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Commit a1ddd588 authored by Nicolas Ollinger's avatar Nicolas Ollinger
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qorleans

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=== Environnement Qiskit pour slides avec jupyter ===
<nicolas.ollinger@univ-orleans.fr>
** LOGICIELS REQUIS
Avant d'installer cet environnemennt, il est nécessaire de disposer :
- de jupyter notebook
- d'une installation de python avec virtualenv et pip
** INSTALLATION
Le script [genenv] crée un environnement virtuel dans le répertoire [qisenv] :
$ ./genenv
Ce script ajoute un noyau [qiskitenv] à jupyter et installe l'extension RISE.
** UTILISATION
Le script [gojupyter] exécute jupyter dans l'environnement virtuel.
notebooks/qistest.ipynb
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...@@ -8,10 +8,11 @@ ...@@ -8,10 +8,11 @@
} }
}, },
"source": [ "source": [
"# Informatique quantique : \n", "# Qubits et portes quantiques : \n",
"## programmation 101\n", "## premiers pas en informatique quantique\n",
"\n", "\n",
"### Nicolas Ollinger, LIFO, U. Orléans" "### Nicolas Ollinger, LIFO, U. Orléans\n",
"<img style=\"width:15%; height: auto;\" src=\"img/lifo.png\">"
] ]
}, },
{ {
...@@ -22,16 +23,105 @@ ...@@ -22,16 +23,105 @@
} }
}, },
"source": [ "source": [
"### Mesdames et messieurs 🦊\n", "## Mesdames et messieurs 🦊\n",
"\n", "\n",
"Tout ce que vous avez *toujours* voulu **savoir** sur les **_circuits_** quantiques 💾 sans _jamais_ oser le demander.\n", "Tout ce que vous avez *toujours* voulu **savoir** sur les **_circuits_** quantiques 💾 sans _jamais_ oser le demander.\n",
"\n", "\n",
"Et aussi $x=y+\\sqrt{z}$ !" "Et aussi $x=y+\\sqrt{z}$ !"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Lapin\n",
"\n",
"Write content using inline or external Markdown.\n",
" Instructions and more info available in the [readme](https://github.com/hakimel/reveal.js#markdown).\n",
" \n",
" $$\n",
" x \\otimes y = \\alpha \\left|001\\right> + \\beta \\left|10\\right> \\otimes \\left( \\frac{1}{\\sqrt{2}}\\left|0\\right> + \\frac{1}{\\sqrt{2}}i\\left|0\\right>\\right)\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## porte TOTO\n",
"$$\n",
"\\operatorname{TOTO}(x \\otimes y) = \\begin{pmatrix}\n",
"0 & 0 & 0 & \\color{red}{e^{i\\theta}} \\\\\n",
"1 & 0 & 0 & 0 \\\\\n",
"0 & 0 & 1 & 0 \\\\\n",
"0 & 1 & 0 & 0\n",
"\\end{pmatrix}\n",
"\\begin{pmatrix}\n",
"x_0 y_0 \\\\\n",
"x_0 y_1 \\\\\n",
"x_1 y_0 \\\\\n",
"x_1 y_1\n",
"\\end{pmatrix}\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## Mesure quantique (observation)\n",
"\n",
"<img style=\"width=100%; height=auto; margin: auto\" src=\"img/mesure.png\" />"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"## Mesure quantique d'un qubit particulier\n",
"\n",
"Partant d'un état $\\left|\\varphi\\right> = \\sum_x \\alpha_x\\left|x\\right>$, si on mesure le qubit numéro $i$, on observe la valeur $r$ avec la probabilité $p_r$ et le système change d'état :\n",
"\n",
"$$\n",
"\\sum_{x\\in\\left\\{0,1\\right\\}^n} \\alpha_x\\left|x\\right> \\underset{\\phantom{blop}p_r\\phantom{blop}}{\\longrightarrow}\n",
"\\frac{1}{\\sqrt{p_r}} \\sum_{x\\in\\left\\{0,1\\right\\}^n | x_i = r} \\alpha_x\\left|x\\right>\n",
"$$\n",
" \n",
"$$\n",
"\\mbox{avec}\\quad p_r = \\sum_{x\\in\\left\\{0,1\\right\\}^n | x_i = r}|\\alpha_x|^2\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"<img style=\"width: 85%; height: auto; margin: auto;\" src=\"img/qproc.jpg\" />"
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 11,
"metadata": { "metadata": {
"slideshow": { "slideshow": {
"slide_type": "slide" "slide_type": "slide"
...@@ -43,7 +133,7 @@ ...@@ -43,7 +133,7 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"\n", "\n",
"Total count are: {'00': 4902, '11': 5098}\n" "Total count are: {'00': 4935, '11': 5065}\n"
] ]
}, },
{ {
...@@ -53,17 +143,14 @@ ...@@ -53,17 +143,14 @@
"<Figure size 911.6x292.4 with 1 Axes>" "<Figure size 911.6x292.4 with 1 Axes>"
] ]
}, },
"execution_count": 1, "execution_count": 11,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"import numpy as np\n", "import numpy as np\n",
"from qiskit import(\n", "from qiskit import QuantumCircuit, execute, Aer\n",
" QuantumCircuit,\n",
" execute,\n",
" Aer)\n",
"from qiskit.visualization import plot_histogram\n", "from qiskit.visualization import plot_histogram\n",
"\n", "\n",
"# Use Aer's qasm_simulator\n", "# Use Aer's qasm_simulator\n",
...@@ -99,7 +186,7 @@ ...@@ -99,7 +186,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 12,
"metadata": { "metadata": {
"slideshow": { "slideshow": {
"slide_type": "slide" "slide_type": "slide"
...@@ -108,18 +195,18 @@ ...@@ -108,18 +195,18 @@
"outputs": [ "outputs": [
{ {
"data": { "data": {
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\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 504x360 with 1 Axes>" "<Figure size 504x360 with 1 Axes>"
] ]
}, },
"execution_count": 2, "execution_count": 12,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"# Plot a histogram\n", " # Plot a histogram\n",
"\n", "\n",
"plot_histogram(counts)" "plot_histogram(counts)"
] ]
...@@ -132,40 +219,31 @@ ...@@ -132,40 +219,31 @@
} }
}, },
"source": [ "source": [
"## Algorithme de Bernstein-Vazirani " "# Algorithme de Bernstein-Vazirani "
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 6,
"metadata": { "metadata": {
"slideshow": { "slideshow": {
"slide_type": "slide" "slide_type": "slide"
} }
}, },
"outputs": [ "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Total count are: {'1101': 1}\n"
]
},
{ {
"data": { "data": {
"image/png": 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fm8Pkvpu1M7d/AABgH+F/2o1hM2bM0KBBgypLsQodO3ZUdHS0kpOTqyxftGiRPB6PMjIyQhnTljz16yli+DCVzZot7z//qagZ0+Vp2MB0rJApysvWlS0TFFWnXpXl+/O/Uov27jtbrH///qYjIABMFmPHDJ2pdr5ijgFk9u/C5NfguUweA5P/FiGwmA8AAFZxxlgQFRQUaPPmzZo0adIFj+Xn5yspKUl169atXLZjxw699tpr6tOnTyhjXpLH4/Fr/eg17wY+REmJIu9JlefKKwO6WX8/t5r61euBubt1UV62DhflauEvYqssP11arOvueDIg+wjWMaiJ6r4vLqVHjx5atGiRX8+ZM2eOX+sj+B64baruu3VytY8NfLRm26jJeu/PunDZqRPl8ngia7aTIEof+pLu/HF6tY8F+xjs23NAHk/zmu0EQTVjzGpd32lQtY8F6uuguq8BSfo46wv1HG5+1njpl1+oc9sbqn0s2Mfg/95creQ7htRsJwgZf2cDyf/5gNkgfDz+/EJJZ+fZ8z92A7cfg+o+X46B+47B+by1eLcpzhgLooIC3w1tWrZsWWX5yZMnlZmZWeUyyjNnzuihhx7SggULqpRlblb+/ocq//+Wy3P7bSr761u1+gJ3sqJd69X77md077NfVvkVFV1fcS48Y+zNN980HQEBEBFhrpiKiIiwxYBg9BjYoBiEj8m/i0ibfB2Y/F6INLhvBBbzAQDAKs4YC6LYWN+ZPjk5ORoy5OyrkjNnzlRhYWGVG+9Pnz5dgwcPVvfu3S/Yjkn+llF13lsdkP2W/yNbZfPmK3LaM/LEx+vMz0fJm/WRPP36BmT7Uu2a5Jp4eKn1bRzel6vS49+rXfLtahzTpuryE4cV1+F66ztR8I5BTWzfvt2v9efMmeP3u7jOnj3br/URfHmfSXmfVP/Yxc7sqFBxZsjl1ruYiEjfuwSblrNWyt9Q/WPBPgYxza903YsMdvXlX33vEFmdYH8d3HDjdfL+wfzXwfpl0uGL3IA/2Mdg0JDb9Pgi88cAVfk7G0j+zwfMBuHjiRd8ZwpW/Fw7/2M3cPsxqO7z5Ri47xgEAsVYEHXo0EHJycmaMWOGmjVrptatWysjI0Pvvuu73LCiGPviiy/04Ycfat26dQbT2kf5lq0qm/G8In/9iCKSu0qS715jry+T599udsU7UhblZSuqbgM1b9utyvLCHZ+qUcxVatCkhaFkgDUNm5nbd4PAXo1daw04BpDU8ErpgKF92+XroMGVFy/GQrFvAAAAiUspgyoiIkIrVqxQUlKSxo8fr1GjRik2NlZpaWmKjIysvPH+2rVrtXPnTl1zzTW6+uqr9fnnn2vChAn6/e9/b/gzCD3vrn+pbPIzihz3n4r48U2VyyN++hPpyBF5sz4ymC50ivKyFdf+ekVEVu2uC3M/c+VllAgfjePcue9zXWEwh8l9o6rGLS+/TrDY5euAfw8AAIAdcMZYkCUkJGjt2rVVlt1///3q0qWL6tevL0l64okn9MQTT1Q+3r9/f6WnpyslJSWkWe3A0/5qRa9cfuHyevUUvfyNkOcxpe991Z/mf8uoBSFOYh/btm0zHQEBUL+JFF1POl0S+n1fYbCIOFejWMkTKXnLQr9vuxwDmP27sEspZPIY8L0QPpgPAABWccaYAevXr69yfzEAl7d8+YWFKZzH45HiOhvYb4TUIiH0+61ORJTUIj70+42MlmKvCf1+Ub0GTc2UMw2utE8pdEVLqX5TM/ttYGC/CA7mAwCAVRRjIVZcXKycnJwq70h5vnXr1rnybDHgUqZMmWI6AgKkjYH3GGmRINVtGPr9XsxVBo7Bj5KkqDqh3y8uzsT3QutuvoLaDjweM8fAxD4RPMwHAACruJQyxBo1aqSyMgPXzwCATTSKlZq1lQ7lh26fV/UI3b5qosn/396dh1lV2Pfj/9xZWGRTBARBRWQRRoZNjStLlIhLloZhosnX5PGx0S8MTxNNF7t8XbClRqn0yU9tNGlr8zSxhQGNbTWNpgJqmggxuCFSqwZHaURTFwyIzMzvjxswKOhcF61zIgAAIABJREFU7tw558x5vZ6HR+fMOfe+73Hu3A9vzzK8eDrbW7/soidMqIDgwx02LuK/1kS8++uueb7qHhGHH9c1z9VRh9dFPPfjiNadXfN8tQcV9zsAwG6OGAOgy407I6Kqumue6/CJEQcP75rn6qhCIWL87IjooiN3jjq+WEiSLtW1Ecee0XXPN3Zm8Rp/aVLbO2LMjK57vmPPLO53AIDdFGNAJtxyyy1JR6AT9Tk04pjTKv88PfsVy4A06j80YuSJlX+ePgMjRp1a+efhwBw2rmuufzdwZLEkTqPh9REDj6r88xw2LuKwlFxrkM5jPgCgXE6lBDKhrq4u6Qh0siOnRbz+UsTWZzu2/v1LSnv8qpqIiedF1PQsPVtXGXVyxBsvR/zvix1bv9R9UNMz4rhPRlT7tE+1Y2dHvP1qxNu/6tj6pf4c9OofUTcnPdcWe79CIaLu7Ii134vY8WbHtil1H/Q5NGLcmaVnI/3MBwCUyxFjQCbMmNGF59rQJQpVEcedF3Ho0Z3/2FU1EZM+k75TKN+vqiZi0u9EHDyi8x+7pmfElLkR/QZ3/mPTuXr0jpgyL+KggZ3/2L36RUxtjOjZt/MfuzP17FvM2atf5z/2QQMjpjQU9zPdj/kAgHIpxgBITPVvCqwRkzrvMXv1L/4F+9CRnfeYlVTTo1hgDR3feY950MCIaedHDDi88x6TyurVL+L4zxVvTNFZBhwecfwFEQcd3HmPWUkHHVzM25k/twOPjDj+/MoUbgBA9+DkCgASVVVdPJVs8NiIp38QseOtA3+sEZMjRk8vlk1ZUl0bcdy5xWtNbbwvYueB3qWwULzQ/qhTXGA8i3r0KR459tLjEf+1KqL13QN7nKrqiGNOjzhyavHIzCzp1b9YZG3+WcR/PxTRdoA38q6ujRgzs3j9srSeQgoApINiDMiEefPmJR2BCjv0qIiTLorY8lREy/qIt1/r2HZV1RGHjY84YnLxgvZZNmRMxCFHRLz8ZHEfbH+9Y9tV10YMnVDcB32dOplphULxCMrBx0S0PFYsyXa+3bFta3sXL7A/YlJE7wGVzVlJhaqIo04oFsUtj0W8/HjEuzs6tm2PPsUybMSk9J8+SucwHwBQLsUYkAmLFi1KOgJdoKZHxBFTikd+vfFSxP+2RLz5y4i3fvneRblre0ccdEhEv8Mi+h9WLBBqu9G1g2p7FY/6OnJa8aL8r/9mH2x75b2j6Wp7F+822e+wYhk4+Jh032SA0vXsG3HMqRFHnxTx2gvFmzS89cuIba9GvLOtuE6PPhF9Dy3+HAwYFnHoqO51o4XeAyLGTC8eAfnacxFvbPnNPnjtvbKwZ9+IvoN+sw8OL55CXVWdaGy6mPkAgHJ1o/EJ6M7mzp0bK1asSDoGXaRQKF6Q/rcvSr/7LnQzmpLJ1NUKheL1kX77mlN52wcUS57BxxT/7Lb752D6/GQydbXqmuLRY0PGvrds9z44/f8mk4n0MB8AUK6MXXkCyKsNGzYkHQEASBnzAQDlUowBAAAAkEuKMSATBg92RXEAYG/mAwDKpRgDMmHNmjVJRwAAUsZ8AEC5XHyfTrVz9tlJR0jcX38h6QTd00033RQLFy5MOgYAkCLmAwDK5YgxIBNuvvnmpCMAACljPgCgXIoxAAAAAHJJMQYAAABALinGgExobm5OOgIAkDLmAwDKpRgDAAAAIJcUY0AmNDQ0JB0BAEgZ8wEA5VKMAQAAAJBLijEAAAAAckkxBmRCU1NT0hEAgJQxHwBQLsUYkAkLFy5MOgIAkDLmAwDKpRgDMmH69OlJRwAAUsZ8AEC5FGNAJowcOTLpCABAypgPACiXYgzIhLVr1yYdAQBIGfMBAOVSjAEAAACQS4oxAAAAAHJJMQZkQnNzc9IRAICUMR8AUC7FGAAAAAC5pBgDMqGhoSHpCABAypgPACiXYgwAAACAXFKMAQAAAJBLijEgE5qampKOAACkjPkAgHIpxoBMWLhwYdIRAICUMR8AUK6apAMAdMT06dNjzZo1ScfosB733Zt0hA7ZOfvspCPQzXkvAJWUtfkAgPRxxBiQCVu3bk06AgCQMuYDAMqlGAMAAAAglxRjQCZMmDAh6QgAQMqYDwAol2IMyIQVK1YkHQEASBnzAQDlUowBmXDllVcmHQEASBnzAQDlUowBmbB8+fKkIwAAKWM+AKBcijEAAAAAckkxBgAAAEAuKcaATFi9enXSEQCAlDEfAFAuxRiQCU899VTSEQCAlDEfAFAuxRiQCQsWLEg6AgCQMuYDAMqlGAMAAAAglxRjAAAAAORSTdIBADrimmuuSToCCWhri3j12YgX17+37KHbIoaOjxheH9F7QHLZAEie+QCAcinGgExobGxMOgJdbNvWiPUrI3a8FRGF95bveDPihZ8W/xx1QsTo6RGFwn4fBoBuzHwAQLmcStkF2traYsmSJTFmzJjo1atXTJo0KVavXh3jxo2LSy65JOl4kAnjx49POkKXa9++Pd6dd360rXnovWXvvBO7vvq12LXoL6K9rS3BdJW17dWItXdE7Nj2mwXt+17vF2sjNt4f0b6f79M95Pm9AHy4PM4HAHQuxVgXuPjii+Paa6+NSy+9NO69995obGyMCy64IJ577rmYNm1a0vGAlCr07h1VDXOj9bvfi/b29mhvbY3WP//LiNraqL7iD6NQ1T1/hbe3RzzxLxGt78Z+C7Hf9tJjEVufrXgsEpTX9wIAAJXnVMoKu+OOO+L222+PVatWxYwZMyIiYtasWfHoo4/GypUrY+rUqQknBNKs6lOfjLbmldH+4MPRtnZdtL/6atQsuT4KPWqTjlYx//tixNuvlbBBIeLFRyOGjKlYJFIgj+8FAAAqTzFWYYsXL445c+bsKcV2Gz16dNTW1kZ9fX1ERMycOTN+8YtfxIABxStJz5kzJ6677rouzwtpNXPmzKQjJKLQu1dUzZsbrUtujDjk4Kj567+KQp+Dko5VUS89HsVrinX09Mj2Ypn26/+NOOiQCgYjUXl8LwAfLa/zAQCdRzFWQS0tLfHkk0/GZZdd9oHvbd68Oerq6qJnz557lt1www3R0NDQlRE/UsEVramQfb0vPsyUKVPitttuK2mbpUuXlrR+Z6r94T2d+4A7dkT15xqjcEjnNj9pfI/f8tWfxZjhpR9NO/Pks2PtMz+oQKL0uO+GYluYxv9u++O90Pmy+HPQ2eyD7qnU2SCi9PkgydmAzvVH190aEe/9Hnj/13mQ932wr9drH+RvH7xf+wFcfNhFOSqopaUlIiKGDh261/Lt27fH6tWrnUYJJbjrrruSjpCItvv/I9r+eVkUzvpEtN75/QP6RZ811VUH9v9saqqdUted5fG9AHy0vM4HAHQeR4xV0KBBgyIiYtOmTXHOOefsWX799dfHli1bPnDh/T/90z+Na665JkaNGhXXXnvtntMsk+QvHlTKxo0bS1p/6dKlJd/F9cYbbyxp/c7U4757y36MtkfWRutNN0f1oqujMGZM7PriRdG+5sEozJjeCQmL0vge//mKiNdeiI6fSvkbP/jR3dF/6Eevl2X3Lyn+M43/3fbHe6HzZfHnoLPZB91TqbNBROnzQZKzAZ3riq8XjxTc/Xvg/V/nQd73wb5er32Qv33QGRRjFTRq1Kior6+PxYsXx8CBA2P48OHR3Nwc99xTPK3kt4ux73znO3HEEUdEoVCIf/qnf4qzzjornn322ejTp09S8YEEtT21IVoXXxfVf/C1qKqfGBFRvL7SP94RhdNP69Z34Rs2IeK150vb5qBDIvodVpk8JCvP7wUAACrPNFlBVVVVsXz58qirq4v58+fHRRddFIMGDYqmpqaorq7e64iwI488cs85wOeff3706NEjnnnmmaSiAwlqf/6FaL3y6qi+9MtRdeope5ZXfeq8iDfeiPY1DyaYrvKGjImo7VXaNkdMicjpZRS6tby/FwAAqDxHjFXY2LFj44EHHthr2YUXXhgTJkyI3r17R0TEjh07Ytu2bXtOvfzRj34Ub731VowePbrL80JaPf3000lH6DKFo0dG7YplH1zeq1fULvtel+fpalU1Ecd+IuKJuzu2fv9hEYdPrGwmklE4Ot/vBeCj5Wk+AKAyHDGWgHXr1u11GuWbb74ZZ511VkycODEmTZoUV199ddx9993Rv3//BFNCuixb9sG/HNN9HTY2ou7siNjfUWC/WT7g8Igpn41w3X2AfDIfAFAuR4x1sW3btsWmTZtiwYIFe5YNGTIkfvaznyWYCtLvqquuisbGxqRj0IWG1RWPBmtZH/HyExGt7773vQHDiqdPDhkbUVWdXEYAkmU+AKBcirEu1rdv32htbU06BkAm9BkYMe7jEaNPj9jxVkTbroja3hG9+iWdDAAA6A4UYwCkXnVtsSQDAADoTK4xBmTCLbfcknQEACBlzAcAlEsxBmRCXV1d0hEAgJQxHwBQLsUYkAkzZsxIOgIAkDLmAwDKpRgDAAAAIJcUYwAAAADkkmIMyIR58+YlHQEASBnzAQDlUowBmbBo0aKkIwAAKWM+AKBcijEgE+bOnZt0BAAgZcwHAJRLMQZkwoYNG5KOAACkjPkAgHIpxgAAAADIJcUYkAmDBw9OOgIAkDLmAwDKpRgDMmHNmjVJRwAAUsZ8AEC5apIOANARN910UyxcuDDpGB22c/bZSUeAVPBeACopa/MBAOnjiDEgE26++eakIwAAKWM+AKBcijEAAAAAckkxBgAAAEAuKcaATGhubk46AgCQMuYDAMqlGAMAAAAglxRjQCY0NDQkHQEASBnzAQDlUowBAAAAkEuKMQAAAABySTEGZEJTU1PSEQCAlDEfAFAuxRiQCQsXLkw6AgCQMuYDAMqlGAMyYfr06UlHAABSxnwAQLkUY0AmjBw5MukIAEDKmA8AKJdiDMiEtWvXJh0BAEgZ8wEA5VKMAQAAAJBLijEAAAAAckkxBmRCc3Nz0hEAgJQxHwBQLsUYAAAAALmkGAMyoaGhIekIAEDKmA8AKJdiDAAAAIBcUowBAAAAkEuKMSATmpqako4AAKSM+QCAcinGgExYuHBh0hEAgJQxHwBQLsUYkAnTp09POgIAkDLmAwDKpRgDMmHr1q1JRwAAUsZ8AEC5FGMAAAAA5JJiDMiECRMmJB0BAEgZ8wEA5VKMAZmwYsWKpCMAACljPgCgXIoxIBOuvPLKpCMAACljPgCgXIoxIBOWL1+edAQAIGXMBwCUSzEGAAAAQC4pxgAAAADIJcUYkAmrV69OOgIAkDLmAwDKpRgDMuGpp55KOgIAkDLmAwDKpRgDMmHBggVJRwAAUsZ8AEC5FGMAAAAA5JJiDAAAAIBcqkk6AEBHXHPNNUlHgETseidiy4aIlvXvLVt1U8SwCREjJkf0GZhcNoCkmQ8AKJdiDMiExsbGpCNAl3vthYjH745o3bn38l07Il58tPjnyGkRY2ZGFApJJARIlvkAgHI5lbILtLW1xZIlS2LMmDHRq1evmDRpUqxevTrGjRsXl1xySdLxIBPGjx+fdAToUr/aHLF+ZUTrux++3uafRTzzo4j29q7JBZAm5gMAyuWIsS5w8cUXx8qVK+P//b//F9OmTYsf//jHccEFF8TWrVvj8ssvTzoeACnTtiviiX/5TdnVgcKrZX3E4GMiDj264tEAAKBbUYxV2B133BG33357rFq1KmbMmBEREbNmzYpHH300Vq5cGVOnTk04IQBp88p/Rby7vYQNChEv/lwxBgAApXIqZYUtXrw45syZs6cU22306NFRW1sb9fX1ERGxc+fOuPzyy2PMmDExceLEmD59ehJxIbVmzpyZdAToMi89HhGlXDOsPeLV5yLe2VapRADpZD4AoFyOGKuglpaWePLJJ+Oyyy77wPc2b94cdXV10bNnz4iI+JM/+ZN46623YuPGjVFdXR1btmzp6rj7VHA1ZypkX++LDzNlypS47bbbStpm6dKlJa0PafG9P90cgw8+ouTtphx3cjz9i59UIBFpct8NxfNr8/wZbR90T6XOBhGlzwdmg+7jj667NSLe+z3w/q/zIO/7YF+v1z7I3z54v/YDuPCuI8YqqKWlJSIihg4dutfy7du3x+rVq/ecRvnrX/86br311rjhhhuiuro6IiKGDRvWtWEh5e66666kI0CXOdBBpqrgYx3IF/MBAOVyxFgFDRo0KCIiNm3aFOecc86e5ddff31s2bIlpk2bFhERzz77bAwYMCBuvPHG+MEPfhBVVVVx+eWXp+L20wfStkJHbNy4saT1ly5dWvJdXG+88caS1oe0WPu9iDe2RIcuvL/Xdusfjt4DKhKJFLl/SfGfef6Mtg+6p1Jng4jS5wOzQfdxxdeLRwru/j3w/q/zIO/7YF+v1z7I3z7oDIqxCho1alTU19fH4sWLY+DAgTF8+PBobm6Oe+65JyJiTzG2a9eueOmll2LYsGHxyCOPxAsvvBCnnHJKjBkzJqZMmZLkSwAgAYcfF/HGyyVsUIg4ZEQoxQAAoETOuaigqqqqWL58edTV1cX8+fPjoosuikGDBkVTU1NUV1fvufD+kUceGRERX/rSlyIiYuTIkXHqqafGI488klh2AJIz9NiI6h4lbNAeMcL/RwEAgJIpxips7Nix8cADD8Tbb78dmzdvjmuvvTaeeOKJmDBhQvTu3TsiiqdczpkzJ/7t3/4tIiJee+21eOSRR2LSpElJRodUefrpp5OOAF2mukfEhLM6vv6QsRFDxlQuD0BamQ8AKJdiLAHr1q3bcxrlbt/85jfj1ltvjYkTJ8aMGTPiiiuuiJNOOimhhJA+y5YtSzoCdKnDxkXUnROx3+vpF95b77hzInJ64yEg58wHAJTLNca62LZt22LTpk2xYMGCvZYfddRRcf/99yeUCtLvqquuSsUNKaArDZsQcfDwiJcej3jpsYh3dxSXFwoRg8dEjJgcccgRSjEgv8wHAJRLMdbF+vbtG62trUnHACAjeg+IGH16xKhTI97dHtHeFlHbK6K6NulkAACQfYoxAMiAqqqInn2STgEAAN2La4wBmXDLLbckHQEASBnzAQDlUowBmVBXV5d0BAAgZcwHAJRLMQZkwowZM5KOAACkjPkAgHIpxgAAAADIJcUYAAAAALmkGAMyYd68eUlHAABSxnwAQLkUY0AmLFq0KOkIAEDKmA8AKJdiDMiEuXPnJh0BAEgZ8wEA5VKMAZmwYcOGpCMAACljPgCgXIoxAAAAAHJJMQZkwuDBg5OOAACkjPkAgHIpxoBMWLNmTdIRAICUMR8AUC7FGJAJN910U9IRAICUMR8AUC7FGJAJN998c9IRAICUMR8AUC7FGAAAAAC5pBgDAAAAIJcUY0AmNDc3Jx0BAEgZ8wEA5VKMAQAAAJBLijEgExoaGpKOAACkjPkAgHIpxgAAAADIJcUYAAAAALmkGAMyoampKekIAEDKmA8AKJdiDMiEhQsXJh0BAEgZ8wEA5VKMAZkwffr0pCMAACljPgCgXIoxIBNGjhyZdAQAIGXMBwCUSzEGZMLatWuTjgAApIz5AIByKcYAAAAAyCXFGAAAAAC5pBgDMqG5uTnpCABAypgPACiXYgwAAACAXFKMAZnQ0NCQdAQAIGXMBwCUSzEGAAAAQC4pxgAAAADIJcUYkAlNTU1JRwAAUsZ8AEC5FGNAJixcuDDpCABAypgPAChXTdIBADpi+vTpsWbNmqRjdFiP++5NOkKH7Jx9dtIRAHLB50JlZG0+ACB9HDEGZMLWrVuTjgAApIz5AIByKcYAAAAAyCXFGJAJEyZMSDoCAJAy5gMAyqUYAzJhxYoVSUcAAFLGfABAuRRjQCZceeWVSUcAAFLGfABAuRRjQCYsX7486QgAQMqYDwAol2IMAAAAgFxSjAEAAACQS4oxIBNWr16ddAQAIGXMBwCUSzEGZMJTTz2VdAQAIGXMBwCUSzEGZMKCBQuSjgAApIz5AIByKcYAAAAAyCXFGABARrS3/9a/tyWXAwCgu6hJOgBAR1xzzTVJRwBIzK//N6LlsYiXH39v2ar/L2LYcREjJkX0HZRcNkiS+QCAcinGgExobGxMOgJAIn6xLuK/Vn1weeu7ES0/L/45+uSIUadEFApdHg8SZT4AoFxOpewCbW1tsWTJkhgzZkz06tUrJk2aFKtXr45x48bFJZdcknQ8yITx48cnHaHLtW/fHu/OOz/a1jz03rJ33oldX/1a7Fr0F9He5jwq6O42/2zfpdj7Pf+fEc/9uOJxSJjPhQ/K43wAQOdSjHWBiy++OK699tq49NJL4957743Gxsa44IIL4rnnnotp06YlHQ9IqULv3lHVMDdav/u9aG9vj/bW1mj987+MqK2N6iv+MApVfoVDd7bjzYhNqzq+/vP/GbFta8XikAI+FwCg8zmVssLuuOOOuP3222PVqlUxY8aMiIiYNWtWPProo7Fy5cqYOnVqwgmBNKv61CejrXlltD/4cLStXRftr74aNUuuj0KP2qSjARXW8nhEtH/kantv81jEsWdWJA4p4XMBADqXYqzCFi9eHHPmzNlTiu02evToqK2tjfr6+nj99ddj5syZe763c+fOePrpp+Pxxx+PiRMndnFiSKfffo/kSaF3r6iaNzdal9wYccjBUfPXfxWFPgclHQvoAr99of0Ob/NkxNhZEVXVnZ+HdPC5sLe8zgcAdB7FWAW1tLTEk08+GZdddtkHvrd58+aoq6uLnj17Rs+ePWP9+vV7vved73wnbrzxxlSUYgVX8aVC9vW++DBTpkyJ2267raRtli5dWtL6nan2h/d07gPu2BHVn2uMwiGHdOrDeo9DOlVX1cQPvv5uydu17Yo4dMCQeP3t7n1O5X03FA+ly9LvMJ8LH63U2SCi9PkgydmAzvVH190aEe/9zL7/6zzI+z7Y1+u1D/K3D96vvb3Ew+3DNcYqqqWlJSIihg4dutfy7du3x+rVq/d7GuW3vvUtF+WH97nrrruSjpCItvv/I9r+eVkUzvpEtN75/QP6RQ/kS3up51+SKT4X9pbX+QCAzuOIsQoaNGhQRERs2rQpzjnnnD3Lr7/++tiyZcs+L7y/cePGePTRR+Nf//Vfuyznh8n7sEXlbNy4saT1ly5dWnJhfOONN5a0fmfqcd+9ZT9G2yNro/Wmm6N60dVRGDMmdn3xomhf82AUZkzvhIRF3uOQXmv+JmLn26VtU10b8as3t0Z3vwb7/UuK/8zS7zCfCx+t1NkgovT5IMnZgM51xdeLRwru/pl9/9d5kPd9sK/Xax/kbx90BsVYBY0aNSrq6+tj8eLFMXDgwBg+fHg0NzfHPfcUD6XfVzF22223RWNjYwwYMKCr4wIp0vbUhmhdfF1U/8HXoqq+eFp11by50fqPd0Th9NPceQxyYHh98U6TpTj8uOj2pVhe+VwAgMrwCVpBVVVVsXz58qirq4v58+fHRRddFIMGDYqmpqaorq6O+vr6vdZ/55134jvf+Y7TKCHn2p9/IVqvvDqqL/1yVJ16yp7lVZ86L+KNN6J9zYMJpgO6yvD6iCjx8iAjJlckCgnzuQAAleOIsQobO3ZsPPDAA3stu/DCC2PChAnRu3fvvZbfeeedMWzYsDj55JO7MiJkwtNPP510hC5TOHpk1K5Y9sHlvXpF7bLvdXkeIBm9+kUce0bExvs7tv4xp0f0ObSymUhG4WifC/uTp/kAgMpwxFgC1q1bt8/TKL/1rW/Fl7/85QQSQfotW/bBvxAAdHcjJkcce2Z85JFjo6dHjDyxSyJBqpgPACiXYqyLbdu2LTZt2rTPO1L+6Ec/it/7vd9LIBWk31VXXZV0BIBEjJgccdqXI44+KaLHQe8tr+0VcdQJEaf8brEUy+ld2ck58wEA5XIqZRfr27dvtLa2Jh0DAMiQXv0jjjmt+KdtV0R7e/EOlAAAlEcxBgCQIVWmNwCATuNUSiATbrnllqQjAAApYz4AoFyKMSAT6urqko4AAKSM+QCAcinGgEyYMWNG0hEAgJQxHwBQLsUYAAAAALmkGAMAAAAglxRjQCbMmzcv6QgAQMqYDwAol2IMyIRFixYlHQEASBnzAQDlUowBmTB37tykIwAAKWM+AKBcijEgEzZs2JB0BAAgZcwHAJRLMQYAAABALinGgEwYPHhw0hEAgJQxHwBQLsUYkAlr1qxJOgIAkDLmAwDKVZN0AICOuOmmm2LhwoVJx+iwnbPPTjoCACnic6EysjYfAJA+jhgDMuHmm29OOgIAkDLmAwDKpRgDAAAAIJcUYwAAAADkkmIMyITm5uakIwAAKWM+AKBcijEAAAAAckkxBmRCQ0ND0hEAgJQxHwBQLsUYAAAAALmkGAMAAAAglxRjQCY0NTUlHQEASBnzAQDlUowBmbBw4cKkIwAAKWM+AKBcijEgE+bPn590BAAgZcwHAJRLMQZkwqpVq5KOAACkjPkAgHIpxgAAAADIJcUYAAAAALmkGAMyobm5OekIAEDKmA8AKJdiDAAAAIBcUowBmdDQ0JB0BAAgZcwHAJRLMQYAAABALinGAAAAAMglxRiQCU1NTUlHAABSxnwAQLkUY0AmLFy4MOkIAEDKmA8AKJdiDMiE6dOnJx0BAEgZ8wEA5apJOgBAR2zdujXpCCXpcd+9SUfokJ2zz046AkAu+FyojKzNBwCkjyPGAAAAAMglxRiQCRMmTEg6AgCQMuYDAMqlGAMyYcWKFUlHAABSxnwAQLkUY0AmXHnllUlHAABSxnwAQLkUY0AmLF++POkIAEDKmA8AKJdiDAAAAIBcUowBAAAAkEuKMSATVq9enXQEACBlzAcAlEsxBmTCU089lXQEACBlzAcAlEsxBmTCggULko4AAKSM+QCAcinGAAAAAMglxRgAAAAAuaQYAzLhmmuuSToCACmwa+d7/966c//rkQ/mAwDKVZN0AICOaGxsTDoCAAlpb4944+WIlvURv3ygfl2iAAASx0lEQVTmveWrb44YOj5ixOSI/kOTy0dyzAcAlMsRY0AmjB8/PukIACSgvS3imf+IWHdHxP9sLH69W1trxMtPRTzyjxH//VCxQCNfzAcAlEsx1gXa2tpiyZIlMWbMmOjVq1dMmjQpVq9eHePGjYtLLrkk6XhASrVv3x7vzjs/2tY89N6yd96JXV/9Wuxa9BfR3tb2IVsDdA+bHoho+flvvthX8fWbZc//JOL5/+yqVMnwuQAAnU8x1gUuvvjiuPbaa+PSSy+Ne++9NxobG+OCCy6I5557LqZNm5Z0PCClCr17R1XD3Gj97veivb092ltbo/XP/zKitjaqr/jDKFT5FQ50b29siXjx5x+93m7P/Tji169XLk/SfC4AQOdzjbEKu+OOO+L222+PVatWxYwZMyIiYtasWfHoo4/GypUrY+rUqQknhGyYOXNm0hESUfWpT0Zb88pof/DhaFu7LtpffTVqllwfhR61SUcDqLiWxyKiEPs+Umw/XlofMWZmhQKlgM+FveV1PgCg8/jfShW2ePHimDNnzp5SbLfRo0dHbW1t1NfXR0TEqlWr4oQTTojJkyfH+PHjY8mSJUnEhdT6m7/5m6QjJKLQu1dUzZsbrUtujPbHH4+axddGoc9BSccCqLi21oj/eTpKKsUiIl5+siJxUsPnwt7yOh8A0HkcMVZBLS0t8eSTT8Zll132ge9t3rw56urqomfPnhERceGFF8Y//MM/xMc//vHYunVrjBs3Ls4999zELyhaKBQSfX66r329Lz7MXXfdFZ/5zGdK2mbp0qUlrd+Zan94T+c+4I4dUf25xigcckinPqz3OJBWh/Q7LJZd+T8lb/fujojamh6xq/XdCqQ6cD4XPlqps0FE6fNBkrMBneuPrrs1It77mX3/13mQ932wr9drH+RvH7xf+wHciccRYxXU0tISERFDh+59//Dt27fH6tWr9zqNslAoxOuvFy+KsW3btujZs2cMHDiw68JCyj3//PNJR0hE2/3/EW3/vCwKZ30iWu/8/gH9ogfIora21kS2TTufC3vL63wAQOdxxFgFDRo0KCIiNm3aFOecc86e5ddff31s2bJlrwvvL1u2LObOnRuXXXZZvPLKK/Gtb30rDjvssC7P/H55H7aonI0bN5a0/tKlS0u+i+uNN95Y0vqdqcd995b9GG2PrI3Wm26O6kVXR2HMmNj1xYuifc2DUZgxvRMSFnmPA2nV1hax5uaIXe+Utl2vfhGtKSzGfC58tFJng4jS54MkZwM61xVfvy0i3vuZff/XeZD3fbCv12sf5G8fdAbFWAWNGjUq6uvrY/HixTFw4MAYPnx4NDc3xz33FA+l312Mtba2xjXXXBO33357zJ49O5599tmYNWtWTJ48OY477rgkXwKQkLanNkTr4uui+g++FlX1EyMiiteU+cc7onD6ae48BnR7VVURwydG/GJdaduNmFyZPEnzuQAAleETtIKqqqpi+fLlUVdXF/Pnz4+LLrooBg0aFE1NTVFdXb3nwvvr16+PZ555JmbPnh0RxQvzn3TSSfHggw8mGR9S5emnn046Qpdpf/6FaL3y6qi+9MtRdeope5ZXfeq8iDfeiPY1fjcA+TB8chTvStlBhaqIw7vh/1P0ubB/eZoPAKgMxViFjR07Nh544IF4++23Y/PmzXHttdfGE088ERMmTIjevXtHRMQRRxwRv/zlL+Oxxx6LiIhXXnklfvKTn8TEiROTjA6psmzZsqQjdJnC0SOjdsWyqDp7zt7Le/WK2mXfi6qZM/a1GUC3c9DBEeM+3vH1686O6NGncnmSUjja58L+5Gk+AKAyFGMJWLdu3V7XFxsyZEj8/d//fXzxi1+MyZMnx8yZM+Pyyy+P0047LcGUkC5XXXVV0hEASMARUyKOnV08Gmx/qmoijjsvYmiyN/MmAeYDAMrlGmNdbNu2bbFp06ZYsGDBXssbGxujsbExoVQAAOk1YlLEkDERLz8R8dITETveKp5h2XtAxPBJEcPqImp7JZ0SAMgixVgX69u3b7S2pu9OSQAAadbjoIiRHyv+AQDoLE6lBDLhlltuSToCAJAy5gMAyqUYAzKhrq4u6QgAQMqYDwAol2IMyIQZM/J7xy0AYN/MBwCUSzEGAAAAQC4pxgAAAADIJcUYkAnz5s1LOgIAkDLmAwDKpRgDMmHRokVJRwAAUsZ8AEC5FGNAJsydOzfpCABAypgPACiXYgzIhA0bNiQdAQBIGfMBAOVSjAEAAACQS4oxIBMGDx6cdAQAIGXMBwCUSzEGZMKaNWuSjgAApIz5AIByKcaATLjpppuSjgAApIz5AIBy1SQdAKAjbr755li4cGHSMTps5+yzk44AQIr4XKiMrM0HAKSPI8YAAAAAyCXFGAAAAAC5pBgDMqG5uTnpCABAypgPACiXYgwAAACAXFKMAZnQ0NCQdAQAIGXMBwCUSzEGAAAAQC4pxgAAAADIJcUYkAlNTU1JRwAAUsZ8AEC5FGNAJixcuDDpCABAypgPACiXYgzIhOnTpycdAQBIGfMBAOWqSToAkE/HHntsSesvWLCg5G0AgOw4kM958wEA5XLEGJAJV199ddIRAICUMR8AUC7FGAAAAAC5pBgDAAAAIJcUYwAAAADkkmIMAAAAgFxSjAEAAACQS4oxAAAAAHJJMQYAAABALinGAAAAAMglxRgAAAAAuaQYAwAAACCXFGMAAAAA5JJiDAAAAIBcUowBAAAAkEuKMQAAAABySTEGAAAAQC4pxsicpqamqKmpSToGAADQjaxatSrq6upi9OjR8bu/+7vR2tqadKQu9ZWvfCVGjBiR679rvfjii3HGGWfE+PHjo66uLv74j/846UiJ+MQnPhGTJ0+OiRMnRkNDQ7z55ptJR6qoQnt7e3vSIaCjHnzwwfj2t78d3/3ud2PXrl1JxwEAACpo9U/Xx6qfPPaB5dt3vBMREb179dzn17sdekj/mP9/Ph3VVR9+TEhbW1uMHTs27r777pgwYUI0NjbGueeeG1/60pc642WU5QerH4mfrn/6A8s7ug+GHzYoLv7cOVEoFD70eR566KEYPXp0jBgxInV/17rz3x+Mxzc+t9eyfb3e/e2DY448PP7P78z+yOfZsmVLvPTSS3H88cfHzp0744wzzojf//3fj09/+tPlvoSy3XH3j2LT8y17LStlHxw39uiYe/b0Dj3XG2+8EQMGDIiIiK9+9atx8MEHx9VXX32g0VPPEWNkxjvvvBNXXHFFLFmyJOkoAABAFzhpSl3U1FTH9h3v7PVnt/19vfvPrJOnfGQpFhGxdu3aOPzww2PChAkREXHxxRfHihUrOv8FHYDTT6iP9vb2A94HZ5w69SNLsYiI0047LYYOHVqR11CuWSdPiXd37frQ17+/ZTve2RlnnDq1Q88zbNiwOP744yMiokePHjFlypTYvHlz576YA/Txk6fEO+/sPKB98O67u2LWyZM7/Fy7S7G2trbYsWNHh35+skwxRmYsWrQoLr744hg8eHDSUQAAgC7Qs0dtzJl+4gFtO/qo4TFh9FEdWrelpSWOOOKIPV8feeSR8eKLLx7Q83a2Pgf1ijNPnXZA204cNyqOPmJYJyfqegf37xvTT5x0QNueOOnYGDbk0JK3+9WvfhV33XVXzJ790UeadYXDBg+Mj00Zf0DbnnbCxBh4cP+Stvmd3/mdGDJkSDzzzDPxta997YCeNysUY2TC448/Hj/96U/joosuSjoKAADQhaYcNyaGDx1U0jaFQiHO/fhJHT7SJe1XGDpp6oQYNHBASdvUVFfH2TMPrFRMoxkfmxT9+x5U0jY9e9TG7NOOL/m5du7cGQ0NDfGVr3wljj322JK3r5QzTz0+evXsUdI2ffv0jlkndfxosd3uvPPOePnll2PEiBHR3Nxc8vZZohgjEx5++OHYsGFDHH300TFy5MhobW2NkSNHdvuLAAIAQN5VFQrxyTNOKWmbUo8SOuKII/Y6Qmzz5s0xYsSIkp6zkmqqq+PcWSeVtM2BHCWUZj171MZZM0or+s44ZWr07dO7pG1aW1vj85//fEyePDl1R0odyNGDZ00/IXqWWKbt1qNHjzj//PPjzjvvPKDts0IxRibMnz8/Xn755XjhhRfihRdeiOrq6njhhReif//u84seAADYt5Ejhkb9saM6tG7PHrUx+/TSjhI6/vjjo6WlJTZs2BAREX/7t38bn/3sZ0vOWUnHHnNkjBk5vEPr9jvAo4TSbkrdmBgxrGOX1jn04P5xyrTjSn6OSy65JPr16xd/9Vd/VfK2XeHkqXUxuINHDx5+2KEx7bixJT3+W2+9FVu2bImI4jXG7r777qirqys5Z5YoxgAAAEi9s2d+LGqqqz9yvTNOnRZ9DyrtKKHq6ur49re/HQ0NDXHMMcdE375948ILLzzQqBVRPD305A6dHnrW9BNLPkro0ksvjREjRkRra2uMGDEimpqaDjRqxVQVCvHJj5/coXXPmXVS1NR89M/Lb3v44Yfj7/7u72LdunUxZcqUmDx5cnzjG984kKgVU11dFed2cB+cd8YpUdWBm0/8trfeeis+9alPRX19fdTX18euXbviz/7szw4kamYU2tN+MjWUaFdrazy87sk4cdKxH7hFLQAAkF3/vmZtPPCfP9/v9w89pH9cdvG8DhVoWXXXDx+Kn/x8w36/f/hhh8bCL302qrrxnQTvuPtH8djT/73f7x9z1OHxu587t9veTbG9vT3+btm98V8vtOx3nYnjjo4vfCYdNw5IO0eM0e387Iln4t5VP40Xt2xNOgoAANCJZp40Ofp9yAXYz5l1UrcuxSIiZp/24Rdg/+QZp3TrUiziN0cP7udosEKhEOd18Mi6rCq+xpP2+9+5uroqzp75sS5OlV2KMbqVXa2t8R8//nkcNfywDp9/DwAAZEPPHrUxZ/q+L8A++qjhMWH0UV2cqOv1OahXnHHq1H1+b+K4UXH0EcO6OFHXO7h/35h+4qR9fu+E+nEl3Xghqw4bPDA+NmX8Pr93+gn13erGC5WmGEuB73//+3HeeefFkCFDomfPnnHUUUfF5z//+XjiiSeSjpY5P3vimXjjrbfjzFOndev/QwAAAHk15bgxMXzooL2WFa+/dVJu/g5w8tS6GPS+C7DXVFfH2TNLu2tjls342KTo/76jB3v2qI1PnH5CQom63pmnfvDowb7d9MYLlaQYS9CuXbviC1/4QnzmM5+JJ554Ij772c/GV77ylZgyZUqsWLEiXnrppaQjZspvHy022tFiAADQLVUVCvHJM07Za9mJk47NxVFCu9VUV8e5s07aa9lpJ0zM1VFCPXvUxlkz9i4CzzhlavTtU9qNF7Ksz0G94sxTp+217KzpJ5R844W8c/H9BM2fPz+++c1vxsKFC2Pp0qVRU1Oz53stLS0xYMCA6NevX4IJI674+m2JPj8AAABAR1z3R5eUvE3NR69CJTz44IPxzW9+M+bMmRPf+MY3PnDI74gRIxJKBgAAAJAPjhhLyNy5c2PlypWxfv36mDRp3xcNpON+un5D3PnvD8XFjefEmKOVigAAkAdrH9sYU44b0+3vRPlhfrp+Q5wwaXy3vxPlh/nJzzfExyaPz8015t6vvb09frr+6ThpyoSko2SSYiwh/fr1i0GDBsXzzz+fdJTM29XaGjfc+k9xcP++8X+/8Knc/jIEAAAASqMYS8Drr78ehxxySMycOTMeeOCBpON8KNcYAwAAALLgQK4x5q6UCdjdRb7yyisJJwEAAADIL0eMJeSYY46J559/Pn74wx/GmWeeudf3nnnmmRg3blxCybLFtcUAAACAA6UYS8iyZcvic5/7XNTU1MSnP/3pOOaYY+KVV16JH//4xzFhwoS48847k46Yeq4tBgAAAJSjJukAedXY2BgDBgyIG264Ie677774l3/5lxgyZEiceOKJ8dWvfjXpeJnwsyeeiTfeejsazp6hFAMAAABK5ogxMutv/vH7ERGOFgMAAAAOiGKMzNq1qzW2/Xp7HNy/b9JRAAAAgAxSjAEAAACQS1VJBwAAAACAJCjGAAAAAMglxRgAAAAAuaQYAwAAACCXFGMAAAAA5JJiDAAAAIBcUowBAAAAkEuKMQAAAABySTEGAAAAQC4pxgAAAADIJcUYAAAAALmkGAMAAAAglxRjAAAAAOSSYgwAAACAXFKMAQAAAJBLijEAAAAAckkxBgAAAEAuKcYAAAAAyCXFGAAAAAC5pBgDAAAAIJcUYwAAAADkkmIMAAAAgFxSjAEAAACQS4oxAAAAAHJJMQYAAABALinGAAAAAMglxRgAAAAAuaQYAwAAACCXFGMAAAAA5JJiDAAAAIBcUowBAAAAkEuKMQAAAABySTEGAAAAQC4pxgAAAADIJcUYAAAAALmkGAMAAAAglxRjAAAAAOTS/w/8ygzaAzPPsgAAAABJRU5ErkJggg==\n",
"text/plain": [ "text/plain": [
"<Figure size 1599.6x894.4 with 1 Axes>" "<qiskit.circuit.instructionset.InstructionSet at 0x12144b9e8>"
] ]
}, },
"execution_count": 3, "execution_count": 6,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"s = '1011'\n", "s = '101101110000110'\n",
"k = len(s)\n", "k = len(s)\n",
"\n", "\n",
"circuit = QuantumCircuit(2*k+1,k)\n", "circuit = QuantumCircuit(2*k+1,k)\n",
...@@ -193,17 +271,123 @@ ...@@ -193,17 +271,123 @@
"circuit.measure(list(range(k)), list(range(k)))\n", "circuit.measure(list(range(k)), list(range(k)))\n",
"\n", "\n",
"# Execute the circuit on the qasm simulator\n", "# Execute the circuit on the qasm simulator\n",
"job = execute(circuit, simulator, shots=1)\n", "#job = execute(circuit, simulator, shots=1)\n",
"\n", "\n",
"# Grab results from the job\n", "# Grab results from the job\n",
"result = job.result()\n", "#result = job.result()\n",
"\n", "\n",
"# Returns counts\n", "# Returns counts\n",
"counts = result.get_counts(circuit)\n", "#counts = result.get_counts(circuit)\n",
"print(\"\\nTotal count are:\",counts)\n", "#print(\"\\nTotal count are:\",counts)\n",
"\n", "\n",
"# Draw the circuit\n", "# Draw the circuit\n",
"circuit.draw(output='mpl',scale=1)" "# circuit.draw(output='mpl',scale=1)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'qiskit-terra': '0.10.0',\n",
" 'qiskit-aer': '0.3.2',\n",
" 'qiskit-ignis': '0.2.0',\n",
" 'qiskit-ibmq-provider': '0.3.3',\n",
" 'qiskit-aqua': '0.6.1',\n",
" 'qiskit': '0.13.0'}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import qiskit\n",
"qiskit.__qiskit_version__"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ibmq_burlington 8\n"
]
}
],
"source": [
"from qiskit import IBMQ\n",
"from qiskit.providers.ibmq import least_busy\n",
"\n",
"# Load local account information\n",
"provider = IBMQ.load_account()\n",
"\n",
"# Get the least busy real quantum system\n",
"backend = least_busy(provider.backends(n_qubits=5, operational=True, simulator=False))\n",
"print(backend, backend.status().pending_jobs)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"realjob = execute(circuit, backend, shots=1024)\n",
"rresult = realjob.result()\n",
"\n",
"# Returns counts\n",
"counts = rresult.get_counts(circuit)\n",
"print(\"\\nTotal count are:\",counts)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ibmq_qasm_simulator 1\n"
]
}
],
"source": [
"simback = provider.get_backend('ibmq_qasm_simulator')\n",
"print(simback, simback.status().pending_jobs)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Total count are: {'011000011101101': 1}\n"
]
}
],
"source": [
"simjob = execute(circuit, simback, shots=1)\n",
"sresult = simjob.result()\n",
"\n",
"# Returns counts\n",
"counts = sresult.get_counts(circuit)\n",
"print(\"\\nTotal count are:\",counts)"
] ]
}, },
{ {
......
notebooks/qorleans.css 0 → 100644
View file @ a1ddd588
@font-face {
font-family: "FiraSans";
src: url("fonts/FiraSans-Light.woff2") format('woff2');
font-weight: normal;
font-style: normal;
}
@font-face {
font-family: "FiraSans";
src: url("fonts/FiraSans-SemiBold.woff2") format('woff2');
font-weight: bold;
font-style: normal;
}
@font-face {
font-family: "FiraSans";
src: url("fonts/FiraSans-SemiBoldItalic.woff2") format('woff2');
font-weight: bold;
font-style: italic;
}
@font-face {
font-family: "FiraSans";
src: url("fonts/FiraSans-LightItalic.woff2") format('woff2');
font-weight: normal;
font-style: italic;
}
.reveal {
font-family: FiraSans;
font-weight: normal;
font-style: normal;
}
.reveal h1 {
font-family: FiraSans;
font-weight: bold;
color: #e07;
}
.cool {
color: #e07;
}
.reveal h2, h3, h4, h5, h6 {
font-family: FiraSans;
}
.reveal p {
font-weight: normal;
}
notebooks/qorleans.ipynb 0 → 100644
View file @ a1ddd588
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