S4.3_Implementacion.ipynb

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    "<table width=\"100%\"><tr><td style=\"color:#bbbbbb;background-color:#ffffff;font-size:11px;font-style:italic;text-align:right;\"></td></tr></table>\n",
    "$ \\newcommand{\\bra}[1]{\\langle #1|} $\n",
    "$ \\newcommand{\\ket}[1]{|#1\\rangle} $\n",
    "$ \\newcommand{\\braket}[2]{\\langle #1|#2\\rangle} $\n",
    "$ \\newcommand{\\dot}[2]{ #1 \\cdot #2} $\n",
    "$ \\newcommand{\\biginner}[2]{\\left\\langle #1,#2\\right\\rangle} $\n",
    "$ \\newcommand{\\mymatrix}[2]{\\left( \\begin{array}{#1} #2\\end{array} \\right)} $\n",
    "$ \\newcommand{\\myvector}[1]{\\mymatrix{c}{#1}} $\n",
    "$ \\newcommand{\\myrvector}[1]{\\mymatrix{r}{#1}} $\n",
    "$ \\newcommand{\\mypar}[1]{\\left( #1 \\right)} $\n",
    "$ \\newcommand{\\mybigpar}[1]{ \\Big( #1 \\Big)} $\n",
    "$ \\newcommand{\\sqrttwo}{\\frac{1}{\\sqrt{2}}} $\n",
    "$ \\newcommand{\\dsqrttwo}{\\dfrac{1}{\\sqrt{2}}} $\n",
    "$ \\newcommand{\\onehalf}{\\frac{1}{2}} $\n",
    "$ \\newcommand{\\donehalf}{\\dfrac{1}{2}} $\n",
    "$ \\newcommand{\\hadamard}{ \\mymatrix{rr}{ \\sqrttwo & \\sqrttwo \\\\ \\sqrttwo & -\\sqrttwo }} $\n",
    "$ \\newcommand{\\vzero}{\\myvector{1\\\\0}} $\n",
    "$ \\newcommand{\\vone}{\\myvector{0\\\\1}} $\n",
    "$ \\newcommand{\\stateplus}{\\myvector{ \\sqrttwo \\\\  \\sqrttwo } } $\n",
    "$ \\newcommand{\\stateminus}{ \\myrvector{ \\sqrttwo \\\\ -\\sqrttwo } } $\n",
    "$ \\newcommand{\\myarray}[2]{ \\begin{array}{#1}#2\\end{array}} $\n",
    "$ \\newcommand{\\X}{ \\mymatrix{cc}{0 & 1 \\\\ 1 & 0}  } $\n",
    "$ \\newcommand{\\Z}{ \\mymatrix{rr}{1 & 0 \\\\ 0 & -1}  } $\n",
    "$ \\newcommand{\\Htwo}{ \\mymatrix{rrrr}{ \\frac{1}{2} & \\frac{1}{2} & \\frac{1}{2} & \\frac{1}{2} \\\\ \\frac{1}{2} & -\\frac{1}{2} & \\frac{1}{2} & -\\frac{1}{2} \\\\ \\frac{1}{2} & \\frac{1}{2} & -\\frac{1}{2} & -\\frac{1}{2} \\\\ \\frac{1}{2} & -\\frac{1}{2} & -\\frac{1}{2} & \\frac{1}{2} } } $\n",
    "$ \\newcommand{\\CNOT}{ \\mymatrix{cccc}{1 & 0 & 0 & 0 \\\\ 0 & 1 & 0 & 0 \\\\ 0 & 0 & 0 & 1 \\\\ 0 & 0 & 1 & 0} } $\n",
    "$ \\newcommand{\\norm}[1]{ \\left\\lVert #1 \\right\\rVert } $\n",
    "$ \\newcommand{\\pstate}[1]{ \\lceil \\mspace{-1mu} #1 \\mspace{-1.5mu} \\rfloor } $\n",
    "\n",
    "<img style=\"float: right;\" src=\"https://avatars.githubusercontent.com/u/141567859?s=200&v=4\">\n",
    "    \n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<font size=\"8\">QuantumQuipu/</font><br>\n",
    "<br>\n",
    "<br>\n",
    "<font size=\"15\"><b>QuantumScholars2023</b></font>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "\n",
    "<div style=\"border-top: 20px solid #DE781F;\"></div>"
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    "_uuid": "1752ce061957fd1ce93d2e4db9494b7b29da7935",
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   "source": [
    "**Autor:** Gustavo Valdivia Mera\\\n",
    "**Institución:** University of Houston\\\n",
    "**Correo:** gvaldiviamera@uh.edu\n",
    "          \n",
    "Este material está sujeto a los términos y condiciones de la licencia\n",
    "[Creative Commons CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).\\\n",
    " Se permite el uso gratuito para cualquier propósito no comercial.\n",
    "\n",
    "*Puede consultar la última versión de este notebook en nuestro [repositorio](https://github.com/QuantumQuipu/QuantumScholars2023) y los videos de clase en nuestro canal de [Youtube](https://www.youtube.com/channel/UCze8vzQLcplutz0nWDNjFCA).*    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementación"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"imagenes/sesion4/adj_3.png\" width=\"80%\" align=\"center\">\n",
    "    </td></tr>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit\n",
    "from qiskit.visualization import plot_histogram\n",
    "from qiskit import execute, Aer\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Oráculo constante\n",
    "\n",
    "Sea $x\\in\\{0,1\\}^4$\n",
    "\n",
    "<img src=\"imagenes/sesion4/adj_im1.png\" width=\"80%\" align=\"center\">\n",
    "    </td></tr>"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">           ░ \n",
       "q_0: ──────░─\n",
       "           ░ \n",
       "q_1: ──────░─\n",
       "           ░ \n",
       "q_2: ──────░─\n",
       "           ░ \n",
       "q_3: ──────░─\n",
       "     ┌───┐ ░ \n",
       "q_4: ┤ X ├─░─\n",
       "     └───┘ ░ </pre>"
      ],
      "text/plain": [
       "           ░ \n",
       "q_0: ──────░─\n",
       "           ░ \n",
       "q_1: ──────░─\n",
       "           ░ \n",
       "q_2: ──────░─\n",
       "           ░ \n",
       "q_3: ──────░─\n",
       "     ┌───┐ ░ \n",
       "q_4: ┤ X ├─░─\n",
       "     └───┘ ░ "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oraculo_c = QuantumCircuit(5)\n",
    "fx = np.random.randint(2)\n",
    "\n",
    "if fx == 1:\n",
    "    oraculo_c.x(4)\n",
    "oraculo_c.barrier()\n",
    "\n",
    "oraculo_c.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Oráculo balanceado\n",
    "\n",
    "Sea $x\\in\\{0,1\\}^4$\n",
    "\n",
    "<img src=\"imagenes/sesion4/adj_im2.png\" width=\"60%\" align=\"center\">\n",
    "    </td></tr>"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">           ░                      ░       ░ \n",
       "q_0: ──────░───■──────────────────░───────░─\n",
       "     ┌───┐ ░   │                  ░ ┌───┐ ░ \n",
       "q_1: ┤ X ├─░───┼────■─────────────░─┤ X ├─░─\n",
       "     └───┘ ░   │    │             ░ └───┘ ░ \n",
       "q_2: ──────░───┼────┼────■────────░───────░─\n",
       "           ░   │    │    │        ░       ░ \n",
       "q_3: ──────░───┼────┼────┼────■───░───────░─\n",
       "           ░ ┌─┴─┐┌─┴─┐┌─┴─┐┌─┴─┐ ░       ░ \n",
       "q_4: ──────░─┤ X ├┤ X ├┤ X ├┤ X ├─░───────░─\n",
       "           ░ └───┘└───┘└───┘└───┘ ░       ░ </pre>"
      ],
      "text/plain": [
       "           ░                      ░       ░ \n",
       "q_0: ──────░───■──────────────────░───────░─\n",
       "     ┌───┐ ░   │                  ░ ┌───┐ ░ \n",
       "q_1: ┤ X ├─░───┼────■─────────────░─┤ X ├─░─\n",
       "     └───┘ ░   │    │             ░ └───┘ ░ \n",
       "q_2: ──────░───┼────┼────■────────░───────░─\n",
       "           ░   │    │    │        ░       ░ \n",
       "q_3: ──────░───┼────┼────┼────■───░───────░─\n",
       "           ░ ┌─┴─┐┌─┴─┐┌─┴─┐┌─┴─┐ ░       ░ \n",
       "q_4: ──────░─┤ X ├┤ X ├┤ X ├┤ X ├─░───────░─\n",
       "           ░ └───┘└───┘└───┘└───┘ ░       ░ "
      ]
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   "source": [
    "oraculo_b = QuantumCircuit(5)\n",
    "\n",
    "oraculo_b.x(1)\n",
    "oraculo_b.barrier()\n",
    "\n",
    "for x in range(4):\n",
    "    oraculo_b.cx(x,4)\n",
    "\n",
    "oraculo_b.barrier()\n",
    "oraculo_b.x(1)\n",
    "oraculo_b.barrier()\n",
    "\n",
    "oraculo_b.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algoritmo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Constante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">                ░ ┌───┐ ░       ░ ┌───┐ ░ ┌─┐         \n",
       "q_0: ───────────░─┤ H ├─░───────░─┤ H ├─░─┤M├─────────\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░ └╥┘┌─┐      \n",
       "q_1: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫─┤M├──────\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░  ║ └╥┘┌─┐   \n",
       "q_2: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫──╫─┤M├───\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░  ║  ║ └╥┘┌─┐\n",
       "q_3: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫──╫──╫─┤M├\n",
       "     ┌───┐┌───┐ ░ └───┘ ░ ┌───┐ ░ └───┘ ░  ║  ║  ║ └╥┘\n",
       "q_4: ┤ X ├┤ H ├─░───────░─┤ X ├─░───────░──╫──╫──╫──╫─\n",
       "     └───┘└───┘ ░       ░ └───┘ ░       ░  ║  ║  ║  ║ \n",
       "c: 4/══════════════════════════════════════╩══╩══╩══╩═\n",
       "                                           0  1  2  3 </pre>"
      ],
      "text/plain": [
       "                ░ ┌───┐ ░       ░ ┌───┐ ░ ┌─┐         \n",
       "q_0: ───────────░─┤ H ├─░───────░─┤ H ├─░─┤M├─────────\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░ └╥┘┌─┐      \n",
       "q_1: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫─┤M├──────\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░  ║ └╥┘┌─┐   \n",
       "q_2: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫──╫─┤M├───\n",
       "                ░ ├───┤ ░       ░ ├───┤ ░  ║  ║ └╥┘┌─┐\n",
       "q_3: ───────────░─┤ H ├─░───────░─┤ H ├─░──╫──╫──╫─┤M├\n",
       "     ┌───┐┌───┐ ░ └───┘ ░ ┌───┐ ░ └───┘ ░  ║  ║  ║ └╥┘\n",
       "q_4: ┤ X ├┤ H ├─░───────░─┤ X ├─░───────░──╫──╫──╫──╫─\n",
       "     └───┘└───┘ ░       ░ └───┘ ░       ░  ║  ║  ║  ║ \n",
       "c: 4/══════════════════════════════════════╩══╩══╩══╩═\n",
       "                                           0  1  2  3 "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc=QuantumCircuit(5,4)\n",
    "qc.x(4)\n",
    "qc.h(4)\n",
    "qc.barrier()\n",
    "\n",
    "for x in range(4):\n",
    "    qc.h(x)\n",
    "qc.barrier()\n",
    "\n",
    "qc=qc.compose(oraculo_c)\n",
    "qc.barrier\n",
    "\n",
    "for x in range(4):\n",
    "    qc.h(x)\n",
    "qc.barrier()\n",
    "\n",
    "qc.measure([0,1,2,3],[0,1,2,3])\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "results = aer_sim.run(qc).result()\n",
    "answer = results.get_counts()\n",
    "\n",
    "plot_histogram(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Balanceado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">                ░ ┌───┐ ░       ░                      ░       ░ ┌───┐ ░ ┌─┐   »\n",
       "q_0: ───────────░─┤ H ├─░───────░───■──────────────────░───────░─┤ H ├─░─┤M├───»\n",
       "                ░ ├───┤ ░ ┌───┐ ░   │                  ░ ┌───┐ ░ ├───┤ ░ └╥┘┌─┐»\n",
       "q_1: ───────────░─┤ H ├─░─┤ X ├─░───┼────■─────────────░─┤ X ├─░─┤ H ├─░──╫─┤M├»\n",
       "                ░ ├───┤ ░ └───┘ ░   │    │             ░ └───┘ ░ ├───┤ ░  ║ └╥┘»\n",
       "q_2: ───────────░─┤ H ├─░───────░───┼────┼────■────────░───────░─┤ H ├─░──╫──╫─»\n",
       "                ░ ├───┤ ░       ░   │    │    │        ░       ░ ├───┤ ░  ║  ║ »\n",
       "q_3: ───────────░─┤ H ├─░───────░───┼────┼────┼────■───░───────░─┤ H ├─░──╫──╫─»\n",
       "     ┌───┐┌───┐ ░ └───┘ ░       ░ ┌─┴─┐┌─┴─┐┌─┴─┐┌─┴─┐ ░       ░ └───┘ ░  ║  ║ »\n",
       "q_4: ┤ X ├┤ H ├─░───────░───────░─┤ X ├┤ X ├┤ X ├┤ X ├─░───────░───────░──╫──╫─»\n",
       "     └───┘└───┘ ░       ░       ░ └───┘└───┘└───┘└───┘ ░       ░       ░  ║  ║ »\n",
       "c: 4/═════════════════════════════════════════════════════════════════════╩══╩═»\n",
       "                                                                          0  1 »\n",
       "«           \n",
       "«q_0: ──────\n",
       "«           \n",
       "«q_1: ──────\n",
       "«     ┌─┐   \n",
       "«q_2: ┤M├───\n",
       "«     └╥┘┌─┐\n",
       "«q_3: ─╫─┤M├\n",
       "«      ║ └╥┘\n",
       "«q_4: ─╫──╫─\n",
       "«      ║  ║ \n",
       "«c: 4/═╩══╩═\n",
       "«      2  3 </pre>"
      ],
      "text/plain": [
       "                ░ ┌───┐ ░       ░                      ░       ░ ┌───┐ ░ ┌─┐   »\n",
       "q_0: ───────────░─┤ H ├─░───────░───■──────────────────░───────░─┤ H ├─░─┤M├───»\n",
       "                ░ ├───┤ ░ ┌───┐ ░   │                  ░ ┌───┐ ░ ├───┤ ░ └╥┘┌─┐»\n",
       "q_1: ───────────░─┤ H ├─░─┤ X ├─░───┼────■─────────────░─┤ X ├─░─┤ H ├─░──╫─┤M├»\n",
       "                ░ ├───┤ ░ └───┘ ░   │    │             ░ └───┘ ░ ├───┤ ░  ║ └╥┘»\n",
       "q_2: ───────────░─┤ H ├─░───────░───┼────┼────■────────░───────░─┤ H ├─░──╫──╫─»\n",
       "                ░ ├───┤ ░       ░   │    │    │        ░       ░ ├───┤ ░  ║  ║ »\n",
       "q_3: ───────────░─┤ H ├─░───────░───┼────┼────┼────■───░───────░─┤ H ├─░──╫──╫─»\n",
       "     ┌───┐┌───┐ ░ └───┘ ░       ░ ┌─┴─┐┌─┴─┐┌─┴─┐┌─┴─┐ ░       ░ └───┘ ░  ║  ║ »\n",
       "q_4: ┤ X ├┤ H ├─░───────░───────░─┤ X ├┤ X ├┤ X ├┤ X ├─░───────░───────░──╫──╫─»\n",
       "     └───┘└───┘ ░       ░       ░ └───┘└───┘└───┘└───┘ ░       ░       ░  ║  ║ »\n",
       "c: 4/═════════════════════════════════════════════════════════════════════╩══╩═»\n",
       "                                                                          0  1 »\n",
       "«           \n",
       "«q_0: ──────\n",
       "«           \n",
       "«q_1: ──────\n",
       "«     ┌─┐   \n",
       "«q_2: ┤M├───\n",
       "«     └╥┘┌─┐\n",
       "«q_3: ─╫─┤M├\n",
       "«      ║ └╥┘\n",
       "«q_4: ─╫──╫─\n",
       "«      ║  ║ \n",
       "«c: 4/═╩══╩═\n",
       "«      2  3 "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qcc=QuantumCircuit(5,4)\n",
    "qcc.x(4)\n",
    "qcc.h(4)\n",
    "qcc.barrier()\n",
    "\n",
    "for x in range(4):\n",
    "    qcc.h(x)\n",
    "qcc.barrier()\n",
    "\n",
    "qcc=qcc.compose(oraculo_b)\n",
    "qcc.barrier\n",
    "\n",
    "for x in range(4):\n",
    "    qcc.h(x)\n",
    "qcc.barrier()\n",
    "\n",
    "qcc.measure([0,1,2,3],[0,1,2,3])\n",
    "qcc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aer_si = Aer.get_backend('aer_simulator')\n",
    "result = aer_si.run(qcc).result()\n",
    "answe = result.get_counts()\n",
    "\n",
    "plot_histogram(answe)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ¡Tú puedes!\n",
    "\n",
    "1. Implementa el oráculo balanceado para la función $f(x)$, donde $x\\in\\{0,1\\}^3$, tal que:\n",
    "\n",
    "\\begin{align}\n",
    "f(001)&=0\\\\\n",
    "f(000)&=0\\\\\n",
    "f(111)&=0\\\\\n",
    "f(110)&=0\\\\\n",
    "f(011)&=1\\\\\n",
    "f(010)&=1\\\\\n",
    "f(100)&=1\\\\\n",
    "f(101)&=1\\\\\n",
    "\\end{align}\n",
    "\n",
    "2. En la construcción más simple posible de un oráculo balanceado, se utiliza la compuerta $CX$, la cual toma como objetivo el último qubit del circuito y como control cada uno de los $n$ primeros qubits. Sin embargo, ¿es realmente necesario aplicar $CX$ a todos los $n$ primeros qubits, o podríamos prescindir de algunos y obtener igualmente un oráculo balanceado?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6ucKfX5Q-7Ga"
   },
   "source": [
    "---\n",
    "\n",
    "## 5. Recursos útiles\n",
    "\n",
    "[1] David Deutsch and Richard Jozsa (1992). \"Rapid solutions of problems by quantum computation\".\\\n",
    "Proceedings of the Royal Society of London A. 439: 553–558. [doi:10.1098/rspa.1992.0167](https://royalsocietypublishing.org/doi/10.1098/rspa.1992.0167).\n",
    "\n",
    "[2] [Qiksit: Deutsch-Jozsa Algorithm](https://learn.qiskit.org/course/ch-algorithms/deutsch-jozsa-algorithm)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Donaciones\n",
    "<br>\n",
    "Puedes donar una vez en el siguiente enlace (Ko-Fi)\n",
    "\n",
    "<a href=\"https://ko-fi.com/rcrdphysics\">\n",
    "<img src=\"https://habrastorage.org/webt/8r/ml/xf/8rmlxfpdzukegpxa62cxlfvgkqe.png\" width=20% />\n",
    "\n",
    "</center>"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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