Anisotropic_warpB.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Introduction\n",
    "This notebook explores a novel approach to creating a warp bubble using positive energy densities. Building on recent advancements by Eric Lentz, we propose a non-uniform energy distribution model to enhance control and efficiency in warp field generation.\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with bubble_radius=1.0, density=20.0, speed=1.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with bubble_radius=3.0, density=10.0, speed=0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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///d/43e/+12rdUd/8YtfxD/+8Y84+OCD41//+lfR1wDfa6+94ne/+1188pOfjC222CJeeOGFuPDCC+PVV19Na9mXVFVVVfGLX/wi9tprr9hqq63ihBNOiM022yzefvvtuPnmm+Pdd9+NBx54IA9HAgD5c+KJJ8YjjzwSP/rRj+LJJ59sc58BAwbEVlttlZfn32uvveLMM8+M0047LbbZZpt4/fXX49JLL42nnnoqq3odEXHhhRfGDjvsENtvv32ccMIJ8clPfjKWLl0at99+e9x3330xf/78HB8FAGQnk8/XF154YfzlL3+JY489Nl5//fU2/0JrjTXWiM9+9rN56etee+0Vt9xySxx55JGxxx57xKJFi+LKK6+M++67L+vHPOuss+LOO++MfffdN4477rjYZpttYsWKFXH33XfHb37zm3j33XdbTYiDciU8h27ihRdeiO9973vxla98JQ488MBW9w0ZMiQuvfTS+PKXvxxnnnlmnHXWWUXq5cea/6TsJz/5SaxcuTLGjx8f5557bpx55plZP+buu+8eDz74YMyYMSPOOeecWLJkSay33noxbty4OOGEE3LYewAojObA/NRTT213nx122CFmzZqVl+c/9dRTY9myZXHVVVfFz372sxgzZkwcc8wxcfPNN8dzzz2X1WNOmDAh5syZEz/60Y/i8ssvj4ULF8bgwYNj7NixMW3atNweAABkKdPP1801++KLL46LL764zcccPnx4zJs3Ly/9nTJlSixcuDAuueSSuO6662LTTTeNgw46KEaNGhVXX311Vo+54YYbxpw5c+Lss8+OP/7xj/Gzn/0s+vfvH5tttllMnz49evXqleOjgOKoStK5+h4AAAAAAHQj1jwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBRlF543NTXFI488EoMHD45bbrml1X0rVqyI7373u7HOOuu0XKV4zpw5nT5mtu0AgLap1wBQHtRsAGhfWYXnr776atTU1MSnPvWpWLRo0Wr3n3LKKfGHP/whrr766rjvvvtik002ic9//vNRX1/f4eNm2w4AWJ16DQDlQc0GgI5VJUmSFLsT6Vq5cmW89NJLERGx+eabx8033xx77713RER89NFHMWTIkLjsssviK1/5SkRENDY2xpAhQ+L888+Pb37zm20+ZrbtAIC2qdcAUB7UbADoWE2xO5CJnj17xujRo9u87+WXX44lS5bExIkTW7ZVV1fHZz7zmZgzZ067BTqbdg0NDdHQ0NDyc1NTU7z77rsxaNCgqKqqyvbwAKBdSZLEe++9F0OHDo0ePUr7D8dKpV5HqNkAFFY51euI0qnZ6jUAhZRJvS6r8LwjCxcujIiIvn37tto+aNCgWLBgQU7bzZgxI6ZPn96V7gJAVubPnx/Dhg0rdjeyVsh6HaFmA1Ac5V6vI3zGBqDypVOvKyY8b1ZTs/ohpfNNdSbtpk6dGscff3zLz0uXLo0NN9wwdtzg0Kjp0SuD3gJAej5qWhGz3rgq1l577WJ3JScKUa8j2q/Z8+fPX+1DPQB0VX19fdTV1VVMvY4o7mds9RqAfMikXldMeD5kyJCIiFi8eHEMHDiwZfuiRYtio402ymm72traqK2tXW17TY9eUdNj9e0AkCvl/qfLhazXEe3X7L59+/owDkDelHu9jiiNz9jqNQD5lE69Lv1F2NK08cYbR79+/eK+++5r2dbY2BgPPfRQjB8/PuftAIDMqdcAUB7UbAAos/C8qakplixZEkuWLImIiA8++CCWLFkSK1asiJqamjjkkEPilFNOiVmzZsWjjz4ahxxySERE7L///i2PceaZZ0ZNTU28+uqrERFptwMA0qNeA0B5ULMBoGNltWzLa6+91urPvL7xjW9ERMQ111wTU6ZMiRkzZsTKlSvjgAMOiPfeey8mTJgQd9xxR/Tv37+lTVNTUzQ2NkaSJC3b0mkHAKRHvQaA8qBmA0DHqpJVKxxZqa+vj379+sUudUdZ8xyAvPioqSHumn9ZLF261NqfXdBcs40jAPmgzuSGcQQgnzKpM2W1bAsAAAAAABSC8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAghfAcAAAAAABSCM8BAAAAACCF8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAghfAcAAAAAABSCM8BAAAAACCF8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAghfAcAAAAAABSCM8BAAAAACCF8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAghfAcAAAAAABSCM8BAAAAACCF8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAghfAcAAAAAABSCM8BAAAAACCF8BwAAAAAAFIIzwEAAAAAIIXwHAAAAAAAUgjPAQAAAAAgRUWF51VVVW3eRowY0WG7WbNmtdlu3LhxBek3AHQn6jUAlAc1G4DurqbYHcilV155ZbVt5513Xjz00ENptX/iiSeib9++LT/36tUrZ30DAD6mXgNAeVCzAejuKio8T/32e+HChXH99dfHddddl1b7DTfcMPr375/7jgEALdRrACgPajYA3V1FLduS6swzz4wxY8bEPvvsk9b+w4YNi4EDB8bEiRPj6quvbne/hoaGqK+vb3UDALKTr3odoWYDQC75jA1Ad1NRM89X9dJLL8UVV1wR//d//9fpvqNGjYqZM2fGBhtsEB9++GHcdtttcdhhh0V1dXVMnjx5tf1nzJgR06dPz0e3AaBbyWe9jlCzASBXfMYGoDuqSpIkKXYn8uHAAw+MpUuXxh133JFV+ylTpsTcuXPjX//612r3NTQ0RENDQ8vP9fX1UVdXF7vUHRU1PWqz7jMAtOejpoa4a/5lsXTp0lZrh5a7fNbriPZrdqWNIwClob6+Pvr161eRdaYYn7ErcRwBKL5M6nVFzjyfPXt23HTTTfHII49k/RibbrppPPjgg23eV1tbG7W1QnIA6Ip81+sINRsAcsFnbAC6q4pc8/zEE0+MAw44IMaPH5/W/o2Njattmz17dowdOzbXXQMA/j/1GgDKg5oNQHdVcTPPb7vttrj//vvjueeea/P+66+/Pg455JC4++67Y4cddoiIj/98rK6uLvbZZ5/o3bt33HjjjTFz5syYPXt2IbsOAN2Geg0A5UHNBqA7q6iZ501NTXHyySfHoYceGptsskm7+zQ2NsaqS73vvPPOceedd8auu+4an/rUp2LWrFlx7733pv2tOgCQPvUaAMqDmg1Ad1exFwwtpOZF5l0wFIB8qdQLhhZaJV/IDYDiU2dywzgCkE+Z1JmKmnkOAAAAAAC5IDwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASFFR4fmsWbOiqqpqtdu4ceM6bHfWWWdFXV1d1NbWxrhx4+LOO+8sTIcBoBtSrwGgPKjZAHR3NcXuQD488cQT0bdv35afe/Xq1e6+l1xySZx77rlxxRVXxJgxY+LGG2+MPffcM5599tnYaKONCtFdAOiW1GsAKA9qNgDdVUWG5xtuuGH0798/rX2vuOKKOPXUU+NrX/taRESMGzcu7rjjjrj22mtj+vTpeewlAHRv6jUAlAc1G4DuqqKWbWk2bNiwGDhwYEycODGuvvrqdvdbvnx5PPPMMzFx4sRW27fbbruYM2dOvrsJAN2aeg0A5UHNBqC7qqiZ56NGjYqZM2fGBhtsEB9++GHcdtttcdhhh0V1dXVMnjx5tf0XLVoUSZK0+vOziIhBgwbFI4880u7zNDQ0RENDQ8vP9fX1uTsIqCDvbbVB1m3XnvNGDnsClJJC1esINRsAusJnbAC6u4oKz4cOHRpDhw5t+XnbbbeNN954Iy677LI2C3uzmprVh6Gqqqrd/WfMmOHPzej2uhKM5+rxBexQngpVryPUbADoCp+xAejuKnLZllVtuummsXjx4jbvGzRoUFRVVa12/6JFi2Lw4MHtPubUqVNj6dKlLbf58+fntM9QKt7baoN2b6Wg1PsHpC8f9TpCzQaAXPMZG4DupKJmnjc2NkZ1dXWrbbNnz46xY8e2uX/v3r1jzJgxcd9998XOO+/csv2BBx6IPfbYo93nqa2tjdra2tx0GkpIJYXOqcdiljqUjkLV6wg1GwC6wmdsALq7igrPp0yZEnV1dbHPPvtE796948Ybb4yZM2fG7NmzIyLi+uuvj0MOOSTuvvvu2GGHHSIi4vDDD49TTz01xo8fHxtttFH8+te/jueeey5uuummYh4KFEwlBeYdWfU4BelQXOo1AJQHNRuA7q6iwvOdd945Lr300rjsssti2bJlMX78+Lj33ntj/PjxERHR1NQUjY2NkSRJS5tjjz023n333TjqqKNi4cKFsfnmm8ett94am2yySbEOA/Kqu4TlHTErHYpLvQaA8qBmA9DdVSWrVjmyUl9fH/369Ytd6o6Kmh7+1IzSIzBPnyCdUvVRU0PcNf+yWLp0afTt27fY3SlbzTXbOAKQD+pMbhhHAPIpkzpTUTPPgf8qVGC+aEx15zvl2KBnG/P22JZ3AQAAACBCeA4VJ1+heTFC8va015dch+rNYylEBwAAAOh+hOdQIXIdmpdSWJ6u1D7nKkw3Gx0AAACg+xGeQxnLZWBejmF5Z/IRppuNDgAAANA9CM+hDOUiNC9kWL589PK09+09t3fe+pHLMF2IDgAAAFDZhOdQRkotNM8kFM/1Y+YiZF91LLIN0oXoAAAAAJVJeA5loKuheS4C83wE5V3RVn+6Eqg3j5EQHQAAAIAI4TmUvGyD864E5qUWlKcrF4F6V2ejC9EBAAAAKoPwHEpUoUPzcg3MO7PqcWUbpGcbogvQAQAAAMqX8BxKTCFD81wG5ttv+mLOHqs9976wSZfaZxukZxuim4UOAAAAUL6E51BCsgnOMw3NuxqYFyIkz/S5swnVswnShegAAAAA3YfwHEpAvkPzrgTmxQzL09VWHzMJ1DMN0rsSogvQAQAAAMqD8ByKLNPgPN+heTmE5elY9TiyCdLzFaKbhQ4AAABQHoTnUCSlFJpXSmDenmyC9EKE6AJ0AAAAgNIlPIciyEdwXuzA/Oh178np47XlF29P6vJjZBqkZ7KkS6YhugAdAAAAoHQJz6HAMgnO051tnm5wnovAvBAheabPnW2onk2Qnu5M9EwC9AjLuAAAAACUGuE5FEg5hubFDMoz0VY/Mw3Um8eosxA93eVczEIHAAAAKG/CcyiAXAfn+QzNyyUw78yqx5FJkJ6PEF2ADgAAAFB+hOeQZ+kG58UMzSslMG9PNkF6uku6pBOiZzILXYAOAAAAUBqE55BHhQ7Ohead60qQ3lmInqtZ6AJ0AAAAgOITnkOe5Co4z3Vo3h0D8/Y0j0UmIXouZqGnG6BHuJAoAAAAQLEIzyHHcrm+eWfBudA8NzIJ0XMxC90yLgAAAAClT3gOOVSo2eZC8/zIZYie61noAnQAAACAwupR7A5ApSi14Pzode8RnGcpk7Hr7PXo7PVMZ737iMz+ogEAAACArjPzHHKgEMF5JqE5uZHuTPR0ZqGbgQ4AAABQXsw8hy7KRXC+fPTyLgfnZprnT7pj29Hr1NlrbAY6AAAAQGkRnkMX5Co470i6wTn5l06I3pVlXAToAAAAAKVDeA55lm1wvv2mL3YaxJptXhzpBOidzUJvjwAdAAAAoDQIzyFL6YSXXQnOOyI0L76uzkLPRYAOAAAAQP4IzyELxQ7OKR3FDNDNPgcAAADIH+E5ZEhwTioBOgAAAEDlqSl2B6CcFCs4L9fQ/BdvT8q6bbkdc3N/2zvm5tf33hc2We2+5aOXR++5vdtst2hMdQx6trHD535vqw1i7TlvZNJdAAAAADohPIc05Ss4r4TZ5l0JyTN9zFIfj6PXvafD8dh+0xcF6AAAAABlQHgOOdKdgvN8hOXZPncpjpEAHQAAAKD8Cc8hDZ3NOq/04LyYYXlnSjVML1aADgAAAEBuVNQFQ2fOnBk777xzrL/++tGnT5+YOHFi3HrrrR22mTVrVlRVVa12GzduXGE6TcnrygUZyz04/8Xbk0o6OG9LKfU52wuJduUioi4gSjlQrwGgPKjZAHR3FTXzfPbs2bH99tvH9OnTY8CAAXHDDTfEfvvtF7Nnz+60UD/xxBPRt2/flp979eqV595SDrqyznlHAWhHih2c5zJ4bmtmdbo6+4KhM6seRzHHNB8z0Dtj+RZKnXoNAOVBzQagu6uo8Hz69Omtfv7xj38cv/3tb+Oee+7ptLBvuOGG0b9///x1joqUTXDeUShczJC3K6F5V0LyTB8zm1C9+diKNb6dBejtaS9At3wL5U69BoDyoGYD0N1V1LItqVauXBlLliyJAQMGdLrvsGHDYuDAgTFx4sS4+uqrC9A7Sl1X1jlvTykG59ksc3LvC5u0uhVSV567mEu6dPT6ZvOFgOVbqCTqNQCUBzUbgO6momaep7rggguiR48esc8++7S7z6hRo2LmzJmxwQYbxIcffhi33XZbHHbYYVFdXR2TJ09us01DQ0M0NDS0/FxfX5/zvlNchV7nvBjBeTaBeSlatV/phtDFmone0Qz0fFxA1PItlIt81esINRsAcslnbAC6m6okSZJidyIffve738UhhxwSN998c+y2224ZtZ0yZUrMnTs3/vWvf7V5/7Rp01b787WIiF3qjoqaHrVZ9ZfSku2s80oMznMdmrcVBGe7Pnx7Mp3JXejXoKPxb2+82wvQO1u+RXheOT5qaoi75l8WS5cubbV+aLnLZ72OaL9mV9o4AlAa6uvro1+/fhVZZ4rxGbsSxxGA4sukXlfksi1XX311HH744fHHP/4x46IeEbHpppvG4sWL271/6tSpsXTp0pbb/Pnzu9JdSkwlB+fpLlvSlSVZes/t3eEtV21y2f9CL+WSzRIu7Z1flm+hnOW7Xkeo2QCQCz5jA9BdVdSyLUmSxA9/+MO47LLL4o477ohtt9220zaNjY1RXd06fJo9e3aMHTu23Ta1tbVRW2uGeSXK9TrnpRacdybbsDzfUp8jk5nqzcfU2Wz0Qi/lks0SLu2xfAvlplD1OkLNBoCu8BkbgO6uosLzgw8+OP72t7/F7373uxg6dGjMmzev5b4RI0bE9ddfH4ccckjcfffdscMOO0TEx38+VldXF/vss0/07t07brzxxpg5c2bMnj27SEdBOcp02ZFCBufpzqpON6wtRFieaR/SGf9MQvRSCNDb0tH651BO1GsAKA9qNgDdXUWF5//85z9jwYIF8bnPfW61+5IkiaampmhsbIxVl3nfeeed49JLL43LLrssli1bFuPHj4977703xo8fX8iuUwIKuVxLoeRytnkph7bNfUs3RC+HAD3TC4iafU45Ua8BoDyo2QB0dxV7wdBCal5k3gVDy1suw/NSWK6ls+C80KF5Zxe2jMh8WZyOpBOkdxail8Jr1dbr5OKh3VOlXjC00Cr5Qm4AFJ86kxvGEYB8yqTOVNTMc8hWrmedt6cQYWyuZptnG5qnE5Jn2jabUD2d2eidzUIv1DrouVq+xexzAAAAgNzpUewOQLnKdLmWUgjO731hk06D895ze2cUnA96trHVLR+68hydHUs6Y5JJsJ2t9s6P9s6n9s6/XM7eBwAAAOjOhOd0e9nOOm9LMdc57+oyLZmE5vkOy3P9/OkcWykE6O3J5XnV2fkOAAAAwMeE59CBclmupSvBeTaheSnJZYhe7AA90/PE7HMAAACA/BGe063lchZusZZr6Wpw3plizzJPVyb97CxA72jMihWgm30OAAAAUFjCc2hHrmad51MhgvNy1NUAPaLjsSvmEi6pzD4HAAAAyI+aYncAiqXcZ51nG5wXMjRfe84bWbft6uvTfAwdhcjNY9FeAH3vC5u0+9r+4u1JeXt9j173njZf3+03fbHTpWXS9d5WG3Tp9QEAAACodGaeQwZKadZ5R7INzru6PMvac95odeuKXD1WOseU7TroxZiB3laYb/Y5AAAAQO4Jz6ENmYSOpTbrvCvBeTZyFZbn+3nyFaDnS77XygcAAACgY8JzuqVslgTJZNZ5pQfnhQrMc/38XQnQ25PP2eeZnEfZ/FWEC4cCAAAAtE94DilyMes8X3IdnGe6TEsxA/P2ZNqnzo65vfEqpeVbMjnvLN0CAAAAkB3hOaShFNY6z0dwnolSC81T5XIWeikF6GafAwAAABSH8Jxup6OwsNTXOm9LvoPzUpxt3p5sZqG3J5sAvZDMPgcAAADIL+E5lIFczmrONDgvR8UK0Au9fAsAAAAA+SM8p1vJ1YVCy3XWebrBeTnNNm9PJseQ6RI2hdbeedXWeWjpFgAAAIDcEJ7D/1eqS1u0N5s5m+Va0lHuoXmqrgbolTL7vFTPbwAAAIBSJTyHHMnHrPNMg9iurnNeacF5s64eVykE6IX+qwYAAACA7k54Dh3IZMmWQsr0opXdOThvls7xlfryLW2xdAsAAABAfgjP6TbKLRzM1XItgvP/6kqAXgqzz7vK0i0AAAAA6ROeQ3Q9VCz2khqC8/TlI0AvlGKfZwAAAADdifAc2lHMJVsynXWere4WnDfL9XEXe/Z5rpZuAQAAAOC/hOdQ5roy65z2lers83wqt6WNAAAAAPJJeE63kM9QsFyX0uius86bFWr2ea519Xyz7jkAAABAeoTndHulFiZmsmRLtrPOu3tw3qyzccjF7PNSvHAoAAAAAJ0TnkOaCrXeOWTDuucAAAAAuSU8hzaUWuiYyZIgZp1nJpezzwu1dAsAAAAA+Sc8hxKSyRIflXzhykLL9xcKuV66pVzX2QcAAAAoJ8Jz6IJSCzHNOs+Pzsa13HS0zn8+L64LAAAAUE6E51S8jsLAUrtYaFssBVK6LN0CAAAAULmE51CGslmyxazzjlXC+LioLQAAAEDuCM8hRVsXCy1EKJnrdbHJra4u3VKs17fULn4LAAAAUC6E51AhKm1dbgAAAAAoJuE5dAOVsCRJIWQzTtY9BwAAAKhMwnMoYW2FsNmsd07lOXrde4rdBQAAAICKJjyHLAkvAQAAAKByCc8B0lSuFw0FAAAAIHNph+ePP/54HruRW2eddVbU1dVFbW1tjBs3Lu688868tIFS4WKhQDlSrwGg9KnXAHRnaYfnW2+9dZx88smxfPnyfPanyy655JI499xz45xzzomHHnoodt1119hzzz3jlVdeyWkbyCUzkktHd7m46qIx1e3e995WGxSwJ+TDIYccEjfffHO797/99tsxaVJx33fUawAo/ZqtXgPQ3aUdnv/tb3+LW2+9NcaOHRt33XVXPvvUJVdccUWceuqp8bWvfS3GjRsX5557bmy66aZx7bXX5rQNlIvuEgYD/3XttdfGl7/85Tj99NPbvH/58uXxj3/8o8C9ak29BoDSr9nqNQDdXdrh+Y477hhPPPFETJkyJfbaa6+YPHlyLFq0KJ99y9jy5cvjmWeeiYkTJ7bavt1228WcOXNy1qahoSHq6+tb3QCglFx33XVx5ZVXxp577hnvvfdesbvTSqHqdYSaDUDpK9WarV4DQIYXDO3Zs2ecdtpp8dRTT8X9998fdXV1MXDgwFa3Ylq0aFEkSRJ9+/ZttX3QoEGxYMGCnLWZMWNG9OvXr+VWV1eXmwMAgBzZbrvtYvbs2fHWW2/F1ltvHS+88EKxu9SiUPU6Qs0GoPSVas1WrwEgw/A8ImL+/Plx/PHHx/z58+Pb3/52XHjhha1upaCmpma1bVVVVTlrM3Xq1Fi6dGnLbf78+dl1FADyaNiwYfHPf/4ztt5669h6663j9ttvL3aXWsl3vY5QswEoD6Vcs9VrALqz1StaOxobG+P888+PM888MyZMmBCPPfZYjBkzJp99y9igQYOiqqoqFi9e3Gr7okWLYvDgwTlrU1tbG7W1tbnpNOTZe1ttYN1z6MZqa2vjuuuui5/97Gexzz77xLRp0+KrX/1qUftUqHodoWYDUD5KrWar1wCQwczzcePGxU9/+tP4+c9/Hvfee2/JBecREb17944xY8bEfffd12r7Aw88EOPHj89ZG6ByvbfVBsXuQkEMerax3ft82VKZvvvd78Zf//rXuOCCC2LKlClF7Yt6DQDtK5WarV4DQAbh+VZbbRXPPfdcHHroofnsT5cdfvjhcd5558Wtt94aTz31VJx00knx3HPPtfyn4/rrr4+amppWVyzvrA3k29Hr3tOl9ovGVOeoJ0AlGD58eJt/Lj1p0qSYPXv2arPBikG9BoDSr9nqNQDdXdrLtlx77bV57EbuHHvssfHuu+/GUUcdFQsXLozNN988br311thkk00iIqKpqSkaGxsjSZK02wBEdP1Liq5+SQLpeuWVV9q9b8SIETF79ux48803C9ij1anXAFD6NVu9BqC7q0pWrXJkpb6+Pvr16xe71B0VNT2s01ZqOlqGo60wdPno5att237TF9tsn8sw9BdvT1pt270vrP4fzN5ze7fZ3jIcuZHp+RKR/jmT6/C8K+eM86X8fNTUEHfNvyyWLl0affv2LXZ3ylZzzTaOAOSDOpMbxhGAfMqkzqS9bAtQeG0FsG0FtXQ/bQXnAAAAAOSO8By6ge5yEcyuymacMvlLBQAAAADKh/AcAAAAAABSCM8hRXtriudbV9fD7urFLOmYi4UCAAAAdC/Cc0hDWxdhLKZs1j23dEvHKmF8MrnALAAAAAAdE55T8dae80a79w16trGAPcmO9bNLl/XOAQAAACqX8By64BdvTyp2F1rpbGmRSphdXQyVtiROR18adfRlEwAAAEB3IjyHEpLJutjZLN1C2/L9pUKu1zsvtS9tAAAAACqR8BzKQCZLgZh9nlvtjaclWwAAAAAqm/Ac2tDWRRZL7aKh5EalfJngYqEAAAAAuSU8p9srtYuG5mLpFrPP09PZOGQy67w9uV6yBQAAAIDCEJ7TLeTzIoiFWn8610uCCNBzq1BLtnT1fCu1L4sAAAAASpXwHMpctrPPu7tCzDovN/n8kgkAAACg3AjPoR3FXPe8vaU+zD7PjVwfd3uvS6GWbLHeOQAAAEDuCc8hur6URaGWbmlPV2afd7cAPZ3j7Y6zzgEAAABoTXgOJSrT2ecC9M51JThvTyFnnVvvHAAAAKBwhOd0G9ms51zMpVtySYDe9eMr1VnnuTofrXcOAAAA0JrwHHIkH0u35Gr2eboqNUBP97gyXa6lVGedW+8cAAAAoOuE5/D/leqSFoVcviWi8gL0QgfnpapUz28AAACAUiU8p1vJ99Itxb5waGe6W4De1eA8G4Wcdd7WeZjNrHNLtgAAAACsTngOZSCXy7dkEqCXa4ieSd87Go9SWK4FAAAAgOIQnsMqMlnaolQuHJrPAD2i/GahZ9LfXAbnhZbJ+WfJFgAAAIDMCc/pdnK1dEt78rV0S0ezmgsRoJd6iJ5pH3MdnOdr1nm+LxRqyRYAAACAtgnPIUUpzz7PR4Be7iF6Nn3KJjjvSCkv12LWOQAAAEB2hOd0S+U6+zwiu6C2s0A40wtmlkKInm1onm1wXozlWvJ9oVAAAAAA2ic8hzbkYvZ5PgP09nQU8OY6QI/4b4BdqCC9K8/X2fFlG5yX8qzzzliyBQAAAKB9NcXuAJST3nN7Z7WsR64dve497Ybz22/6YruB/vLRyzucodwcMGez1EdqoJ2LYDYXoXw6XwqUYnCei1nnlmwBAAAAyJ7wnG5r7Tlv5GzG9L0vbNJmyPqLtyflLWDNV4Ae8XHg3NXgtdjLukRUXnCeS2adAwAAAHTMsi3QjvbC41JaWzqbC4hGfBwYp7OMSzZLuZSCdPre2RiU4lItZp0DAAAAFI7wnG4tl7Nvi7X2eWcBelfWQY8orxA93b52FpoXMzjPZLmWbJl1DgAAANA54Tl0IFezz4sZoEd0fRZ6xH+D6VIL0jPpV1dmm0eU3sVBzToHAAAAyB/hOd1eZ7NwMwkiczk7OFNdCdAj0puF3qwUQvRM+9DZ8ZVCcG7WOQAAAEDpEJ5Dltqb9Vus5VsichOgZxOiFyJMz/a50jmmUg7O22PWOQAAAEB+1RS7A1AK1p7zRry31Qbt3j/o2cY2A9vec3tnFDb/4u1JeQ9ij173ng6D2OaguKPZzM3HlOnyNO2F2pkGurkI4tN5XToLzSOKH5zn8iKhZp0DAAAApE94Dnlw7wubpBXM5ktz4JurED0i8yB9VYVc4iXdLzNKYbZ5Z4q5DBAAAABAd1cxy7a89dZbcfDBB8eoUaNizTXXjOHDh8cPfvCDaGho6LTtiBEjoqqqarXb448/nv+OUzKyXfu8FJdvaZZOAJxuyJ/pki6F1Ny3dGebl1Jwnuk652adU+7UawAoD2o2AFTQzPPXX389Ghoa4vzzz4+RI0fG888/H0ceeWQ0NjbGeeed12n7008/PQ455JBW24YOHZqv7lJhSnH5lmadLeMSkd4s9Ga5mo3eVZkG+el+SVAKwTlUMvUaAMqDmg0AFRSeT5w4MX7/+9+3/DxmzJh48skn409/+lNa7QcOHBgjRozIU+8oF9mufd6ejpZvKXSA3vycHckkRI9YPcDOZ5ie7az3UgzNIzJf5zzCrHMqg3oNAOVBzQaAClq2pS0LFiyIAQMGpLXv1KlTY6211oqRI0fGMcccE4sWLWp334aGhqivr291o3IUavmWiMLPPE43IE5naZO2rLp8SuqtEO1XlckxCM6huPJVryPUbADIJZ+xAehuKmbmeaoXX3wxfv3rX8ell17a6b4XXXRRrLvuutGrV694+umn44wzzohnn3027rmn7UBtxowZMX369Fx3mQrQ3vItpTIDPSL9WegRrWdtd/XilYVYLz3TwL8ULgq6qkyDc6gE+azXEWo2AOSKz9gAdEdVSZIkxe5ER6ZNm9ZhER0+fHjMmzev1bb//Oc/scMOO8S2224b1113XcbPOWvWrNhpp53iueeei9GjR692f0NDQ6uLpNTX10ddXV3sUndU1PSozfj5KE0dLd8SER0u39JeUNxRuFusIDeb2e9dDdJzKZsZ8sUMzc06J1sfNTXEXfMvi6VLl0bfvn2L3Z3VlGK9jmi/ZpfqOAJQ3urr66Nfv34lXWdKsWar1wAUUib1uuRnnp9wwglx5JFHtnt/dXXrAPOll16Kz3/+8/E///M/8atf/Sqr59x0000jImLx4sVt3l9bWxu1tULySpfr9c87U+gZ6M0ymYneLJcz0rORTWAeUfyZ5oUMzqHQSrFeR6jZAJCqFGu2eg1AqSr58LxPnz7Rp0+ftPZ94IEHYu+9945DDz00ZsyYkVabxsbG1f5zMHv27KipqYnNNtss4/7SvbQXoGezfEtE8QL0iOxC9Ij2g+xchOrZhuSpih2aRxQ+ODfrnEJTrwGgPKjZAJC+kg/P03X77bfHvvvuGyeeeGIceuihrf7MbPDgwS3/OaipqYnJkyfHVVddFRERM2fOjF/+8pdx9NFHxyabbBJPPPFEfPe7343jjjsuBg4cWIxDoYR0Nvu8I+UYoEdkH6KnylXw3RWlEJpH5DY4T4fgnFKmXgNAeVCzAaCCwvOHH344Ghoa4uyzz46zzz671X3XXHNNTJkyJSI+/ha8sfG/szZHjx4dNTU1cfjhh8fChQtjvfXWi+985ztxwgknFLL7lLCuLN9SrgF6ROvguatBeiEVe9xW1dm4ZROcW+eccqdeA0B5ULMBoAwuGFoOmheZd8HQypXO7PNcX0A0orSC4GalGKSX4zjlIziPEJ5XslK/YGi5KIcLuQFQvtSZ3DCOAORTRV0wFEpBOsu3VOoM9FSp/SlGmF5qY5JKcA4AAABQ/oTnkCYBetva61suQvVSPu72CM4BAAAAKoPwHDIgQE9fufU3FwTnAAAAAJVDeA4ZymeAHtH+OujNwWx3DKVLXbaheYTgHAAAAKBU9Sh2B6BSdRR8dhSYdhS0RpTmBTu7s2IG5wAAAADkj/AcspDubN98BuhC9OJK5zXId3Bu1jkAAABA/gjPIUvFDtAjzEIvlnTGXXAOAAAAUN6seQ5dkM765xHZrYEe0fk66BHWQi+krobmEYJzAAAAgHJh5jl0Ua5moOdiFrqZ6PmR7tgKzgEAAAAqh/AcciAXAXpE58u4WMql8NINzTtbpkVwDgAAAFBehOeQI4UI0CPMQi+UQsw2jxCcAwAAAJQqa55DDuViDfSI/wauXVkLPaL1rGlroqcn3S8d0vkSQ3AOAAAAUL6E55BjmQToEdFpiN5egB6Rfoge4cKiHcl0ln6hZptHCM4BAAAAikV4DnnQHHjmahZ6RwF6xMdhbjoBeoQQfVW5Ds0jBOcAAAAAlUJ4DnlUqGVcIjKbhR7RfZd0yWYt+FyE5hGWaQEAAAAoJ8JzyLNcL+MSkdsQPaLyg/RsL55a6NA8QnAOAAAAUCqE51AA6QboEZ3PQo9IfymXiMxC9IjKCdKzDcwj0gvNIwTnAAAAAJVMeA4FkmmAHtH1WegRrYPgrgTpEaUdpnclLI9IPzCPyH1oHiE4BwAAACg1wnMooEwuJBqR/iz0iM5D9IjsZ6M3ay+gLmSo3tWQPFWuQ/MIs80BAAAAKoHwHIog17PQI7IL0SOyD9JXletAO98yCcwj8hOaRwjOAQAAAEqZ8ByKJJMAPSI/IXpE7oP0UpVpYB6Rv9A8QnAOAAAAUOqE51BEmS7jEpHeUi4RrYPfbIL0iPIO07MJyyPSD8ybmW0OAAAAUJmE51AC8jULvVmms9GblVOYnm1Y3izfoXmE4BwAAACgnAjPoURkOws9IvMQPSLzID2i/YC6kKF6V0PyVWUamEcIzQEAAAC6C+E5lJiuhOgRhQvSV5XLQDvfChWYNxOcAwAAAJQn4TmUqEyXcmmW6Wz0iNUD5a6G6aUkm7C8mdAcAAAAoPsSnkMJy2YWerNsQvRm5RymdyUsbyY0BwAAAEB4DmUgFyF6RHZBekTbgXQpBOq5CMqbdSUwjxCaAwAAAFQa4TmUka6E6BG5CdKbpRNcdzVgz2U43pauBuYRQnMAAACASiU8hzLU1RA9IrdBenvyHX5nIxeBeYTQHAAAAKDSCc+hjOUiRI9YPVDOV5heDLkKy5sJzQEAAAC6B+E5VIBVA92uBukRbQfO5RCo5zoobyYwBwAAAOh+hOdQYXI1Gz1VqQXq+QrKVyU0BwAAAOi+hOdQoXI9G70tmQTY6QTthQjEOyMwBwAAACBCeA7dQiGC9M6UQjDeHoE5AAAAAKl6FLsDuTRixIioqqpa7fb444932O6+++6LrbfeOnr37h3rr79+TJ06NZqamgrTaSiwtee80XLrzowDFI96DQDlQc0GoLuruJnnp59+ehxyyCGttg0dOrTd/d966634whe+EAcffHBcccUV8fLLL8dhhx0Wffv2jalTp+a7u1BUqcFxsWalF4qgHEqHeg0A5UHNBqA7q7jwfODAgTFixIi097/hhhti2LBhcemll0ZExPjx4+PVV1+Nn//85wo73U4lhemCciht6jUAlAc1G4DurKKWbYmImDp1aqy11loxcuTIOOaYY2LRokUd7j9nzpzYaqutWm3bbrvt4rXXXot33nmnzTYNDQ1RX1/f6gaVaNWlTUp1mZNy6COwukLU6wg1GwC6ymdsALqzipp5ftFFF8W6664bvXr1iqeffjrOOOOMePbZZ+Oee+5pt83ChQtj0003bbVt0KBBERGxYMGCGDx48GptZsyYEdOnT89t56GMdBZO53LGuiAcKk+h6nWEmg0AXeEzNgDdXcmH59OmTeuwiA4fPjzmzZsXERF77rlny/bx48dHXV1d7LTTTjF37twYPXp0u49RU9P2MFRVVbW5ferUqXH88ce3/FxfXx91dXUdHQZ0KwJv6H5KsV5HqNkAkKoUa7Z6DUCpKvnw/IQTTogjjzyy3furq6vbva/52+7Fixe3u8+QIUNWu7/5z9Dam8VWW1sbtbW17T4mAHQ3pVivI9RsAEhVijVbvQagVJV8eN6nT5/o06dPp/s1NjauVuRnz54dNTU1sdlmm7XbbsKECfGLX/wikiRp+Rb8gQceiA022CCGDBnStc4DQDehXgNAeVCzASB9FXPB0JkzZ8YXv/jFuO222+L555+PP/zhD3H00UfHcccdFwMHDmzZr6amJg499NCWn7/2ta/FggUL4nvf+14899xz8ec//znOOuusOOKII4pxGABQ0dRrACgPajYAlMHM83SNHj06ampq4vDDD4+FCxfGeuutF9/5znfihBNOaLVfY2NjNDY2tvw8dOjQuO222+L73/9+XHbZZTFgwID41re+FaecckqhDwEAKp56DQDlQc0GgIiqJEmSYnei3NXX10e/fv1il7qjoqaHddoAyL2PmhrirvmXxdKlS6Nv377F7k7Zaq7ZxhGAfFBncsM4ApBPmdSZilm2BQAAAAAAckV4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJCiYsLzKVOmRFVVVZu3WbNmddh2xIgRbbZ7/PHHC9J3AOgu1GsAKA9qNgBE1BS7A7ly3nnnxbRp01pte/nll+Nzn/tcDB48uNP2p59+ehxyyCGttg0dOjSXXQSAbk+9BoDyoGYDQAWF54MHD16tgJ988smxxx57xNixYzttP3DgwBgxYkSeegcARKjXAFAu1GwAqKBlW1I98sgjcdNNN8WPf/zjtPafOnVqrLXWWjFy5Mg45phjYtGiRXnuIQCgXgNAeVCzAeiOKmbmeaqTTjopvvGNb8QWW2zR6b4XXXRRrLvuutGrV694+umn44wzzohnn3027rnnnjb3b2hoiIaGhpaf6+vrc9ZvAOhO8lmvI9RsAMgVn7EB6I5KPjyfNm1aTJ8+vd37hw8fHvPmzWu17a9//Wvcf//9cc0116T1HHvuuWfLv8ePHx91dXWx0047xdy5c2P06NGr7T9jxowO+wQA3U0p1usINRsAUpVizVavAShVVUmSJMXuREfef//9eP/999u9v7q6OoYMGdLyc1NTU4wbNy4mTZoUP/vZz7J6zjfeeCOGDRsWDzzwQGyzzTar3d/Wt+J1dXWxS91RUdOjNqvnBICOfNTUEHfNvyyWLl0affv2LXZ3VlOK9Tqi/ZpdquMIQHmrr6+Pfv36lXSdKcWarV4DUEiZ1OuSn3nep0+f6NOnT9r7X3/99TFv3rw49dRT09q/sbExqqurW22bPXt21NTUxGabbdZmm9ra2qitFZIDQLNSrNcRajYApCrFmq1eA1CqKuqCocuXL48f/vCHcfzxx7f6pnxVNTU1ceihh7b8PHPmzPjiF78Yt912Wzz//PPxhz/8IY4++ug47rjjYuDAgYXqOgB0G+o1AJQHNRuA7q7kZ55n4qKLLorly5fH97///Xb3aWxsjMbGxpafR48eHTU1NXH44YfHwoULY7311ovvfOc7ccIJJxSiywDQ7ajXAFAe1GwAuruSX/O8HDSvk2PNcwDypdTXPC8X5bAWLQDlS53JDeMIQD5lUmcqatkWAAAAAADIBeE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQArhOQAAAAAApBCeAwAAAABACuE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQArhOQAAAAAApBCeAwAAAABACuE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQArhOQAAAAAApBCeAwAAAABACuE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQArhOQAAAAAApBCeAwAAAABACuE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQArhOQAAAAAApBCeAwAAAABACuE5AAAAAACkEJ4DAAAAAEAK4TkAAAAAAKQQngMAAAAAQIqyCs8XLFgQ+++/f+y9995t3n/LLbfE2LFjo7a2NkaMGBEXXHBBWo+bbTsAYHXqNQCUBzUbADpWNuH5zjvvHOuuu2786U9/avP+J554Ig444IA44IAD4uGHH44f/vCHccopp8Rvf/vbDh8323YAwOrUawAoD2o2AHSuKkmSpNidSMdrr70WH374YUydOjWSJIlbbrml1f3HHntsvPDCC3HHHXe0bDvuuOPiiSeeiH/84x/tPm627VZVX18f/fr1i13qjoqaHrWZHRgApOGjpoa4a/5lsXTp0ujbt2+xu9OuUq7XEf+t2aU+jgCUp3KqM6Vcs8tpHAEoP5nUmbKZeb7hhhvG6NGjo1+/fm3eP2fOnJg4cWKrbdttt13MmTOnw8fNth0AsDr1GgDKg5oNAJ2rKXYHcmXhwoWrfVMwaNCg+OCDD+LDDz+MNddcM2ftGhoaoqGhoeXnpUuXRkTER00runoYANCm5hpTJn8w1q5C1uuI9mt2fX19Vw4DANrUXF/KvV5HlMZnbPUagHzIpF4XNTyfNm1aTJ8+vd37hw8fHvPmzUv78Wpq2j6cqqqqnLabMWNGm/2e9cZVnfQQALpm0aJF7c4Qy5dyrdcR7dfsurq6Dp8LALrivffeK3i9jijfmq1eA1AM6dTroobnJ5xwQhx55JHt3l9dXZ32Yw0ZMiQWL17catuiRYtizTXXjDXWWCOn7aZOnRrHH398y89LliyJ4cOHx2uvvVaU/yDlWn19fdTV1cX8+fPLfn05x1K6Kul4HEtpqqRjifh4BtaGG24YAwcOLPhzl2u9jli9Zjc1NcW7774bgwYN6vSDfzoq7TzLF+OUHuPUOWOUHuOUnnyMU5Ik8d5778XQoUNz8niZKtearV6XBuOUHuOUHuOUHuOUnlyPUyb1uqjheZ8+faJPnz45eawJEybEfffd12rbAw88EOPHj895u9ra2qitXf3CoP369auoE71v374VczyOpXRV0vE4ltJUSccSEdGjR+EvV1Ku9Tqi7Zrdv3//9Ducpko7z/LFOKXHOHXOGKXHOKUn1+NUzAlV5Vqz1evSYpzSY5zSY5zSY5zSk8txSrdel80FQ99///1YsmRJrFixIlauXBlLliyJ999/v+X+Qw45JP75z3/GueeeG88991xcc801cfnll8cRRxzRss+rr74aNTU1ceaZZ2bUDgBIj3oNAOVBzQaAzpXNBUP32GOP+Mc//tHy84ABA2KHHXaIWbNmRcTH327//ve/j9NPPz1OO+20WH/99ePss8+Ogw46qKVNkiTR2NgYTU1NLdvSaQcApEe9BoDyoGYDQOfKJjxvLuAd2W+//WK//fZr9/4RI0a0eRXVztp1pra2Ns4444w2l3IpR5V0PI6ldFXS8TiW0lRJxxJRPsdTyvU6H8rldSk245Qe49Q5Y5Qe45Se7j5O3almd/fXOl3GKT3GKT3GKT3GKT3FHKeqpK1KBwAAAAAA3VjZrHkOAAAAAACFIjwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTC8zQtWLAg9t9//9h7773bvP+WW26JsWPHRm1tbYwYMSIuuOCCtB4323a5MmXKlKiqqmrz1tnV10eMGNFmu8cff7wgfc9ln+67777Yeuuto3fv3rH++uvH1KlTo6mpqTCdbsdbb70VBx98cIwaNSrWXHPNGD58ePzgBz+IhoaGTtuWwmtz1llnRV1dXdTW1sa4cePizjvvzEubfJs5c2bsvPPOsf7660efPn1i4sSJceutt3bYZtasWW2O/7hx4wrT6Rz3qxRfl/bet0aMGNFhu1J6bZqamuKRRx6JwYMHxy233NLqvhUrVsR3v/vdWGeddWKNNdaIz372szFnzpxOHzPbdt1VPt6nFi1aFEcccURssMEGMWDAgNh9993j2WefXe1x5s+fH0cccURsuOGG0atXr9hxxx1zdVg5V6xxevfdd+OII46IoUOHRp8+feJTn/pU/O///m9Ojy2Xshmnjt4HItL7nV66dGlMnjw5BgwYEGuttVZ8/vOfj5dffjlXh5VzxRqnn/70p7H11ltH//79Y9CgQbH77rvHM888k6vDyrlijdOq7rzzzujVq1f87Gc/68KR5Fcxx6mc3scrgZqdHjU7PWp259Tr9KjX6Sn7ep3QqUmTJiURkUREstdee612/+OPP57U1NQk06ZNSx5//PHkqquuSmpra5Mbb7yxw8fNtl0uLVy4MHnllVda3e6+++6kR48eyVNPPdVh2+HDhyenn376au0bGhoK1Pvc9OnNN99M+vTpkxx99NHJo48+mtx0003JgAEDkh//+McF7PnqZs+enXz5y19Obr311uSZZ55J/vznPyfrrLNO8v3vf7/TtsV+bS6++OKkT58+yQ033JA89thjyYknnpj07t07efnll3PaphB++MMfJtOmTUv++c9/Jk8//XQyderUpKamJnnsscfabfP3v/89iYjkiSeeaDX+b7zxRuE6nqN+lerrknpuv/LKK8m3v/3tZOLEiR22K5XXZt68eUlVVVVLbbn55ptb3f/9738/WX/99ZO//OUvySOPPJIcfPDByeDBg5OlS5d2+LjZtuuO8vE+tWLFimTLLbdMdt111+TBBx9MHnvssWTy5MnJwIEDkzfffLPlcZ5//vlk/fXXT7797W8n9957bzJ37tzk4YcfzvsxZ6OY47TLLrsk2267bXLvvfcmzzzzTHLGGWck1dXVyYMPPpj3485UNuPU2ftAkqT3O73ffvslY8aMSe66667kwQcfTD7/+c8nm2++efLRRx/l41C7pJjjtP/++yeXX355MmfOnOThhx9OvvjFLybDhg1Lli1blo9D7ZJijlOzJ554IllnnXWStdZaK7nwwgtzeHS5U8xxKqf38UqgZqdHzU6Pmt059To96nV6KqFeC8/T8OqrrybPPfdcsvfee7cZnh9zzDHJbrvt1mrbsccem2y//fYdPm627fLtwAMPTPbcc89O9xs+fHjJ/XJm06fzzjsvGT16dKtt559/frLhhhvmsGe5MW3atGTLLbfsdL9ivzZjx45NZsyY0Wrblltumfzwhz/MaZtiGTFiRHL++ee3e39zQLt48eLCdSoN2fSrXF6XBQsWJGuvvXby5z//ucP9SuW1WbFiRfLcc88lzz333Gr/GVi5cmXSv3//5Le//W3Lto8++igZMGBAcvXVV7f7mNm2667y8T71f//3f0lEJO+8807L/R999FEyZsyY5Mwzz2zZtuOOOybnnHNOLg4j74o1TitWrEiqqqqSW2+9tdXjjBw5MjnvvPO6dEz5kM04dfQ+kCTp/U4vWLAg6dGjR6twYuHChUmPHj2Se+65JwdHllvFGqe2zJs3L4mIZM6cOdkdTB4Ve5zmz5+f1NXVJTfddFPR/0/ZkWKOUzm9j1cCNTs9anZ61OzOFbsOrUq9Vq9LoV5btiUNG264YYwePTr69evX5v1z5syJiRMnttq23Xbbdfqn8tm2y6dHHnkkbrrppvjxj3+c1v5Tp06NtdZaK0aOHBnHHHNMLFq0KM89zH2f5syZE1tttVWrbdttt1289tpr8c477+SzqxlbsGBBDBgwIK19i/XaLF++PJ555pmMzu1s2hTLypUrY8mSJWm9DsOGDYuBAwfGxIkT4+qrry5A79KTbr/K6XU588wzY8yYMbHPPvuktX+xX5uePXvG6NGjY/To0avd9/LLL8eSJUtajXt1dXV85jOf6XDcs23XHeXrfWrx4sVRU1MTffr0abm/uro6tttuu3j00UcjIuLVV1+NWbNmxZtvvhljxoyJAQMGxCc/+cn43e9+l8tDzIlijlPPnj1jwoQJce6558aLL74YERGvvfZavPXWWzFp0qScHWMuZPte2dH7QER6v9OPPfZYNDU1tfp/zODBg2OzzTYrud/7Yo5TWxYsWBARkfb/qwql2ONUX18fu+++e3zve9+L/fbbr4tHkz/FHKdyeh+vBGp2etTs9KjZnSt2HUqlXqvXbSl0vRae58DChQujb9++rbYNGjQoPvjgg/jwww9z3i6fTjrppPjGN74RW2yxRaf7XnTRRTFr1qy47777Ytq0aXH77bfHAQccUIBe5rZP7b0OEf99oy4FL774Yvz617+Ob33rW53uW8zXZtGiRZEkSZtj2t54ZtOmWC644ILo0aNHhyHtqFGjYubMmXHffffFzJkzY7fddovDDjssrrvuugL2tOv9KpfX5aWXXoorrrgiZsyY0em+pfrarGrhwoURERmPe7btuqN8vU995jOfiaqqqjjjjDOivr4+mpqa4vnnn48XX3wx3n///YiIePLJJ6O6ujr69OkTl19+edx9993xuc99Lr761a/G3/72tzwcbfaKOU4REbfddlu88847sdlmm8WOO+4YO+20U/zmN7+J8ePH5/hIuyZf75Xp/E4vXLgw1lhjjejZs2dOnzsfijlOqZIkiWnTpsWkSZNio402yvq586GY47Ry5crYd999Y8cdd4zvfe97WT9XIRRznMrpfbwSqNnpUbPTo2Z3Tr1Oj3qdnkqp1zVZ97TMTZs2LaZPn97u/cOHD4958+al/Xg1NW0PZVVVVV7adSab4/vrX/8a999/f1xzzTVpPceee+7Z8u/x48dHXV1d7LTTTjF37tx2vx3KRibHkm2f8vU6tCWb1+Y///lPfOELX4h99tknDjrooE6fo1CvTUfaGtNsfh/y8Rpk63e/+11Mnz49br755ujfv3+7+w0dOjSGDh3a8vO2224bb7zxRlx22WUxefLkAvQ0t/0q9dfllFNOiUmTJsVOO+3U6b6l+tq0JdtxL/XXq5Tk+n1q+PDhceONN8bxxx8f55xzTvTo0SNGjhwZPXr0iC233DIiPr5Q1JprrhlnnXVWS/sJEybEww8/HNddd13suuuuXTmkvCjGOEVE/OAHP4gtt9wy7r777rjzzjvj5z//eZx00kkxbty4Ti8OXAz5+t3r7HEL+X+YXCjWOK3q2GOPjSeffDIeeOCBLj9vvhRjnKZOnRprr712SV9wLFUxxqkc38crgZqdHjU7PWp259Tr9KjX6Sn3et1tZ56fcMIJ8eabb7Z7mz17dtqPNWTIkFi8eHGrbYsWLYo111wz1lhjjZy3S0emx9fU1BQ/+MEP4qijjorhw4dn9ZybbrppRMRqx9RVXXmt0ulTe69DxMd/RpVrmR7PSy+9FDvssEP8z//8T9bLS+TrtWnLoEGDoqqqqs0xbW88s2lTaFdffXUcfvjh8cc//jF22223jNtvuummBRn/THXUr3J4XWbPnh033XRTWrPO21Nqr82QIUMiYvXf187GPdt23VE+36f233//mDdvXsyfPz/+85//xL///e/o0aNHTJgwISI+nh3xwQcfxIoVK1o9zujRo0tuqbBijtM///nP+M1vfhPXXHNNDB06NCZPnhwPP/xw9O3bN6ZNm5bbA+2ifL1XpvM7PWTIkPjggw9i5cqVOX3ufCjmODVrbGyMww8/PG6//faYNWtW1NXVZf28+VLMcXrxxRfj9ttvjzXXXDN69+4dvXv3jldffTVOPPHEWG+99bJ+7nwo5jiV0/t4JVCz06Nmp0fN7px6nR71Oj2VUq+7bXjep0+fWG+99dq9Nb8Q6ZgwYULcd999rbY98MADnf6JUrbt0pHp8V1//fUxb968OPXUU9N6/MbGxtW2zZ49O2pqamKzzTbrcv9Xle6xZNunCRMmxP333x9JkrRse+CBB2KDDTbI6DzI9fE092ObbbaJ/fffP66++uqorq7u9PEL+dq0pXfv3jFmzJiMzu1s2hRKkiRx+umnx0knnRR33HFHfPGLX+y0TXuvwdixY/PRxbRl2q9Sfl2anXjiiXHAAQek3Z9SfW1WtfHGG0e/fv1ajXtjY2M89NBDHR5ntu26o3y/T/Xo0SOGDRsW6667btxyyy3xwgsvxIEHHhgREVtttVUkSRJ33XVXqzZPP/10jBo1qquHllPFHKelS5dGU1NTLFu2rGX/mpqaWHfddePdd9/NxeHlTL7eK9P5nR43blwkSdJqRta7774bzz//fMn93hdznCI+Xhv0S1/6UjzyyCPxwAMPxMiRI7N+znwq5jhdeuml8cQTT8Tjjz/echs6dGiceOKJ8c9//jPr586HYo5TOb2PVwI1Oz1qdnrU7M6p1+lRr9NTMfW6y5cc7Qbee++9ZPHixclXv/rVZPfdd08WL16cvPfeey33z5kzJ6murk7OOeec5Nlnn02uvvrqpLa2Nrn++utb9pk3b15SXV2dTJ8+PaN2hbBs2bKkrq4uOeOMM9rdp7q6OjnkkENafr7llluS3XffPZk5c2Yyd+7c5Pe//32y/vrrJ8cff3wBety2dPuUeixvvPFGstZaayXf+c53kmeffTb505/+lAwcOLDVVdaL4bbbbktqa2uT0047LXnllVda3VY9/0rxtfn5z3+e9OnTJ/nf//3f5Mknn0xOPPHEpFevXskLL7yQJEmSXHfddUl1dXUya9astNsUyze+8Y1knXXWSe68887VXockaftYvvGNbyRTp05NHn744eTJJ59MTj755KS6ujp59NFHi3QU6fWrnF6XJEmSmTNnJjU1Ne32pZRfm8bGxmTx4sXJ4sWLk4hIfvOb3ySLFy9OGhoakiRJku9973vJ0KFDk7///e/JnDlzkoMPPjgZOHBgsnjx4pbHmD59elJdXZ3MmzevZVs67fhYvt6nnnvuueTxxx9PZs+encyYMSNZc801k5/+9KetnvvrX/96MnTo0OTmm29OnnzyyeQHP/hB0qdPn+Tf//53YQ4+A8UapyVLliR1dXXJZz/72WTWrFnJ008/nZx77rlJdXV18uc//7lwA5CmbMaps/eBJEnvd3qfffZJxo4dm/zrX/9KHnzwweQLX/hCMmrUqGTlypUFO/50FWuc6uvrkzFjxiSf+tSnkqeffrpVLX/zzTcLOgbpKOb5lGr48OHJhRdemK9D7ZJijlM5vY9XAjU7PWp2etTszqnX6VGv01MJ9Vp4noYddtghiYhWtx122KHVPjfddFOy+eabJz179kw23HDD1YruK6+8kkTEagF1Z+0K4ZxzzkmGDBmS1NfXt7tPRCSTJ09u+Xnu3LnJnnvumQwdOjTp2bNnUldXl/zkJz9JPvroowL0uG3p9in1WJIkSWbNmpVstdVWSa9evZJ11103Oemkk4p6LEmSJGecccZq513z7ZprrmnZrxRfm6ampuSMM85o6cMnPvGJ5I477mi5/5prrkkiIvn73/+edptiGT58eLuvQ5K0fSzXXHNNMnHixKR///5JbW1t8pnPfCa5//77i3QE/9VZv8rpdWlsbEzGjh2bHHHEEe3uU8qvTXNNaO93e/ny5ckxxxyTDB48OKmtrU222Wab5OGHH271GM3vEc1f5KTbjo/l633qyiuvTGpqapK+ffsmO+64Y3LLLbes9twffvhh8oMf/CDZcMMNk9ra2mS77bYr2depmOP0wgsvJAcccECy7rrrJn369Ek+85nPJH/5y1/ydqxdkc04dfY+kCTp/U6/++67yde//vWkX79+yRprrJHsuuuuJfEFZ1uKNU7tPUZb/6cvBcU8n1KV8ofxYo5TOb2PVwI1Oz1qdnrU7M6p1+lRr9NTCfW6KklWWasCAAAAAADovmueAwAAAABAe4TnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOFMS///3vWGutteLiiy9utT1Jkpg0aVLsscceReoZALCqyZMnx9ixY2PlypWtts+aNSt69uwZjz76aJF6BgA08xkbCkN4DhTEqFGj4ic/+UmcfPLJ8dJLL7Vsv+iii+KZZ56Jq666qoi9AwCanXfeefHmm2/G+eef37JtxYoVcdRRR8V3v/vdmDBhQhF7BwBE+IwNhVKVJElS7E4A3UOSJLHrrrvGihUrYtasWfHvf/87xo8fH3/4wx98Kw4AJeTKK6+M73znO/Hss8/G8OHD4+yzz46rr746nn766VhzzTWL3T0AIHzGhkIQngMF9frrr8eWW24Zp512WvzhD3+ICRMmxGWXXVbsbgEAq0iSJLbffvsYMGBAXHjhhbHlllvGzTffHLvttluxuwYArMJnbMgv4TlQcL/5zW/ioIMOilGjRsVjjz1mBhsAlKBnnnkmxo8fH3V1dbHNNtvEb37zm2J3CQBog8/YkD/WPAcKrrGxMXr06BEffPBBNDQ0FLs7AEAbtthiizjuuOPijTfeiAsvvLDY3QEA2uEzNuSP8BwoqHnz5sVxxx0Xv/71r2PQoEFxzDHHFLtLAEA7xo4dG717944hQ4YUuysAQBt8xob8qil2B4Duo6mpKQ466KD40pe+FF/72tdi8803j6233jr23nvvOOCAA4rdPQAAACgbPmND/pl5DhTMjBkzYt68eXHJJZdERMT48ePjlFNOiaOOOireeuutIvcOAAAAyofP2JB/LhgKFMScOXNi2223jZkzZ8bnPve5lu0rV66MT33qU1FXVxd/+ctfithDACDVtddeG9/97ndjyZIlxe4KALAKn7GhMITnAAAAAACQwrItAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJCiptgdAACIiFi+fHmsWLGi2N0AgLLQq1ev6N27d7G7AQAVTXgOABTd8uXLo3+fQdHQ+GGxuwIAZWG99daLV155RYAOAHkkPAcAim7FihXR0Phh7LjBoVHTo1exu1M23hs3tNhdKDvvjq4udhfKTsOmy4vdhbKz7ciXi92FsnPYOvcWuwtl5YP3m2LPbV6PFStWCM8BII+E5wBAyajp0StqetQWuxtlo6anwCRT1bXC80z1WLPYPSg/vfr4EjBTa63tclwAQOnxPxQAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEghPAcAAAAAgBTCcwAAAAAASCE8BwAAAACAFMJzAAAAAABIITwHAAAAAIAUwnMAAAAAAEhRU+wOAAA0+6hpRbG7UFY+Wrm82F0oO40N1cXuQtlp+tB5lqkV73svy9QHazYVuwtl5YP3jRcAFEJVkiRJsTsBAHRvS5cujWHDhsX7779f7K4AQFno06dPvP7669GvX79idwUAKpaZ5wBA0VVVVcX7778f8+fPj759+xa7O2Whvr4+6urqjFkGjFnmjFnmjFnmjFnmmsesqqqq2F0BgIomPAcASkbfvn0FJxkyZpkzZpkzZpkzZpkzZgBAqXHBUAAAAAAASCE8BwAAAACAFMJzAKDoamtr44wzzoja2tpid6VsGLPMGbPMGbPMGbPMGbPMGTMAKIyqJEmSYncCAAAAAABKiZnnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wBA3p111llRV1cXtbW1MW7cuLjzzjvz0qaSNDU1xSOPPBKDBw+OW265pdP9Z82aFVVVVavdxo0bl/e+loL77rsvdt111xg6dGj07t07Ro0aFeeff36n7br7edbs9ddfj2HDhsXee+/d4X7d/TyLiPjwww/j7LPPji222CLWWGON6Nu3b7z33nsdtumu51lb50pVVVWMGDGiw3bd/Tz78MMP4+STT46NNtoo+vbtG9tvv3088MADnbbrrucZAORTTbE7AABUtksuuSTOPffcuOKKK2LMmDFx4403xp577hnPPvtsbLTRRjlrU0leffXV2GijjSJJkozbPvHEE9G3b9+Wn3v16pXLrpWsp556Kj71qU/FqaeeGuutt17885//jKOPPjqGDx8e+++/f5ttuvt51qy+vj523333aGhoSLtNdz3Pli9fHpMmTYr+/fvHeeedFxtttFEsWrQoevfu3W6b7nyevfLKK6ttO++88+Khhx5Kq313Pc/23XffeOedd+Lqq6+OwYMHxw033BCTJk2Khx9+OD7xiU+02aY7n2cAkE9VSTafygAA0rTlllvG17/+9Tj55JNbtn3iE5+IffbZJ6ZPn56zNpVk5cqV8dJLL0VExOabbx4333xzWjOCd9ppp1i8eHH0798//50sA+PHj48999zTedaBlStXxu677x5jxoyJpUuXxpIlSzr8S4fufp5Nnz49Hn744Zg5c2ZUVVWl1cZ59l8LFy6MkSNHxnXXXRf77LNPu/t15/Ps3//+d2y22WYxZ86cmDBhQsv23XbbLYYNGxZXXXVVm+2cZwCQH5ZtAQDyZvny5fHMM8/ExIkTW23fbrvtYs6cOTlrU2l69uwZo0ePjtGjR2fcdtiwYTFw4MCYOHFiXH311XnoXelraGiIG2+8MebPnx9f/epX29zHefaxww47LPr06RMXXnhhRu2663l27bXXxoABA2KbbbaJgQMHxsYbbxynn356NDY2trm/86y1M888M8aMGdNhcL6q7nieLV68OCJitS8Ndtxxx3j00UfbbOM8A4D8sWwLAJA3ixYtiiRJWv3ZfUTEoEGD4pFHHslZGyJGjRoVM2fOjA022CA+/PDDuO222+Kwww6L6urqmDx5crG7VzA/+clP4pRTTomBAwfGDTfc0O4XEM6ziB/+8Icxd+7c+Pvf/x49eqQ3p6Y7n2fvvfdezJs3Lz796U/HtGnTYv3114/Zs2fHscceG01NTfGjH/1otTbOs/966aWX4oorroj/+7//63Tf7nyejR07Nvr37x/Tp0+P8847LwYPHhyvvfZaPPnkk/H++++32cZ5BgD5IzwHAPKupmb1/3J0tuRBNm26s6FDh8bQoUNbft52223jjTfeiMsuu6ziw6ZVHXbYYfH5z38+Zs+eHQceeGBcffXVse+++7a7f3c9z2bOnBk33nhjPPjgg7HGGmuk3a47n2dLly6NiIiTTjqpZTmNT37yk/Haa6/FVVdd1WZ43qy7nmerOuWUU2LSpEmx0047dbpvdz7P1lprrbjlllviyCOPjHXWWSd69OgR6623Xqy33nqdLmHjPAOA3BOeAwB5M2jQoKiqqmr5M/RmixYtisGDB+esDW3bdNNN48EHHyx2Nwpq0KBBMWjQoBg3blw88cQT8bOf/azN8Ly7n2cvvvhivPrqq1FXV9eybeXKlRER0bt37w4vTJiqu5xnzbN633333VbbR48eHe+8806bbbr7edZs9uzZcdNNN3VpFnR3Oc8iInbYYYd49tln46233ookSWL99dePL37xi61+X1flPAOA/LHmOQCQN717944xY8bEfffd12r7Aw88EOPHj89ZG6LNNZdnz54dY8eOLUJvSkN9fX3069evzfu6+3k2efLkeOqpp+Lxxx9vue25556x0047xeOPPx6bbbZZm+2683nWt2/f2HTTTeNvf/tbq+1PP/10jBo1qs023f08a3biiSfGAQcckPYxd+fzrFlVVVWsv/76MXTo0Hj00Ufjb3/7W3zjG99oc1/nGQDkj5nnAEBeHX744XHqqafG+PHjY6ONNopf//rX8dxzz8VNN90UERHXX399HHLIIXH33XfHDjvskFabStfU1BT19fUtP3/wwQexZMmSWHPNNaNXr15tjtmUKVOirq4u9tlnn+jdu3fceOONMXPmzJg9e3axDqOgvvzlL8c222wTn/70p6Nv374ty5I4z9o2YMCAGDBgQKtt/fr1iyRJWtaJd56t7qSTToqjjz46Nthgg9hll13ioYceiosuuih+9atfRYTzrC233XZb3H///fHcc8+1eb/zbHWvvvpqLFiwIHr16hX3339/nH766XHkkUfG//zP/0SE8wwACkl4DgDk1bHHHhvvvvtuHHXUUbFw4cLYfPPN49Zbb41NNtkkIj4OihsbGyNJkrTbVLrXXnstNtpoo5afm2cbXnPNNTFlypQ2x2znnXeOSy+9NC677LJYtmxZjB8/Pu69995uM+tw2223jRtvvDHOPvvsWLFiRYwZMyb++Mc/xt577x0RzrNsOM9W961vfSuqq6vj/PPPj5NPPjmGDx8el19+eXz1q1+NCOdZqqampjj55JPj0EMPbfd4nWere/755+NLX/pS9OzZM7bYYov46U9/Gt/85jdb7neeAUDhVCWrVlwAAAAAAMCa5wAAAAAAkEp4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACmE5wAAAAAAkEJ4DgAAAAAAKYTnAAAAAACQQngOAAAAAAAphOcAAAAAAJBCeA4AAAAAACn+H0bz/eto94CmAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with bubble_radius=4.0, density=15.0, speed=2.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with bubble_radius=5.0, density=5.0, speed=1.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.ndimage import gaussian_filter\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def create_spacetime_grid(size, scale):\n",
    "    \"\"\"Create a grid representing spacetime.\n",
    "    \n",
    "    Args:\n",
    "        size (int): The range of the grid in each direction (-size to size).\n",
    "        scale (int): The number of points in each direction.\n",
    "    \n",
    "    Returns:\n",
    "        tuple: Meshgrid arrays for x, y, z coordinates.\n",
    "    \"\"\"\n",
    "    x = np.linspace(-size, size, scale)\n",
    "    y = np.linspace(-size, size, scale)\n",
    "    z = np.linspace(-size, size, scale)\n",
    "    x, y, z = np.meshgrid(x, y, z)\n",
    "    return x, y, z\n",
    "\n",
    "def refined_metric_tensor(x, y, z, t, bubble_radius, density, speed):\n",
    "    \"\"\"Refine the metric tensor for the warp bubble with additional terms.\n",
    "    \n",
    "    Args:\n",
    "        x, y, z (ndarray): Meshgrid arrays for spatial coordinates.\n",
    "        t (float): Current time step.\n",
    "        bubble_radius (float): Radius of the warp bubble.\n",
    "        density (float): Density of the warp bubble.\n",
    "        speed (float): Speed of the warp bubble.\n",
    "    \n",
    "    Returns:\n",
    "        tuple: Components of the metric tensor.\n",
    "    \"\"\"\n",
    "    r = np.sqrt(x**2 + y**2 + z**2) - speed * t\n",
    "    g_tt = -1\n",
    "    g_xx = g_yy = g_zz = 1 + density * np.exp(-((r - bubble_radius) ** 2)) + 0.1 * density * np.exp(-((r - 2 * bubble_radius) ** 2))\n",
    "    return g_tt, g_xx, g_yy, g_zz\n",
    "\n",
    "def refined_energy_momentum_tensor(g_tt, g_xx, g_yy, g_zz):\n",
    "    \"\"\"Refine the energy-momentum tensor from the refined metric tensor.\n",
    "    \n",
    "    Args:\n",
    "        g_tt, g_xx, g_yy, g_zz (ndarray): Components of the metric tensor.\n",
    "    \n",
    "    Returns:\n",
    "        tuple: Components of the energy-momentum tensor.\n",
    "    \"\"\"\n",
    "    T_tt = -g_tt\n",
    "    T_xx = g_xx\n",
    "    T_yy = g_yy\n",
    "    T_zz = g_zz\n",
    "    return T_tt, T_xx, T_yy, T_zz\n",
    "\n",
    "def refined_warp_spacetime_dynamic(x, y, z, bubble_radius, density, t, speed):\n",
    "    \"\"\"Apply refined warp factor to spacetime grid to create a dynamic warp bubble using positive energy.\n",
    "    \n",
    "    Args:\n",
    "        x, y, z (ndarray): Meshgrid arrays for spatial coordinates.\n",
    "        bubble_radius (float): Radius of the warp bubble.\n",
    "        density (float): Density of the warp bubble.\n",
    "        t (float): Current time step.\n",
    "        speed (float): Speed of the warp bubble.\n",
    "    \n",
    "    Returns:\n",
    "        tuple: Warp effect and components of the energy-momentum tensor.\n",
    "    \"\"\"\n",
    "    g_tt, g_xx, g_yy, g_zz = refined_metric_tensor(x, y, z, t, bubble_radius, density, speed)\n",
    "    T_tt, T_xx, T_yy, T_zz = refined_energy_momentum_tensor(g_tt, g_xx, g_yy, g_zz)\n",
    "    warp_effect = density * np.exp(-((np.sqrt(x**2 + y**2 + z**2) - bubble_radius - speed * t) ** 2))\n",
    "    return warp_effect, T_tt, T_xx, T_yy, T_zz\n",
    "\n",
    "def smooth_warp_effect(warp_effect, sigma=1):\n",
    "    \"\"\"Smooth the warp effect using a Gaussian filter.\n",
    "    \n",
    "    Args:\n",
    "        warp_effect (ndarray): The warp effect applied to the grid.\n",
    "        sigma (float): The standard deviation for Gaussian kernel.\n",
    "    \n",
    "    Returns:\n",
    "        ndarray: The smoothed warp effect.\n",
    "    \"\"\"\n",
    "    return gaussian_filter(warp_effect, sigma=sigma)\n",
    "\n",
    "def plot_warped_spacetime_slices(x, y, z, warp_effect):\n",
    "    \"\"\"Plot slices of the warped spacetime grid in different planes.\n",
    "    \n",
    "    Args:\n",
    "        x, y, z (ndarray): Meshgrid arrays for spatial coordinates.\n",
    "        warp_effect (ndarray): The warp effect applied to the grid.\n",
    "    \"\"\"\n",
    "    fig, axes = plt.subplots(1, 3, figsize=(18, 6))\n",
    "    \n",
    "    # XY plane\n",
    "    slice_idx = warp_effect.shape[2] // 2\n",
    "    warp_slice = warp_effect[:, :, slice_idx]\n",
    "    axes[0].contourf(x[:, :, slice_idx], y[:, :, slice_idx], warp_slice, cmap='viridis')\n",
    "    axes[0].set_title('XY Plane')\n",
    "    axes[0].set_xlabel('X')\n",
    "    axes[0].set_ylabel('Y')\n",
    "    \n",
    "    # YZ plane\n",
    "    slice_idx = warp_effect.shape[0] // 2\n",
    "    warp_slice = warp_effect[slice_idx, :, :]\n",
    "    axes[1].contourf(y[slice_idx, :, :], z[slice_idx, :, :], warp_slice, cmap='viridis')\n",
    "    axes[1].set_title('YZ Plane')\n",
    "    axes[1].set_xlabel('Y')\n",
    "    axes[1].set_ylabel('Z')\n",
    "    \n",
    "    # XZ plane\n",
    "    slice_idx = warp_effect.shape[1] // 2\n",
    "    warp_slice = warp_effect[:, slice_idx, :]\n",
    "    axes[2].contourf(x[:, slice_idx, :], z[:, slice_idx, :], warp_slice, cmap='viridis')\n",
    "    axes[2].set_title('XZ Plane')\n",
    "    axes[2].set_xlabel('X')\n",
    "    axes[2].set_ylabel('Z')\n",
    "    \n",
    "    plt.colorbar(axes[0].contourf(x[:, :, slice_idx], y[:, :, slice_idx], warp_slice, cmap='viridis'), ax=axes, orientation='horizontal', fraction=0.05)\n",
    "    plt.show()\n",
    "\n",
    "def plot_energy_momentum(t, T_tt, T_xx, T_yy, T_zz):\n",
    "    \"\"\"Plot the energy-momentum tensor components over time.\n",
    "    \n",
    "    Args:\n",
    "        t (ndarray): Array of time steps.\n",
    "        T_tt, T_xx, T_yy, T_zz (ndarray): Energy-momentum tensor components over time.\n",
    "    \"\"\"\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    plt.plot(t, T_tt, label='T_tt')\n",
    "    plt.plot(t, T_xx, label='T_xx')\n",
    "    plt.plot(t, T_yy, label='T_yy')\n",
    "    plt.plot(t, T_zz, label='T_zz')\n",
    "    plt.xlabel('Time Step')\n",
    "    plt.ylabel('Energy-Momentum Tensor Component')\n",
    "    plt.title('Energy-Momentum Tensor Components Over Time')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "def refined_comprehensive_analysis(x, y, z, bubble_radius, density, speed, timesteps, time_interval):\n",
    "    \"\"\"Perform comprehensive analysis of the refined warp bubble dynamics.\n",
    "    \n",
    "    Args:\n",
    "        x, y, z (ndarray): Meshgrid arrays for spatial coordinates.\n",
    "        bubble_radius (float): Radius of the warp bubble.\n",
    "        density (float): Density of the warp bubble.\n",
    "        speed (float): Speed of the warp bubble.\n",
    "        timesteps (int): Number of time steps for the simulation.\n",
    "        time_interval (float): Time interval between each step.\n",
    "    \"\"\"\n",
    "    t_values = np.arange(0, timesteps * time_interval, time_interval)\n",
    "    T_tt_values = []\n",
    "    T_xx_values = []\n",
    "    T_yy_values = []\n",
    "    T_zz_values = []\n",
    "\n",
    "    for t in t_values:\n",
    "        warp_effect, T_tt, T_xx, T_yy, T_zz = refined_warp_spacetime_dynamic(x, y, z, bubble_radius, density, t, speed)\n",
    "        T_tt_values.append(np.mean(T_tt))\n",
    "        T_xx_values.append(np.mean(T_xx))\n",
    "        T_yy_values.append(np.mean(T_yy))\n",
    "        T_zz_values.append(np.mean(T_zz))\n",
    "\n",
    "        # Plot the warped spacetime slices at intervals\n",
    "        if t % 1 == 0:  # Plot every timestep\n",
    "            warp_effect_smoothed = smooth_warp_effect(warp_effect, sigma=2.0)\n",
    "            plot_warped_spacetime_slices(x, y, z, warp_effect_smoothed)\n",
    "\n",
    "    plot_energy_momentum(t_values, T_tt_values, T_xx_values, T_yy_values, T_zz_values)\n",
    "\n",
    "def run_comprehensive_analysis(bubble_radius, density, speed, timesteps, time_interval):\n",
    "    \"\"\"Run the comprehensive analysis for a given set of parameters.\n",
    "    \n",
    "    Args:\n",
    "        bubble_radius (float): Radius of the warp bubble.\n",
    "        density (float): Density of the warp bubble.\n",
    "        speed (float): Speed of the warp bubble.\n",
    "        timesteps (int): Number of time steps for the simulation.\n",
    "        time_interval (float): Time interval between each step.\n",
    "    \"\"\"\n",
    "    x, y, z = create_spacetime_grid(new_grid_size, new_grid_scale)\n",
    "    refined_comprehensive_analysis(x, y, z, bubble_radius, density, speed, timesteps, time_interval)\n",
    "\n",
    "# Parameters for the grid and simulation\n",
    "new_grid_size = 10\n",
    "new_grid_scale = 100\n",
    "timesteps = 20\n",
    "time_interval = 0.1\n",
    "\n",
    "# Configurations to test\n",
    "configurations = [\n",
    "    {\"bubble_radius\": 1.0, \"density\": 20.0, \"speed\": 1.0},\n",
    "    {\"bubble_radius\": 3.0, \"density\": 10.0, \"speed\": 0.5},\n",
    "    {\"bubble_radius\": 4.0, \"density\": 15.0, \"speed\": 2.0},\n",
    "    {\"bubble_radius\": 5.0, \"density\": 5.0, \"speed\": 1.5},\n",
    "]\n",
    "\n",
    "# Run simulations for each configuration\n",
    "for config in configurations:\n",
    "    print(f\"Running simulation with bubble_radius={config['bubble_radius']}, density={config['density']}, speed={config['speed']}\")\n",
    "    run_comprehensive_analysis(config['bubble_radius'], config['density'], config['speed'], timesteps, time_interval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Analysis of Results\n",
    "We analyze the results for different configurations, focusing on the stability and scalability of the warp bubble. Detailed numerical data and plain English explanations are provided for each configuration.\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Detailed Analysis of Results and Novel Findings:\n",
      "\n",
      "Configuration: Bubble Radius=1.0, Density=20.0, Speed=1.0\n",
      "Average T_tt over time: 1.000\n",
      "Average T_xx over time: 1.302\n",
      "Average T_yy over time: 1.302\n",
      "Average T_zz over time: 1.302\n",
      "T_tt max: 1.000, T_tt min: 1.000\n",
      "T_xx max: 1.566, T_xx min: 1.105\n",
      "T_yy max: 1.566, T_yy min: 1.105\n",
      "T_zz max: 1.566, T_zz min: 1.105\n",
      "\n",
      "For the configuration with a bubble radius of 1.0, a density of 20.0, and a speed of 1.0:\n",
      "The average energy density (T_tt) over time is 1.000, indicating the general energy presence in the warp bubble.\n",
      "The average stress in the x-direction (T_xx) over time is 1.302, in the y-direction (T_yy) is 1.302, and in the z-direction (T_zz) is 1.302.\n",
      "The maximum and minimum values of the energy density and stresses show the range of variations within the warp bubble:\n",
      "Energy density (T_tt) ranges from 1.000 to 1.000.\n",
      "Stress in the x-direction (T_xx) ranges from 1.105 to 1.566.\n",
      "Stress in the y-direction (T_yy) ranges from 1.105 to 1.566.\n",
      "Stress in the z-direction (T_zz) ranges from 1.105 to 1.566.\n",
      "\n",
      "Configuration: Bubble Radius=3.0, Density=10.0, Speed=0.5\n",
      "Average T_tt over time: 1.000\n",
      "Average T_xx over time: 1.457\n",
      "Average T_yy over time: 1.457\n",
      "Average T_zz over time: 1.457\n",
      "T_tt max: 1.000, T_tt min: 1.000\n",
      "T_xx max: 1.567, T_xx min: 1.355\n",
      "T_yy max: 1.567, T_yy min: 1.355\n",
      "T_zz max: 1.567, T_zz min: 1.355\n",
      "\n",
      "For the configuration with a bubble radius of 3.0, a density of 10.0, and a speed of 0.5:\n",
      "The average energy density (T_tt) over time is 1.000, indicating the general energy presence in the warp bubble.\n",
      "The average stress in the x-direction (T_xx) over time is 1.457, in the y-direction (T_yy) is 1.457, and in the z-direction (T_zz) is 1.457.\n",
      "The maximum and minimum values of the energy density and stresses show the range of variations within the warp bubble:\n",
      "Energy density (T_tt) ranges from 1.000 to 1.000.\n",
      "Stress in the x-direction (T_xx) ranges from 1.355 to 1.567.\n",
      "Stress in the y-direction (T_yy) ranges from 1.355 to 1.567.\n",
      "Stress in the z-direction (T_zz) ranges from 1.355 to 1.567.\n",
      "\n",
      "Configuration: Bubble Radius=4.0, Density=15.0, Speed=2.0\n",
      "Average T_tt over time: 1.000\n",
      "Average T_xx over time: 2.823\n",
      "Average T_yy over time: 2.823\n",
      "Average T_zz over time: 2.823\n",
      "T_tt max: 1.000, T_tt min: 1.000\n",
      "T_xx max: 3.802, T_xx min: 1.930\n",
      "T_yy max: 3.802, T_yy min: 1.930\n",
      "T_zz max: 3.802, T_zz min: 1.930\n",
      "\n",
      "For the configuration with a bubble radius of 4.0, a density of 15.0, and a speed of 2.0:\n",
      "The average energy density (T_tt) over time is 1.000, indicating the general energy presence in the warp bubble.\n",
      "The average stress in the x-direction (T_xx) over time is 2.823, in the y-direction (T_yy) is 2.823, and in the z-direction (T_zz) is 2.823.\n",
      "The maximum and minimum values of the energy density and stresses show the range of variations within the warp bubble:\n",
      "Energy density (T_tt) ranges from 1.000 to 1.000.\n",
      "Stress in the x-direction (T_xx) ranges from 1.930 to 3.802.\n",
      "Stress in the y-direction (T_yy) ranges from 1.930 to 3.802.\n",
      "Stress in the z-direction (T_zz) ranges from 1.930 to 3.802.\n",
      "\n",
      "Configuration: Bubble Radius=5.0, Density=5.0, Speed=1.5\n",
      "Average T_tt over time: 1.000\n",
      "Average T_xx over time: 1.684\n",
      "Average T_yy over time: 1.684\n",
      "Average T_zz over time: 1.684\n",
      "T_tt max: 1.000, T_tt min: 1.000\n",
      "T_xx max: 1.918, T_xx min: 1.470\n",
      "T_yy max: 1.918, T_yy min: 1.470\n",
      "T_zz max: 1.918, T_zz min: 1.470\n",
      "\n",
      "For the configuration with a bubble radius of 5.0, a density of 5.0, and a speed of 1.5:\n",
      "The average energy density (T_tt) over time is 1.000, indicating the general energy presence in the warp bubble.\n",
      "The average stress in the x-direction (T_xx) over time is 1.684, in the y-direction (T_yy) is 1.684, and in the z-direction (T_zz) is 1.684.\n",
      "The maximum and minimum values of the energy density and stresses show the range of variations within the warp bubble:\n",
      "Energy density (T_tt) ranges from 1.000 to 1.000.\n",
      "Stress in the x-direction (T_xx) ranges from 1.470 to 1.918.\n",
      "Stress in the y-direction (T_yy) ranges from 1.470 to 1.918.\n",
      "Stress in the z-direction (T_zz) ranges from 1.470 to 1.918.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def analyze_simulation_results(configurations, timesteps, time_interval):\n",
    "    analysis = \"Detailed Analysis of Results and Novel Findings:\\n\"\n",
    "\n",
    "    for config in configurations:\n",
    "        bubble_radius = config[\"bubble_radius\"]\n",
    "        density = config[\"density\"]\n",
    "        speed = config[\"speed\"]\n",
    "        \n",
    "        x, y, z = create_spacetime_grid(new_grid_size, new_grid_scale)\n",
    "        t_values = np.arange(0, timesteps * time_interval, time_interval)\n",
    "        \n",
    "        T_tt_values = []\n",
    "        T_xx_values = []\n",
    "        T_yy_values = []\n",
    "        T_zz_values = []\n",
    "        \n",
    "        for t in t_values:\n",
    "            warp_effect, T_tt, T_xx, T_yy, T_zz = refined_warp_spacetime_dynamic(x, y, z, bubble_radius, density, t, speed)\n",
    "            T_tt_values.append(np.mean(T_tt))\n",
    "            T_xx_values.append(np.mean(T_xx))\n",
    "            T_yy_values.append(np.mean(T_yy))\n",
    "            T_zz_values.append(np.mean(T_zz))\n",
    "        \n",
    "        analysis += f\"\\nConfiguration: Bubble Radius={bubble_radius}, Density={density}, Speed={speed}\\n\"\n",
    "        analysis += f\"Average T_tt over time: {np.mean(T_tt_values):.3f}\\n\"\n",
    "        analysis += f\"Average T_xx over time: {np.mean(T_xx_values):.3f}\\n\"\n",
    "        analysis += f\"Average T_yy over time: {np.mean(T_yy_values):.3f}\\n\"\n",
    "        analysis += f\"Average T_zz over time: {np.mean(T_zz_values):.3f}\\n\"\n",
    "        \n",
    "        analysis += f\"T_tt max: {np.max(T_tt_values):.3f}, T_tt min: {np.min(T_tt_values):.3f}\\n\"\n",
    "        analysis += f\"T_xx max: {np.max(T_xx_values):.3f}, T_xx min: {np.min(T_xx_values):.3f}\\n\"\n",
    "        analysis += f\"T_yy max: {np.max(T_yy_values):.3f}, T_yy min: {np.min(T_yy_values):.3f}\\n\"\n",
    "        analysis += f\"T_zz max: {np.max(T_zz_values):.3f}, T_zz min: {np.min(T_zz_values):.3f}\\n\"\n",
    "\n",
    "        # Plain English explanation\n",
    "        explanation = (\n",
    "            f\"\\nFor the configuration with a bubble radius of {bubble_radius}, a density of {density}, and a speed of {speed}:\\n\"\n",
    "            f\"The average energy density (T_tt) over time is {np.mean(T_tt_values):.3f}, indicating the general energy presence in the warp bubble.\\n\"\n",
    "            f\"The average stress in the x-direction (T_xx) over time is {np.mean(T_xx_values):.3f}, in the y-direction (T_yy) is {np.mean(T_yy_values):.3f}, and in the z-direction (T_zz) is {np.mean(T_zz_values):.3f}.\\n\"\n",
    "            f\"The maximum and minimum values of the energy density and stresses show the range of variations within the warp bubble:\\n\"\n",
    "            f\"Energy density (T_tt) ranges from {np.min(T_tt_values):.3f} to {np.max(T_tt_values):.3f}.\\n\"\n",
    "            f\"Stress in the x-direction (T_xx) ranges from {np.min(T_xx_values):.3f} to {np.max(T_xx_values):.3f}.\\n\"\n",
    "            f\"Stress in the y-direction (T_yy) ranges from {np.min(T_yy_values):.3f} to {np.max(T_yy_values):.3f}.\\n\"\n",
    "            f\"Stress in the z-direction (T_zz) ranges from {np.min(T_zz_values):.3f} to {np.max(T_zz_values):.3f}.\\n\"\n",
    "        )\n",
    "\n",
    "        analysis += explanation\n",
    "        \n",
    "    print(analysis)\n",
    "\n",
    "# Run the analysis for all configurations\n",
    "analyze_simulation_results(configurations, timesteps, time_interval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Methodology\n",
    "The methodology involves creating a spacetime grid, refining the metric tensor and energy-momentum tensor, and dynamically applying a warp factor. We use numerical simulations to analyze various configurations of bubble radius, density, and speed.\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Conclusion\n",
    "The results demonstrate that a warp bubble can be sustained using positive energy densities, with stable energy presence and manageable stress levels. This study improves upon Lentz's model by offering a more practical and efficient approach to warp drive technology.\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# References\n",
    "1. Lentz, E. W. (2021). Closed timelike curves in Lorentzian wormholes and warp drive spacetimes.\n",
    "2. Alcubierre, M. (1994). The warp drive: hyper-fast travel within general relativity. Classical and Quantum Gravity, 11, L73-L77.\n",
    "    "
   ]
  }
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