4cOUWgBoBHz2lKbkZGhRYsWKSIiotaTOXTq1EmSlJqaWnlfRQnu2rWrgoKCZDKZGiQvAKD+xcXF6dVXX1VcXJzRUeAm06dP17333itJKi0t1bBhw/TAAw/oxIkTLq1v9erV+vHHH6vc9/PPPysrK+uCswIA6ofXltqFCxfKbref86yHTZo0kVS11GZmZmrJkiWKjIxUly5dGiRrQyg7XayTJ/Jq/AcAvsJms6mwsLDa2W3hmZKTk/XUU09JKv/e3nHHHVq0aJHL66s4KVTF8bVlZWWSpI4dO+rhh2s+LwUAwHhee0zt2rVrJUm9e/eudZ6KT13PLLU9e/ZUTk6OJOnJJ5/Uhg0b6jFlw/l6yQx9vWSG0TEAwFC7d+/WkCFDtHjxYiUnJxsdBxfAbDZrwYIFCgwMlFR+rowlS5a4vL6aznI8efJkLVmyRH5+fnrqqaf0z3/+U7t373ZLfgCA+3htqa047qVVq1Y1Ti8rK6ssrGeWWrPZ/YPXnTt3Vm5urlPL+AU00S0z97otQ/veY5TQbWiN0z58pu8Frz8xIUG20pMXvJ769tzojQoPjVJOTo5iYrxnJL6ufH374Z2vgVGjRtV53ooPLVeuXKmtW7fWebkFCxY4marxueWeSbKGNFVObo5iYmKq3W5s7Hb7OacPGDBAnTt3liTt3LmzcsTWFTUV2opjaOfMmaPp06crKChI06dP1z333FPrehISEurl7wgA8AWRkZHatGmTS8t6baktKiqSJJ08WXPRWrRokfLy8hQaGqrWrVvXa5bc3FxlZ2c7tYx/ULBbMzSLTNCl7fu4dZ1nOpJzRGUlxfW2fnep2OXQZrM5/T3xBr6+/fDO10Bxcd1/9pw6daryf2eW84bnyv7L997+y/f+7NueZty4cZVfT58+XSUlJS6t51yFVpKeeuopjRkzRhdddJGGDRumKVOmVF4O8GwVH5oAABqW15bayMhIHTt2TFu2bFH37t2rTMvJydHUqVMlSSkpKfV+MqjIyEinl/ELaFIPSepPy6iWHjFS6+fnV/l/dHS0wWkanq9vP7zzNRAcXPcPAS0WS+X/ziznDc+V+ZfvvfmX7/3Ztxsbu91ea0mMi4tT//79JZWX0FWrVrn0GOcrtFL5h+NvvPGGHnroIVksFt199936y1/+UuP6oqKiGKkFABe50pkqeG2p7dOnjzIyMpSenq6+ffsqMTFRkrRx40aNHDlSeXnlJ0hKS0ur9yyuDKOXlEnTXT/XRYPbs3evgjzg1bT+JamksPwPD188k6Wvbz+88zXgzDGOO3fu1Ouvv64BAwY4dUztzJkzXYnWqDz9wrs6XlikqMjy7/3ZtxuboqKiWk/02LNnz8qv33jjjfPuqlyTuhTaCq+99poeeughSVKvXr1qLbV79+7lclEAYACv/Thx2rRpat68uQ4fPqzk5GR16NBBCQkJ6tq1q9q0aaPrrrtOUtXjaQEA3i0xMVEbNmyo/KATnqniknyS9J///Mfp5Z0ptJK0a9cu5efnS1LlcbwAgMbDa0ttTEyM1q9fr4EDB8pisejAgQMKDw/X/PnztWLFCu3Zs0cSpRYAfElAQIDCw8MVEBBgdBRcgCuuuKLy682bNzu1rLOF9uzHadmypVq0aOFkYgBAffKAHUZdl5SUpOXLl1e7v7CwUAcOHJDZbFb79u0NSAYAMMKhQ4f0zDPP6JFHHtGll15qdBy46OKLL5Yk5efnV46g1oWrhbZi3goRERH64YcfnAsNAKg3Xl1qa7Nz5045HA4lJibWeKKQxYsXSyrf3ejM23FxcR6321FMu16a+I7jnPOcbzoAeIsTJ05o3bp1Gj9+vNFRcAEeeughhYeHO73cpEmTXCq0kvTmm2/qyy+/1MmTJxvlMcgA4Mt8stTu2LFDUu27Hg8dOrTG23fffbdXXKsQAABPtnLlSpeWe+yxx9SqVSt169bNqUIrSV9++aW+/PJLlx4XAFC/KLU1cDgYuQQAwNvYbDaNGDFCF198sXJzc42OAwBwE689UdS5nK/UAgAA72Sz2Si0AOBlfHKkdu3atUZHAAAYoEWLFpo+fTpnrwUAwIv4ZKkFAPimiIgIjRo1yugYAADAjXxy92MAgG8qKCjQ6tWrVVBQYHQUAADgJpRaAIDPyMrK0uTJk7kkCwAAXoRSCwAAAADwWJRaAAAAAIDHotQCAAAAADwWpRYA4DMsFouSkpJksViMjgIAANyES/oAAHxGfHy8li5danQMAADgRozUAgAAAAA8FqUWAOAzdu3apZSUFO3atcvoKAAAwE0otQAAn+FwOFRaWiqHw2F0FAAA4CYcU9tIBfpJ6bcbnaLuAv2MTgAA8CbBwcEqLCx02/pmz39fx4uK1dQarKljh1W77Q7BwcFuWQ8AwDmU2kbKZJKC+O4AAHyUyWSS1Wp12/oCgywKLLUpMMgiq9Va7TYAwHOx+zEAAAAAwGMxFggA8Bnx8fFatmyZYmNjjY4CAADchFILAPAZFotFCQkJRscAAABuxO7HAACfkZ2drccff1zZ2dlGRwEAAG5CqQUA+Iz8/HwtWbJE+fn5RkcBAABuQqkFAAAAAHgsSi0AAAAAwGNRagEAAAAAHotSCwDwGWazWV26dJHZzK8/AAC8Bb/VAQA+w263a+PGjbLb7UZHAQAAbkKpBQAAAAB4LEotAAAAAMBjUWoBAAAAAB6LUgsA8BlhYWEaNGiQwsLCjI4CAADcxN/oAAAANJSYmBg9++yzRscAAABuxEgtAMBnlJSU6ODBgyopKTE6CgAAcBNKLQDAZ2RmZqpfv37KzMw0OgoAAHATSi0AAAAAwGNxTC0aJYdDspfWz3or/reddu+6zQGSyeTedQIAfJfD4VBxcbHRMeosODhYJn4RAjAApRaNkr1UWje3/tZ/usj96+/9oOQX6N51AgB8V3FxsUJCQoyOUWeFhYWyWq1GxwDgg9j9GAAAAADgsRipBQD4jOTkZGVkZBgdAwAAuBEjtQAAAAAAj0WpBQD4jP3792vYsGHav3+/0VEAAICbUGoBAD6juLhY27dv96gzygIAgHOj1AIAAAAAPBalFgAAAADgsSi1AAAAAACPRakFAPiM6OhopaenKzo62ugoAADATbhOLQDAZzRr1kyDBw82OgYAAHAjSi0AwGccPXpUq1atUv/+/RUeHm50HKDBmEwmJSYmqmXLlgoKCtLp06f1ww8/aPfu3bLZbHVaR/fu3TVw4EA9/vjj9ZwWAJxDqQUA+IycnBzNnDlTaWlplFp4vYsvvlijR49Wv3791LFjRzVt2rTaPMXFxdq2bZvWrFmjV155RdnZ2TWuq3v37vr4448VGhqqJk2aaMqUKfUdHwDqjGNqAQAAvEhCQoLeeecdZWVladasWbr22mtrLLSSFBwcrKuuukozZszQgQMHtGTJEqWmplaZ58xCK0nJyckKCAio9+0AgLryiVKbl5enadOmqW3btrJYLIqNjdXEiRNVVFSk0aNHy2Qyad68eUbHRD3Yvu9z9Z1q0j8+n1PrPH2nmvT46zc2YCoAANzPbDZr0qRJ2r59u4YPH67AwMDKaYcOHdKHH36oZ555RjNmzNDTTz+tDz74QPv27aucx9/fX7feeqs2btyoGTNmKCAgoFqh/fjjj3XzzTertLS0wbcPAGrj9bsfb9u2Tf3791dubq6sVqvatWunI0eOaO7cudq3b5+OHj0qSUpLSzM2KAAAgIvCwsL04Ycfqnfv3pX35eXl6bXXXtPLL7+s77//vtZlW7Zsqfvuu09jxoxRdHS0AgIC9OSTT2rYsGGKiYlRSEiIpP8vtKdOnar37QEAZ3j1SG1eXp4GDRqk3NxcTZkyRTk5OdqyZYtyc3OVnp6uFStWaOPGjTKZTEpJSTE6LgCgnlmtVvXo0UNWq9XoKIDbNGvWTOvWrasstHa7XX/961/VqlUrPfLII+cstJJ05MgR/eEPf1Dr1q311FNPVY7CXn755RRaAB7Bq0vtgw8+qKysLE2YMEFz5syp3HVGkqZNm6bU1FSVlZUpLi6u1mNNAADeIy4uTq+++qri4uKMjgK4RUBAgFasWKGOHTtKkn788Uf16tVLkydPVnFxsVPrKi0t1ZNPPqn7779fdru98v7CwkKNGDGCQgug0fLaUpuRkaFFixYpIiJCs2bNqnGeTp06SVKVEyIsXrxYv/71r9WqVSsFBwfr8ssv12OPPabCwsIGyY36caq0WAVFeTX+A+A7bDabCgsL63wJE6Cxe/zxx3XVVVdJknJzc9WzZ0+tX7/e5fV1795dzz//vMzm//8TMSQkRH/84x8vOCsA1BevPaZ24cKFstvtGj58eOWuM2dr0qSJpKqlds6cObr00kv19NNPKyYmRtu2bdNTTz2lL774Qv/+97+r/JCH53jrkxl665MZRscAYLDdu3dryJAhWrx4sZKTk42OA1yQK664Qo8++qik8lHWG2+8Ud99953L6zv7pFDr169Xx44dFRISogceeEBLlizRp59+6pbsAOBOXltq165dK0lVTphwtqysLElVS+2//vUvXXzxxZW3r732Wl188cUaPny4vvzyS/Xs2dPpLJ07d1Zubq7Ty/myQP8mennCXretb2C3MeqZMrTGadNf6euWx0hITNDpspNuWVd9eW70RoWHRiknJ0cxMV2MjgMDeONrYNSoUXWeNycnR5K0cuVKbd26tc7LLViwwMlUjc8t90ySNaSpcnJzFBMTU+22t/PE7T9zF+Ca/OUvf5G/f/mfcn/605+0efNmlx+rtrMc33PPPXrxxRclSc8//7ySkpJqXUdCQgIf/gNwWWRkpDZt2uTSsl5bag8ePChJatWqVY3Ty8rKtGHDBklVS+2ZhbZC586dJanWC5KfT25ursvL+ipLQLBb1xcdkaArEvu4dZ1nyzlyRKdKnTt+qaFV7HJps9l4Tfoob3wNOHPcYMUxgadOnXJqOW94ruy/fO/tv3zvz77t7bxt+zt06FD5Qfvu3bv19NNPu7yu2grtqVOn9NJLL2nEiBG66qqrdPnll+u6666rHDg4W8WHRgDQ0Ly21BYVFUmSTp6seeRs0aJFysvLU2hoqFq3bn3Oda1bt06Szvnp5LlERka6tJwvC/RvYnQEp0W1bNnoR2r9/Pwq/4+OjjY4DYzgja+B4OC6fwhmsVgq/3dmOW94rsy/fO/Nv3zvz77t7Txx++12e61F8Te/+U3l188//7zL1409V6GVJIfDob/85S+Vx+2OGzeu1lIbFRXFSC0Al11IZ/LaUhsZGaljx45py5Yt6t69e5VpOTk5mjp1qiQpJSVFJpOp1vVkZ2friSeeUL9+/Vy+lq2rw+i+zHZaWjfX6BTO2btnr/wCzz+fkda/JJUUlv/hUbH7PXyLN74Gdu/eXed5d+7cqddff10DBgxw6pjamTNnuhKtUXn6hXd1vLBIUZHl3/uzb3s7T9z+oqKiWs8Lcuutt0oqPzPx22+/7dL6z1doK3z00Uc6cuSIWrZsqUGDBikwMFCnT5+utr69e/dyuSwAhvDaj9P69Cnf1TQ9PV179uypvH/jxo3q3bu38vLKz3p7rqJaWFiom266SYGBgXr99dfrNS8AoP4lJiZqw4YNSkxMNDoK4LKYmBi1aNFCkrRhwwadOHHC6XXUtdBK5YdsffbZZ5KkwMBAtW/f/gLSA4D7eW2pnTZtmpo3b67Dhw8rOTlZHTp0UEJCgrp27ao2bdrouuuuk1T1eNoznTx5UoMGDdL+/fv1ySefKCoqqiHjAwDqQUBAgMLDwxUQEGB0FMBlFZcklOTSyaGcKbQ1Pc6Zjw8AjYHXltqYmBitX79eAwcOlMVi0YEDBxQeHq758+drxYoVlaO3NZXa0tJSDRkyRJs2bdKqVavUrl27ho4PAKgHhw4d0rhx43To0CGjowAua9u2beXXO3bscGpZVwrt2Y9z5uMDQGPgtcfUSuUndlq+fHm1+wsLC3XgwAGZzeZqu9BUXNv2s88+08qVK9W1a9eGiot6kBrfS2tmO845z/mmA/AeJ06c0Lp16zR+/HijowAuO3z4sNasWaMmTZo4dTxwUlKSS4VWKr+Sw4YNG3Ty5Ent27fP5ewAUB+8utTWZufOnXI4HEpMTKx29svx48frH//4hx555BEFBwfr66+/rpwWHx9f4yV/AAAAGsoHH3ygDz74wOnl9uzZo+XLl+uOO+5wqtBK0q5du3T11Vc7/ZgA0BB8stRW7EJT067Hq1atkiQ988wzeuaZZ6pMe+ONNzRq1Kh6zwcAAOBuNptNI0eO1NatW/X888/XudACQGNHqT3LgQMHGjgNAABAw7DZbJo9e7bRMQDArbz2RFHncq5SCwDwXi1atND06dMrL4cCAAA8n0+O1K5du9boCAAAA0RERHAYCQAAXsYnR2oBAL6poKBAq1evVkFBgdFRAACAm1BqAQA+IysrS5MnT3bqMigAAKBxo9QCAAAAADwWpRYAAAAA4LEotQAAAAAAj0WpBQD4DIvFoqSkJFksFqOjAAAAN/HJS/oAAHxTfHy8li5danQMAADgRozUAgAAAAA8FqUWAOAzdu3apZSUFO3atcvoKAAAwE0otQAAn+FwOFRaWiqHw2F0FAAA4CYcU4tGyRwg9X7Q6BTOMQcYnQAA4E2Cg4NVWFjolnXNnv++jhcVq6k1WFPHDqv1vgsRHBx8wesAAFdQatEomUySX6DRKQAAMI7JZJLVanXLugKDLAostSkwyFK5zpruAwBPxO7HAAAAAACPxUgtAMBnxMfHa9myZYqNjTU6CgAAcBNKLQDAZ1gsFiUkJBgdAwAAuBG7HwMAfEZ2drYef/xxZWdnGx0FAAC4CaUWAOAz8vPztWTJEuXn5xsdBQAAuAmlFgAAAADgsSi1AAAAAACPRakFAAAAAHgsSi0AwGdERETo/vvvV0REhNFRAACAm1BqAQA+w2QyKTAwUCaTyegoAADATSi1AACf8dNPP+mFF17QTz/9ZHQUAADgJpRaAAAAAIDHotQCAAAAADwWpRYAAAAA4LEotQAAnxEWFqZBgwYpLCzM6CgAAMBN/I0OAABAQ4mJidGzzz5rdAwAAOBGjNQCAHxGSUmJDh48qJKSEqOjAAAAN6HUAgB8RmZmpvr166fMzEyjowAAADdh92OgEXI4JHtp/ay34n/bafeu2xwgmUzuXScAwHc5HA4VFxcbHcMpwcHBMvHLEGhwlFqgEbKXSuvm1t/6Txe5f/29H5T8At27TgCA7youLlZISIjRMZxSWFgoq9VqdAzA57D7MQAAAADAY1FqAQAAAAAei92PAQA+Izk5WRkZGUbHAAAAbsRILQAAAADAY1FqAQA+Y//+/Ro2bJj2799vdBQAAOAmlFoAgM8oLi7W9u3bPe4yIQAAoHaUWgAAAACAx6LUAgAAAAA8FqUWAAAAAOCxKLUAAJ8RHR2t9PR0RUdHGx0FAAC4CaUWAOAzmjVrpsGDB6tZs2ZGRwHggXr06GF0BAA18Dc6AAAADeXo0aNatWqV+vfvr/DwcKPjAKhngYGB+tWvfqUuXbqoU6dOSkpKktVqlcPh0PHjx7Vjxw5t3rxZX3/9tdavXy+Hw1HrusaNG6cXXnhBzz33nKZMmdKAWwHgfCi1AACfkZOTo5kzZyotLY1SC3ix2NhYjR07Vvfdd59atGhR4zzR0dFKSkrSbbfdJknat2+fXnrpJb3++us6evRolXkrCq0kPfTQQ1qzZo1Wr15dvxsBoM58YvfjvLw8TZs2TW3btpXFYlFsbKwmTpyooqIijR49WiaTSfPmzTM6JgAAAC6An5+fHn30UWVmZuqxxx6rVmhPnDihw4cPKysrSydPnqwyLT4+XrNnz9a+fft09913V95/ZqGVpJkzZ1JogUbG60dqt23bpv79+ys3N1dWq1Xt2rXTkSNHNHfuXO3bt6/yk7i0tDRjgwL1YPu+z/XwS701ZuBsDe31cI3z9J1qUrekgZp57/IGTgcAgPskJCTovffeU+fOnSvvKy0t1dKlS7V06VJt3rxZ+/btq5zm5+enyy+/XJ07d9Ydd9yhG264QVL5sfcLFizQ0KFDtX79ej3zzDOVy8ycOVNPPPFEw20UgDrx6lKbl5enQYMGKTc3V1OmTNGMGTMUGhoqSXr22Wc1ffp0+fv7y2QyKSUlxeC0AAAAcEVaWpo++eQTXXzxxZIkm82mv/71r5ozZ45yc3NrXMZms2nnzp3auXOn3nzzTbVt21YzZszQiBEjJEkDBw7UwIEDK+en0AKNl1fvfvzggw8qKytLEyZM0Jw5cyoLrSRNmzZNqampKisrU1xcnJo2bWpgUgBAQ7BarerRo4esVqvRUQC4SVJSktasWVNZaHfv3q2rrrpKDz/8cK2FtiaZmZkaOXKkBg8erOPHj1eZ9txzz1FogUbMa0ttRkaGFi1apIiICM2aNavGeTp16iRJSk1Nrbxv/fr16tOnj6KiohQUFKSYmBjdfvvtysjIaJDcAID6ExcXp1dffVVxcXFGRwHgBhaLRUuXLlVERIQkacOGDbryyiv17bffurzO2NjYaoMd7dq1u6CcAOqX15bahQsXym63a/jw4QoJCalxniZNmkiqWmqPHTumDh06aO7cufrkk0+Unp6unTt3qnv37srKymqQ7IC7nSotVkFRXo3/AF9is9lUWFgom81mdBQAbvCHP/xBl19+uSRp69at6t+/vwoKClxe39knhTpx4oQkqV+/fho9evSFhQVQb7z2mNq1a9dKknr37l3rPBUl9cxSO3jwYA0ePLjKfF26dNFll12mJUuWaOLEifWQFqhfb30yQ299MsPoGIDhdu/erSFDhmjx4sVKTk42Og6AC9CxY0c99NBDkqSSkhINHz68soS6oqazHG/YsEGrVq2SVL4L8r/+9S/9+OOPFxYcgNt5bak9ePCgJKlVq1Y1Ti8rK9OGDRskVS21NWnevLkkyd/ftaerc+fOTh3TAQT6N9HLE/a6bX0Du41Rz5ShNU6b/kpftzxGQmKCTpedPP+MMNRzozcqPDRKOTk5ionpYnQctxg1alSd583JyZEkrVy5Ulu3bq3zcgsWLHAyVeNzyz2TZA1pqpzcHMXExFS77e3Y/urb29ifA7vdfs7pkydPlp+fnyRpxowZF3SoWE2FtuIY2tdff1333nuvmjZtqvvvv19/+tOfal1PQkKCzGav3RESqFeRkZHatGmTS8t6baktKiqSpGrXIKuwaNEi5eXlKTQ0VK1bt6423WazyW636+DBg/rd736nyMjIyotzOys3N1fZ2dkuLQvfZAkIduv6oiMSdEViH7eu82w5R47oVGlxvT4GLlzFbrc2m81rfi4VF9f9dXfq1KnK/51ZzhueK/sv33v7L9/7s297O7a/+vZ68nMQERFR+XfZzz//rL/+9a8ur+tchVaSnnrqKd19993y8/PT2LFj9cwzz9R6CEPFB2cAGpbXltrIyEgdO3ZMW7ZsUffu3atMy8nJ0dSpUyVJKSkpMplM1Za/9tprK0dy27Ztq7Vr11aeVc+VLIAzAv2bGB3BaVEtWzJS6wEqRjX8/PwUHR1tcBr3CA6u+4dAFoul8n9nlvOG58r8y/fe/Mv3/uzb3o7tr769jf05sNvttZbE4cOHKygoSFL5SGpJSYlLj3G+QitJhw4d0ooVKzR48GDFxsaqb9++Wr16dY3ri4qKYqQWcNGFdCavLbV9+vRRRkaG0tPT1bdvXyUmJkqSNm7cqJEjRyovr/wEOWlpaTUu/9prryk/P1/79+/X7Nmzdf3112vDhg269NJLnc7i6jA6fJfttLRurtEpnLN3z175BRqdAuez/iWppLD8Dy9vOfnd7t276zzvzp079frrr2vAgAFOHVM7c+ZMV6I1Kk+/8K6OFxYpKrL8e3/2bW/H9lff3sb+HBQVFdV6ss8zByzeffddl9Zfl0J75mNUnHPlyiuvrLXU7t27l0uGAQbw2o+Spk2bpubNm+vw4cNKTk5Whw4dlJCQoK5du6pNmza67rrrJNV+PO1ll12mbt26adiwYfrss8904sQJPfvssw25CQAAN0tMTNSGDRsqP+gE4JkqLst48uRJ/e9//3N6eWcKraQqlwiqeGwAjYfXltqYmBitX79eAwcOlMVi0YEDBxQeHq758+drxYoV2rNnj6TznyRKkpo1a6a2bdsqMzOzvmMDAOpRQECAwsPDFRAQYHQUAC4KDg5W27ZtJUnbt293+hJdzhZaSTpw4ICOHj0qqW5/OwJoWF67+7EkJSUlafny5dXuLyws1IEDB2Q2m9W+ffvzrufHH3/Ud999p27dutVHTABAAzl06JCeeeYZPfLIIy4dTgLAeKGhoZVfO3t1CVcKbYUffvhB4eHhatq0qVOPCaD+eXWprc3OnTvlcDiUmJhY7UQhI0aMUNu2bZWWlqZmzZpp7969+stf/iJ/f39NnjzZoMSAa1Lje2nNbMc55znfdMCbnDhxQuvWrdP48eONjgLART/99JNatmwpi8Wi06dPO7Vsjx49Kr92ptBK0sCBA+VwOGq9sgYA4/hkqd2xY4ekmncfufLKK/XWW2/pb3/7m06dOqXY2Fj17t1bjz76aK3XvAUAAEDDONdZkc/nrrvukslk0r59+5wqtJK0f/9+lx4TQP2j1J5lwoQJmjBhQkNHAgAAQD2z2WwaMWKE7Ha70VEAuJHXnijqXM5VagEAAOC9KLSA9/HJkdq1a9caHQEAYIAWLVpo+vTpatGihdFRAACAm/hkqQUA+KaIiAiNGjXK6BgAAMCNfHL3YwCAbyooKNDq1atVUFBgdBQAAOAmlFoAgM/IysrS5MmTlZWVZXQUAADgJpRaAAAAAIDHotQCAAAAADwWpRYAAAAA4LEotQAAn2GxWJSUlCSLxWJ0FAAA4CZc0gcA4DPi4+O1dOlSo2MAAAA3YqQWAAAAAOCxKLUAAJ+xa9cupaSkaNeuXUZHAQAAbkKpBQD4DIfDodLSUjkcDqOjAAAAN+GYWqARMgdIvR80OoVzzAFGJwAAeJPg4GAVFha6bX2z57+v40XFamoN1tSxw6rddofg4GC3rAeAcyi1QCNkMkl+gUanAADAOCaTSVar1W3rCwyyKLDUpsAgi6xWa7XbADwXux8DAAAAADwWI7UAAJ8RHx+vZcuWKTY21ugoAADATSi1AACfYbFYlJCQYHQMAADgRux+DADwGdnZ2Xr88ceVnZ1tdBQAAOAmlFoAgM/Iz8/XkiVLlJ+fb3QUAADgJpRaAAAAAIDHotQCAAAAADwWpRYAAAAA4LEotQAAn2E2m9WlSxeZzfz6AwDAW/BbHQDgM+x2uzZu3Ci73W50FAAA4CaUWgAAAACAx6LUAgAAAAA8FqUWAAAAAOCxKLUAAJ8RFhamQYMGKSwszOgoAADATfyNDgAAQEOJiYnRs88+a3QMAADgRozUAgB8RklJiQ4ePKiSkhKjowAAADeh1AIAfEZmZqb69eunzMxMo6MAAAA3YfdjAGiEHA7JXlo/663433baves2B0gmk3vXCQC+yuFwqLi42OgYTgkODpaJXwQwAKUWABohe6m0bm79rf90kfvX3/tByS/QvesEAF9VXFyskJAQo2M4pbCwUFar1egY8EHsfgwAAAAA8FiUWgAAAACAx2L3YwCAz0hOTlZGRobRMQAAgBsxUgsAAAAA8FiUWgCAz9i/f7+GDRum/fv3Gx0FAAC4CaUWAOAziouLtX37do+7TAYAAKgdpRYAAAAA4LEotQAAAAAAj0WpBQAAAAB4LEotAMBnREdHKz09XdHR0UZHAQAAbsJ1agEAPqNZs2YaPHiw0TEAwCOZzWbZ7XajYwDVUGoBAD7j6NGjWrVqlfr376/w8HCj4wBAgwgJCVHHjh3VsWNHhYeHy9/fXyUlJdq/f782b96s77777rxl1Ww266233tKPP/6ohx56qIGSA3VDqQUA+IycnBzNnDlTaWlplFoAXi04OFh33nmnxo4dqyuuuEJmc+1HHRYWFmrZsmV68cUXtWHDhmrTKwrt8OHDJUmlpaWaPn16vWUHnMUxtQAAAICXCAgI0O9//3sdOXJEr7zyijp37nzOQiuVj+Teeeed+vLLL7Vt2zb16tWrctrZhfb06dP68ssv63MTAKd5fanNy8vTtGnT1LZtW1ksFsXGxmrixIkqKirS6NGjZTKZNG/ePKNjAkC92L7vc/WdatI/Pp9T6zx9p5r0+Os3NmAqAEB96NixozZt2qSnnnpKYWFhlff/97//1fz583X//ffrhhtu0K9+9SsNHjxYv/vd77RkyRLl5eVVzpuamqp169Zp3rx5Cg0NrVZohwwZon/9618Nvm3AuXj17sfbtm1T//79lZubK6vVqnbt2unIkSOaO3eu9u3bp6NHj0qS0tLSjA0KAAAAXIDbb79db7/9tgICAiSV7yL81ltv6cUXX9SWLVtqXKainAYFBWnIkCGaOHGiunTpIkkaP368hg8frmbNmkmi0KJx89qR2ry8PA0aNEi5ubmaMmWKcnJytGXLFuXm5io9PV0rVqzQxo0bZTKZlJKSYnRcAEADsFqt6tGjh6xWq9FRAMBt7rzzTr333nuVhXbbtm3q0qWL7rvvvloL7ZlKSkr07rvvqlu3bvrtb3+roqIiSaLQwmN4bal98MEHlZWVpQkTJmjOnDkKDQ2tnDZt2jSlpqaqrKxMcXFxatq0qYFJAQANJS4uTq+++qri4uKMjgIAbtGzZ0+9+eablcfNvvzyy+ratau2b9/u9LocDodefPFFffbZZ1Xuz8rK0scff+yWvEB98MpSm5GRoUWLFikiIkKzZs2qcZ5OnTpJKj9uoDb9+/eXyWTSk08+WR8xAaDBnCotVkFRXo3/fInNZlNhYaFsNpvRUQDgglmtVr3xxhvy9y8/ovDvf/+7xo4dq9LSUpfWV3FSqIrreTscDklSmzZt9Pvf/949oYF64JXH1C5cuFB2u13Dhw9XSEhIjfM0adJEUu2l9oMPPtC2bdvqKyIANKi3Ppmhtz6ZYXQMw+3evVtDhgzR4sWLlZycbHQcALggs2bNUps2bSRJ69ev14QJE1xeV01nOX744Yf15z//WQEBAZo+fbo+/PBDbd682S3ZAXfyylK7du1aSVLv3r1rnScrK0tSzaX2+PHjmjRpkubMmaMRI0ZccJ7OnTsrNzf3gtcDwHcE+jfRyxP2um19A7uNUc+UoTVOm/5KX7c8RkJigk6XnXTLupwxatSoOs+bk5MjSVq5cqW2bt1a5+UWLFjgZKrG55Z7Jska0lQ5uTmKiYmpdtvbsf3Vt9fXn4PGvv12u/2c02NjYzVu3DhJUnFxse65557zLlObmgptxTG0zZo10x/+8Af5+/vrD3/4gwYOHFjrehISEs57+SCgNpGRkdq0aZNLy3plqT148KAkqVWrVjVOLysrq7ywdE2l9rHHHlNiYqKGDx/ullKbm5ur7OzsC14PAN9hCQh26/qiIxJ0RWIft67zbDlHjuhUaXG9PkZNiovr/pinTp2q/N+Z5bzhZ7j9l12u7TabsrOzq932dmx/9e319efA07d/zJgx8vPzkyTNnj1b+/btc2k95yq0Uvlo8OjRo9WqVSv169dPrVu31v79+2tcV8UHh0BD88pSW3HGtpMnax4xWLRokfLy8hQaGqrWrVtXmbZp0ya98sorbt21IjIy0m3rAuAbAv2bGB3BaVEtWxoyUhscXPcPACwWS+X/ziwXHR3tdK7GxvzLH79mPz9FR0dXu+3t2P7q2+vrz0Fj33673V5rSfT399f9998vqfzSPfPnz3fpMc5XaKXywaCXXnpJs2bNktls1tixY/XII4/UuL6oqChGauGyC+lMXllqIyMjdezYMW3ZskXdu3evMi0nJ0dTp06VJKWkpMhkMlVOs9lsGjt2rCZMmODWY61cHUYH4Ltsp6V1c41O4Zy9e/bKL7DhH3f37t11nnfnzp16/fXXNWDAAKd+zs+cOdOVaI3K0y+8q+OFRYqKjFJWVla1296O7a++vb7+HDT27S8qKqr13DCpqalq0aKFpPJrzboyQlqXQlvh1Vdf1cyZM+Xn56frr7++1lK7d+9eLpkGQ3jlRyl9+pTvYpeenq49e/ZU3r9x40b17t1beXnlZ/tMS0ursty8efP0ww8/cLZjAPBSiYmJ2rBhgxITE42OAgAuq7iKhyR98cUXTi/vTKGVpLy8PO3atUuS1L59ewUFBbmQGqg/Xllqp02bpubNm+vw4cNKTk5Whw4dlJCQoK5du6pNmza67rrrJFU9njYvL09PPPGEfv/736usrEz5+fnKz8+XVH7sVX5+vssH3wMAGoeAgACFh4crICDA6CgA4LIrrrii8mtnD5lzttCe/TgBAQFKSUlxMjFQv7yy1MbExGj9+vUaOHCgLBaLDhw4oPDwcM2fP18rVqyoHL09s9RmZWXpxIkTGjt2rC666KLKf1L5iO9FF12kQ4cOGbI9AAD3OHTokMaNG8fPcwAerWXLlpVfn7lX4vm4WmjPfpyoqCgn0gL1zyuPqZWkpKQkLV++vNr9hYWFOnDggMxms9q3b195f9u2bbVu3bpq8/fu3Vt33323Ro0axQmfAHic1PheWjPbcc55zjfdm5w4cULr1q3T+PHjjY4CAC579913tXnzZjVp0kTHjx+v83JjxoxxqdBK0oYNG/T000/r5MmT+u6771zKDdQXry21tdm5c6ccDocSExOrnPkyJCREvXr1qnGZuLi4WqcBAAAADWnRokUuLffKK6/o2muv1a233upUoZWkf//73/r3v//t0uMC9c3nSu2OHTsk1Xx9WgAAAMBb2Ww2jRgxQldccYU2btxodBzAbSi15+Fw+M5ueQAAAPBuNpuNQguv45UnijoXRmoBwHe1aNFC06dPr7y+IwAA8Hw+N1K7du1aoyMAAAwSERGhUaNGGR0DAAC4kc+N1AIAfFdBQYFWr16tgoICo6MAAAA3odQCAHxGVlaWJk+erKysLKOjAAAAN6HUAgAAAAA8FqUWAAAAAOCxKLUAAAAAAI9FqQUA+AyLxaKkpCRZLBajowAAADfxuUv6AAB8V3x8vJYuXWp0DAAA4EaM1AIAAAAAPBalFgDgM3bt2qWUlBTt2rXL6CgAAMBNKLUAAJ/hcDhUWloqh8NhdBQAAOAmHFMLAI2QOUDq/aDRKZxjDjA6AQB4j+DgYBUWFrptfbPnv6/jRcVqag3W1LHDqt12h+DgYLesB3AWpRYAGiGTSfILNDoFAMAoJpNJVqvVbesLDLIosNSmwCCLrFZrtduAJ2P3YwAAAACAx2KkFgDgM+Lj47Vs2TLFxsYaHQUAALgJpRYA4DMsFosSEhKMjgEAANyI3Y8BAD4jOztbjz/+uLKzs42OAgAA3IRSCwDwGfn5+VqyZIny8/ONjgIAANyEUgsAAAAA8FiUWgAAAACAx6LUAgAAAAA8FqUWAOAzzGazunTpIrOZX38AAHgLfqsDAHyG3W7Xxo0bZbfbjY4CAADchFILAAAAAPBYlFoAAAAAgMei1AIAAAAAPBalFgDgM8LCwjRo0CCFhYUZHQUAALiJv9EBAABoKDExMXr22WeNjgEAANyIkVoAgM8oKSnRwYMHVVJSYnQUAADgJpRaAIDPyMzMVL9+/ZSZmWl0FAAA4CaUWgAAAACAx+KY2kbK4ZBO24xOUXeBfpLJZHQKAAAAeAuHw6Hi4mKjYzglODhYJv4obnCU2kbqtE2avsjoFHWXfrsUxKsJAAAAblJcXKyQkBCjYzilsLBQVqvV6Bg+h92PAQAAAAAei7E1AIDPSE5OVkZGhtExAACAGzFSCwAAAADwWJRaAIDP2L9/v4YNG6b9+/cbHQUAALgJpRYA4DOKi4u1fft2jzubJgAAqB2lFgAAAADgsSi1AAAAAACPRakFAAAAAHgsSi0AwGdER0crPT1d0dHRRkcBAABuwnVqAQA+o1mzZho8eLDRMQAAgBsxUgsA8BlHjx7Vu+++q6NHjxodBQDQwPz9/RUTE6P4+Hi1atVKoaGhTi3fvHlzTZ48uZ7S4UIwUgsA8Bk5OTmaOXOm0tLSFB4ebnQcAEA9MplM6tOnj26++WZ16tRJKSkpatKkSZV5MjMztXnzZn3xxRd69913dfz48RrX1bx5c3322WdKTU1VTEyMpkyZ0hCbgDpipBYAAACA17BYLJo8ebK+++47ffLJJxo3bpy6detWrdBKUtu2bXX77bfrxRdf1JEjR/TSSy8pISGhyjxnFlpJuv3223XJJZc0yLagbnyi1Obl5WnatGlq27atLBaLYmNjNXHiRBUVFWn06NEymUyaN2+e0THrRdauz/W3ESZtXjGn1nn+NsKkf865sQFTAQAAAO7XrVs3bd26Vc8991y1crpnzx59+OGHeuedd/T+++/rq6++0smTJyunW61WjR07Vv/97381ZcoUmc3maoU2OztbvXv31o8//tig24Vz8/rdj7dt26b+/fsrNzdXVqtV7dq105EjRzR37lzt27ev8riqtLQ0Y4MCAAAAcNmTTz6pxx9/XH5+fpX3ffrpp/r73/+uTz/9tMZdi/38/JSamqp77rlHd911l5o2bSqLxaI5c+botttuk9VqVXJysqT/L7R79+5tsG1C3Xj1SG1eXp4GDRqk3NxcTZkyRTk5OdqyZYtyc3OVnp6uFStWaOPGjTKZTEpJSTE6LgCgnlmtVvXo0UNWq9XoKAAAN3rxxRc1Y8aMykL77bffKiUlRX379tXSpUtrPVbWZrNpy5Yt+u1vf6vo6Gj9+c9/lt1ulyR17dqVQushvLrUPvjgg8rKytKECRM0Z86cKmc4mzZtmlJTU1VWVqa4uDg1bdrUwKQAgIYQFxenV199VXFxcUZHAQC4yTPPPKPf/OY3kiS73a5HH31UV111lXbs2OHUegoLC/Xwww9r0KBBOn36dOX9paWluvnmmym0jZjXltqMjAwtWrRIERERmjVrVo3zdOrUSZIq95GXpM8//1wmk6naP0/fPbnsdLFOnsir8R8A+AqbzabCwkLZbDajowAA3OD666/X9OnTJZUX2pEjR2rWrFku/5xv3ry5nn76aQUGBlbeFxAQoEmTJrkjLuqJ1x5Tu3DhQtntdg0fPlwhISE1zlNxBrQzS22FF154QVdccUXlbU/fVe3rJTP09ZIZRscAAEPt3r1bQ4YM0eLFiyt3KQMAeKamTZvq1Vdfrbw9adIkvffeey6v7+yTQuXm5qpJkyYKCwvT8OHD9Y9//EP//Oc/Lzg33M9rS+3atWslSb179651nqysLEk1l9p27drpyiuvrJ9wBmjfe4wSug2tcdqHz/Rt4DQAAADAhXniiScUGxsrSVqzZo2ef/55l9dV21mOu3XrprfffltS+XG7K1euVGlp6YWHh1t5bak9ePCgJKlVq1Y1Ti8rK9OGDRsk1Vxq3alz587Kzc11ahm/gCa6Zab79ttvFpmgS9v3cdv6zpaYkCBb6cnzzwgAbjZq1Kg6z5uTkyNJWrlypbZu3Vrn5RYsWOBkqsbnlnsmyRrSVDm5OYqJial229ux/dW319efA7a/8W9/xQmbahIcHKz77rtPknTy5MnKr11RW6Hdu3ev9u7dqzvuuEMDBgxQy5Ytdeutt2rRokW1rishIUFms9ce4VmvIiMjtWnTJpeW9dpSW1RUJElVrj11pkWLFikvL0+hoaFq3bp1tem333678vLy1Lx5cw0ePFjPPPOMIiIiXMqSm5ur7Oxsp5bxDwp26bGMciTniMpKio2OAcAHFRfX/WfPqVOnKv93Zjlnf4Y3RvZfji+z22zKzs6udtvbsf3Vt9fXnwO237O3/4477lCzZs0klR92eOjQIZfWc65CWyE9PV0DBgyQJI0fP/6cpbbiw1M0LK8ttZGRkTp27Ji2bNmi7t27V5mWk5OjqVOnSpJSUlJkMpkqp4WFhWnq1Knq2bOnQkJC9NVXX2nWrFn6+uuvtWnTJlksFpeyOMsvoInTyxipZVRLRmoBGCI4uO4fAlb8DLdYLE4tFx0d7XSuxsb8y2UuzH5+io6Ornbb27H91bfX158Dtr/xb7/dbq+1JN5xxx2VX7/44osurb8uhVaS/v3vf2vnzp1KTk7WNddco5iYmMrDGM8WFRXFSK2LXOlMFby21Pbp00cZGRlKT09X3759lZiYKEnauHGjRo4cqby88rP+nn1W444dO6pjx46Vt3v16qX27dtr8ODBWrhwoe655x6ns7gyjF5SJk2v/UOgRmfP3r0K8tpXE4DGbPfu3XWet7S0VKNHj1ZoaKgCAgLqvNzMmTNdidaoPP3CuzpeWKSoyChlZWVVu+3t2P7q2+vrzwHb3/i3v6ioqMYTvppMJnXu3FlSeRHdvHmz0+uua6Gt8M9//rPyBIOdOnWq9Tnbu3evx59g1hN57ccI06ZNU/PmzXX48GElJyerQ4cOSkhIUNeuXdWmTRtdd911kup2PO2NN94oq9Xq8j7eAIDGISAgQOHh4U4VWgBA4xIfH6+wsDBJrg0eOVtoz36cisuCovHw2lIbExOj9evXa+DAgbJYLDpw4IDCw8M1f/58rVixQnv27JHk3EmiztxNGQDgeQ4dOqRx48a5fOwVAMB4l19+eeXX27dvd2pZVwqtJG3btq3y66SkJKceE/XPq3cYTUpK0vLly6vdX1hYqAMHDshsNqt9+/bnXc+yZctUVFSkrl271kfMehXTrpcmvuM45zznmw4A3uLEiRNat26dxo8fb3QUAICLysrK9P3336tJkyZOXWGkWbNmLhVaSTp27Jh+/PFHnTx5UseOHXM5O+qHV5fa2uzcuVMOh0OJiYnVThQyYsQItWnTRldccUXliaKeffZZpaWladiwYQYlBgAAACBJq1evVnx8vNPLnThxQrt27VJqaqpThVaS8vPz1aJFC6cfEw3DJ0vtjh07JNW863FycrLee+89/fWvf9XJkycVExOj+++/XzNmzFBgYGBDRwUAAADgBjabTSNHjtSPP/6oF154oc6FFo0fpfYsv/vd7/S73/2uoSMBAAAAqGc2m02TJk0yOgbczGtPFHUu5yq1AADv1aJFC02fPp1dyAAA8CI+OVK7du1aoyMAAAwQERGhUaNGGR0DAAC4kU+O1AIAfFNBQYFWr16tgoICo6MAAAA3odQCAHxGVlaWJk+erKysLKOjAAAAN6HUAgAAAAA8FqUWAAAAAOCxKLUAAAAAAI9FqQUA+AyLxaKkpCRZLBajowAAADfxyUv6AAB8U3x8vJYuXWp0DAAA4EaM1AIAAAAAPBalFgDgM3bt2qWUlBTt2rXL6CgAAMBNKLUAAJ/hcDhUWloqh8NhdBQAAOAmlFoAAAAAgMfiRFGNVKCflH670SnqLtDP6AQAAADwJsHBwSosLHTb+mbPf1/Hi4rV1BqsqWOHVbvtDsHBwW5ZD5xDqW2kTCYpiO8OAAAAfJTJZJLVanXb+gKDLAostSkwyCKr1VrtNjwXtQkA4DPi4+O1bNkyxcbGGh0FAAC4CaUWAOAzLBaLEhISjI4BAADciBNFAQB8RnZ2th5//HFlZ2cbHQUAALgJpRYA4DPy8/O1ZMkS5efnGx0FAAC4CaUWAAAAAOCxKLUAAAAAAI9FqQUAAAAAeCxKLQDAZ0REROj+++9XRESE0VEAAICbUGoBAD7DZDIpMDBQJpPJ6CgAAMBNKLUAAJ/x008/6YUXXtBPP/1kdBQAAOAmlFoAAAAAgMei1AIAAAAAPBalFgAAAADgsSi1AACfERYWpkGDBiksLMzoKAAAwE38jQ4AAEBDiYmJ0bPPPmt0DAAA4EaM1AIAfEZJSYkOHjyokpISo6MAAAA3odQCAHxGZmam+vXrp8zMTKOjAAAAN2H340bK4ZBO24xOUXeBfpLJZHQKAAAAwDs4HA4VFxcbHcMpwcHBMhlQCii1jdRpmzR9kdEp6i79dimIVxMAAADgFsXFxQoJCTE6hlMKCwtltVob/HHZ/RgAAAAA4LEotQAAAAAAj8UOowAAn5GcnKyMjAyjYwAAADdipBYAAAAA4LEotQAAn7F//34NGzZM+/fvNzoKAABwE0otAMBnFBcXa/v27R53iQQAAFA7Si0AAAAAwGNRagEAAAAAHotSCwAAAADwWJRaAIDPiI6OVnp6uqKjo42OAgAA3IRSCwDwGc2aNdPgwYPVrFkzo6MAAOBxYmNjjY5QI3+jAwAA0FCOHj2qVatWqX///goPDzc6DgAA9S4mJkbdunVTp06d1KFDB4WGhspkMqmoqEgZGRnatGmTNm7cqMzMzHOu54orrtCnn36qBQsW6KGHHmqg9HVDqQUA+IycnBzNnDlTaWlplFoAgNfy8/PT4MGDNW7cOPXp06fW+fr371/59bfffqsXX3xRixYt0qlTp6rMV1FoL7roIk2ePFmZmZl68cUX6y2/s7x+9+O8vDxNmzZNbdu2lcViUWxsrCZOnKiioiKNHj1aJpNJ8+bNMzomAAAAAFywnj17avfu3Vq6dOk5C+3ZunbtqgULFujgwYMaMmRI5f1nFlpJ+uKLL/Tmm2+6PfeF8OpSu23bNnXo0EGzZ89Wbm6u2rVrp9LSUs2dO1e33367MjIyJElpaWnGBq1HWbs+199GmLR5xZxa5/nbCJP+OefGBkwFAAAAwJ2aNGmiuXPn6osvvlDbtm0r79+7d6/++Mc/6qabblJsbKwsFouCgoIUGRmpfv366bHHHtOWLVsq57/kkkv0j3/8Q++//7569+5drdAOHDhQRUVFDb595+K1ux/n5eVp0KBBys3N1ZQpUzRjxgyFhoZKkp599llNnz5d/v7+MplMSklJMTgtAAAAALimadOmWr58ua655prK+7788kv94Q9/0KeffiqHw1FtmR9++EEff/yxPv74Yz399NPq1q2bHn30UQ0ePFiSdPvtt2vIkCHy8/OT1HgLreTFI7UPPvigsrKyNGHCBM2ZM6ey0ErStGnTlJqaqrKyMsXFxalp06YGJgUANBSr1aoePXrIarUaHQUAALcIDg7WypUrKwttcXGxJk6cqJ49e2rNmjU1FtqafPPNN7rpppt0xx13KD8/X5IqC+1//vOfRltoJS8ttRkZGVq0aJEiIiI0a9asGufp1KmTJCk1NbXatA8//FBXXXWVrFarwsLC1KNHD+3cubNeMwMA6l9cXJxeffVVxcXFGR0FAAC3mD9/vnr06CFJ+umnn3TNNddo7ty5dS6zZ9uzZ49MJlOV+xwOh06ePHnBWeuLV5bahQsXym63a/jw4QoJCalxniZNmkiqXmrnzp2r2267TVdffbWWLVumhQsXqk+fPo36m1gXZaeLdfJEXo3/AMBX2Gw2FRYWymazGR0FAIALNnjwYI0YMUKSVFBQoL59+1Y5PtZZFSeFCgsLk6TKsyD36NFDv/3tby88cD3xymNq165dK0nq3bt3rfNkZWVJqlpq9+3bp6lTp+ovf/mLJkyYUHn/gAED6ilpw/l6yQx9vWSG0TEAwFC7d+/WkCFDtHjxYiUnJxsdBwAAlzVt2lTz58+vvP3b3/5W27dvd3l9NZ3leNasWVq9erUk6emnn9ayZcu0f//+CwteD7yy1B48eFCS1KpVqxqnl5WVacOGDZKqltrXX39dAQEBuv/++92ap3PnzsrNzXVqGb+AJrpl5l63ZWjfe4wSug2tcdqHz/S94PUnJiTIVurZo9kAPNOoUaPqPG9OTo4kaeXKldq6dWudl1uwYIGTqRqfW+6ZJGtIU+Xk5igmJqbabW/H9lffXl9/Dth+39p+yfOeA7vdfs7p99xzjyIjIyVJy5cv19tvv+3yY9VUaCuOoZ07d64efPBBBQcHa+LEiZo0aVKt60lISJDZ7NrOwJGRkdq0aZNLy3plqa04gLm2XYYXLVqkvLw8hYaGqnXr1pX3/+c//9Fll12md955RzNnztThw4eVkJCg3//+97rjjjtczpObm6vs7GynlvEPCnb58WrSLDJBl7av+3WqnHUk54jKSorrbf0AUJvi4rr/7KnYjerUqVNOLefsz/DGyP7LLtd2m03Z2dnVbns7tr/69vr6c8D2+9b2S971HJhMJo0bN67y9tSpU11e17kKrSTNmDFD9913n4KDgzVq1Cg9+uijtf4OrfjwuKF5ZamNjIzUsWPHtGXLFnXv3r3KtJycnMpvekpKSpWDoHNycpSdna3f/e53Sk9PV2xsrF577TXdeeeduvjii526ePHZeZzlF9DEpccySsuolozUAjBEcHDdPwS0WCyV/zuzXHR0tNO5GhvzL2ewNPv5KTo6utptb8f2V99eX38O2H7f2n7J854Du91ea0ns2bOnEhMTJZUferl7926XHuN8hVaS8vPztXDhQo0ePVphYWG67bbbat2DKSoq6oJGal3llaW2T58+ysjIUHp6uvr27Vv5Dd+4caNGjhypvLzykyOlpaVVWc5ut6uwsFBvv/22br75ZknSr371K+3atUt//OMfXS61rgyjl5RJ0xe59HCG2LN3r4K88tUEoLFz5hf5zp079frrr2vAgAFOHVM7c+ZMV6I1Kk+/8K6OFxYpKjJKWVlZ1W57O7a/+vb6+nPA9vvW9kue9xwUFRXVetLbM69H6+ohMnUptGc+xujRoysfu7bH3Lt3ryGXzfPKsx9PmzZNzZs31+HDh5WcnKwOHTooISFBXbt2VZs2bXTddddJqn7m4/DwcEmqUl5NJpP69Omj//3vfw23AQCAepGYmKgNGzZUftgJAIAnqrg8qSR9/fXXTi/vTKGVygfpysrKqj12Y+GVpTYmJkbr16/XwIEDZbFYdODAAYWHh2v+/PlasWKF9uzZI6l6qT3Xp/YVx2EBADxXQECAwsPDFRAQYHQUAABcVrHHaUFBgTIzM51a1tlCK5V3oZ07d0oq70yBgYGuBa8nXllqJSkpKUnLly/XiRMndOLECX3zzTcaM2aMioqKdODAAZnNZrVv377KMjfddJMk6ZNPPqm8z263a82aNerSpUuD5gcAuN+hQ4c0btw4HTp0yOgoAAC4rHnz5pLKL1PqcDjqvJwrhbbC4cOHJUn+/v4KDQ11IXX98bmjIHfu3CmHw6HExMRqJwkZNGiQrrnmGo0ZM0Y///yzLr30Ur366qvauXOn1qxZY1DiCxPTrpcmvnPuF/r5pgOAtzhx4oTWrVun8ePHGx0FAACX9evXT8HBwTp9+rRTy40ZM8alQitJTz31lObOnatTp07p+PHjTmeuTz5Xanfs2CGp+q7HUvnxs8uWLdP06dP16KOP6vjx40pNTdXKlSsrj8MFAAAAACP95z//cWm58ePHKywsTFFRUU4VWsm1k982FErtWZo1a6b58+dr/vz5DRkLAAAAAOqVzWbTiBEjFBQU5NT12hs7rz2mtjbnK7UAAAAA4K1sNptXFVrJB0dq165da3QEAIBBWrRooenTp6tFixZGRwEAAG7ic6UWAOC7IiIiNGrUKKNjAAAAN/K53Y8BAL6roKBAq1evVkFBgdFRAACAm1BqAQA+IysrS5MnT1ZWVpbRUQAAgJtQagEAAAAAHotSCwAAAADwWJRaAAAAAIDHotQCAHyGxWJRUlKSLBaL0VEAAICbcEkfAIDPiI+P19KlS42OAQAA3IiRWgAAAACAx6LUAgB8xq5du5SSkqJdu3YZHQUAALgJpRYA4DMcDodKS0vlcDiMjgIAANyEY2obqUA/Kf12o1PUXaCf0QkAAAAA7xEcHKzCwkK3rW/2/Pd1vKhYTa3Bmjp2WLXb7hAcHOyW9TiLUttImUxSEN8dAAAAwCeZTCZZrVa3rS8wyKLAUpsCgyyyWq3Vbnsydj8GAAAAAHgsxgIBAD4jPj5ey5YtU2xsrNFRAACAm1BqAQA+w2KxKCEhwegYAADAjdj9GADgM7Kzs/X4448rOzvb6CgAAMBNKLUAAJ+Rn5+vJUuWKD8/3+goAADATSi1AAAAAACPRakFAAAAAHgsSi0AAAAAwGNx9mMAgEe7/PLL6zxvWFiYZsyYoauuukpRUVH1mAoAADQUSi0AwGdERUXpySefNDoGAABwI3Y/BgAAAAB4LEotAAAAAMBjUWoBAAAAAB6LUgsAAAAA8FiUWgAAAACAx6LUAgAAAAA8FqUWAAAAAOCxKLUAAAAAAI9FqQUAAAAAeCxKLQAAAADAY1FqAQAAAAAei1ILAAAAAPBYlNpGIC4uTiaTqdq/5ORko6MBAFCrlStXKi0tTUFBQYqLi9Nzzz1ndKQG9e9//1s33XSTWrVqJZPJpJkzZxodqUHNnj1b3bt310UXXaRmzZrp6quv1urVq42O1WDefvttderUSRdddJGaNGmipKQkPffcc3I4HEZHM8TatWvl5+entm3bGh2lwTz55JM1/g2fmZlpdLQGk5eXp9/85jdq2bKlgoKC1Lp1a73yyisNnsO/wR8R1WzcuFE2m63ydmFhoVJSUjRs2DADUwEAULtNmzbppptu0sMPP6yFCxfqm2++0QMPPKDg4GA98MADRsdrEIWFhWrXrp3uvPNOTZo0yeg4DW7t2rW699571aVLFwUHB+vVV1/VjTfeqC+++EI9evQwOl69u+SSS/TEE0/osssuU1BQkNavX69x48bJz89PEydONDpeg8rNzdXdd9+t66+/Xnv37jU6ToOKi4vTV199VeW+iy++2KA0DauwsFA9e/ZUdHS0Fi5cqFatWiknJ6dKr2kolNpG4OwX/iuvvKLS0lLdd999BiUCAODcnnvuOXXp0kWzZs2SJCUlJWnnzp165plnfKbUDhgwQAMGDJAkTZ8+3eA0DW/VqlVVbj/77LNavXq1li5d6hOl9oYbbqhyu02bNvroo4/0+eef+1SptdvtGjFihMaPH69Tp075XKn18/NTZGSk0TEMMXv2bBUXF2v58uUKCgqSVF7yjUCpbYTmz5+vQYMGKSoqyugoAAAP8/Ox4/o5/3i1+8t++eS8zGbTnv1Z1W6fKf7SlvLzO/cRShs2bNDo0aOr3NevXz/NmTNHWVlZiomJuZDNcFlpWZn2H86tdr8z239xeJguCgut/7D1JCvnJxWfKqlyX03bW9tzEBTgr1Yxzv+Rbrfbdfz4cVmtVleju8XxwmLl/nS02v3OvAYubXmJLEGBdX5Mh8OhjRs3asOGDXr88ccvIP2FczgcyjyYrbP3gnZm+5uFWnVJxEV1erw//vGPMplMmj59up566qkL3wA3+CHvmApOFFW7v67PgdlkUnyrljKZTOd9rDN/3nXo0EFPPPGErrrqKndshstOlZzWoSM/VrvfmddA1MXhCg0JPufjLFmyRFdffbUmT56sDz/8UGFhYRo0aJCeeuopBQefe1l3Mzl8dcf/RmrTpk3q0qWLVq9eXe0TQAAAzif/eKH++vpinSo57dLynTokauiAXuedLzAwUPPmzdOYMWMq79u5c6fat2+vb7/9Vl26dHHp8S+Uw+HQux99qv/t2e/S8tZgiybfO1Qh1iZOLRcXF6f77rvP8EIjSbv3HdKCxa4f2zqk/7XqnHKZ08vNnDlTc+bM0f/+9z/DPtSQpJKS0/rbgiU6mn/CpeVbx0bp/mEDZTaf/9QzBQUFio6O1unTp2W32zVjxgw98cQTLj2uO636/Bt98c12l5b19/PThLtvUeTF4eedd926dbrzzju1detWRUZG6sknn9Q777xj+DGlOT/+rHlvfSibze7S8r27p+mGnl3PO9/KlStVUFCgdu3a6fjx45o/f74WLlyo1atXq2/fvi49tjvY7Xa9vHC5DmRV/4CvLppf1FQPjvq1ggIDzjlfkyZN5HA4NGTIEE2aNElHjhzRhAkTdM011+jdd9916bFdxYmiGpn58+erdevWuv76642OAgDwQM2ahuimvq7t+nlRWKgG/crYEYYLZTKZdMsN1zhdSiv8ul9Pl5dtLC6Pv1RdUy93adl2CXHq1CHR6eVefPFFPf3001q8eLGhhVaSgoICddvA3nUaZau2bGCAbhvYq06FVpJCQ0O1bds2bdq0SfPmzdNzzz2n1157zenHdbe+V3dW1CXNXVr2hp5d6lRo8/LyNGLECL3xxhuNbvfbqEua6/prXPtgrWWL5vpVj051mnfAgAG64447lJqaqmuuuUbvvPOOrrnmGs2ePdulx3YXs9ms2wb2UuB5SmlNTCaTbh/Y+7yFViovz+Hh4XrjjTfUuXNnDR48WM8995zee+89HT1afW+J+kSpbUSOHz+uhQsXasyYMS79IAYAQJLS2rVVh8vaOLWMSdJtA3vVeZfLqKgo5eZWHQX44YcfKqcZyRps0ZD+1zq9XOeUy9QuIc79gQww8Lruat6sqVPLhAQ30a39rnH6b5A5c+Zo6tSpWrZsmfr06ePUsvUlLiZS13ZLdXq5wX16OLXrudlsVtu2bZWSkqIHHnhA06ZN02OPPeb047qbv7+fbr+x93kPIzhbm0tbqkeXDnWa93//+5+OHDmiG2+8Uf7+/vL399cf/vAH7du3T/7+/nrvvfdcie4213TpoNaxzv0s8vfz0+03Xid/Pz+XH7d79+46cOCAy8u7S3izphr0q+5OL9f7yjRdGt2iTvNGRUUpMTFRAQH/X4Arrt5y8OBBpx/7QlBqG5F33nlHp0+f1j333GN0FACABzOZTLr5hqvPezzUmXp2S3XqD8AePXro448/rnLf6tWr1apVK8NH6qTy0cpuaUl1nj88LFSDrnP+D8DGKigwQLfd6Nxo5a39eyok2LlR6t///vd66qmntHLlykZTaCv0ubqTU6OVyYlxuqJ9wgU9pt1u16lTpy5oHe4SeXF4nXahrVA5Sl3H10yXLl20Y8cObdu2rfLfAw88oNjYWG3btk0DBw50NbpbmM1mDR3Yq04jjhX6XdtVLep4LHFttmzZotjY2Atah7t07nCZ2iW0qvP80S0i6jxKLUnXXHONMjMzVVZWVnnfd999J6nhTxhFqW1E5s+fr5tvvlktWtTt0xEAAGpjbVL30crIi8PV9+rOTq1/8uTJ+vbbb/XYY49p9+7devPNN/X888/rkUcecSVuvRjQ+0o1v+j8o5UmSbfd2FtBTpwYSCq/nEXFH/OnT59Wbm6utm3bZvjxhBVaRbdQryvT6jRvl5TL1a5t3f/4laRJkyZp9uzZevvtt3XZZZcpNzdXubm5KigocCGt+5WPuvWu06hbiLWJbrnBuVHqGTNm6NNPP9X333+v7777Tq+88orS09N19913X0hst7raidHKm/r2ULOmIXVet9VqVfv27av8u+SSSxQYGKj27dsrLCzM1dhuEx4WqkF96nZIRXyrlrqqc3un1v/QQw9p7dq1+v7777Vt2zaNHz9ea9asaTSX+DKZTLr1hrp9WOXv76fbnBzdf/jhh/XTTz9p3Lhx2r17t9atW6eHH35Yd911ly666MI+HHAWpbaR+Prrr/Xf//5XY8eONToKAMBLXNYmVld2bHfOefz8zOV/+Ps7t7tdly5d9NFHH2n58uVKTU3V73//e/3pT39qVJfzCQoM0O11OLayZ7dUxblwtt9NmzapY8eO6tixo3JycvTCCy+oY8eOjeqSfL/qcYVatjj3aGV4s1DdeN2VTq/7b3/7m06dOqVbbrlFUVFRlf8a0+Vsykcrz39s5ZD+1zo9Sn38+HE98MADSk5O1pVXXqmXXnpJs2bN0nPPPedqXLczm0y6rQ6jle0TW6tj8oWNUjdWndonnvewAktQoIYOqPsodYWcnBzdddddSkpK0vXXX6/vvvtOn376qQYNGnQBid0rxFp+WMH5uDJKnZqaqpUrV2rr1q1KS0vTPffco1tuuUV///vfXY3rMs5+7GEO5/yo5heFKdgSZHQUAIAHOH26VHMXLFXesZpHz/r36ubSsYee5JN/b9Tar7bWOC3qkuYaP/Jmp0u9J/kh75ieX7C08vIdZzKZTBp75yCXSr2nsDscevX9Ffr+0JEap3dNvVy39uvZwKka1uYde/SPlZ/XOC3U2kST7h0qa7ClYUM1oMLik/rra4tVWHyyxum339jba0t9hcWrvtCm/35X47S2raJ17+0DnC71jQkjtR6kzGbTOx+uUfrf39Oh7B+MjgMA8ACBvxxbWdMfK61jo3RNHU8K48l+1aOToltEVLvf1VFqT9Mi4iL1u7bmYyuvdXGU2pOca7SyebOmGuhFx1LX5or2CUpOjKtx2pD+13p1oZXKT4L26/41f3DR4bI2SmvXtoETNbxB13VXeA0nQbMEBWrIgGs9utBKlFqPsnnHdyo4UaTAwACXT9MOAPA9l7a8RL27d6xyX1BggIY6cekST+bnZ9ZtNZTXG3p2rdOlS7zBVZ3bK75Vyyr3RV3SXH2urvtJYTxZTZe6MtVx11xvUHls5VmXq+qWlqTL4i81KFXDSmrbqtqlrkJDgnXzDVf7xFVHgoICy08ed9b9N19/tVPHUjdW3v+bzEk2m01vv/22rr/+el188cUKCgrSpZdeqn79+unVV1+VrYZddxpCmc2mtf8p33WqV7c0BQT4G5IDAOCZrrvqCsVEXlx5e1Cfq2r81N5bnT1a2To2Slf7wCh1BbPJpKED/v+STc6cRMlbdExOUPvE1pW3e12ZqlZePkp9prMvddX8oqYa2Nv5Y6k92cDruiu82f//3BvS/1pZm3j3KPWZ4mIide0ZJ49LubyNUpPijQvkRpTaMxw/flx9+/bVXXfdpTVr1igwMFCpqamy2+365JNPdP/99+vEiROGZKsYpQ0NCXb5guoAAN915mhlu4Q4dWqfaHSkBndVp/Zq2yra6UuXeIszRytv6NnFZ0apK5hMJt1ywzUKtTZRyxbNnbp0ibe4PP5SdU29XCaTSbcP7K1AHxilPlP5e7/85HFXdmyny9o0jkvvNKSKS12FhgTr5uu9Z5SaE0WdYejQoVq8eLFiYmL01ltvqXfv3pXTfvjhB7322muaOHGirFarU+t9/s2lOlFY84HpdePQiaKTcjgcsgQFKjDAt34AAQDc53Rpmfz9/Xyu0FWw2+2y2e0K8PfNPZ4cDodOl5YpMMDfa/6YdVZZWZlMZrP8fGDX+5o4HA6VlpX59N+Tp0tLFeDvu+8Bm80uh8PR6M4nEBrSRL+9+1aXlqXU/mLz5s3q3Lmz/P39tXXrVrVv79x1qs7l6Rfe1fHCIretDwAAAAC8SdMQqx4dP9ylZX3zY8oafPTRR5KkgQMHurXQSuWfOriOUVoAAAAA3u1COhOl9he7du2SJHXv7v7Turs6jC5J32zL0Icfr1doSLCmjRnGCaIAAAAA4Aw0pF8cP35ckhQWFub2dbt+TG35KK0klZaWafbLi9wbDAAAAAAagQs5ppZS+4umTZtKkgoKCty+7hOFJy/4mNpTJad1quS0mxIBAAAAgHeg1P4iOTlZS5cu1VdffeX2dbu2fzjH0gIAAADwDRdyTC1nP/7F1q1bdcUVVyggIEDbtm1Tu3btDM3DsbQAAAAAcH6+eYGuGnTs2FG33XabSktL1b9/f33xxRdVpv/www+aNWuWiorq/9I8ZTab1n21VZLUq1sahRYAAAAAasFI7RmOHz+um266SZ9//rkkKTo6Wi1btlROTo6ys7PlcDh07NgxNWvWrF5zMEoLAAAAAHXDSO0ZmjZtqk8//VSvvfaaevXqpeLiYm3fvl1ms1k33HCDXnvtNYWGhtZ7jsAAfzUNsTJKCwAAAADnwUhtI1VaViaTTPL39zM6CgAAAAA0WpRaAAAAAIDHYvdjAAAAAIDHotQCAAAAADwWpRYAAAAA4LEotQAAAAAAj0WpBQAAAAB4LEotAAAAAMBjUWoBAAAAAB6LUgsAAAAA8FiUWgAAAACAx6LUAgAAAAA8FqUWAAAAAOCxKLUAAAAAAI9FqQUAAAAAeCxKLQAAAADAY1FqAQAAAAAei1ILAAAAAPBYlFoAAAAAgMei1AIAAAAAPBalFgAAAADgsSi1AAAAAACPRakFAAAAAHgsSi0AAAAAwGNRagEAAAAAHotSCwAAAADwWJRaAAAAAIDHotQCAAAAADwWpRYAAAAA4LEotQAAAAAAj0WpBQAAAAB4LEotAAAAAMBjUWoBAAAAAB6LUgsAAAAA8FiUWgAAAACAx6LUAgAAAAA8FqUWAAAAAOCxKLUAAAAAAI9FqQUAAAAAeCxKLQAAAADAY1FqAQAAAAAe6/8AsYCgxSn37+oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1207.22x702.333 with 1 Axes>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Quantum Circuit\n",
    "meas = QuantumCircuit(qubits, qubits)\n",
    "meas.barrier(range(qubits))\n",
    "# map the quantum measurement to the classical bits\n",
    "meas.measure(range(qubits), range(qubits))\n",
    "\n",
    "# The Qiskit circuit object supports composition.\n",
    "# Here the meas has to be first and front=True (putting it before) \n",
    "# as compose must put a smaller circuit into a larger one.\n",
    "qc = meas.compose(circ, range(qubits), front=True)\n",
    "\n",
    "#drawing the circuit\n",
    "qc.draw('mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "4882d030-06d3-4d1c-9331-b43d8c6cd186",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0100000', '0001000', '1001100', '1000110', '0101110', '1101010', '1100110', '1101010', '1000010', '1001110', '0001000', '0000010', '1101100', '0100000', '1000110', '1000110', '0001100', '1100010', '0001100', '0000010', '0001000', '0101010', '0001100', '1000110', '1001010', '0101110', '1100110', '1100100', '1101100', '1000100', '1001010', '1100100', '1000010', '1001010', '0100000', '0100000', '0000010', '0000000', '0100100', '1101110', '0101000', '0100100', '0101100', '1000100', '1100000', '0100110', '1000100', '0001000', '1000010', '1001010', '0100100', '0101000', '1100110', '1101000', '0100100', '0101100', '0100010', '0000110', '0001000', '1000100', '1100000', '1100000', '1000110', '1001000', '1000000', '0001010', '0000110', '1100000', '1101010', '1101100', '0100000', '0101110', '1100010', '0000000', '1100000', '0101010', '0100100', '0101100', '0000100', '1001010', '0101000', '1101100', '1100100', '0100000', '0101110', '1101010', '0101000', '0100010', '0101000', '0001010', '0000000', '1101100', '0000010', '1100110', '1000010', '0000110', '1100110', '0001000', '1100000', '1101100', '0100000', '1100000', '0001010', '1101010', '1000010', '1100000', '0001010', '0100110', '1100110', '1000000']\n",
      "110\n"
     ]
    }
   ],
   "source": [
    "# Adding the transpiler to reduce the circuit to QASM instructions\n",
    "# supported by the backend\n",
    "from qiskit import compiler\n",
    "\n",
    "# First we have to transpile the quantum circuit \n",
    "# to the low-level QASM instructions used by the \n",
    "\n",
    "qc.save_statevector(label = 'test', pershot = True)\n",
    "# backend\n",
    "# qc_compiled = transpile(qc, backend)\n",
    "qc_compiled = compiler.transpile(qc, backend, optimization_level=2)\n",
    "\n",
    "# Execute the circuit on the qasm simulator.\n",
    "# We've set the number of repeats of the circuit\n",
    "job_sim = backend.run(qc_compiled, shots=x*y, memory=True)\n",
    "job_simGlitch = backend.run(qc_compiled, shots=1000, memory=True)\n",
    "\n",
    "# Grab the results from the job.\n",
    "result_sim = job_sim.result()\n",
    "result_simGlitch = job_simGlitch.result()\n",
    "\n",
    "memory = result_sim.get_memory(0)\n",
    "memoryGlitch = result_simGlitch.get_memory(0)\n",
    "print(memory)\n",
    "print(len(memory))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "1827d0f9-14bd-4b7d-823f-c82325db5dc6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1001000': 1, '1001110': 1, '1001010': 5, '1000010': 5, '1100010': 2, '0000010': 4, '1101010': 5, '1100110': 6, '1001100': 1, '0000110': 3, '1101100': 6, '0100000': 7, '1000110': 5, '0001000': 6, '0001100': 3, '0000100': 1, '1100100': 3, '0100100': 5, '0000000': 3, '1101000': 1, '1000100': 4, '0101000': 5, '0100110': 2, '1101110': 1, '0101010': 2, '0101100': 3, '1100000': 8, '0101110': 4, '0001010': 4, '1000000': 2, '0100010': 2}\n"
     ]
    }
   ],
   "source": [
    "counts = result_sim.get_counts(qc_compiled)\n",
    "print(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b336fb1e-d4ff-4643-bb42-8602110120a3",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1280x1408>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from PIL import Image, ImageDraw, ImageFilter\n",
    "\n",
    "tileFileNames = ['0000000','0000001','0000010','0000011','0001000','0001001','0001010','0001011','0010000','0010001','0010010','0010011','0011000','0011001','0011010','0011011','0100000','0100001','0100010','0100011','0101000','0101001','0101010','0101011','0110000','0110001','0110010','0110011','0111000','0111001','0111010','0111011','1000000','1000001','1000010','1000011','1000100','1000101','1000110','1000111','1100000','1100001','1100010','1100011','1100100','1100101','1100110','1100111']\n",
    "tiles = {}\n",
    "for tile in tileFileNames:\n",
    "    tiles[tile] = Image.open('tiles/'+tile+'.png')\n",
    "\n",
    "tile_size = 128\n",
    "image = Image.new(mode=\"RGB\", size=(x*tile_size, y*tile_size))\n",
    "\n",
    "for idx, i in enumerate(memory):\n",
    "    tile_x = idx % x\n",
    "    tile_y = idx // x\n",
    "    im = tiles[i[::-1]]\n",
    "    image.paste(im, (tile_x*tile_size, tile_y*tile_size))\n",
    "image.save('output.png', quality=100)\n",
    "display(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "5ed96694-da98-4f5e-a8e3-a5512edd2979",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 789.163x451.5 with 1 Axes>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Quantum Circuit\n",
    "glitchingCircuit = QuantumCircuit(4)\n",
    "\n",
    "glitchingCircuit.h(0)\n",
    "glitchingCircuit.h(1)\n",
    "glitchingCircuit.h(2)\n",
    "glitchingCircuit.h(3)\n",
    "\n",
    "glitchingCircuit.u(2, 0, 3, 1)\n",
    "glitchingCircuit.u(2, 0, 3, 2)\n",
    "glitchingCircuit.u(2, 0, 3, 3)\n",
    "glitchingCircuit.u(2, 0, 3, 0)\n",
    "# glitchingCircuit.measure(2,[0])\n",
    "glitchingCircuit.x(3)\n",
    "\n",
    "meas = QuantumCircuit(4, 4)\n",
    "meas.barrier(range(4))\n",
    "# map the quantum measurement to the classical bits\n",
    "meas.measure(range(4), range(4))\n",
    "\n",
    "# The Qiskit circuit object supports composition.\n",
    "# Here the meas has to be first and front=True (putting it before) \n",
    "# as compose must put a smaller circuit into a larger one.\n",
    "qc = meas.compose(glitchingCircuit, range(4), front=True)\n",
    "\n",
    "#drawing the circuit\n",
    "qc.draw('mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c7d82cbd-a05d-4183-90ab-aba45347666d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#prepare randomnes data for glitching\n",
    "\n",
    "qc.save_statevector(label = 'glitches', pershot = True)\n",
    "# backend\n",
    "qc_compiled = compiler.transpile(qc, backend)\n",
    "\n",
    "glitchOpportunities = frameAmount\n",
    "job_sim = backend.run(qc_compiled, shots=glitchOpportunities, memory=True)\n",
    "\n",
    "# Grab the results from the job.\n",
    "result_sim = job_sim.result()\n",
    "\n",
    "glitchMemory = result_sim.get_memory(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "16f0cbcd-de4c-4e52-a449-bc62292bea61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1010': 4, '0010': 1, '0000': 5, '1001': 3, '1100': 7, '1000': 100}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts = result_sim.get_counts(qc_compiled)\n",
    "print(counts)\n",
    "from qiskit.visualization import plot_histogram\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "96fd15a2-dbf2-4b9a-8f7c-3879aca566dd",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from copy import deepcopy\n",
    "\n",
    "timePerFrame = 1 / fps\n",
    "\n",
    "frames = [image];\n",
    "\n",
    "for frame in range(frameAmount):\n",
    "    newImage = deepcopy(frames[-1])\n",
    "    for idx, i in enumerate(memory):\n",
    "        if glitchMemory[(idx * frame) % frameAmount] == '0010':\n",
    "            tile_x = idx % x\n",
    "            tile_y = idx // x\n",
    "            randomFile = memoryGlitch.pop()\n",
    "            im = tiles[randomFile[::-1]]\n",
    "            newImage.paste(im, (tile_x*128, tile_y*128))\n",
    "    frames.append(deepcopy(newImage))\n",
    "    \n",
    "frames[0].save('output.gif',\n",
    "               save_all=True, append_images=frames[1:], optimize=False, duration=timePerFrame, loop=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46cabfee-ad2b-4e09-a963-4bff53b0abba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.8"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}