Calculate 1+1 with real quantum computer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate 1+1 with real quantum computer\n",
    "\n",
    "This software includes the work that is distributed in the Apache License 2.0  \n",
    "https://github.com/QISKit/qiskit-tutorial/blob/master/hello_world/quantum_world.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.6.5 (default, May 11 2018, 04:00:52) \n",
      "[GCC 8.1.0]\n",
      "qiskit version: 0.5.4\n"
     ]
    }
   ],
   "source": [
    "import sys, qiskit\n",
    "print(sys.version)\n",
    "print(\"qiskit version:\", qiskit.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass, time\n",
    "import qiskit\n",
    "from qiskit import ClassicalRegister, QuantumRegister, load_qasm_string\n",
    "from qiskit import QuantumCircuit,  available_backends, execute, register, get_backend\n",
    "\n",
    "# import basic plot tools\n",
    "from qiskit.tools.visualization import plot_histogram, circuit_drawer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Please input your token and hit enter: ········\n",
      "\n",
      "You have access to great power!\n",
      "['ibmqx4', 'ibmqx5', 'ibmqx2']\n",
      "The best backend is ibmqx4\n"
     ]
    }
   ],
   "source": [
    "APItoken = getpass.getpass('Please input your token and hit enter: ')\n",
    "qx_config = {\n",
    "    \"APItoken\": APItoken,\n",
    "    \"url\":\"https://quantumexperience.ng.bluemix.net/api\"}\n",
    "\n",
    "try:\n",
    "    register(qx_config['APItoken'], qx_config['url'])\n",
    "\n",
    "    print('\\nYou have access to great power!')\n",
    "    print(available_backends({'local': False, 'simulator': False}))\n",
    "except: \n",
    "    print('Something went wrong.\\nDid you enter a correct token?')\n",
    "    \n",
    "def lowest_pending_jobs():\n",
    "    \"\"\"Returns the backend with lowest pending jobs.\"\"\"\n",
    "    list_of_backends = available_backends(\n",
    "        {'local': False, 'simulator': False})\n",
    "    device_status = [get_backend(backend).status\n",
    "                     for backend in list_of_backends]\n",
    "\n",
    "    best = min([x for x in device_status if x['available'] is True],\n",
    "               key=lambda x: x['pending_jobs'])\n",
    "    return best['name']\n",
    "\n",
    "backend = lowest_pending_jobs()\n",
    "print(\"The best backend is \" + backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Execute with simulator\n",
    "\n",
    "ref:\n",
    "[Basic Circuit Identities and Larger Circuits — Experience Documentation 2.0 documentation](https://quantumexperience.ng.bluemix.net/proxy/tutorial/full-user-guide/004-Quantum_Algorithms/061-Basic_Circuit_Identities_and_Larger_Circuits.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0 + 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def toffoli(c0, c1, t, q, qc):\n",
    "    qc.h(q[2])\n",
    "    qc.cx(q[1],q[2])\n",
    "    qc.tdg(q[2])\n",
    "    qc.cx(q[0],q[2])\n",
    "    qc.t(q[2])\n",
    "    qc.cx(q[1],q[2])\n",
    "    qc.tdg(q[2])\n",
    "    qc.cx(q[0],q[2])\n",
    "    qc.t(q[1])\n",
    "    qc.t(q[2])\n",
    "    qc.h(q[2])\n",
    "    qc.cx(q[0],q[1])\n",
    "    qc.t(q[0])\n",
    "    qc.tdg(q[1])\n",
    "    qc.cx(q[0],q[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1133x293 at 0x7F7A7C280588>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "toffoli(0, 1, 2, q, qc)\n",
    "qc.cx(q[0], q[3])\n",
    "qc.cx(q[1], q[3])\n",
    "\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a7c2441d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Process Process-4:\n",
      "Process Process-2:\n",
      "Process Process-1:\n",
      "Process Process-3:\n",
      "Traceback (most recent call last):\n",
      "Traceback (most recent call last):\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 258, in _bootstrap\n",
      "    self.run()\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 258, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 258, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/usr/lib/python3.6/concurrent/futures/process.py\", line 169, in _process_worker\n",
      "    call_item = call_queue.get(block=True)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 258, in _bootstrap\n",
      "    self.run()\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/usr/lib/python3.6/concurrent/futures/process.py\", line 169, in _process_worker\n",
      "    call_item = call_queue.get(block=True)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/process.py\", line 93, in run\n",
      "    self._target(*self._args, **self._kwargs)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/queues.py\", line 93, in get\n",
      "    with self._rlock:\n",
      "  File \"/usr/lib/python3.6/concurrent/futures/process.py\", line 169, in _process_worker\n",
      "    call_item = call_queue.get(block=True)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/synchronize.py\", line 96, in __enter__\n",
      "    return self._semlock.__enter__()\n",
      "KeyboardInterrupt\n",
      "  File \"/usr/lib/python3.6/multiprocessing/queues.py\", line 93, in get\n",
      "    with self._rlock:\n",
      "  File \"/usr/lib/python3.6/concurrent/futures/process.py\", line 169, in _process_worker\n",
      "    call_item = call_queue.get(block=True)\n",
      "  File \"/usr/lib/python3.6/multiprocessing/queues.py\", line 94, in get\n",
      "    res = self._recv_bytes()\n",
      "  File \"/usr/lib/python3.6/multiprocessing/queues.py\", line 93, in get\n",
      "    with self._rlock:\n",
      "  File \"/usr/lib/python3.6/multiprocessing/synchronize.py\", line 96, in __enter__\n",
      "    return self._semlock.__enter__()\n",
      "  File \"/usr/lib/python3.6/multiprocessing/connection.py\", line 216, in recv_bytes\n",
      "    buf = self._recv_bytes(maxlength)\n",
      "KeyboardInterrupt\n"
     ]
    }
   ],
   "source": [
    "job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "    if lapse > 6:\n",
    "        break\n",
    "print(job_exp.status)\n",
    "\n",
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0 + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1134x293 at 0x7F7A7B97C9E8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "qc.x(q[1])\n",
    "toffoli(0, 1, 2, q, qc)\n",
    "qc.cx(q[0], q[3])\n",
    "qc.cx(q[1], q[3])\n",
    "\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a6a291cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1+0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1134x293 at 0x7F7A7B86CD68>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "qc.x(q[0])\n",
    "toffoli(0, 1, 2, q, qc)\n",
    "qc.cx(q[0], q[3])\n",
    "qc.cx(q[1], q[3])\n",
    "\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "{'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a7c2446d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1134x293 at 0x7F7A7C2672E8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "qc.x(q[0])\n",
    "qc.x(q[1])\n",
    "toffoli(0, 1, 2, q, qc)\n",
    "qc.cx(q[0], q[3])\n",
    "qc.cx(q[1], q[3])\n",
    "\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a6a29ad30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute 1+1 with real quantum computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1134x293 at 0x7F7A7B973908>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "qc.x(q[0])\n",
    "qc.x(q[1])\n",
    "toffoli(0, 1, 2, q, qc)\n",
    "qc.cx(q[0], q[3])\n",
    "qc.cx(q[1], q[3])\n",
    "\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'job_id': None, 'status': <JobStatus.INITIALIZING: 'job is being initialized'>, 'status_msg': 'job is begin initialized please wait a moment'}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:IBMQuantumExperience.IBMQuantumExperience:Got a 400 code response to https://quantumexperience.ng.bluemix.net/api/Jobs?access_token=WNvtHe8oQFCDv0iZnPlI5yeFPKajbTJyY2Cfg0snHUgpThgBq6yixQiro7EQT4Wl: {\"error\":{\"status\":400,\"message\":\"Error parsing QASM. Error parsing qasm number 0. Gates after a measure are blocked\",\"code\":\"QASM_NOT_VALID\",\"statusCode\":400}}\n",
      "WARNING:IBMQuantumExperience.IBMQuantumExperience:Got a 400 code response to https://quantumexperience.ng.bluemix.net/api/Jobs?access_token=WNvtHe8oQFCDv0iZnPlI5yeFPKajbTJyY2Cfg0snHUgpThgBq6yixQiro7EQT4Wl: {\"error\":{\"status\":400,\"message\":\"Error parsing QASM. Error parsing qasm number 0. Gates after a measure are blocked\",\"code\":\"QASM_NOT_VALID\",\"statusCode\":400}}\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-14-350d2468b414>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Status @ {} seconds'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minterval\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mlapse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjob_exp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m     \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m     \u001b[0mlapse\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlapse\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:IBMQuantumExperience.IBMQuantumExperience:Got a 400 code response to https://quantumexperience.ng.bluemix.net/api/Jobs?access_token=WNvtHe8oQFCDv0iZnPlI5yeFPKajbTJyY2Cfg0snHUgpThgBq6yixQiro7EQT4Wl: {\"error\":{\"status\":400,\"message\":\"Error parsing QASM. Error parsing qasm number 0. Gates after a measure are blocked\",\"code\":\"QASM_NOT_VALID\",\"statusCode\":400}}\n",
      "WARNING:IBMQuantumExperience.IBMQuantumExperience:Got a 400 code response to https://quantumexperience.ng.bluemix.net/api/Jobs?access_token=WNvtHe8oQFCDv0iZnPlI5yeFPKajbTJyY2Cfg0snHUgpThgBq6yixQiro7EQT4Wl: {\"error\":{\"status\":400,\"message\":\"Error parsing QASM. Error parsing qasm number 0. Gates after a measure are blocked\",\"code\":\"QASM_NOT_VALID\",\"statusCode\":400}}\n",
      "WARNING:IBMQuantumExperience.IBMQuantumExperience:Got a 400 code response to https://quantumexperience.ng.bluemix.net/api/Jobs?access_token=WNvtHe8oQFCDv0iZnPlI5yeFPKajbTJyY2Cfg0snHUgpThgBq6yixQiro7EQT4Wl: {\"error\":{\"status\":400,\"message\":\"Error parsing QASM. Error parsing qasm number 0. Gates after a measure are blocked\",\"code\":\"QASM_NOT_VALID\",\"statusCode\":400}}\n"
     ]
    }
   ],
   "source": [
    "# This cell is fail to execute because of physical restriction of ibmqx4.\n",
    "job_exp = execute(qc, backend='ibmqx4', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "    if lapse > 6:\n",
    "        break\n",
    "print(job_exp.status)\n",
    "\n",
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Improve the circuit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Toffoli, CNOT, SWAP gate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def toffoli(c0, c1, t, q, qc, backend):\n",
    "    qc.h(q[t])\n",
    "    cx(c1, t, q, qc, backend)\n",
    "    qc.tdg(q[t])\n",
    "    cx(c0, t, q, qc, backend)\n",
    "    qc.t(q[t])\n",
    "    cx(c1, t, q, qc, backend)\n",
    "    qc.tdg(q[t])\n",
    "    cx(c0, t, q, qc, backend)\n",
    "    qc.t(q[c1])\n",
    "    qc.t(q[t])\n",
    "    cx(c0, c1, q, qc, backend)\n",
    "    qc.h(q[t])\n",
    "    qc.t(q[c0])\n",
    "    qc.tdg(q[c1])\n",
    "    cx(c0, c1, q, qc, backend)\n",
    "\n",
    "def cx(con, tar, q, qc, backend):\n",
    "    ibmqx2config = [[0,1],[0,2],[1,2],[3,2],[3,4],[4,2]]\n",
    "    ibmqx4config = [[1,0],[2,0],[2,1],[4,2],[3,2],[3,4]]\n",
    "    ibmqx5config = [[1,0], [1,2], [2,3], [3,4], [3,14], [5,4], [6,5], [6,7], [6,11], [7,10], [8,7], [9,8], [9,10], [11,10], [12,5], [12,11], [12,13], [13,4], [13,14], [15,0], [15,2], [15,14]]\n",
    "    devices = {'ibmqx2':ibmqx2config, 'ibmqx4':ibmqx4config, 'ibmqx5':ibmqx5config}\n",
    "    if backend in devices.keys():\n",
    "        if [con, tar] in devices[backend]:\n",
    "            qc.cx(q[con], q[tar])\n",
    "        elif [tar, con] in devices[backend]:\n",
    "            qc.h(q[con])\n",
    "            qc.h(q[tar])\n",
    "            qc.cx(q[tar], q[con])\n",
    "            qc.h(q[con])\n",
    "            qc.h(q[tar])\n",
    "        else:\n",
    "            raise ValueError('Don\\'t support such CNOT gate')\n",
    "    else: # simulator\n",
    "        qc.cx(q[con], q[tar])\n",
    "        \n",
    "def swap(q0, q1, q, qc, backend):\n",
    "    cx(q0, q1, q, qc, backend)\n",
    "    cx(q1, q0, q, qc, backend)\n",
    "    cx(q0, q1, q, qc, backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check circuit with simulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": 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UR71795YsHhaL5e3tLdm2oAg+f/68bdu2Xr16UaOC9uzZc8uWLfn5+UzHBdAA4aGrqanJZrNx6MqIYp4iFi5c2Lp1a2lqmDdvHnX58/Lykj6exMREQsjFixelr6p+1J+DapGoo6PD1J+DCoO6pdTX11eQowJA1ohAIAgJCan6ZlY4hkGvXr2EQyzk5eXV3Dg9Pd3U1JQq0KVLl/HjxwvfcZmbm2dmZlYt3KxZMzabXbOS2bNnE0LCwsJED1o4XHhiYqKY+ysQ1JtKibVHVYWEhBBCHj58KEE80hM3lZo7dy61U/Pmzav5aU5ODvWqkBBy7do1CeJBKvXN8PLyUlVVZToKALFJf1cNoti1a1etV3ZGSP9HF76MunPnjvTxyC2VolCjMfv5+cnn6+pCdSy/fv06s2EAyA2bEDJmzJiAgAAtLS3qDMLj8RwcHPz9/R88eJCXl0cIsbKyMjQ0rPlGq2XLli9evHByciKEvHjx4ty5c1SXJ2dn58ePH5uYmFQt3KRJEz6fX1FRUa2SsrIyUu8I4/Ik1h5V5e/vb21t3atXL/nFKqmtW7f++eefhJBRo0bt3bu3ZgEjIyNhO0b0mAIAgMagvLyc6ubAZrOlmV8EABoVFer/3NzcXFxcoqKidHR0rK2tqVf2aWlp2dnZpN5GwyYmJrdv33758uWNGzdyc3PNzMycnJyELQaropKltLS0aqNhUlMANzj8S1Uy7cMj+h4JZWZmXr161cvLS3ZR0eXvv/+msqNu3bqdPn26rn6iS5cuPXz4cGVl5dOnTy9fvkwNyAEAAPCtio6OpjqH29jY6OrqMh0OACgHFeGSvr6+o6Nj1c9E73/p4ODg4OBQf5n27ds/e/YsISGhWioVGxuroaFBjeOnOETZI6Fjx46xWKxp06bJNCTphYWF/fzzz4QQc3PzsLAw4XvImiwsLCZMmHD69GlCyPr160eMGCH9ZB0AAAAKSzg5r7KMOQEAiqC+CeyFsyvQclpxcXEhVSb8pSQkJOTk5Dg5OVHvwZSUv7//8OHDjY2NmQ6kPo8ePZo4cWJlZWWTJk2uXLnSYLQrVqygFqKioqieYAAAAN8qpRu+DwAUQX2pFHVaUVFREf39TD2GDh2qrq4eEBBQUlIiXLlv3z5CyKhRo6SvnykPHjyIj49X8Omk4uLiRowYUVxcrKqqGhISYmNj0+AmdnZ2Q4YMoZY3bNjA5/NlHCMAAABjkEoBgATqTKUEAsHz588JIZ07d9bQ0JD+m3R1dZcvX/7+/fsJEyYkJyeXlJT4+Pj4+vp26NBh+vTp0tfPFH9/f2Nj42HDhjEdSH2sra2pMRjLy8v79+8v4lbCEfCp6adkGiEAAACD4uLiqEtely5dmI4FAJSGSl0fxMXFFRUVEUKEk7dKb8OGDfn5+QcPHgwLC6PWdOrU6dKlS7SkaozgcrnBwcFz585VUanzlwQAAAAAgG9PnQkAvR2lKBwO58CBA7/++uuNGze4XK69vf3QoUOV+nXH2bNnuVyucOhwAAAAAABoJOpMpSZPnjxu3DhCCO2vjGxsbETpq6MUAgICvv/++29mdwAAAAAAQER1plKqqqqqqqryDEVuLCwsuFwuLVV9/Phx69attFQFAAAAAABKpDH28KGGDaRFYmIiXVUBAAAAAIASUeJ+SgAAAAAAAExBKgUAAAAAACA2pFIAAAAAAABia4x9pb49hYWF9+7d+/nnn5kO5F8CgSA3N5fpKAAAoBHJzs7Oz89XnEshNTkn9b8A8K1CKvUtMDAwyM3NvXXrFtOB/EtbW7tZs2ZMRwEAAI2IgYEBi8VSnEshn8/X1NQ0NDRkOhAAkCGkUt+C169fMx0CAAAAk3x9fX19fZmOAgAaF6RSAAAAoGTGjh379OlTY2NjpgMRT2pq6saNG3/77TemAwEAeiCVAgAAACXz/v378vJyS0tLpgMRz4sXL1JTU5mOAgBog1QKAAAAlIypqamBgUFwcDDTgYiHw+GYmJgwHQUA0AaDoX8LmjdvzlIwy5YtY/pXAQCQiYEDBzJ9iq2OzWbfuHGD6R8GAKDRwVupb4GmpmaPHj3Gjh3LdCD/WrVqlba2NtNRAADIhL6+vomJycKFC5kO5F8ZGRn79+9ns/FsFABA3pBKfQu0tLTs7e1XrFjBdCD/WrVqla6uLtNRAADIhL6+vpGRkeKccl+8eLF//34VFVzQAQDkDQ+xAAAAAAAAxIZUCgAAAAAAQGyNMZXi8Xjl5eW0VFVWVkZLPQAAAAAAoFwaYyo1d+7c6dOn01KVubn5wYMHaakKAAAAAACUSGNMpbKysrKysmipqkuXLvv376elKgAAAAAAUCL0pFKVlZWJiYkRERGvX7/m8/m01MksEffI3d09Li7u0aNH8owNAAAAmPXp06e+ffviBgCgkZN27FQ+n79v375du3Z9/PiRWtO6deulS5fOmzdP6tiYIdYejRo1ytDQ0N/fv1evXvINEwAAgAHl5eV37ty5ceNGWlra3bt3+Xz+0KFDTUxM7OzsRo0aZWlpyXSAcvL+/fv79+8/f/6c2RuAuLi40NDQN2/epKenE0I2bdp069atNm3aODs7//jjjxgiH0DWpHorVVZW5urqumjRIirr0NLSIoR8+PBh/vz5EyZMUMbXU+LukZqa2tSpU8+cOVNcXMxAuFIoKCjIzs7Ozs7Oy8sTpXxpaWn2/5N1bAAAoIAyMjI8PT2NjIyGDBly/PjxjIwMfX19FoslEAiePXu2dOnStm3b2tnZnTx5UhlvAMRlamoq/F/54/F4fn5+NjY2NjY269ate/HiBZU16enpffjwwc/Pb8CAAcbGxgsWLMjNzWUkQoBGQqpUasOGDSEhIYSQWbNmZWVlcbncmJgYV1dXQsjZs2e9vLzoiVGOJNgjDw+PoqKi8+fPyztW6QQHB5uYmJiYmJiamqakpNRfuLi4uF+/flT5o0ePyidCAIBvxpIlS1SlQL1wYFBFRcWaNWvatWsXHBz8888///PPP1lZWQ8ePPD09GSxWNeuXYuJicnOzj569GizZs1++umnbt26PXz4kNmYZc3Y2FhFRYWRVOr27dudO3f29PS0tLQ8ffp0Tk7Oq1evgoODCSGLFi36559/cnNzIyMjf/rpp7/++qtt27bbt29vDMktACMkT6USEhJ2795NCJk2bZqfn5+xsTGLxbK1tQ0KChozZgwhZMOGDQ3eoysUyfbIzs7OwcEhICCAgYil4O7ubmFhQQjh8Xg7d+6sp2RlZeWkSZMeP35MCFmwYMHy5cvlFCIAwLfin3/+4UnKyMjIzMyMweA/ffo0ePDgHTt2eHp6JiYm7ty58/vvv2ezq98/GBoaurm53b59+/r16xUVFf369fP392ckYPlgs9kmJiYtWrSQ8/fu3bvX2dlZR0fnP//5T3h4+KRJk/T19auV4XA4jo6Of/zxR0JCwsSJE9esWePi4lJUVCTnUAEaA8kb0R45coTH42loaOzYsaPqejab7ePjExoayuPxjh8/vn79eqmDlBOJ98jDw2P+/PkpKSlUcqIUVFVV169f7+7uTggJCAhYt25dXdeDX3/99fLly4SQiRMn7tmzR65RAgB8ExYvXlx1PkNVVVUOh0MISUhIWLVqFSGkTZs21LM8gUBQWVnJ4/GEhZs3by73eP8rOzu7T58+ubm5YWFhQ4YMEWWTwYMHP3nyxMPDY+bMmRkZGevWrZN1kExp0aKFnN9KLVmyxMfHx9PT88CBA6qqqg2Wb9GihZ+f3+DBg2fMmNGnT5///Oc/TZo0kX2YAI2I5KnUqVOnCCGOjo41zyPm5uaOjo4REREnTpxQolRK4j2aMmXK0qVLAwMDN23aJKdY6TBt2rRt27YlJCSUlZV5e3v7+PjULLN169bDhw8TQpycnI4dO8ZiseQeJgCA0qMaitf0999/Uwt9+/YdN26cHCMSSVlZ2ZgxYz5//vzw4UMbGxvRN9TU1Dx16lSLFi02bNjQvn37iRMnyi5I0S1ZsmTfvn0Sb56SkmJmZnbnzp39+/d/9913Xbp0MTExiYiIePbsWVRU1ODBgz09PWmMtqZDhw75+Phs2bJl7dq1Ym3o6upqbm7u5OQ0adKk8PBwKo0HAFpI2MAvOTmZGpjBzs6u1gLU+oSEBBFHNWCcNHvUtGlTFxeXwMBA5WqLzOFwNmzYQC0fPny45n4dPXqUeppob29/4cIFNTU1eYdYGz6fr1y/MwAFhy7URLWdJoT06NGD2UhqtWDBgmfPnp07d06sPIrCYrF27do1YsQIDw+Pt2/fyiI8cdHSzPL9+/dPnz59/Pjxo0ePcnNznzx58vz58+fPn8t6Hx8/fjx//nw3Nzdx8yhK9+7djx8/fvPmTSV6wC0NnG9BbiR8KxUVFUUt1JV4dOjQgVqIjo4eMGCAZN8iT1Lukbu7e3BwcERExMCBA2UWI/0mT568bdu2N2/eFBcX79mz5/fffxd+dP369VmzZhFCLCwsrl69qqenx1yYhBCSlZW1Z8+eS5cuJSUlCQQCS0vLkSNHLl68uGXLlswGBlA/HLpQjydPnlALCphKxcTE/PXXX5s2berXr59kNbDZ7JMnT1pbW69YsSI0NJTW6CRBSzPLGTNmzJgxg1q2s7NbtmyZpqamHIJfsmSJhYXFkSNHJK5h9OjRCxcu3L179+zZs83NzekLTYHgfAvyVz2VEggEN2/ePHHiRFxcnJ6eXo8ePebNm2dqarp06dLw8HA2m/3ixQt1dfX8/HyqvJWVVa31CtfLYuSJQ4cOJSUlEUJWrlxpaGhIS51S7tHgwYPNzMwCAgKUK5Vis9kbN26cMGECIcTX13f58uVU79UXL16MHz+eeg53/fp1ExMTZuMMDg728PD4+vWrcE1CQoKPj8+ff/55+PDhadOmMRgbQD1w6EI9iouLY2NjCSGqqqr29vZMh1PdqlWrTE1NFy9eLE0lurq6Gzdu9PT0/M9//vPjjz/SFZtkaG9mmZCQkJqaKsErO3FdunTpwYMH586dU1dXl6aetWvXBgYGrlu37vjx43TFpjhwvgVG/E8Dv4yMDCcnJ2dn5+PHjz99+vT27dvbt2+3sbGJjIwMCwuLi4vjcDjUP+OCggJqk7oexmhra1MLX758oT3oM2fOeHt7e3t7C8OQnpR7xGaz3dzcQkJCaAxJPsaPH0+9iCssLDxw4AAhJDU1dfjw4VwuV1tbOzw8vF27dsxGGBwcPGnSpKonR6GSkhI3N7djx47JPyqABuHQhfo9f/68srKSEGJvby/lLTLt0tLSrly5smrVKulfuXh4eFhYWFDdbhWTZM0sCwsLS0pKMjMzZRPU/zh8+LC9vf3YsWOlrMfAwGDRokVnzpz5/PkzLYEpDpxvgSn/TaWSkpK6d+8eGRlJCNHS0poyZcrWrVtnzZrF5XLHjBkTHx9PqpxlhAlDXf1nhAPLyCKVkgXp98jd3b20tDQoKEgG0ckQi8USjpaxZ8+eDx8+DBkyJCsrS0VF5dy5c927d2c2vOzs7JkzZwoEgnrKzJkzJyMjQ24hAYgChy40SJFb9128eJHFYkl/704I4XA448aNCw8Pr9q4TqFI9ofIyckhhMghleJyuRERERMmTKBl5KdJkyZVVFRcuXJF+qoUB863wKB/U6nCwsKBAwdSZ4S+ffsmJSWdPHlyzZo1fn5+x48fLygooA7Qnj17UuWFzzMaTDy4XG6tBSorK+v6qEHr168PCgoKCgoyNjaWrIaapN8jKyurvn37KuM0Gi4uLl27diWEfPr0yd7e/t27d4SQv/76S8Rxb2Vq7969DR4nJSUltQ4/CMAgHLrQIEVOpa5cufL999/T1brbxcWlsLDwn3/+oaU2eknczPLTp0+EEDmMrXXz5s2ysrJRo0bRUpuVlZWNjU14eDgttSkInG+BQf+mUgsWLEhNTSWEzJw5MyIiourZc9KkSZaWltSy8HQvfLZU1wApwvVVe20Kpaam9u/fX9g6WVz9+/efOHHixIkTdXR0JKuhJin3iOLh4fH06VPqpKxcNm/eTC1QKeWOHTumT5/OaET/oqa0apAidGgGqAqHLjRIkYfvS0xMrGsQJgl07tyZqpOuCmkkcTNLFRUVUuUxq+wkJiaqqqrS2CPLzs6O6nD+zcD5FhikQgh59erV0aNHCSHt2rXz9fWlzg5CLBbLysoqOTlZU1OzY8eO1EphDlPX+3rh+qqTcJ85c+b+/fuvX7++e/cun89XqDk0JNujalxdXefNmxcQEEANASSZtLQ06r2Q6L5+/Splw4lhw4bZ2dlFR0cTQmbNmrV8+XJpaiOEJCQk3Lp1S8pKqHpEKZacnHzjxg02W8LB/eUgPz9fVVVVV1eX6UDE8+7dOz6fT8ufUnYEAkF6enqrVq2YDuR/fDOHbl5enpaWlpaWFtOBiCc5Ofnr168yOnQ/fvxYUVEhZSU5OTnv378nhOjp6QlHiJXG8+fP63nSJ660tDQul9vgD5iQkCAQCET5nTU1NSMjI2kcOC4vL4+WKTokfjdI5V0aGhrifqO418cHDx7o6+tHRETUX6y4uJgQ8vbt2wYrLy8vT0pKktG/Duq5/MuXL+V5WvtmzreEkM+fP3M4HMaHTZaD0tLSoqIiZqcgryorK8vAwECs5ykcDqdXr15EIBAIRzW5ffu2oDbUXAp9+vQRrhFOXh4VFVXrJvfu3aMK7NmzR7jS0dGxZcuWzs7Offr0IYTs3bu31m1lbcSIEf369au2UrI9qsnd3d3ExITP50scHvXjiMvBwUHibxQIBBcvXhTO2TdixAhpqhLU21gZAOAboK2tLeV5UvgcfcCAAVJW9Y011hKdsbGxlD+dQCCgxrAlhBw9elSsDak+5KdOnRJrK0Z/MACgma+vr0plZSX1xtPe3t7JyalmoYyMjPT0dPK/D2yED9frGoNB2BGz6jucO3fuUJ0mV61adf/+fXp2giaS7VFN5eXlqqqq0vQNPX/+fFpamlibjB8/3sHBQeJvfPDgweTJk6kWDoSQsLCwx48fC/vFSYDFYi1YsOCnn36SuAahSZMmidImpE2bNufPn5f+62SnqKiIw+EIx4FUFgEBAYcOHRI2Q1JYWVlZjA/ZX803c+jm5+dra2sr2vhyDdq1a9edO3dk1Ld+8+bNIj4Fr4fwn5U0J1sKdfAfPnyY6vVKix9//HHq1Kk///xz/cWOHz++f/9+4YudevTp08fNzc3T05OmAMnChQuFTwClIXEzS8neSrHZ7Hnz5ok1MPfu3btv3bp19erV+ot9/frV0dFx7dq1o0ePbrDC27dvy+hfR1JS0sSJEw8cONCrVy9Z1F+rb+Z8S5T2bkEC5eXlXC63adOmTAfyr7y8PH19fbGa7LLZ7I4dO6o8e/assLCQENK/f/9ayz169IhaqHqWadasGbWQlJRU61sUYTPcJk2aCFfSMviMjEi2R9UUFhaGhIRIOQtH8+bNxX3dqaGhUa1ZpujevHkzcuTIkpISa2vr2bNnL1myhBCyfv3669evS1YhxczMjJaL+uTJk7ds2SJKMRrvIUDo1q1bbDYbv60EcOgyy9TUVENDQ0a/raGhofRTJtI+5kT79u1p3N9WrVqJ8m//zp07hJAGixUUFJSWlvbq1YvGCPX19UtLS6WsRJpmllQSJcFg8eJeH7t27Xr27Fl7e/v6U8eioiJCSJs2bRqsvLKy0tLSUkb/OqgMs127dvI8s+F8CwxiUycRQkiLFi1qLSFMpao+OaO6kBJCqBfcNQkTD2H3KgVHyx4FBQWVlJQI50FXfOnp6UOGDPn8+XPz5s2vXLkyb948qjHnjRs3FOS14fz58+t/DUgI0dXVXbRokXziARARDl2oh0AgePr0KbXM+JwTtWrXrt3Lly/pqo2qSjjTveIQJrTdu3cX92kvlURJ0FdKXO3atePxeDSOaPXy5UsF/FtIA+dbYBCbGs2TVBkNvBoqlTIyMqraW9TW1pY6fTx//rzWrWJiYgghBgYGjE/wKiJa9sjf39/R0VFZzlAFBQVDhw5NS0vT1NQMDQ21sLBQVVUVnmiEnceY1axZs+PHj9fTSZTNZh89elRxui0CUHDoQj0SEhKoa66ZmVldzzGZNXz48KdPn1LN+6V36dIlQ0PD77//npbaaCRNM0tdXV0VFRUaRxKuy8CBA7W0tC5evEhLba9fv05ISBg5ciQttSkInG+BQWwjIyNqiRq9rZr09HTqmU21Fgjq6urUv8O7d+/m5ubWtdXo0aMVuVFfVdLv0evXr588eeLh4SHrUGlRWlo6atSo2NhYNpt98uRJ4VXE09PTwMCAEBIZGUm13GDcyJEjQ0NDa21Na2BgcPHixTFjxsg/KoAG4dCFuijyjFKUUaNGsVisc+fOSV9VRUXFhQsXhg8fLnFDdNmR8g/RtGlTQ0NDWiOqhZaW1oABA86ePVvXZC1iCQ4OVldXV4R5I+mF8y0whS18x3LlypWoqKiqnxUXF7u7u1OjbNc8y7i5uRFCSktLd+zYUe2jLVu2UMPUuLu7yyZsmZByj/z9/XV1dcePHy/TIGnB5/OnTJlCjUno4+NT9fyio6Pz66+/UssK8mKKEDJ8+PCkpKRt27ZRLWF0dHR69uy5ZcuWpKSkb+zRGnxjhIcuNUWPnp4eDl0gypBKtWjRYvTo0V5eXg3OfNqgQ4cOpaWl/fLLL7QERiPpm1k2bdpUPp3mf/3119evX58+fVrKenJzc/fu3fvTTz99k2NtC8+3vXr1otr72dnZ4XwLMicQCITdhExMTMLDw0tLSz99+hQSEmJrayssdvXq1Zpjeg4dOpQQwmKxjhw5Ilx54MAB6h2ri4tLXYOBrly5kkgxGLqrq6uZmZmZmVlKSooEm9c6GDpF4j0qLy83MjKaPXu2BPFIz9ra2tPTU/Tyc+fOpf6s8+bNq/lpTk6OsB/ttWvXJIiHxWJ5e3tLsGGDCgoKCCF//fWXLCqHmry8vFRVVZmO4lvw9u1bQkh4eDjTgTQWCxcubN26tYwqd3d379SpkzQ1CDOoO3fuSB8P1S6dlqqqiouLU1FRWbNmTT1ldu3axWaz6ynw6dMnIyMjV1dXemMTCATDhw+Xchx54RSOZmZmktXg6Ogo7twnbDZ7165dEnzXgAEDLCwsuFxuXQWoIcT8/PzqqWTOnDlaWloZGRkSBCAiqjfE9evXZfcVoggLCyOExMXFMRsGNAZsQsjGjRupVCErK2v48OG6urrNmjUbO3asjo6OcIiFWh/Y+Pn5mZqaCgQCT0/Prl27urq6tm/f/rfffuPz+ebm5ocOHaIl2aspNzc3PT09PT1dOH43XSTeo7CwsNzcXKVo3bd169Y///yTEDJq1Ki9e/fWLGBkZCR8+aY4L6YAAL4N5eXlVBsQBR8es0OHDvPnz/fy8pJ41Gwejzdx4sSysrLt27fTGxstpH83uHnzZrn1YvD29s7MzJw+fbpA0smpTp06dfjw4dWrVytm9zwAJcUmhIwZMyYgIEA4mT2Px3NwcPD393/w4EFeXh4hxMrKqtbWwC1btnzx4gU1G9WLFy/OnTtHTbXh7Oz8+PFjRZvmRRQS75G/v7+1tbU8Z1GQzN9//01lR926dTt9+nRdfTSXLl1KDbr69OlT4TySAAAgvejoaKrlvI2NjXBKQ8Xk5eXl6Og4efLkFy9eiLstn8//7bffIiIiTp482bZtW1mEJyXpU6kff/yRvnAaYG9vf+TIkfPnz69cuVKCbOrevXuzZs0aPXr0qlWrZBEeQKP1bx9QNzc3FxeXqKgoHR0da2tramqwtLS07OxsUu9ZxsTE5Pbt2y9fvrxx40Zubq6ZmZmTk5OwxaCMyHQ4BAn2KDMz8+rVq15eXrKLihZhYWHUfIvm5uZhYWHC5LkmCwuLCRMmUM2y169fP2LECGUZPgQAQMFJPCes/KmqqgYHBzs6Ov7444+BgYGidwYuKiqaOnVqeHi4j4/PiBEjZBqkxGicJVk+pk2blpiYuHnz5rS0tL///lv0Ka38/f1/+eUXOzu7Y8eO1TPMHQBI4L/D6ejr6zs6Olb9TPQHNg4ODg4ODrQHxyCx9ujYsWMsFkusycvl79GjRxMnTqysrGzSpMmVK1eMjY3rL79ixQoqlYqKigoJCRk3bpxcwgQA+MYp/pgTVRkaGv7zzz9TpkyZMGHCjBkzNm/eTE0/WBeBQHDu3LlVq1ZlZWUFBwcr7FBMytLMsppNmza1bt36l19+iY6O3rVr17Bhw+ovn5SUtHr16uDg4MmTJ4uVfQGAiOp7OCEc2UYpTvcM8vf3Hz58eIPJCYPi4uJGjBhRXFysqqoaEhJiY2PT4CZ2dnbCwVI3bNhAyxisAACgXKkUIURPTy80NNTLyyskJKR9+/Zz5869ceMG1UaxqrS0NF9f3549e06YMKFFixb//POPwuZRRKmaWVYzc+bMu3fvamlpDR8+/Mcffzxy5EhWVla1MqWlpWFhYR4eHt99911ERISvr+/JkyeRRwHIQn2TPFCnexUVFbreOF25coUa2uXhw4eEkFu3bpWWlhJCevXqVe2FmBJ58OBBfHz8rl27mA6kPtbW1lS3N7FcvXpVFsEAADRmcXFxTIcgNjabvXz58pkzZ27fvv3EiROHDh3S1dVt06bN169fBQJBnz59MjIy3r9/z2KxevXqdenSpVGjRjEdcgOUqJllTb169Xry5MmZM2d8fHzmzJkzd+5cc3Nz6nnuzp079+7dm5KSUlxc3LJly2XLli1btowaGRwAZKHOVErw/+Ordu7cWUNDg5YvO3v2bGBgoPA/w8LCqNEqV65cqbyplL+/v7GxcYMv2QEAAJSaoaGht7f3zp07Hz58ePPmzffv30dHR+vq6pqYmHTt2tXW1nbUqFGK3ECjKqV7N1gNi8WaNGnSpEmT0tPTQ0ND4+LiPnz4oK2t3bRp044dO06aNMnZ2blbt27o5wwga3WmUnFxcUVFRYTW7pgBAQEBAQF01aYIuFxucHDw3LlzFXASdwAAANqx2ezevXv37t2b6UCkouyplJCZmZkCTn8M0HjUmQCgo5Qozp49y+VyhbMwAQAAgOJTxmaWAKCA6kylJk+eTA3aRlfrvm9SQEDA999/L8ooDgAAAAAA8C2pM5VSVVVVVVWVZyhyY2FhweVyaanq48ePW7dupaUqAAAAAABQIo2xh8++ffvoqioxMZGuqgAAAAAAQIlg0msAAAAAAACxIZUCAAAAAAAQW2Ns4Pft+fr1a1RU1I4dO5gO5L8KCwuZDgEAQCby8/Nzc3MV55SbkZFBCCkrK2M6EACARgep1LdAIBDExMQkJCQwHci/2Gw2n89nOgoAAJng8Xj5+fmKk0rx+XwOh/OtjhQFAKDIkEp9C9LS0pgOAQCgsQgLC2M6BAAAUAhIpQD+xeVyu3XrZmVlpaWlxXQsYigqKsrIyIiOjmaz0fWxkXr//v2AAQNsbW3V1NSYjkUMnz59Kisru3//PtOBgFLKyMj4+PHjhAkTmA5EPAKBgGqQCQDfBqRSAP/Kysp69+6durp68+bNmY5FDBkZGW/fvi0uLtbR0WE6FmBGfHx8UlKSgYFBkyZNmI5FDKmpqenp6UxHAcqqU6dOJSUlnz9/ZjoQ8bRs2bJjx45MRwEAtEEqBfAv6on+unXrxo8fz3QsYjh8+PCcOXNYLBbTgQBj9PT0CCF79+7t3bs307GIYePGjXv37mU6ClBWx44dYzoEaKT++uuvOXPm6OrqKteVVyAQfPny5ezZs2PGjGE6lm8KUqlvwdChQyMjIzU1NZkOhBBCBALB169fr1y5MnDgQKZjAYU2f/78w4cPa2trMx3Iv6hD9++//542bRrTsYBCGz9+fFhYmOK0BObz+cXFxbdv3+7bt6+Im8TExHTr1k1TU1NBGgaXlJTY29s/fPiQ6UAAGsbn8ysrK3/99VddXV2mYxFDXl6et7c3j8djOpBvDVKpb0F5eXnTpk0V5P4vNzfX39+/uLiY6UBA0ZWVlXE4HE9PT6YD+ReXy/X19cWhCw0qKyvT09Pz8PBgOpB/ZWdnBwYGfv36VfRNvn79Wl5ePm7cuNatW8suMNGdO3cOg7mDsqCa0//2228mJiZMxyKG+Ph4b29vBXns/i1BKvUtaNasWevWrb28vJgOhBBCYmJi/P398W8VGtSsWTNtbW0FOW4JIZmZmb6+vlRjOYB6GBkZmZiYKM6h++LFi8DAQA0NDdE3odoze3p69uvXT1ZhiSM2Nra0tJTpKAAAxKYQb/YBAAAAAACUC1IpAAAAAAAAsTXGVIrH45WXl9NSFdp2AwAAAABTiouLS0pKmI6i8WqMqdTcuXOnT59OS1Xm5uYHDx6kpSoAAAAAANHx+XxHR8d58+YxHUjj1RhTqaysrKysLFqq6tKly/79+2mpCgAAAABAdMeOHXv27JlyzYf5jaEnlaqsrExMTIyIiHj9+jWfz6elTmaJuEfu7u5xcXGPHj2SZ2zwDfv06VPfvn1xRIHSwaELACBnJSUlGzZscHJyGjJkCNOxNF7SDobO5/P37du3a9eujx8/Umtat269dOlS5X3VKNYejRo1ytDQ0N/fv1evXvINs3HJy8u7cuXKmzdv3r9/Twjx8fGJiYlp06aNs7Pzd999x3R0dHr//v39+/efP3/O7BH18uXLW7dupaWlXb58mcfjzZgxo2XLlp06dRo6dKi+vj6DgSmdjx8/Xrly5d27d3FxcYSQLVu23Lx508rKaujQoZaWlkxHRydFOHT5fP6TJ08iIiI+fvx47ty5vLw8Dw8PMzMzBwcHZ2dnxZlRFwCAFrt3705PT79w4QLTgTRqUqVSZWVlU6ZMCQkJof5TS0uruLj4w4cP8+fPv3fvXlBQkIJMoy46cfdITU1t6tSpgYGBe/fuVcbr9NevX7lcLiFES0urwUm7c3JyBAIBIcTIyEhuf9nQ0FAfH5/79+9XVlaamJgYGRkRQr58+XLhwoXMzMzFixe3a9fOw8Nj/vz5yvj712Rqair8X/krLCz09vY+fvz4+/fv1dXVW7RoQc308uLFi/Dw8Ly8PDU1tf79+y9fvtzJyYmRCJUFn88/derUgQMHnjx5QggxMTExMDAghOTm5p47dy4zM/O3337r3Lnz7NmzPT09qRl+lB2zh252draXl1dQUFBWVpaGhoaZmVlFRQWLxXry5MnFixc/f/6sqanp7Oy8evXq7t27MxLht0TxLxwAjUFOTs6uXbtmzJjRpUsXpmNp1KQ6r23YsIHKOmbNmpWVlcXlcmNiYlxdXQkhZ8+eVZzpC0UnwR55eHgUFRWdP39e3rHSYcmSJSYmJiYmJgEBAfWX/Pz5s7GxsYmJiYWFhXzacL548aJv374uLi5fv3719vZOTk7OzMy8d+8eIWTDhg3v37/Py8s7c+aMg4PD2rVr27VrFxgYKIeoZM3Y2FhFRUX+96MCgeCPP/5o27btzp07HR0dL1y4kJ+fn5ycvHDhQhUVlVevXuXm5r59+3bz5s3p6ekDBgwYOnTou3fv5BwkIWTJkiWqUkhPT5dDkHfv3u3ateu0adPU1dUPHjyYnp7+8eNH6hSxb9++tLS07Ozso0ePtm7dev78+d9999238UCRqUO3oqJi8+bNVlZWfn5+Li4uV69eLSgoSEhIcHNza9GiRWxsbH5+/suXL1esWPHq1auePXtOnDgxLS1NzkESJTl0RaTIFw6AxmP9+vUVFRUbN25kOpDGTvJUKiEhYffu3YSQadOm+fn5GRsbs1gsW1vboKCgMWPGEEI2bNiQkpJCW6SyJ9ke2dnZOTg4NHhFUUyPHz+mFnr06FF/SerhOiGkS5cuKirStgtt0OnTp3v37p2dnX327NknT54sXLjQwsKiWhk9Pb0JEyacOXMmOjq6S5cu7u7uM2fOpGuYe6aw2WwTE5MWLVrI80u/fv06fvz4RYsWDR48+O3bt0ePHh09enTNt3zW1tbU/WhAQEBsbGyPHj2uXLkizzgJIf/88w9PUkZGRmZmZrKOcN++fQMHDiSEXL9+/e7du3PmzKn51zQ0NHRzc7t8+fKjR49atmw5duzYlStXKvuNJiOH7qdPnwYPHrx58+apU6cmJCQcOnRoyJAh6urq1YrZ29tv2LDh7du3f/zxR0RERPfu3f/55x95xkmU4dAVncJeOAAaj7i4uL///nv58uWtWrViOpbGTvJT25EjR3g8noaGxo4dO6quZ7PZPj4+oaGhPB7v+PHj69evlzpIOZF4j6gGZikpKTVv9xVZSUlJbGwsIURNTc3BwaH+wsJrZ8+ePWUd2I4dO1atWjV69Ohjx47p6Og0WL5jx46XL1/ev3//4sWLExMTr127pqmpKesgZadFixbyfLRfUFDg5OT09u3bEydOTJkypcHybDZ7xowZI0eOdHV1HTVq1J9//jl79mw5xElZvHhx1WxZVVWVw+EQQhISElatWkUIadOmDfVARCAQVFZW8ng8YeHmzZvLOrwFCxbs27dv9uzZBw4cEKXZXo8ePSIjIzdu3Lhly5b4+PizZ89Su6Ok5Hzopqen9+vXLy8vLywsTJQu12pqavPmzRszZoyLi4uTk9Pp06epZ2TyoeCHrugU9sIB0KgsXbq0adOmS5YsYToQkCKVOnXqFCHE0dGx5rXT3Nzc0dExIiLixIkTSpRKSbxHU6ZMWbp0aWBg4KZNm+QUKx2eP39OXa3t7OxqPsetRm5XxODg4FWrVs2bN2/Pnj1iNayfN29e+/btR40aNXPmzJMnT7JYLNkFWdWSJUv27dsn8eYpKSlmZmZ37tzZv3//d99916VLFxMTk4iIiGfPnkVFRQ0ePNjT05PGaKvh8XgTJ05MTEy8c+eOWKMFGBoaXr9+3d3d/ZdffrGwsKDew8gB1dq2pr///pta6Nu377hx4+QTTDV//PHHvn37tm3bRt0Zi4jFYm3atKl9+/Zubm7Lli3z8fGRXYTVKPWhW1xcPHr0aC6X++jRI2tra9E3NDMzu3fv3rhx46ZNm3bv3r0GkwG6KPKhKxbFvHAANCqRkZHh4eFHjhxpsLMiyIGEDfySk5OpAe7s7OxqLUCtT0hIyMvLkzg4eZJmj5o2beri4hIYGKhcTXSETS9EucgJCzfYokMasbGx7u7uI0aMEDePojg7Ox88ePD06dPyvB+lpd3O+/fvnz59+vjx40ePHuXm5j558uT58+fPnz9/+/atTINfvXr1rVu3Tpw4IcGoa6qqqn///TeDnU+qEr3FkYxERkYuWbJk9uzZYuVRQlOnTt20adOePXuoBzryodSHrqenZ2xsbEhIiFh5FEVLS+vMmTNt2rQZPXp0QUGBDKITA+OHrrgU8MIB0Kjw+fylS5fa2Ni4u7szHQsQIvFbqaioKGqhrsSjQ4cO1EJ0dPSAAQMk+xZ5knKP3N3dg4ODIyIi5PZ4XnqiPy9MTk6mEsjmzZubm5vLLqSlS5c2a9bs5MmTEg/0NHPmzH/++Wfjxo0//fSTsbExveHVipZ2OzNmzJgxYwa1bGdnt2zZMjm0UUxISNi7d+/y5ctHjRolWQ3q6urnz5+3sbFZs2bNsWPH6A1PLMzesfH5/IULF3bq1OnAgQMSV7JmzZqHDx8uXbrUxcVFW1ubxvDqoryH7oMHD06ePLlv374ffvhBshr09PQuXLjQuXPn7du3V2vRLWdKl2wo4IUDoFE5duzY8+fPr169iv6HCqL6n0EgENy8efPEiRNxcXF6eno9evSYN2+eqanp0qVLw8PD2Wz2ixcv1NXV8/PzqfJWVla11itcL4uRJw4dOpSUlEQIWblypaGhIS11SrlHgwcPNjMzCwgIUKJUSvRLuHwaaURGRl6/fv3o0aNSvrDevn372bNnN2/e7OvrS1ds9aC93U5CQkJqaqqNjQ0NwdVr1apVTZo0kewtipCxsfGqVatWrly5cOFCpsZjLS4upjpvqKqq2tvbyz+AEydOREdH37hxQ5phzVkslo+Pj62trY+Pz7p162gMry7Ke+iuWLGiffv2c+bMkaaS9u3b//LLL/v27fv1119bt25NV2xiYfzQlYCiXTgAGhXMyauA/ufZf0ZGhpOTk7Oz8/Hjx58+fXr79u3t27fb2NhERkaGhYXFxcVxOByqbbSwUURdDyCFT1W/fPlCe9Bnzpzx9vb29vamsW2GlHvEZrPd3NxCQkIYby4iopycnNTUVEKIgYFBu3bt6i8snyYof/zxh7W19U8//SRlPc2bN//111/9/f2pmU+YItmPVlhYWFJSkpmZKZug/uvjx48XLlxYtWqVnp6elFXNmzfP2Nj4zz//pCUwCTx//ryyspIQYm9v32DnDVnw9fXt16/foEGDpKynQ4cOU6dOPXjwILNNhRX80H3x4sWDBw82bdqkqqoqZVVr1qxhs9l//fUXLYFJgPFDV1wKeOEAaFSoOXl37drFdCDwX/9NpZKSkrp37x4ZGUkI0dLSmjJlytatW2fNmsXlcseMGRMfH0+qnBCFCUNdT2GFFzlZpFKyIP0eubu7l5aWBgUFySA6+lV9stjgCA1yeLhYXFx848aNiRMn0jKH4+TJk0tLS69fvy59VRKTrN1OTk4OIUQO96OXLl0SCAR1vZcQi4aGxpgxY0JDQ6mbQvljtolURkbG06dPJ0+eTEttkydPzsrKevToES21SUbBD92LFy9qaWlJ3Cq1KkNDQ2dn50uXLklflWSUrnWfol04ABoVzMmrmP69bS0sLBw4cCB1Fezbt29SUtLJkyfXrFnj5+d3/PjxgoICarZy4Qnx8+fP1EKDiUetbwa4XK40d13r168PCgoKCgqisTOMlHtECLGysurbt6+/vz9dIcmU6Be5ioqKly9fEkJYLFb37t1lFE9ERERxcbGLiwsttXXu3NnCwiIsLIyW2iQgcbudT58+EULkMFhLeHh49+7d6ZqsxsXFJScn59mzZ7TUJi5m70fDw8NZLNbIkSNpqa1///76+vo4dOsRFhY2ePDgmvOeScbFxeXVq1fv37+npTZxKV0qpWgXDoBGBXPyKqZ/+0otWLCAems/c+bMQ4cOVe3KNmnSpLVr1yYnJ5Mqp3thZ+W6GqII11ftqVxZWblv3779+/enpqZqaGjY29v/+uuvU6dOFTfo/v37i7tJgyTbo2o8PDzc3d1jY2NtbW1pj5Bewku4qakp1fGsLm/evCkrKyOEtG/fvkmTJjKKJy4uTkVFpa4xPyTQrVu3d+/e0VWbuCRut0P905O+5VKD3r17N3jwYLpq69q1K1UnI4+fmW1H9O7dOxrnU1JTU+vUqRMO3XrEx8fTOGg4dejGx8e3adOGrjpFp3RN4BTtwgHQeFBz8q5ZswZz8ioaFULIq1evjh49Sghp166dr69vtSFBWCyWlZVVcnKypqZmx44dqZXCiVOrDgBVlXC9vr6+cOWMGTNOnjw5btw4Nze3uLi40NDQn3766c6dOww2VReSbI+qcXV1nTdvXkBAADXslWSKiorEfbL79etXsTpXCASCp0+fUstz584VcSux7pIzMzOp9FtEb968MTQ0pPL5elCtK3NzcxusXEtLKzU1VawYqNHwaSHxw2bq5lVDQ0P0Tag3xikpKWI9p8/IyNDQ0Gjw98nPzxcIBA0WEwgE6urq0dHRYv3gwtfd0sjJyaFeKejp6QmH2ZSyQrH2Ii4uzsDAoMFNqPHis7KyGiypp6eXlJQkVgwZGRmiF66fnA9dPp8v1p5++fLl69evKioqDW5VWFjI4/EaLEad2F++fNm2bVuxwpC+Pxvth65YZ10JjhmZXjgqKytLSkrEOhhkqqCgQBkzwMLCQj09PblNq1ir9PR0Iv49AO2ysrIIIWlpabJ4vkO1Z6ZdSUkJl8ul7nOaNGmioaFR9bJO15y8olyG5KOysrK4uFhxpsYqKirS1tamRrIVEYvFat26NREIBNOmTaNW3b59W1AbqhVQnz59hGuEA0xFRUXVusm9e/eoAnv27KHWnDt3jhBy+vRpYZnXr19TNZ87d67WSmRkxIgR/fr1q7ZSgj2qlbu7u4mJCZ/Plzi8H3/8UYIjwMDAQPSvkOyZt6+vryiV3759W4LKFcemTZsk/dP914QJE6jajh49KtaGVKfEU6dOib6JlOOYMYvD4Yj501Z3+fJlqqoBAwZIWZWCXF0kVvXsKjF5HrrDhg1j9AeTio6Ojpg/bXU0HrpXrlyRbC8CAwNF/xaZXjjwoB2UTmpqqqT/ZAV8Pj8mJubgwYO//fabs7OzpaVlrXfwampq7du3Hzp06JgxYwghW7ZskfgbBQKB8DU40OjgwYMqlZWVoaGhhBB7e3snJ6eahTIyMqhnDFUfUgqTyLrGYBB2Pha+w9m/f/+QIUMmTZokLPPdd9/t3r174sSJW7duZXyWdwn2qFbl5eWqqqrSPBP6+++/G3w5U83WrVuLiopELy/85zRu3DjhwMd16datW2JiIhH5KbWRkREhxMvLi2o5I6I9e/Y8fvy4wUE7vn79Onr06MWLFw8dOrT+kgcPHoyMjAwODhY9hpycnKlTp0ow42dNErfbkeDRPtWa9PLly2JtNWzYsKlTpzbYvPbMmTOBgYFXr15tsMIRI0aMHTvWw8ND9Bj8/f2vXbsmevla0di1nfoBV69eLVYT4rVr13769KnBAQzT0tI8PDx+//33Bg+JzZs3p6Wl+fn5iR5DXFzcvHnzaOn5Js9D187O7u7duxcvXhR9ky9fvowdO3bZsmUNNk/9888/79+/f/LkyfqLUaeU+fPni9XbzdvbW9yzdE00HrpUt2Fvb2/R20gnJCT88ssvYo0CL9MLR/v27Zs1a7Zz507R45EdHo+XkpLS4BCFCigpKal169ZyaGdbj9TU1NmzZ2/fvr1bt24MhvHo0aN169b5+/vLIkuPiIjYvn27BKNuFhYWXrhwITQ09N69e3l5eSwWy8zMrH379oMHD27dunXTpk11dHS0tbUrKirKysqKi4s/ffqUkpKSkJBAPaRet27dgQMHfvzxx7Fjx44aNUrcLqPUi9YtW7b06tVL3Mhlgcvlfv78WXEeo6SmphobG4s7NWKvXr1Unj17VlhYSOrugCQcS6rqCbFZs2bUQlJSUp8+fWpuJWxFLXxFbmlpWXOw4BEjRrDZ7NevX1dUVDD7j1+CPaqpsLAwJCRk8eLF0kRiZWVV19xWdfHz86NapYtI2Iand+/e9WeGhYWF1I6rq6uL1ZGpS5cuYk2x9eLFi1u3bg0YMKD+LJQ6Vr/77rsGK//rr7/at28vVgwfPnwghEg/hKA07XaoO1Gx/iVTLXL79+8v1ryuZmZmurq6Df4+z58/Z7FYDRYrKCgoKysbNGiQWD/4nTt3xHqTXivaO+7b2tqKtRdhYWEXL15scJO4uDhCiL29fYMlt2zZIkqxqqgnQdK36pHzoaumpqaioiLuXHyampoGBgYNbhUeHq6hodFgsbdv3xJChg4dKlYYp06dkr49MO2HbteuXfv16ydi4aZNmxIxjxmZXjg0NDSaNm2qRBMzKiZF+AGpcWvEvQegHXVT9MMPP9DSerYacRv48fn88PDwo0ePhoeHl5aW2tvb//TTT46Ojn379hVlctTAwMDIyMiTJ0+qqKjcv3//xo0bZ8+e1dbWHjly5MyZM8X9ncW9vkCDVIQjF7Vo0aLWEsJUquqTs86dO1MLVKOOmoSJh7B7la+vb80BGzQ1NbW1tb98+fL58+fmzZtLsgc0kWCPagoKCiopKZkxYwbd0dFM9KehT58+FQgEhJAuXbrINNe1tLQsLy+Pj4+n66wXGxvbqVMnWqoSl/CGo3v37uLe3VJ3omI92peMpaVlTEwMXbVR104LCwu6KhSRoErnDaZGCbO0tMzIyPj8+bOBgYH0tVVWVr59+1b62dUkoxSHrrm5OXW80aIxH7riUsALB4CCKysrO3HihLe3d1xcXLt27VasWDF58mSx7nOEc/JOmTKFEEK1wY6Ojg76fw4ODkuXLp0wYUK1kQ5AbtjUCLakymjg1VCplJGRkbm5uXClra0tdcl8/vx5rVtRd2lVZ/HT1NSs2bfs3bt3X758adq0KbN5FJFoj2ry9/d3dHQU952SnJWVlUVHRxNCVFRUHBwc6i8st7F6Bw0apKamRtcEL0lJSa9fv2aqJ4Y07XZ0dXVVVFSEg6DIzrBhw6gGBrTUdvHiRX19/R9++IGW2kSXkJBAnbjMzMzqehgka8OHD+fxeOHh4bTU9s8//+Tm5uLQrcewYcOuXLlS1/hA4rp48WLbtm1l8dy6fopw6IpFMS8cAApLIBAcPXrU0tJy1qxZLVu2vH79enx8/MaNG8U929Q6J6+dnd327duTkpJCQkI0NTWnTp3aoUOHCxcu0LoHICo21bOFEEKdJatJT0+nzonVTojq6upUy/K7d+/m5ubWtdXo0aPrf7RJdZadNWuW5HtAE+n36PXr10+ePBGrrwgjoqKiqLuQTp06NdgaR25zLOrr6zs6OlJjk0jv7NmzKioqw4cPp6U2cUl5G9G0aVNR3vhLycXFpbKykpbctbKy8sKFC8OHD69rTjbZUYQ7trZt23bs2JGuQ/fcuXNNmjRxdHSkpTZxKcuhW1BQQMvwNsXFxVevXqVrOjuxKMKhKxbFvHAAKKYXL1706dNnxowZdnZ2T58+vXXrlmSzj9Q/Jy+bzR4zZsyDBw/u379vamo6duzYQYMGvX79WurwQTxs4TuWK1euREVFVf2suLjY3d2dOnvWPN27ubkRQkpLS3fs2FHtI2qMEUKIu7t7Pd+dkZGxdevWtm3brlq1SqqdoImUe+Tv76+rqzt+/HiZBik94SVclIucWIWlNHv27KdPn0o/OWlhYeHu3bvHjRtHdQaQM+nb7TRt2lQOkbdt29bJyWnbtm3SP90/evRocnLy7NmzaQlMLApyPzp79uzQ0NC6XmiLLj093c/Pb8aMGYy0iVKWQ/eHH37o2LHjxo0bBVKPpL9nz56ioqKZM2fSEphYFOTQFZ3CXjgAFAqPx1u9enWPHj2ysrIuXbp05coVaYbfEHFO3t69e9+7d+/kyZNv3751cHDYuXOn9LM1gOjYdnZ2VDchgUAwdOjQK1eulJWV5efnX7hwoWfPnrdu3aLK1TzdjxgxghpFzcfHp+pgU76+vtQ8US4uLn379q3ri4uKioYPH66qqhoeHi7u7A0TJkxo1apVq1atpB9DqSpp9qiiouL48eOTJk0Sd0AV+RN9hK60tDRqZoZmzZpZWlrKOrDx48f36NFj5cqVFRUV0tSzffv2oqKi33//na7AxCJ9ux1jY2M9PT2646rFjh07UlJSfH19pamEy+WuX79++PDhovd3p5GCPPyeO3euubn5smXLpLy5X7NmjZqa2tq1a+kKTCzKcuhyOJzt27c/efJErPE5a8rOzt65c6e7u/t3331HV2yiU5BDV3QKe+EAUBzv3793dHTcsWPH0qVLX79+PWrUKGlqo+bkXb58uShj3LFYrClTprx7987Dw2PFihXOzs7CcadB1tiEkI0bN1KjlmVlZQ0fPlxXV7dZs2Zjx47V0dERDrFQ60NKPz8/U1NTgUDg6enZtWtXV1fX9u3b//bbb3w+39zc/NChQ3V9a1FR0ZAhQwoKCu7fvy9BI/Xc3Nz09PT09PTKykpxt62fxHsUFhaWm5ur+K37iDhPQ+X83JTFYu3evZsa1lniSq5evert7b1gwQKxJtykkfQ/2ubNm+UzwWK3bt2mTZu2evVq4dAy4hIIBDNmzPj06VPNF7lyUF5eTr1IZ7PZYo28Tzs1NbWdO3feuXNny5YtEldy9OjRY8eObdiwQQ5t5GqlRIfuyJEjBw4cOGfOHMlmOiKEVFRUTJgwgcPhbNq0id7YRKE4h67oFPbCAaAgbt686eDgkJSUdO3aNS8vL+nH4JFgTl5tbe1Dhw6dP3/+xYsX9vb2El/cQSxsQsiYMWMCAgKEr1N4PJ6Dg4O/v/+DBw+oXulWVla1Xt1btmz54sULajaqFy9enDt3LiEhgRDi7Oz8+PFjExOTWr+yqKjI2dk5Nzf3P//5j6LN2yDZHhFC/P39ra2tFWSo/nrk5+dTe6Sjo2NjY1N/Yfk/N+3Tp8/OnTsPHz68d+9eCTaPiYmZMmXKjz/+yNQrKULHbYRkczRL5uDBg9bW1mPHjk1JSZFg87Vr154/f97Pz6+eYS1lJzo6mmqdaGNjw/h06ePHj1+yZMnGjRsbnButVv/5z39+/vnnCRMmLFy4kO7QRKVch+6pU6eaNGni4uIi7qjEhBA+nz937twHDx4EBQUxMuSDQh26olDwCwcA406dOjVixAhbW9uoqKiaE/9I4M6dO+Hh4b///rsEp4ixY8dGRUW1bNlywIABwqnAQXb+HTnRzc3NxcUlKipKR0fH2tqamqAmLS0tOzub1HtlNTExuX379suXL2/cuJGbm2tmZubk5CQcWLymwsJCZ2dnLpd77969ejKT+t25c0eyDUUh7h4RQjIzM69everl5SW7qOhStS9EgxMoMfJwcfHixXFxcYsWLUpLS9u5c6fo8w6FhYVNnTrV1NT07NmzDA6/q1y3Edra2pcuXfrhhx969ux57tw50W+Fy8rK5syZExgYuGbNGqZG7pZ4MlkZ2bFjR0JCwtSpU1NTU1esWCH6+5ljx479/PPP9vb2AQEB8nmrUyvlOnSNjIxCQ0MdHR179ux56dKl+k/RVX358uWnn366fPnyvn37JOsILj1FO3QbpPgXDgAG7d27d8mSJaNGjTp9+jQtE0Lw+fxly5bZ2NhIPLlOq1atIiMjx40bN2bMmMOHDzPSI7Tx+O8g9NQQalU/E/2E6ODg0ODoqISQwsLCwYMHV1RUREZGCqfEVUwi7hHl2LFjLBZr2rRpMg2JFqJfwvl8vrAbvZyviIcPH27duvX69eufPXvm4+PTYAOYvLy8LVu2HDhwwMnJ6cyZM4yMNkFRxnY7rVu3fvLkyZgxYwYNGrRs2bLly5c32N3lP//5z6JFi2JiYnx9fX/55Rf5xFmTot2xcTic8+fPL168eNWqVQ8ePNi1a5e1tXX9m6Snp69du/bo0aOurq6BgYEM9rRUxkO3U6dOjx49cnFx6d2797p16+bPn9/gTUx4ePiSJUvS0tKCgoKo6VkYoWiHboOU4sIBwIjU1NRFixbNnj37zz//lH7SecqxY8eeP39+9epVaaaK0tPTCw8PnzVr1r59+5BKyVR9j5eED6JoOSEWFBQMGjSIxWJFREQoeB4lLn9//+HDhxsbGzMdSMNEv4S/efOGy+USQtq1ayfn5ITFYq1du/bSpUtpaWndu3efOHHi5cuXS0pKqhUTCATPnj1btWqVlZWVn5/fmjVrrl69ymAeRZSw3Q6lRYsWd+/enTNnzs6dO62srDZv3lzr7L1cLvfcuXMjR450dHQsLS29efMmg3kUUcj7URUVlX379h09evTZs2edOnXy8PC4efNmzTES+Xz+/fv3Fy5c2L59+4sXL+7evfvMmTPMjlijpIdu+/btHz58OG7cuFWrVrVv337Xrl1UO7RqPn/+fOLEiX79+o0YMUJPT+/+/fsM5lFEIQ/d+inFhQOAEebm5m/evDly5AhdeZRwTt4hQ4ZIWZWamtqxY8eqjc4NtKsv36XOnqLMxycKDw+Pp0+fOjo6Tps2TSAQVBsxwt/f39TUVPpvkb8HDx7Ex8dXmz1NYYk+1Litra30Yw1LY+TIkYMHDz548OCePXuCg4O1tbXt7OyoadD+/PPPU6dOvXv3LiMjQ1tbe/LkyRs2bDAzM2MwWorStdsR0tDQ+OOPP+bNm7d+/frt27dv2LChTZs27du3//jxY2Vl5dixYzMzM6OiokpLS6nE1d3dna7LhsTi4uKYDaAubm5uY8eO9fHx8fX1DQgI0NfX79SpE5WfeHl57dy58+3btzk5OU2aNPn555/XrFmjCI+WlPfQbdKkSWBg4OLFi9euXbtmzZrly5dbWVlZWVnFx8fn5OS4uLh8/PgxKiqKx+N16tSJehnFYCtKisIeunVRogsHgPw12IFQLHv27ElPTw8NDaWrQsbPeN+8OlMpgUBAvabv3LkzLU0/qXlv7969W+unxcXF0n8FI/z9/Y2NjYcNG8Z0IN8gdXX1RYsWLVy48MWLF6Ghoa9fv/748aOKikp+fr6pqeno0aOdnZ0HDhzY4HyRcqN0D5ursbKyOnXqFJfLvXbt2s2bN9PT0wsLC1VUVHJzc1u3bj1ixAgXFxdbW1umw1QCOjo669evX7t27cOHD8PCwuLi4tLT01VUVPLy8qysrKZOnTp06NB+/fox2KmvGmU/dDt37hwaGvr58+crV65ERERkZGR8/fqVEPL58+d27dpNnDhx9OjRVlZWTIcJANCAoqKipUuX2tnZMR0IiKrOVCouLq6oqIjQ1wX53r17tNSjULhcbnBw8Ny5c6Vpzwr1Y7FYXbt2VYr+G8p+P0rR0dEZP3684k82rfjYbHbv3r179+7NdCAN+zYOXQMDg6lTp06dOpXpQAAAJKQUY5hBVXUmAPR2lPpWnT17lsvluru7Mx0IKASla7cDQMGhCwAAIIE6U6nJkyePGzeOEEJL675vVUBAwPfff09vM1kAAAAAAFB8daZSqqqqitOOn14WFhbUEEPS+/jx49atW2mpCgAAAAAAlEhj7OGzb98+uqpKTEykqyoAAAAAAFAiDUxbDgAAAAAAADUhlQIAAAAAABBbY2zg9+358uVLTk7OkSNHmA6EEEIyMjIIITwej+lAQNFxudzS0lIFOW4JIYWFhYSQsrIypgMBRffly5f8/HzFOXQ/fPhACKk28X39+Hw+ISQsLCw+Pl5WYYnjw4cPWlpaTEcBACA2pFLfgqysrOTk5J9//pnpQP6rpKSE6RBA0WVlZXG5XIU6bgkh1Hx6APXIzMzMyMhQtEO3tLRU9MJU3rV7926ZhSM2S0tLpkMAEElFRQUh5PLly02aNKGx2g8fPujo6DRt2pQQkpubW15e3rJlSxrrz8zMJHjSLQNIpb4FL168+PTpE5utKM01VVVVdXR0mI4CFN2ZM2cOHTrEdBT/g8Ph6OnpMR0FKLr79+/n5+ezWCymA/kvcc+6PXv25HK55eXlsgtJLAKBgN67UgDZycnJIYR4enoyHYgkPn/+zHQI3xqkUt8IQ0NDpkNQetRj2sOHD9+8eZPpWMTw9u1bpkOQnIGBAdMhfAuol8A7d+40MTFhOhYxPH/+XHmbU1JPjpWatra2trY201EAKJ9ly5a5ubmpqanRW22fPn0cHBz2799PCJk+fXpOTs7Vq1fp/YqKiormzZvTWycglQL4l56enp6eXlxcXHJyMtOxiKG0tLRp06bq6upMBwKMMTQ01NbWjo6Ojo2NZToWMRQXFxsZGTEdBQCA2IyNjWmvk8PhqKmpUU8Y1dTUVFRU8LRRKSCVAviXoaEhNfAAgHLp1KkTXdOOAwAAUDIyMqytrQ0MDFRVVZmORTw5OTmLFy/etGmTHL4LqRQAAAAAAPyPwsJCLpfbp0+f1q1bMx2LeAICAnJzc+XzXUilAAAAAADgf6ioqBBCfv311xEjRjAdi3hOnz4ti0aYtVKUMd8AAAAAAACUCFIpAAAAAAAAsSGVAgAAAAAAEFtjTKV4PB5d8xIq76QoAAAAAABKhM/nMx1CdY0xlZo7d+706dNpqcrc3PzgwYO0VAUAAAAAALVasWLFDz/8wHQU1TXGVCorKysrK4uWqrp06ULNSw0AAAAAALKQmJi4d+/eH3/8kelAqqMnlaqsrExMTIyIiHj9+rUCvnqTgIh75O7uHhcX9+jRI3nGBgAAAADQeKxcuVJHR2flypVMB1KdtPNK8fn8ffv27dq16+PHj9Sa1q1bL126dN68eVLHxgyx9mjUqFGGhob+/v69evWSb5gAAAAACqG4uPjWrVtJSUkvX74khOzfv//Vq1cWFhaDBg3S09OTWxgFBQW3bt1KSUmJiIgghHh5ednZ2VlZWQ0YMEBTU1NuYQDtHj16FBIS8scffzRt2pTpWKqTKpUqKyubMmVKSEgI9Z9aWlrFxcUfPnyYP3/+vXv3goKC2Gwla0Ao7h6pqalNnTo1MDBw7969WlpaTIQMAAAAwIybN2/6+vreuHGjpKSEw+FQd7r//PPP9evXKyoq1NTU+vfv//PPP48ZM0Z2MQgEgvPnzx85ciQyMpL6Um1tbUJIeHj48ePHKysrtbW1Bw8ePG/evP79+8suDJARgUCwdOlSS0vLn3/+melYaiFVqrNhwwYq65g1a1ZWVhaXy42JiXF1dSWEnD171svLi54Y5UiCPfLw8CgqKjp//ry8YwUAAABgyKtXrwYPHjx48OD4+Pjly5e/ePGivLyceh10+vTpsrKy2NjYTZs25eTkjB079ocffnj48KEswrh3716vXr1cXV0/f/68devWN2/elJWVHT9+nPqorKzs2bNnixcvfvPmjZOT0/Dhw9+8eSOLMEB2zpw58+DBA29vbzU1NaZjqY1AUvHx8SoqKoSQadOmVV1fWVlJPXtQUVFJTk6WuH7ZGTFiRL9+/Wqul3iPHBwc+vfvL6twAQAAABTJmTNntLS0WrVqdfjwYR6PJ1wfExNDCLl+/XrVwjdv3uzUqROHw/Hy8qI3jMOHD6uoqNjY2AQHB1ddHxYWRgiJi4sTrqmsrAwODrawsNDQ0Dhx4gS9YdCiU6dO7u7u1PK4ceN69+7NbDwCgeDdu3eEkMuXLzMYQ1lZWdu2bb///ns+ny/6Vrq6uhs3bpRdVFVJ/lbqyJEjPB5PQ0Njx44dVdez2WwfHx8Oh8Pj8ainAspC4j3y8PCIjIxMSUmRV6QAAAAAzNi6deukSZOcnZ3fvHnj6enJ4XDqLz9w4MBnz55Nnz595cqVdPWlFwgEc+bM+fnnn2fNmhUdHU01IKoHm812dXWNiooaMGDAtGnTdu7cSUsYIGv79u1LTk7evXs3i8ViOpbaSZ5KnTp1ihDi6Ohoampa7SNzc3NHR0dCyIkTJ6QJTs4k3qMpU6aoqakFBgbKPkYAAAAAxhw7dmzdunWLFi06d+6cjo6OiFupqan9/fffXl5eBw4c2LVrl/Rh/P7774cPH96zZ8+ff/6pqqoq4lZ6enqXLl365ZdfVq5ceebMGenDAJn6/Pnz9u3bJ0+e/P333zMdS50kTKWSk5OpAe7s7OxqLUCtT0hIyMvLkzg4eZJmj5o2beri4hIYGPhtDAQPAAAAUNOTJ088PT1dXV29vb0lGFpsxYoVv/7668qVK69fvy5NGKGhoevXr1+8ePHChQvF3ZbD4ezbt2/kyJHu7u7R0dHShAGytmnTJi6Xu2XLFqYDqY+EqVRUVBS1UFfi0aFDB2pBWQ5TKffI3d39w4cPVG9LAAAAgG+MQCCYP3++hYVFYGCgxK2t9u7d27Nnz3nz5lVUVEhWQ1lZ2YIFC3788UeJG+mx2ewTJ06YmpouWLBAshpADpKTkw8dOrRo0SJLS0umY6lP9VRKIBDcuHHDzc2tR48eAwcOXL16dWZmJiFk6dKlNjY2HTt2LCsrI4Tk5+dT5a2srGqtV7heFj2IDh06tGzZsmXLln369ImuOqXco8GDB5uZmQUEBNAVDwAAAIDiOHfu3OPHj3fs2CHN7C8qKip79+5NTEz08/OTrIYDBw68f/9+9+7dDfbRqoeuru62bdvu3r1LDVABCmj58uXa2trLly9nOpAG/E8qlZGR4eTk5OzsfPz48adPn96+fXv79u02NjaRkZFhYWFxcXEcDkddXZ0QUlBQQG1S15Rn1Ij+hJAvX77QHvSZM2e8vb29vb2FYUhPyj1is9lubm4hISE0hgQAAACgIPbu3fv999+PGjVKynp69OgxatQoHx8fCbYVCAR//PGHq6tr165dpQxjwoQJXbp02b17t5T1gCxQc/Ju3LhRAefkrea/qVRSUlL37t0jIyMJIVpaWlOmTNm6deusWbO4XO6YMWPi4+MJIT169KAKCxOGuoZ4F3YBlEUqJQvS75G7u3tpaWlQUJAMogMAAABgTHZ29qNHj3766Sdaavvpp5+SkpKokdPF8uzZs7S0tGnTpkkfA4vFmjp16r1795SlV3/jIVDsOXmr+TeVKiwsHDhwINWWr2/fvklJSSdPnlyzZo2fn9/x48cLCgoEAgEhpGfPnlT5z58/UwsNJh5cLrfmp2VlZbWuF9H69euDgoKCgoKMjY0lrqQaKfeIEGJlZdW3b19/f3+6QgIAAABQBNTkQtK/kqIMGTJEQ0MjNDRUgjC0tbUHDBhASxguLi6VlZVXr16lpTagi6LPyfu//k2lFixYkJqaSgiZOXNmRESEiYmJsMSkSZOE/b2Eb6XKy8uphbrGrBOu5/F4VdcHBATY29traWnp6uq2adNm+/btpaWl4gbdv3//iRMnTpw4UfRROBsk8R5V5eHh8fTp09jYWLqiAgAAAGDcmzdvzMzMzMzMaKlNR0fH1tb2zZs3EoRhb29fV18McbVt27Z58+YShAGyU15evnbt2u+//97FxYXpWESiQgh59erV0aNHCSHt2rXz9fVVUVGpWoLFYllZWSUnJ2tqanbs2JFaKcxhhBlINcL1+vr61AKfz58yZcqZM2cGDx7s4eGhra197ty51atXR0ZGXr16VYIhNeklwR7V5OrqOm/evICAAGma3lZWVhYVFUm8uTQqKyul6cQpH3w+n/GjRQJKGjbBUUEfpfgla1KK37ZWShG5UgRZPyU9sOunpH8XmYb9/v17Y2NjYROeulA3MFwut8GSRkZGaWlpDRarJj093dTUtMGtqAZERUVFDZY0NjZ+//69uGHIQmVlZXl5+adPn1gsVnl5OY/HYzwqmd6OlpWV8fn8mlkxNSfv8ePHpZyTt6SkRKwfUIJ/PhwOR09PjwgEAmGT09u3bwtqQz2E6NOnj3DNunXrqE2ioqJq3eTevXtUgT179lBr9u7dy+Fwjh07VrXYoEGDCCEnTpyotRIZGTFiRL9+/aqtlGCPauXu7m5iYsLn8yUOb+DAgWL9IQEAAAAAZOGPP/6Q+J5WIBB8+fLlxo0b3t7eP//8s5OTk5WVlYGBQdVZlZs0aWJsbNyzZ8+pU6cuX75cR0dnzJgx0nyjQCCQ26OQv//+W6WyspJqq2pvb+/k5FSzUEZGRnp6OqnSuo8QoqurSy3UNQYD1e2KVHmHM3z48JycnGo9BYcPH37z5s0HDx5MnTpV2r2RjgR7VKvy8nJVVVVpMuktW7a4urpKvLk0EhISmjdvXv8OMi42NtbKykpDQ4PpQMSTnp6uoqJStemsUuByuenp6dbW1kwHUp+Kioo3b9507txZyidYMiUQCKKjo21tbau99ld8KSkp+vr6ij+GUjWfP3/Oz89v27Yt04HUp6SkJCUl5bvvvmM6EMl9/fo1LS1NwU8R4iovL3/37l2nTp2YDkRsr1+/btu2rYyuj97e3hUVFatWraq/2MePHzdt2rRgwYIGD+wDBw7k5eVt3LhRrDDWrl1rZmY2Z86c+ovFxMQcOHBg8+bNDXaq37Jli66urgRT/dJu8+bNbdq0GTBgAIfDCQ0NLSwsZHwc8Ozs7PXr17dq1UqCbZ88eXLhwoXIyMhnz57xeDwOh9OmTZt27doNHTpUR0dHX19fT0+Pw+EUFBSUlpYWFha+f/8+NjY2ODi4oqLiwoUL1AAELi4uVLc6cb9dQ0NjwIABI0aMEH2Td+/etWjRQpgOiILNZo8YMULl2bNnhYWFhJD+/fvXWu7Ro0fUQtVUqlmzZtRCUlJSnz59am6VlJRELTRp0oRasLKy+v3336sVoyaGorHLk8Qk2KOaCgsLQ0JCFi9eLE0kvXr16tWrlzQ1AAAAANAoKirq1q1bnp6e9ReLjY3dtGnTsGHDBg8eXH/J48ePt2vXrsEKqwkNDS0tLW1wq/Dw8AMHDkyYMKFDhw71l/z999+dnZ3FDUMWDhw40KFDh82bNxNCYmJisrKyGI8qPj5+/fr1Vd8gNSg5OfnYsWOnTp1KSEjQ09Pr27fvtm3bfvzxRwcHhwbHkEhOTv7uu+88PT179ep19+7dO3fuBAYG6uvrjx492s3Nrdb3PXXhcDhdu3aVzw+o8v79e2qpRYsWtZYQplLC4fsIIZ07d6YWqEHSaxImHsLuVTWVl5efPHmSEDJ69GixgpYFWvYoKCiopKRkxowZdEcHAAAAwJg2bdqkpaUVFxdLMz+vEJ/Pj4+P79atmwRhhIaGCgQCWpohFBUVffz4sXXr1tJXBdHR0bt37z59+jSHwxk0aNDatWvHjx8v1tFCzcm7ffv2pk2buru7E0Jev3599uzZ48ePHz161M7ObvHixZMnTxYrtZMDNvVeiFQZDbwaKpUyMjIyNzcXrrS1taVetz1//rzWrai5AgwMDNq1a1drgezs7HHjxiUnJ//0008//PCD5HtAE+n3iBDi7+/v6OhoZWUloyABAAAA5M/Z2bm0tPTGjRu01Pbo0aOcnJyhQ4dKEEZ6evrLly9pCePKlSs8Hk+CMKCq2NjYIUOG2Nvb37p1a+vWrVlZWZcvX3ZzcxMrj3r48GFISMimTZuqtifv2LHjxo0bExISzp07p6mpOX369A4dOgQHB8tgJyTHNjIyopaio6Nrfpyenv7kyRPyv637CCHq6uojR44khNy9ezc3N7eurUaPHl3zscHEiRM7duzYunXrsLCwWbNm+fn50bQvUpFmjyivX79+8uSJh4eHrEMFAAAAkCd7e3tzc/OQkBBaagsJCdHT0+vXr5+4Gw4aNEhLS+v8+fN0hdG+fftvrLOfPBUWFi5atMjBweHNmzdHjhxJSUlZsWJFPR1h6iL4/zl5a22Sx2azx40b9/Dhw3v37rVp02bixIn9+vWrNW1hBFv4juXKlStRUVFVPysuLnZ3d6cGAa+WShFC3NzcCCGlpaU7duyo9tGWLVsEAgEhhHo9V01JSYmmpqaOjg6LxSopKREO58A4ifeI4u/vr6urO378eJkGCQAAACB/M2bMCAoKSkhIkLKe7OzsI0eOTJ06VYIJWDU1NSdNmnTw4EFhoyqJvX79OiQkpJ77OqjftWvXrK2t//zzz2XLlr19+3b27Nnq6uqSVXXmzJl//vmnwTl5+/Tpc+fOneDg4NTU1K5du65fv76euV7lRyAQCLsJmZiYhIeHl5aWfvr0KSQkxNbWVljs6tWrNYcapF6JslisI0eOCFceOHCAGoLQxcWlnmEK+Xz+3bt3mzVrZmRkFB0dLdYQh66urtQ8cSkpKWJtSKl1MHSKxHtUXl5uZGQ0e/ZsCeIBAAAAUHBFRUXNmzcfN25cPWWo3hDXr1+vp8zcuXO1tbU/fvwoWRgfPnzQ0NBYtGhRPWXCwsIIIXFxcfWUGTZsWMuWLb9+/SpZGLTr1KmTu7s7tTxu3LjevXszG49AIHj37h0h5PLly9XWl5eXL1u2jMVi9e3bNz4+XspvKSsra9u27Y8//ij6JsXFxUuWLGGxWD/88EOtuYCuru7GjRulDExERCAQhISEVB1/XTiWd69evYRDLOTl5dXcmJoojSrQpUuX8ePHC99xmZubZ2ZmNvj1Fy5coLYVayIm4RvhxMRE0bcSqieVkniPqFfeDx8+lCAeAAAAAMX3559/EkKqPm6upsFU6sKFC2w2e9OmTdKEsXr1ag6HEx4eXleBBlOpP/74gxASGBgoTRj0UpZU6uPHjz179mSz2WvXrq2oqJD+W3bt2sVisZ48eSLuhtevXzcxMdHX16/5vkfeqZRAIDh69KiwcxiLxerSpYu/v39lZSU1Hr+VlVVd22dmZtYcndDZ2Tk7O1uUr+fxeNT3ivViSnaplEDSPRoxYoS1tbUEwQAAAAAoBT6fTzXMi4iIqLVA/anUy5cvdXR0nJ2deTyeNGGUl5f3799fX18/Jiam1gL1p1LXr19XUVGZOXOmNDHQTilSqfj4eAsLCyMjo9u3b9PyFfn5+U2bNp0yZYpkm2dnZzs6OqqqqlbLiuWZSv07WaSbm5uLi0tUVJSOjo61tbW2tjYhJC0tLTs7m9TWUUrIxMTk9u3bL1++vHHjRm5urpmZmZOTk7DFYIM4HE6zZs0+fPiQlpYm+lZ37twRsaQEJNijzMzMq1evenl5yS4qAAAAAGaxWKy//vorKSlp2LBhfn5+P/30k+jbhoeHT5kypVWrVkFBQRwOR5owVFVVz549+/333/ft2zcoKMjZ2Vn0bf39/X/55Zcffvjh4MGD0sTQCD179mzYsGHa2tr37t1rcMIuEW3atKm4uHjbtm2Sbd68efPr16+7ubm5u7t//PixwSmkZUFFuKSvr+/o6Fj1M2rMOlJvKkVxcHBwcHCov8yzZ89qTiBQVlaWkZFBCKnaL0sRiLJHQseOHWOxWNOmTZNpSAAAAADM0tDQuHXrlpub27Rp0+7fv7958+bmzZvXv0lhYeHvv/++e/fu/v37BwcHSzDCW02GhoYPHjwYP3788OHDV6xYsXLlSl1d3fo3ycrKWrNmjb+//+TJk//++28JBr1o5EaMGGFiYnLt2rW6pqIVV3Jy8qFDhxYuXNimTRuJK1FXVz99+rSpqen69et//vnnqmOpywe7ns+ePn1KLTSYSoli/PjxQUFB1Vb6+flVVlba2tpK8yMyzt/ff/jw4VRjSAAAAIBvmLa29rlz57Zt23bixAkrK6t169a9fv261pKJiYnbt29v27btH3/8sWzZsmvXrtF4p2tkZHTz5s358+fv2rWrbdu2O3fuTE5OrrXkq1evVq9ebWVlFRwc7O3tffLkSU1NTbrCaDwuXrx4//59uvIoQsjy5ct1dXWlf5XEZrP37t2bk5Mj/zyKVH0rVRP1VkpFRUX09zP12LRp05QpU86dOzd37twePXqUl5cHBwcvW7ZMRUUlMDBQ+vqZ8uDBg/j4+F27djEdCAAAAIA8sFisVatWTZ8+fePGjbt27dq6dauVlVWXLl1UVVUJIQcPHjx69GhUVNSbN29UVFQmTJiwZcsWS0tL2sNQU1Pz8fGZO3fu2rVrV69evWLFCltb286dO3/58oUQ8vvvv5eWlj5//jw5OVlDQ8PDw2P9+vV48C2xXr160VjbgwcPQkJC/vjjD319fVoqNDAwoKUecdWZSgkEgufPnxNCOnfurKGhIf03TZ8+3cDAYMGCBQMHDhSutLCwCAwM7Nq1q/T1M8Xf39/Y2HjYsGFMBwIAAAAgPy1atDhy5Mju3buvXbsWGhqalJSUmppKCHnw4IGlpWWnTp1WrVo1bNgwWb8raNeu3ZkzZz59+hQWFnblypWEhISUlBRCyO3bt83Nzfv27btz584hQ4ZQAwGAgnj16pWDg8OcOXOYDkRadaZScXFxRUVFhJCePXvS9WWjRo0aMmTI3bt3nz17pqKi0rVr1169eglHDlRGXC43ODh47ty5Kir1vd8DAAAA+Cbp6uq6urq6uroyG4ahoeH06dOnT5/ObBggorlz586dO5fpKGhQZwJAb0cpITU1tUGDBg0aNIjGOhl09uxZLpeLqbIBAAAAABqbOlOpyZMnjxs3jhBCS+u+b1VAQMD3339vY2PDdCAAAAAAACBXdaZSqqqqVN/Bb4+FhQWXy6Wlqo8fP27dupWWqgAAAAAAQIk0xh4++/bto6uqxMREuqoCAAAAAAAlUt+8UgAAAAAAAFArpFIAAAAAAABiQyoFAAAAAAAgtsbYVwoAAAAAABoUFRVF72jeX79+LS4uNjIyIoSUl5fn5eW1aNGCxvoJIZWVlRUVFfTWWRekUgAAAAAA8D/Ky8sJIevWrWM6EEm8fftWPl+EVAoAAAAAAP6Hra1tZGSkjo4OvdVu2rQpLi7u9OnThBB/f/+//vrrn3/+ofcr8vPzv//+e3rrrAtSKQAAAAAAqM7R0ZH2Og0NDTU1Nbt27UoIuX79OpvNppaVFIadAAAAAAAAEBtSKQAAAAAAALEhlQIAAAAAABAbUikAAAAAAACxIZUCAAAAAAAQG1IpAAAAAAAAsSGVAgAAAAAAEBtSKQAAAAAAALEhlQIAAAAAABCbCtMB/I/KysqUlJQPHz4YGxvb2Niw2UqQ6SljzAAAAAAAICVFue/n8/l79+5t3bp1u3btBgwYYGtra2FhsX//fqbjqo8yxgwAAAAAALRQiFSqrKzM1dV10aJFHz9+JIRoaWkRQj58+DB//vwJEybw+XymA6yFMsYMAAAAAAB0UYhUasOGDSEhIYSQWbNmZWVlcbncmJgYV1dXQsjZs2e9vLyYDrAWyhgzAAAAAADQhflUKiEhYffu3YSQadOm+fn5GRsbs1gsW1vboKCgMWPGEEI2bNiQkpLCdJj/QxljBgAAAAAAGjGfSh05coTH42loaOzYsaPqejab7ePjw+FweDze8ePHmQqvVsoYMwAAAAAA0Ij5VOrUqVOEEEdHR1NT02ofmZubOzo6EkJOnDjBQGR1U8aYAQAAAACARgynUsnJydSwDXZ2drUWoNYnJCTk5eXJNbK6KWPMAAAAAABAL4ZTqaioKGqhrrSkQ4cO1EJ0dLR8QmqQMsYMAAAAAAD0ku0Uve/fvw8MDLx27VpqampJSUmrVq0sLS3nzJkzdOhQqkB+fj61YGVlVWsNwvWyGMXh0KFDSUlJhJCVK1caGhqKuBWzMQMAAAAAgCKQVSpVVla2detWLy8vHo8nXFlYWBgbGxsaGtqvX787d+4QQgoKCqiPNDU1a61HW1ubWvjy5QvtQZ45cyYyMpIQMmfOHNFTKWZjBgAAAAAARSCTVOrLly/Dhg27f/8+IaR79+6urq7m5ub5+fmpqalBQUGpqanm5uZUSWFaoqamVmtVqqqqwjplEaoElDFmAAAAAACgF/2pFI/Ho/IoDQ2NQ4cOTZ8+veqnmzZt8vX17d27N/Wfnz9/phYaTEu4XG7NT8vLy4uLi5s0aSJZqOvXr58zZw4hxNjYWPS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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1134x293 at 0x7FB078C4BA58>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# シミュレーターで動作を確認する\n",
    "backend = 'local_qasm_simulator'\n",
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q, c)\n",
    "\n",
    "qc.x(q[0])\n",
    "qc.x(q[1])\n",
    "\n",
    "toffoli(0, 1, 2, q, qc, backend)\n",
    "cx(0, 3, q, qc, backend)\n",
    "cx(1, 3, q, qc, backend)\n",
    "qc.measure(q[2], c[1])\n",
    "qc.measure(q[3], c[0])\n",
    "job_exp = execute(qc, backend=backend, shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 10\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb066d0fa58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experiment with real quantum computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'job_id': None, 'status': <JobStatus.INITIALIZING: 'job is being initialized'>, 'status_msg': 'job is begin initialized please wait a moment'}\n",
      "Status @ 20 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 40 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 60 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 80 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 100 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 120 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 140 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 160 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 180 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 200 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 220 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 240 seconds\n",
      "{'job_id': '5b226d167634ac00396d8042', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'job_id': '5b226d167634ac00396d8042', 'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": 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jx4sXLwrV94ZRUFC4dOmSqanp+PHjq6qqJBFhk0iYSQkRfDQqciLhnrpw4cKxY8d27dolbN8bplevXufOnbtz5w42RZzUkDCTAAAxwXGNu9OnTwcFBe3fv1/YvjdMv379Tp8+fePGjYCAANxj4wNqAgCyqmH3G5fLvXfvnpeXl729/bBhw/76668fP34ghPz8/Kytrbt27cpisYiIs6Hjx4+vWLFixYoVxcXFuBRYUlKCfWhuRE3ez5uc423EiBHGxsYtzo1JQlOmTMGmaKqqqmrw9sndu3exd7TNzMxu376toaFBTIgAiETwp4EyMjKwvmc9PT1TU1NJByZLsrOz9+/fv2TJEhcXF5ELWbNmzZAhQ1atWvXraEuSBtUDADKDI1QKnj9/fvXq1d27d4szf/Px48dNTExWrFiBX1wtk4HqQcJN2LdvX15eXmhoqLq6umglaGhoXLlyJTc3V5qvs5MwkxJC9btsZNtT1dXVf/3116hRo5YvXy5yIRMmTFiwYMHu3buxGybSQbZMAgDEB8c1viorK9etW+fq6rpo0SKRC5kyZYq3t/e2bdsKCwtxjI0/qAkAyKr/dL99+/bNyclp5MiR58+ff/PmzcOHD3fs2GFtbf348ePo6OiUlBQ5ObkWX4CVjitXrgQEBAQEBOA14zGvHGVl5SYXUFVVxT5UVFQ0/i2dTvfy8goPDydqBmaR0en0jRs3Yp+PHDlSVlaGfX779u3EiROxSbzv3r1rYGBAWIgAiETw+xTw2r7INmzYoKSktG7dOnEKodFou3fvzszMPH78OF6BtQiqBwBkBkeoFKxevdrS0nLOnDniFKKoqLht27bHjx/funULr8BaJAPVg2ybUFhYGBAQ4OPjY21tLU453bp18/b23r17d+MRNSSEbJmUkKqqKmwyGHl5eXH6ywlEtj31999/f/v2bdeuXWKWg809sXnzZlyiEgTZMgkAEB8c1/jav39/UVHRzp07xSxn8+bN9fX1W7duxSUqQUBNAEBW/a/7LT09vU+fPo8fP0YIqaioTJ06devWrbNnz2YymePHj//y5Qui7NN2guB1mzU3viJvGJYmu98QQt7e3jU1NSEhIRKITrImTpyIDblZVlb2999/I4SysrKcnZ2ZTKaqqurNmzctLCyIjhEA4RQUFGRlZSGEtLS0WqzAVB/PhyiVlZVXrlxZtGiRtra2mEX17t3b2dk5KCgIl8BaBNUDADKDI1QKvnz5EhcX99dff4kwzGADkydPtra2hgZccCTchKtXr1ZWVmIDzotp/fr1FRUVV69eFb+oFpEwkxISHx/PZrMRQra2tiR5FlYoJNxTQUFB48ePF23g9F/p6enNnz//4sWL0hkiiISZBACICY5r3AUFBU2aNEnMJ4oQQkZGRrNnzz5//nxdXR0ugfEHNQEAGfZv91tZWdmwYcOwYRMcHBzS09MvXry4du3awMDA8+fP//z5k8vlIjL1q/v7+4eEhISEhOjr6+NSYGlpKfahxe43JpPZ5ALm5uYODg5Su/uAIxqNtmnTJuzz/v37s7OzR40alZeXx2AwwsLC+vTpQ2x4AIjg1+eGaDQa/4Xh0SHR3L17t7q62sPDA5fS3N3dExMTmxzdF3dQPQAgMzhCpSAiIkJeXt7V1VX8omg02oQJE+7cuVNTUyN+aS2SgepBwk2IiIjo16+fsbGx+EW1b9/e3t7+xo0b4hfVIhJmUkKoPvIk2fZUampqSkrKxIkTcSlt4sSJFRUVDx8+xKU0/siWSQCA+OC4xhd2SwGvFt7d3b20tDQ2NhaX0viDmgCADPu3+23JkiVYN/vvv/8eExPz60iDnp6eHTt2xD7jdcZfW1sr5iCNQ4YMmTx58uTJk9XU1PAKCfvA4XCaXID38/r6+uYK8fHxefPmDTY2CLW4ubn16tULIVRcXGxra/v582eE0KlTp0SbpxQAwgl+OlJXV/fu3TuEEI1Gg85mody9e7dDhw7iPziMcXFxodPpd+7cwaU0/qB6AEBmcIRKwd27dx0cHLS0tHApzdXVtbKyMi4uDpfS+JOB6kG2TaipqXny5MnYsWPxKtDV1fXRo0dSeBmIbJmUHKp3v5FtT926dYvBYOB1ndunTx9DQ0M4gwUAiAaOa3zdvXtXUVFxxIgRuJQ2cODAtm3bQgsPABATAyH0/v37s2fPIoQsLCyOHDnCYDB+XYJGo5mbm2dkZCgrK3ft2lXMv5eYmLhixYqHDx9yOBxTU9PVq1fPmzdPzDJxwevG4/XDNcD7eZs2bZorxMPDw9fXNzg4eO/evbhHKGmbN292dnZG//8i4K5du2bOnEl0UACIiHefwtDQMD09nc+SycnJ2B0iS0tLTU1NKcQmMzIzM7t06YJXaW3bttXT08MeBJE0qB4AkBkcoVKQmZnp4uKCV2nYdwE04AIi2ybk5ubW1taKf5XH06VLl9ra2u/fv5uZmeFVZpPIlknJofoYU2TbU5mZmUZGRniVT6PRrK2tpTx+A0kyCQAQHxzX+MrMzOzQoYOqqioupcnJyXXu3BlaeACAmBgIoYCAAOwfx48fb3I0+eTkZIRQr169GvTMCSs+Pn7IkCF0On3ZsmVaWlrh4eHz58//9u2bNCcrbo66ujr2QZzuN1VVVQ8Pj0uXLgUEBLT4sjAfd+7caW6GuSbl5uai5t/bE9CYMWNsbGwSExMRQrNnz165cqXIRWGTE9y6dUtXV1eckERQVlZWWlpqamoq5b8rlMzMTB0dHQ0NDaIDaRaXy01KSuratas41RhHFRUVVVVVgi/P5XLfvHmDfV6wYIGAawn42j428HdkZCSfpkCavnz5YmJioqysLP0/nZiYaGlp2eL8Lti+uHXrVotjBTMYjJiYGKEmjOHtaMFJtHrU1tZ++fJFOnPeNFBYWFhXV9euXTvp/2m85Ofnc7ncX9+/J6HPnz936NBBSUmJ6ECaVVdXl5qaimPXuJi4XK5QYxJK9Aitrq6ur68n5Aht0sePH62treXk5KT/p3Nzc/Pz81tMxfv377lcriAZU1RUjIyMFOoWAFYxmjvxbpKkq0dVVZWw1SMrK4s8NRzz/PlzoSYpwcbtSEpKanFD8vLyEEItpigtLQ0hdPbsWaG69IqLi9u2bSv48hLNJHYtc+fOnffv3wseUgPYtA5YUeIoKCj4+vUrQkhDQ6Nz587iFFVVVVVeXi5mG5iWlkaewxbz6tWr5uaPaNLjx49pNFqLecD24NOnT6urq/kvWVVVlZKSIlRiscNEqOt3iWayqqqqrKxMQt+P3759U1RUFOoAl77k5GQLCwvx50OVHBaLlZWVJWYjIGn5+fkIIbwmiJGQz58/m5qaSmIeTexBdqG+giV9XIvf5ovm69evmpqahNwwiY2N5XA4LW419sUaGxvLm4eoOSwW682bN0Kl8dOnTwghbAonAUn6FJfJZBJSEwi8WyUgNpv9+fNn8lw7C44S3624KCsr+/nzZ4cOHYgO5F9paWnt2rVTUVERfBU6nY7q6+uxNtHW1pbbFKxrByG0bNmyJhfArFu3DlvswYMHTS7A4XBsbGyUlZUTEhKwn9TX1w8fPlxOTu7jx498Ssadi4vL4MGDG/xw9+7dWPxxcXFNrhUaGootEBQUxKfwadOmmZiYiBNefn6+aKd9R44cEefvRkRE8G4Aubi4iFPU9u3bRYgfAD569eoleA3ERk8VloBH0OrVq3HfOiCmvLw8klQPoe7+ANBKeHp6kuQIxXF4PYCXhQsXkqR6ODg4iLYJampqJNkEbCQi6rKwsCBJJg8cOIDXRu3bt0/wjWpSVFQUVtTQoUPFLAqvZ3SUlJQE/6MS3VPY/VPqunz5MkkyaWRkhPvWAdA6+fv7k+S47tmzJ+5bBwR348YNktQEPT093LcOACAUxj///FNWVoYQGjJkSJNLvHz5Evsg5mAXCQkJiYmJvr6+NjY22E/k5OR27dplZ2e3a9euc+fOiVO4+Hg9xunp6YMGDWq8AO/lXz4P9paVlYWHhy9btkycSPT09H78+IHtFAGlpaWNHDmSN0WfCJ49ezZlyhTe45nR0dGvXr0SeQ5P7JmsJ0+e4DKFu1A4HE59fT3J74DX1tbKy8uT5MWy5rBYLEk8ESaa4cOHY3MTCog3RI+7u/vp06f5L9y7d2/s+VMBmzjsUe7Xr1/r6OgIHpLkELinxo0b17Fjx3379vFf7P79+/Pnz3/8+LGJiQn/JUeNGmVnZydU//21a9dWrlwp1CMLEq0eenp6I0aMWLt2reDx4IXNZnO5XDFfUicWJTaBVG1jc0gVpKWlpZ2dneDLS/QI7dWrV0xMjDivs+CLwD1la2vr7e29ZMkS/osFBgbu2bPny5cv/Bfjcrldu3ZdsmSJUEPKV1VVde/eXagJRCVdPdLS0p4+fSp4PAihVatWpaSkCL68RDcBG1nh+PHjw4cPFzykxMTECRMmhIaGtniu5e3tjRAKDg7mv9ibN288PT0jIiK6d+8ueBgTJ040NzcXfHmJZhKL5P79++JcXmVmZg4bNszCwkLkEjCCTwbTom7dupmbm7e4B/nbtGmTUBM9SnRPYU3ovn373NzcBA9pxYoVnz9/joyM5L8YtgcDAwOdnJz4L+nr65uXlyfUiwXYcSfUxbJEM9mtW7eOHTueOXNG8HgEV19fT6PRCHnVW3CkOndqDvmDbOX7Oj8/f8CAAdbW1oKvItHj2s7OjslkSmfesgZqa2sZDAadTpf+n16yZMm3b9/CwsL4L5aSkuLs7Hzu3LmBAwfyX3Lu3LlVVVUXLlwQPAbsRMjQ0FDwVSRaE6ytrXv06HHixAnB48EL+VstRJEgG6NEe4sLst3nF6HCMBgMBu+RseaehuN1v4l5xo81+iNHjvz1hz179tTV1ZXOVO388S7+m7vFwOt+4zOOSkhISHV19axZs8QMRkdHR6g7+0INetNYcnLy2LFjq6urrays5syZs3z5coSQv7//3bt3xSm2ffv2JB8EElCFsL2VvFGzBw4cyH/Eg7KyMuzQVlRU5D0ZIIgOHTrAM0QdOnSoqKho8c4UNvyIiYlJi0sWFRVZWFgIdatLhBFuJVo9aDRamzZtxLlbB0ArJ+kGnE6nwxGKEDIyMqqpqWkxFdra2gihFhcrLi5msVhdunQRKrdMJlPwhTGSbsAZDIaw1UNdXZ1spyj6+vpCbQXvarbFtbCxg1pcDBs9qXfv3kK9T6OoqEi2TApy6sJHfX29yOv+irel4k/8RqPRlJWVxWwDNTQ0yLan9PT0hNooc3Pz58+ft7gKtgcNDAxaXLKsrMzMzEyoGIqKigRfGCPpBlD8ugFAKyfC6PSSPq7l5eVb23HdqVOnDx8+tLjV2FmooaGhIC28paWlUGn89u2b4AtjJF0TVFRUWltNAIBU6MXFxdin5ka8xbrfdHV1xexKefDgAUKo8VOQnTt3zsrKwuYSIFC3bt2wL8v4+PgmF/jw4QNCSEtLi88zjEFBQY6OjkI9uUm43NzcUaNGlZaW6unp3bp1y9fXF3sK7969e8I+/wsASQj+mPCbN2+4XC5CyM7Ojsxj/ZOTtbX1u3fvhBrdno/U1NTS0lKhnhYUDVQPAMgMjlDpsLa25l3niw8rChpwQZBwEwwMDDQ1NfGtD1paWpKeyJOEmZQE7i+TwfTp04fYYERDwj1lZWWVn5+P18CVNTU1iYmJVlZWuJTGBwkzCQAQExzXuLOyssrJycEm7xRfZWVlUlIStPAAADHRea8OJCYmNv51bm4udjEm/tN2WPPX+ClIMzMzhFBqaqqY5YtJUVERmxHkyZMnhYWFDX7Ly8O4ceOae9wvKSnp9evXPj4+kg4VRz9//hw9enROTo6ysnJkZKSZmZm8vPyff/6J/Xb9+vXEhgeACFgsFtaaMRiMFoc7x/GB4lZo7NixpaWlT548waW069evy8vLjx49GpfSmgPVAwAygyNUasaOHZuQkJCZmYlLaREREe3atZN034AMVA9ybgKDwRgzZkxERAReBUZFRbm4uEh0MBxyZlISsIeTEELGxsZ4zdwmTeTcU87OznQ6/caNG7iU9uDBAyaTKdTolyIgZyYBAOKA41oSXF1duVxui8MLC+jOnTvV1dXQwgMAxETnvct169athISEX39XVVXl7e1dW1uL8Diwy8rK6HR64ysxbBiTyspKMcsXn5eXF0KopqZm165dDX61ZcsW7PkCbM6DJgUFBamrq0+cOFGiQeKopqbG1dX148ePdDr94sWLvIcs5s6dq6WlhRB6/Pjxo0ePCI0RAKElJCRgrVb37t2x5oUPHKfTaIUGDBigq6t76dIl8YvicrkhISG//fYb1vhIDlQPAMgMjlCpwXpHLl++LH5RVVVVERERY8eOlfSktjJQPUi7CW5ubmlpaby3rMTx8uXL1NRUV1dX8Yvig7SZxB3V77KRc0/p6en1798flzNYhNDly5eNjIx69+6NS2nNIWcmAQDigONaEtq1a9e7d28cW3gzMzOhJioWAdQEAGQe3cbGBmtKuFzu6NGjb926xWKxSkpKrl+/3rdvX2zESNTMGX9JSUn+/+PN39DkDxFC5eXlDAajcSHYD4Wd/mHSpEkmJiYmJiZZWVlCrciHi4sL9uLFvn37AgMDeT8/cuTIqVOnEEJubm4ODg5NrltXV3f+/HlPT08VFRW84pEoDoczdepUbNa9ffv2jR8/nvcrNTW1hQsXYp/hBThAObz7FIKcjgi1MGhATk7O19f33LlzSUlJYhZ15cqVd+/eLVu2DJfA+IDqAQCZwREqNbq6utOnT9+zZw9vFHqR7du3r7i42NfXF5fA+JCB6kHaTRg3blynTp1WrlwpflHr1q0zMzPDxhSRHNJmEndU734j7Z5aunTpq1evxH8B7v379yEhIUuXLpX08wekzSQAQGRwXEvI0qVLY2Nj79y5I2Y5r1+/Dg8P5w0PJjlQEwCQeXSE0MaNG+l0OkIoLy/P2dlZXV29bdu2EyZMUFNT69q1K7Zck+PJODs7G/y/AwcOYD+cNGkS74fbtm3jLaykpNTkBNTYvEEt9vA3UFhYmJubm5uby2azhVqRv8DAQENDQy6XO3fu3F69enl4eFhaWi5atIjD4Ziamh4/fry5FaOjowsLCyk08uSiRYuuX7+OEPL19V2yZEmD3y5evBjbI8+ePbt79y4B8QEgKt7TQC3ep8jJycFmnWzbti3MQyuaZcuW6enprVixAns/WDRMJnPdunWOjo5jxozBMbYmQfUAgMzgCJWmzZs319TUbNy4UZxCcnNz9+zZ4+3tzbtkkBwZqB6k3QQFBYVNmzY9fvxYzMGawsPDHz58uGPHDkVFRbxiaxJpM4k7qj/kTto9NWHChH79+q1evbq6ulrkQjgczp9//mlsbLxo0SIcY2sSaTMJABAZHNcS4unpaWdnt3LlypqaGpELYbPZy5cv79ix47x583CMrUlQEwCQeXSE0Pjx44ODg3mvbdXX1/fs2TMoKOjZs2dFRUUIIXNzcx0dHTH/kqamJofDwTrbfsVisbDfilk+LoyMjN6+fevk5IQQevv2bVhYGDYp3ciRI1+9esVnCvGgoCArK6t+/fpJL1YxbN269dixYwghV1dXXr/pr3R1dXnDbMILcIBaBH9MmOoPFJOBqqrq3r17b9++vXnzZtFK4HK5Xl5e379/b7Itwh1UDwDIDI5QaWrfvv1ff/31999/X7hwQbQSqqurx48fr6ysLPJXgFBkoHqQeROmTJni6Og4c+bMz58/i1ZCSkqKj4/P0KFDJ02ahG9sjZE5kziqra3F5oag0+m9evUiOhxRkHZP0Wi0gwcPZmZment7i/wM2fr16x89erR//34lJSV8w2uMtJkEAIgMjmsJodPphw4dSklJmTt3rsiFrFy58vnz5wcPHlRQUMAxtiZBTQBA5v07GqSXl5ebm1tCQoKampqVlZWqqipCKCcnJz8/HzV/YL948ULwv4R1sOXk5DToos/NzUUItWnTRqi4JTcnmYGBwcOHD9+9e3fv3r3CwkJjY2MnJyf+Q/3++PHj9u3bO3fulFBI+Dp9+jTWo9a7d+/Lly9jLz425ufnd+LECTab/ebNm6ioKEmPIQMALkpKSrAuczU1NWtra/4LU/2BYpKYMmXK27dvN23a1L59ez6zYzaJw+H4+flFRERcuHDB1tZWMgH+D1QPAMgMjlDpW7duXUJCwpw5cwwMDIYNGybUujU1NdOnT3///n1MTIyhoaGEIuSRgepB8k2g0+lXr161t7d3dXV98OCBiYmJUKtnZ2e7urrq6OhcuXJF0qPwkTyTOEpMTMQmg7G2tlZXVyc6HKGRfE/Z29sfO3bMx8enQ4cOO3fuFLbenjx5cseOHWvXrp0wYYKEIuQheSYBACKA41qiBg4ceOjQoQULFpiamm7atEnYFv7QoUP79u3bsmWLs7OzhCLkgZoAQGvwv66XNm3aODo69urVC+t7Q3j3q1taWiKEsGblVx8/flRSUjIzMxP/T+CoZ8+eq1atCggIWLp0aYvTbJ47d45Go82YMUM6sYkjOjoae3Xa1NQ0Ojqaz0x1ZmZmvGdX/f39xRlZDgCpefPmDfahT58+zXUt88CjQ3jZuXPnpEmTfHx8Vq1axeFwBFyLyWS6u7sfOHBgy5YtU6dOlWiEGKgeAJAZHKHSR6PRzp0717t379GjRx85ckTwFX/8+DFkyJCoqKjg4OCBAwdKLkIeGage5N8EXV3dqKio8vLyPn36PH/+XPAVnz592qdPHyaTGRkZKf6IKS0ifybxIvhoVORE/j3l7e3t7++/e/fuyZMnV1VVCbgWm81etmzZvHnzpk+fvmnTJolGiCF/JgEAwoLjWtLmz5+/atWqLVu2TJ8+XfBxhuvq6hYuXLhkyZLZs2evXbtWohFioCYA0BrwO7Z5rQAuB7abmxtC6OXLl7/+MDU1taCgwMnJidfnR0VBQUHOzs76+vpEB9KCly9fTp48mc1ma2pq3rp1q8WAV61ahX1ISEgIDw+XfIAAiEvw+xQcDic+Pl7AhQF/cnJyly9f9vf337NnT//+/Z88ecJ/eS6Xe+nSpe7du9+9e/fixYvSOa9FUD0AIDc4Qgmhqqr64MGDGTNmLFq0aPTo0e/fv+e/fG1t7aFDh3r06JGWlnb//n3pPDyBZKJ6UGITunXr9vr1ayMjoyFDhixZsgSbhoCPwsJCX19fJyen9u3bv3nzRgpTACKKZBIXVL/LRok9tWnTprNnz0ZGRvbo0SM0NLTFR04fPnxob29/8ODBbdu2nT17tsVbpbigRCYBAEKB41oKdu7cGRgYGBYWZmtrK8gtzTt37vTu3fvEiRN79uwJDAyU9Nv8GKgJALQG/M4XsTN+BoPRs2dP8f/S6NGjFRUVg4ODf33u4NChQwghV1dX8csnyrNnz758+eLj40N0IC1ISUlxcXGpqqqSl5cPDw9v8aVmhJCNjc2oUaOwzxs2bBD8pRYAiCL4fYrk5GQmk4kQsrCw0NbWlnhkso5Go23atOnWrVuVlZWDBw92cnI6evQoNrbwr5KTk3fs2GFjYzNt2rSOHTu+fPlyypQpUgsSqgcAZAZHKFEUFRWDgoLOnj2blJTUs2fPcePGnTt3rri4+NdluFzumzdv1q5da2VltXTp0qFDh8bHxzs6OkotSBmoHlTZBBMTk7i4uOXLl586dcrc3HzevHm3b9/G5urmqampuXXr1rx588zNzYOCglauXBkbG2tkZCSdCKmSSfFRvfuNKnvKy8vr+fPnRkZGkydP7tWr165du1JSUhosk5OT8/fffzs6Og4bNqy+vv7evXt//fWXdO7MIupkEgAgODiupWP27NlPnz7V1dV1d3fv3bv3nj17Gg/J9vXr14MHDw4aNGj06NEMBuPhw4d+fn5SixBqAgCtAaO5X3C5XKxfvUePHrhMJqyurr5y5cotW7ZMmjTp4MGDhoaGx44dO3LkSOfOnWfOnCl++UQJCgr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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=2346x293 at 0x7FB078B88048>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inefficient version\n",
    "backend = 'ibmqx4'\n",
    "q = QuantumRegister(4)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q, c)\n",
    "\n",
    "# # 1 + 0\n",
    "# qc.x(q[0])\n",
    "\n",
    "# 0 + 1\n",
    "# qc.x(q[1])\n",
    "\n",
    "# 1 + 1\n",
    "qc.x(q[0])\n",
    "qc.x(q[1])\n",
    "\n",
    "# superposition\n",
    "# qc.h(q[0])\n",
    "# qc.h(q[1])\n",
    "\n",
    "\n",
    "toffoli(0, 1, 2, q, qc, backend)\n",
    "swap(2,3,q,qc,backend)\n",
    "cx(0,2,q,qc,backend)\n",
    "cx(1,2,q,qc,backend)\n",
    "qc.measure(q[3], c[1])\n",
    "qc.measure(q[2], c[0])\n",
    "\n",
    "job_exp = execute(qc, backend=backend, shots=8192, max_credits=5)\n",
    "# job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 20\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb08810acc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'job_id': None, 'status': <JobStatus.INITIALIZING: 'job is being initialized'>, 'status_msg': 'job is begin initialized please wait a moment'}\n",
      "Status @ 20 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 40 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 60 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 80 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 100 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 120 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 140 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 160 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 180 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 200 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 220 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 240 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 260 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 280 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 300 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 320 seconds\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'job_id': '5b226e3b5c0cdd003862fa1d', 'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1701x346 at 0x7FB078076F28>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# more efficient version\n",
    "backend = 'ibmqx4'\n",
    "q = QuantumRegister(5)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(q, c)\n",
    "\n",
    "# 1 + 1\n",
    "qc.x(q[3])\n",
    "qc.x(q[4])\n",
    "\n",
    "toffoli(4, 3, 2, q, qc, backend)\n",
    "swap(0,2,q,qc,backend)\n",
    "cx(3,2,q,qc,backend)\n",
    "cx(4,2,q,qc,backend)\n",
    "qc.measure(q[0], c[1])\n",
    "qc.measure(q[2], c[0])\n",
    "\n",
    "job_exp = execute(qc, backend=backend, shots=8192, max_credits=5)\n",
    "# job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 20\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb0781c2b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPENQASM 2.0;\n",
      "include \"qelib1.inc\";\n",
      "qreg q2[5];\n",
      "creg c2[2];\n",
      "x q2[3];\n",
      "x q2[4];\n",
      "h q2[2];\n",
      "cx q2[3],q2[2];\n",
      "tdg q2[2];\n",
      "cx q2[4],q2[2];\n",
      "t q2[2];\n",
      "cx q2[3],q2[2];\n",
      "tdg q2[2];\n",
      "cx q2[4],q2[2];\n",
      "t q2[3];\n",
      "t q2[2];\n",
      "h q2[4];\n",
      "h q2[3];\n",
      "cx q2[3],q2[4];\n",
      "h q2[4];\n",
      "h q2[3];\n",
      "h q2[2];\n",
      "t q2[4];\n",
      "tdg q2[3];\n",
      "h q2[4];\n",
      "h q2[3];\n",
      "cx q2[3],q2[4];\n",
      "h q2[4];\n",
      "h q2[3];\n",
      "h q2[0];\n",
      "h q2[2];\n",
      "cx q2[2],q2[0];\n",
      "h q2[0];\n",
      "h q2[2];\n",
      "cx q2[2],q2[0];\n",
      "h q2[0];\n",
      "h q2[2];\n",
      "cx q2[2],q2[0];\n",
      "h q2[0];\n",
      "h q2[2];\n",
      "cx q2[3],q2[2];\n",
      "cx q2[4],q2[2];\n",
      "measure q2[0] -> c2[1];\n",
      "measure q2[2] -> c2[0];\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(qc.qasm())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "run_control": {
     "marked": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status @ 0 seconds\n",
      "{'job_id': None, 'status': <JobStatus.INITIALIZING: 'job is being initialized'>, 'status_msg': 'job is begin initialized please wait a moment'}\n",
      "Status @ 20 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 9, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 40 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 60 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 80 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 100 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 120 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 140 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 160 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 6, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 180 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 200 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 220 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 240 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 260 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'queue_position': 3, 'status': <JobStatus.QUEUED: 'job is queued'>, 'status_msg': None}\n",
      "Status @ 280 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 300 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 320 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "Status @ 340 seconds\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'status': <JobStatus.RUNNING: 'job is actively running'>, 'status_msg': None}\n",
      "{'job_id': '5b226fba44a1ec0038800bc8', 'status': <JobStatus.DONE: 'job has successfully run'>, 'status_msg': None}\n"
     ]
    },
    {
     "data": {
      "image/png": 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hQk2QGOT/pu7cuXP+/Pl79+5VV1cjhGg0GkJo/fr1WCR9+vRxcnJasWJFr169xBNPm8hfjAAAAEii0/7u+/v7Yy1NXl5eRUVFNTU1qampLi4uCKHr168HBAS03sXT07OqqurmzZvijlU4YWFh2tra2traOjo6ubm53BPX1dWNGTMGS3/+/HnxRAgAAJ2Pj48P9lsaHBzMPeWPHz+0tLS0tbWNjIy4jOYGHJWVlZs2bTIxMTl+/LilpeXVq1fz8/MbGxulpaV3795dXl7+6tWrtWvXfvr0ydnZeeTIkc+ePSMw2k5WE3x8fKSFUFBQQPQnaBeZv6lXr17Z2tra29unpqYuX778xYsX379/x+YSraioKCgoCAsLGzFixNmzZ/v27evj41NeXi6GqNpE5mIEAABAKp2zsSkzM/PQoUMIofnz5585c0ZLS4tCoZibm4eGhjo7OyOE/P39W7fLWFhYWFlZdXjuJBsPDw8jIyOEEIPB2L9/P5eUTCbT1dX11atXCKFVq1atX79eTCECAECng/2WIoSGDRvGPeXr16+xjcGDB2NdFQAXWVlZI0aMOHTo0Pz58zMzM0NDQ11dXQ0MDKSlpbEEampqw4YN27FjR2pq6sOHD+vq6mxtbTdu3Ih1oBC/TlYTXrx4wRCUpqamvr4+0Z+gXaT9pk6fPj169OjPnz+fP3/+/fv3e/bs+emnn9TV1bF3aTSanp6ei4vLpUuXcnNzV69effLkSQsLi8TERFEH1ibSFiMAAACy6Zw//adPn2YwGHJycvv27Wv+OpVKDQwMjIqKYjAYFy9e3Lp1a4sdPT09V65cmZubizXfSARpaemtW7d6eHgghIKDg/38/HR1ddtMuWzZstu3byOE5syZc/jwYbFGCQAAnUh9fX1aWhpCSEZGxsrKintizr3Z8OHDRR6ZhIuLi3N2dlZXV09KSjI3N+8w/fjx4xMTE9evX79v3778/PwLFy6I+Z6289WEtWvXNjY2cv4pLS0tJSWFEMrMzNy0aRNCqFevXtjzPDabzWQyGQwGJ3GPHj3EHi+vyPlNsVisJUuWnD17dunSpX/88YeMjAz39GpqagEBAZ6eng4ODmPGjLl27drUqVNFGmEL5CxGAAAA5NQ5G5uuXLmCELK1tdXR0WnxlqGhoa2tbWxs7KVLl1o3Nrm5ua1bty4kJGT79u1iihUP8+fP37NnT2ZmJp1OP3jwYGBgYOs0u3bt+uuvvxBCdnZ2Fy5cIHaGCwAAkGiJiYnYPbaFhYWsrCz3xHDHxaOMjAxnZ+f+/fvfunWLlykIMTQaLTAwcMCAAYsXL9bQ0Dh69KhIg2yh89UEbMKB1s6dO4dt2NjYzJw5U4wR4YOc35Sfn9+5c+f++OOPlStX8r6Xqanpy5cvZ8yYMXv27Pj4eEtLS5EF2BI5ixEAAAA5dcJhdDk5OdjycxYWFm0mwF7PzMwsKytr8Za6urqjo2NISIhkjS2XkpLy9/fHtv/666/Wn+v8+fN+fn4IIUtLy4iIiA4fnQEAAOCCMzyEl5soTuIOR510ZRUVFQ4ODurq6lFRUby3NHEsWrRo9+7dx44d47SJiEfXqQm8D54iJxJ+U6GhoXv37v3999/5amnCqKqqRkRE9OzZ09HRsbS0VBThtYmExQgAAIC0OmFjU3JyMrbRXmNT3759sY2UlJTW73p4eOTn58fGxoomOlGZO3cutiZuXV1diyFy9+/f9/LyQggZGRndvXtXRUWFmBABoYiazQQA4ZGw9vL+xD4nJwd7ANCjRw9DQ0NRBya59uzZk5+fHxUV1b17d8Fy2LBhg4uLy7p1675//45vbFx0nZog6Q0HZPumqqurV61aNWXKFIG70nfr1i0qKur79+/btm3DNTRuyFaMAADBkPDKCnRKLRub2Gz2gwcP3N3dhw0bNn78+M2bN3/79g0htG7dOjMzswEDBtDpdBz//KlTp3x9fX19fXG8NOSs0GFsbNxmAs7rba7dNnHiRH19fYmbJpxKpXKuNo4fP15ZWYltJyUlzZo1C5u28/79+9ra2oSFCIhQVFS0YcOGfv36RUZGPn/+3NTU1MfHp7CwkOi4AOgAp+q+fPny5s2bZKu6vN94w0ASXhQWFv7555/Lly8fMGCAwJlQKJTDhw83Njbu2bMHx9i46yI1oa6uDpupR1paWpyDtnBEtm/qwIEDP378OHLkCJUq+HNfY2NjHx+f06dPf/jwAcfYuCBbMQIA+MK5uFq1ahVCyNzcnFQXV6Dz+Z8zXGFhoZ2d3aRJky5evJiQkPD48eO9e/eamZnFxcVFR0dnZGRISUl1OEKbL9euXTt48ODBgwcrKirwypOTlby8fJsJFBUVsY3q6urW71KpVHd39/DwcBxDEo9Zs2ZhnbkqKyv//PNPhFBeXt60adNqamoUFRXv3LljYmJCdIxArMLCwoyNjffv3//x40c2m81mszMzMwMDA01MTC5evEh0dAC0i+RVt6SkJC8vDyGkpqbW4e+qpA8+Eo/Dhw9LS0tv3rxZyHz09PR+++23EydOtHl+x13XqQmJiYlMJhMhZGlpie91oHiQ7Zui0+l//PHHokWLhL8wW7dunZqa2h9//IFLYNyRrRgBAHxpfnGFzRiTlZVFnosr0Cn919iUnZ1tbW0dFxeHEFJQUHBzc9u1a5eXl1dNTY2zs/OnT5+QhJwwOI1E7c1MxFk+ub2LUQ8Pj4aGhtDQUBFEJ0IUCoXTGfvw4cP5+fmTJ08uKiqi0Wg3btywtrYmNjwgZmFhYa6urrW1ta3fqq+vd3d3v3DhgvijAqBD5K+6zZ/td7jYAjze50VERISjoyNnrXdhYGfwu3fvCp9Vh7pOTZD0MXRk+6YePXpUVVXl6ekpfFbKysozZ86MjIwUw2SjZCtGAADvyH9xBTqlfxubKisrx48fj42Ys7Gxyc7Ovnz58u+//37mzJmLFy9WVFRgAztxP2Fs3bo1NDQ0NDRUS0sLrzx//PiBbXTY2FRTU9NmAmNjYxsbm6CgILxCEhtHR8chQ4YghL5//25pafnx40eE0NmzZydPnkx0aECsiouLFy1axH089tKlS6HfLCAbiai6vN9ENTU1vX37FiFEoVCgxb89aWlpOTk5Dg4OuOTWv39/ExOTW7du4ZIbd12nJkh6YxPZvqmoqChdXd2hQ4fikpujo2NxcTHnOxIdshUjAIBHEnFxBTolGva/VatWYT1jFy1adOrUKRqNxknh6uq6ZcuWnJwc1M5FRl5e3qFDhxBCa9as6d27N19/fuzYsYJG3q7GxkZso72HPJzXsdVb2+Tp6enh4ZGWlmZubo57hCK1Y8eOadOmof9vdNu3b9+CBQuIDgqI25EjR9prS+Wor68PDAzEDl4ASEIiqi7npk5HRyc7O5tLyvfv32MTHZqamqqqqoohNkmELdZhY2ODV4Y2Njacu2KR6jo1QdKHRJHtm3r37t2oUaM67BzEI+zYSUlJGTFiBC4ZtodsxQgA4JFEXFyBTomGEHr37t358+cRQiYmJsePH2/e0oQQolAoxsbGOTk58vLybc7c6ePjExMT09DQ4Orqym9jkygoKSlhG5xWpxY4r3fr1q29TFxcXFasWBEcHCxxh9zUqVMtLCywa3cvL6/169cTHREgwO3bt3lJFhUVJXE1HHRu5K+6bDY7ISEB2/b29uZxLxhIwsXXr1+lpaU1NTXxylBPT+/r16945daerlMTSkpKPn/+jBBSUVHhrOcrQUj4TRUWFuLYMKSoqKiqqirqOk/CYgQA8Ij8F1egs6IhhA4ePIj949SpU23O+/j+/XuE0JAhQ1q0QyGEHj9+fOfOnQkTJkRHR4s4VF4pKytjG8I0NikqKrq4uFy5cuXgwYOCPXpiMplmZmbYsq88wjo3YmPfBHbr1i1syRiEUFFRkTBZlZaWIoSmTp3a+nsXHpPJrKmpUVFRwevJnthUV1fLyclxBmOSE4/T22dlZeEySQpeGhsb6XQ65xAmJwaDUVdXp6KiQnQgfKuqqlJQUBDF4YwjMVdd7HTQ3smiTZmZmZzB2rzj8Y6rpKTk1KlThMybUF9fz2azFRQUxP+nq6urmUymhoZGhymbmpq2b9++b98+7snq6+sbGhrU1NR4P79g59+MjAwe0yMR14TU1NRv374JWcmxriXCr2/N6c9ibW0t5CmbwWDw8g1yV1VVxddpQqTfVFZWFkLIzMyMr0Xlfvz4ceLECexBLxfYN6inp9dhsVdWVu7evfvYsWO8x9DQ0MClg39rIi1GhFPdEACLxaqurlZWVhZmWUBRo9PpTU1NnKfp5FRTUyMtLU3mBQTYbHZVVZWSkpKUlBSBYRByBySh9wUt1NTU7Nu3b/fu3dLS0nQ6PTU1NSYmhuigRKK6uppCocjLy2NncAaDQYbvRYD7CCqVSmMymVFRUQghS0tLOzu71okKCwsLCgpQW32nGQzGqlWrpk2bRsjlaXs4lyDtzf+NTU2FuDY2IYQaGxulpaUF/iGQkpLauHEj1l7Do4aGhm3btunq6gr2FxFCz58/nzt3LrZkDEIoOjr61atXAj9Wwno+z5s3z9DQUOCQ2tPU1JSUlGRtbU3ms3ubUlJSDA0NuVcewvn5+TU1NXWYjEqlrl+/njztfd+/f//27RvJx67W1dW9f/8er7k2xOnNmzf9+/cn1c91a2KuuklJSWFhYe1N8NcmzniimTNnnjt3jnvioUOHYveiPA4+UlZWNjExmT59Ou/x4KWgoIBOp/fp00f8fzo8PPzt27cbNmzoMOXvv/8+ZswYW1tb7skePnwYGxu7YcMG3mtIU1OTn58fX+dfkdYEfX19JSUlXsqEe4QRERHCHyY4zvRMpVJ5+Qa5CwwM1NPT4z29SL8pHR0dhNDy5cv5av/y8/MbNmyYvb0992TYN+jj49Ph862dO3caGxvPnTuX9xiePn364MED3tOLtBgRTnVDAAwGIzExcejQocQ2QHBXVlZWUlLSv39/ogPhJiMjQ11dvUePHkQH0i4Wi5WQkDB48GBiHxg3Nja+fftWzHdAEnpf0IK/v/+oUaP09PQ0NDRCQ0N79OgxZ84cooMSidOnT8vJydnZ2TU2NiYnJ+fm5vr4+BAdlCD3EVJSUujly5fYP9asWcNuy40bN7AEoaGhLd46cuQIQig2NvaXX35BCMXHx7eZg+jY29uPGTOmxYucib1DQkLa3Gvv3r1YgvDw8PZyrqiokJeX//333/EMtyNYq/PZs2cF2z09PV1NTQ0h1K9fP04fyIkTJwocD3Zh8ezZM4FzAEQZOHAgLz8Bffv2JTpSAP6HmKsu1rOgtLSU912WL1+OxRAYGMg9ZUVFBXbFJisr29jYyEvmvXr1WrVqFe/BdA4nT55ECNXW1naYUlpaOiAgoMNkq1at6tmzJ18xYAv0nDx5kvddRFoTfHx89PT0eA+mTbwXLHcTJ07EPmlkZKSQWfH4DXLXv39/Ly8v3tOL9Ju6cuUKQujr16+8x8Pm+SPw+A0ymUxpaekDBw7wFUNAQIC0tDTv6UVajGyc6gYAoE2d475AWVl527Zt2PaQIUPmzZtHbDyiM2bMGAcHB2x78eLF/fr1IzYeYVCxcfgIofYe6HFao1o80SotLd22bZuNjY0oJvkWxqBBg7CNT58+tZmAM6lhm1NQYUJDQ+vr6xcuXIh3dKJSUFAwefLkHz9+9OjRIyYmZsWKFfr6+gihBw8exMfHEx0dEDcnJydekjk7O4s4EAD4Q/6qy3svj4SEBDabjRAi/DkqyRkYGKBmp2bhZWVlYXmKVBepCexmM/VI6LJiJPymDAwMMjMz8cotLy+vqakJu+oTHRIWIwCAR+S/uAKdFfX79+/YVnsjsbHGJk1NzRZjqX7//feKiopdu3aJOEK+mZuby8nJIYQSExPbTJCamooQUlNTMzExaS+ToKAgW1tbY2NjEQWJr4qKiilTpnz58kVeXj4qKsrIyEhaWnrNmjXYu35+fsSGB8Rv5cqVHQ70U1ZW5lQSAEiC5FWXTqdjyy/QaDQrKyvuiSV9tXixsbW1lZOTw2vmx7q6uidPnkyYMAGX3NrTdWoCZ6YefX19YYb5E4Wc39T48eOfP38uwBRIbbp9+zaVShXpo19yFiMAgEckv7gCnRiVs/4LdhZpoaCgADtntDhhJCYmnjt3bsaMGT///LMYouSLrKwsNuHF06dPW0+ZxPlETk5O7Q1JTU9Pf/36taenp6hDxUVDQ4ODg0NaWhqVSr18+TLnidPixYuxUXVxcXFPnjwhNEYgbhoaGhcvXuQyGpxKpZ4/f57MQ+tB10TyqpucnIzNJj5w4EB5eXnuiXGc6aZzU1JSGjNmTEREBC653b9/v66uztHREZfc2tN1aoKkNxyQ85tycnJiMBh4NbDeunVr5MiRWlpauOTWJnIWIwCARyS/uAKdGJXTuycmJiY5Obn5e3V1dR4eHtjZpflFBpvNXrlyJY1G279/vxhD5YO7uztCqKGhofWqFjt37sQ693p4eLS3e1BQkLKy8qxZs0QaJC5YLJabm9uzZ88QQoGBgc17PyopKS1btgzbhs5NXdD06dOjoqLaXLxATU0tMjIS+soCciJz1eXcePNyE8VX4i5u/vz5CQkJjx49EjIfNpu9d+/egQMHWlpa4hFXu7pOTZD0xiZyflPGxsYjRozYv38/Z0UXgf3zzz9xcXHz58/HJbD2kLMYAQC8I/PFFejEqBYWFtgkR2w2e8qUKTExMXQ6vby8PCIiYvjw4Zwrv+YXGZcvX37x4sXKlSuFX7Zm9uzZBgYGBgYGeXl5QmbVnL29/ZQpUxBCgYGBZ86c4bx+/Pjxs2fPIoQcHR1tbGza3LepqenixYuurq4kX7MJs3z5cuxp8IoVK1atWtXi3ZUrV2IPoJ4/f37//n0C4gOEmjZtWnZ29p49e0aMGKGpqamhoTF8+PCdO3dmZ2cTstwVADwibdXlPLHv8Mb7y5cvRUVFCCENDY3evXuLPDIJ5+rqamFhsWHDBhaLJUw+YWFhCQkJe/bswSuw9nSdmiDpvVRI+03t3bs3LS0NW6NAGOvXrzcxMeHyABUXpC1GAADvSHtxBToxGkJo27Zts2bNYrFYRUVF06ZNk5aWZjAYbDZ7xIgRAwYMSE9PR81mhaypqdmwYYOGhsaWLVuE//OlpaUFBQUIIeGf7bRw5swZa2vrb9++LV68+NSpU717905JScGmYzQ0NDx16lR7O0ZHR5eWlkrEGLpdu3ZhK5U4ODhgKwO2oKmp6eHhceLECYSQn5/fpEmTxBwhIJyqquqmTZs2bdpEdCAA8IecVZf3Xh6S3h9EzKhU6r59+yZPnrx9+/bt27cLlsnnz59Xrlw5duzYDleUF14XqQnYossIISqVOmTIEKLDEQRpv6kxY8bY29uvW7du9OjRpqamgmWyf//++Pj48PBwUc/DTdpiBADwhZwXV6AToyKEnJ2dg4ODOR15GAyGlZVVUFDQ8+fPy8rKEELGxsbdu3fH3o2Njf369WtdXZ2lpaXR/8M618yaNcvIyGjJkiUEfZb/oaenl5SUZGdnhxBKSkq6ceMG1tI0adKkV69eaWtrt7djUFBQv379RowYIb5YBXLu3DlscNzQoUOvXr3a3ijcdevWSUlJIYQSEhJu374t1hABAKATKS8vx84jSkpKZmZm3BNLen8Q8Zs0adKGDRt27tx57do1AXavqalxcnKi0WgXL17EPbYWuk5NSElJweZSMDMzU1ZWJjocvpH8mwoKCurWrZuDg4NgM4XfuXNn8+bNy5cvF/XgF5IXIwAAANKiYf9zd3d3dHRMTk5WUlLq16+foqIiQujLly/FxcXof59O6Onp/fLLLy1yuX//fm1t7aBBg3r06NHheag5kU5cra2t/fjx47dv3z548KC0tFRfX9/Ozg4bM9ieb9++3b17NyAgQHRR4SI6Ohpr1DM0NIyOjuYy4s/IyGj27NlXr15FCG3dutXe3r69adEBAABw0XwBeC6zbGLg8b4A9uzZ8/79+19++aWsrIwz5yAv8vPznZycPn78+OTJEz09PdFFiOk6NYH3wVPkRPJvSlNT89atW6NHjx41alRUVBRfKyAHBwd7e3uPGTPm8OHDoosQQ/JiBAAAQFo0zla3bt1sbW2bv9fmCWPIkCGtHxva2NiUlpZu3bp11KhRIgtVQFZWVh2u0spx4cIFCoUi6nkWhfTy5cs5c+YwmUxVVdWYmJgO1x/ZsGED1tiUnJwcHh4+c+ZMsYQJAACdCu833iwWKzExkcfEgINKpV6/ft3b23v58uVv3rwJCAjo8ATHZrNv3ry5bNkyKSmpJ0+eiKczRdepCZLecED+b2rQoEF///23o6Pj8OHDjx07Nnfu3A6fCH7//n3Lli2nTp1ydXUNCgqi0Wjc0wuP/MUIAACAnLg9oOA8yug6J4ygoKBp06aJdPlYIWVkZNjb29fV1UlLS4eHh/PSj8zCwmLy5MnYtr+/v5DTrwIAQNfE+433+/fva2pqEEImJiZtrvwC2iMrKxsUFHTkyJHr168bGxtv27YtJyenzZQNDQ23b98eOXKki4uLmZlZQkKC2IbtdJ2aIOmNTRLxTVlaWr5+/XrIkCHz5s2ztrYODw+vq6trM2V+fv7u3buNjY3Pnz8fEBBw5coVbBEYUZOIYgQAAEBC3J6HYGcXGo3Ge88gifb8+fNPnz4dOHCA6EC46devHzaRFl/u3r0rimAAAKDriI6O5jGlubk5m80WaTCd26pVq2bPnr19+/bdu3dv37590KBBo0eP1tHRYTKZcXFx2AwyDx8+rKmpMTMzi4yMdHR0FGd4Xacm/F97dx8cRX3Hcfyby8Od4SEJT+EhgUsUQiSEJMJYKw6CzGAoVJFJOu1UGFpHU2t16EwrHWaIig9kGKkPjabiVKdSxKJOcayTYbToyIzVSpLzgg2GkAcCgeQIJHeXe77rH9temZCE5LKX3Uver7/Wvc3tB7Ps3n3Y328bGhq0jjAqsfKbSk9PP3r0aHV19eOPP7558+bk5OS1a9cuWrSoqalJRPbu3dvV1fXFF1/U1NTEx8dv2bLlqaeeysjIGLN4sfK/EQCgN4OWTaFQSLkVNj8/32QyjWEkzfzpT39KT09fv3691kEAAJjQ5syZU1VV9cwzz3z44YdHjhw5evTouXPngsFgdXV1XV1dZmbmo48+eu+99y5fvpyJCDE+3H333XfffXdNTY1ywP/rX/+6cOGCiOzZs2fevHlLlix5+OGHN27cOGvWLK2TAgAwLIOWTQ0NDb29vTK8x0l8/vnnaobSgsPh+Otf//qLX/xiDEa/AwCA65o+ffrWrVu3bt2q/GdXV1dqamq0n/IOaKioqKioqOjJJ58UEb/f393dTbsEAIhRgxYrE23CpsOHDzscjm3btmkdBAAADGDmzJlaRwDGTkJCAk0TACB2DVo2/fjHP1YeWzZBxtC98cYbt91223Dm2wYAAAAAAMBgBi2bEhMT9X+nelZWlvLYi9E7f/78008/rcpbAQAAAAAATFixPT/RSy+9pNZbnT59Wq23AgAAAAAAmLAMWgcAAAAAAADA+EHZBAAAAAAAANXE9jC6cam1tfXEiRNapxARaWho0DoCAERRKBQSEYvFkpqaqnUWERGv1xsIBLROMXG1tbXp5Pp78eLF0R8JwWBQRGpra/XzpJdQKDT6P1cgELDZbDr5TTU3N2sdIUKBQCAUCunkf6OodGwAAHSFsklH4uPjRWT37t27d+/WOsv/dXZ2ah0BAKLi1KlTIrJ27Vqtg/yfxWLROsJEpFx/n3vuueeee07rLP9lNBpH+Q7//ve/RWTlypVqxFFNfX39KN/h3Llzp06d+tvf/qZGHHUotXVsqa+v9/v9y5cv1zrI/43+2AAA6Aplk45Mnjz5ww8/TEhIUD716kFXV9d9992ndQoAiIonnnji5ptvnj17ttZB/stms61evVrrFBOR0Wj8+9//Hh8fr5Prr9v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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1572x346 at 0x7FB0780D06D8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# more and more efficient(?) version\n",
    "qc = load_qasm_string(\"\"\"OPENQASM 2.0;\n",
    "include \"qelib1.inc\";\n",
    "qreg q[5];\n",
    "creg c[2];\n",
    "\n",
    "x q[3];\n",
    "x q[4];\n",
    "h q[2];\n",
    "cx q[3],q[2];\n",
    "tdg q[2];\n",
    "cx q[4],q[2];\n",
    "t q[2];\n",
    "cx q[3],q[2];\n",
    "tdg q[2];\n",
    "cx q[4],q[2];\n",
    "t q[3];\n",
    "t q[2];\n",
    "h q[4];\n",
    "h q[3];\n",
    "cx q[3],q[4];\n",
    "h q[4];\n",
    "h q[3];\n",
    "h q[2];\n",
    "t q[4];\n",
    "tdg q[3];\n",
    "h q[4];\n",
    "h q[3];\n",
    "cx q[3],q[4];\n",
    "h q[4];\n",
    "h q[3];\n",
    "cx q[2],q[0];\n",
    "h q[0];\n",
    "h q[2];\n",
    "cx q[2],q[0];\n",
    "h q[0];\n",
    "h q[2];\n",
    "cx q[2],q[0];\n",
    "cx q[3],q[2];\n",
    "cx q[4],q[2];\n",
    "measure q[0] -> c[1];\n",
    "measure q[2] -> c[0];\"\"\")\n",
    "\n",
    "backend = 'ibmqx4'\n",
    "\n",
    "job_exp = execute(qc, backend=backend, shots=8192, max_credits=5)\n",
    "# job_exp = execute(qc, backend='local_qasm_simulator', shots=1024, max_credits=3)\n",
    "\n",
    "lapse = 0\n",
    "interval = 20\n",
    "while not job_exp.done:\n",
    "    print('Status @ {} seconds'.format(interval * lapse))\n",
    "    print(job_exp.status)\n",
    "    time.sleep(interval)\n",
    "    lapse += 1\n",
    "print(job_exp.status)\n",
    "\n",
    "circuit_drawer(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CzIYDzwDvAxnABqAzsAINtSEi9VCPHj14//332b59O23atCEnJ4dnn322TJu3336bG264gcWLF5e5b1BUVMTFF1/M1VdfzSWXXFLmM0899RRLlizhtddeK3O2sH379ujyNddcw4UXXlhlOFS0reoQz9b+E7jW3bsCX0f+vR5YU60ViYjUEo0aNeLhhx/mggsuIC0tjcsuu4yMjAwmTZpEbm4uEPQu2rdvH5deeilZWVkMGzYMgLlz57Js2TJmzpxJVlYWWVlZrF27FoAbb7yRjz/+mD59+pCVlcU999xTZS19+/bl0ksv5bXXXiMlJYUlS5Yc8bZiZe5VzgcUNDTb6+4nRJY/d/d/NrMGwN/dvXUVH68R2dnZnp+fn4xdi9RKZ08dldT9r/t5TlL3L7ExszXunl1Vu3jOID6J3IOAYIiNPsAZQMMjKVBERGq3eALiv4AfRpZ/B7wOrAMere6iREQk+WK+Se3uk0stP21mbwDN3H1TTRQmIiLJFW8314ZAb74b7ntlTRQlIiLJF08310xgIXA8UAikAPvN7GJ3X1dD9YmISJLEcw9iBsHQ3m3cvSfQhmAIcD0DISJSD8VziakT8KBH+sW6u5vZdOCXNVGYiEhtdix0KY7nDGIRMKzcuh8DL1VfOSIiUltUegZhZrOBkifpGgI5ZrYG2AG0BboDL1TwcRERqcOqusS0tdzr9aWWNwJLqrccERGpLSq9xOTuv4rlJ1HFHomqpgtctmwZ3bp1O2x6v9dffz06fkpWVhbHH388CxcuBGDp0qV069aNzp07M2bMGIqLiwF44YUXyMzMJCsri+zsbFasWAFUPvXgww8/TIcOHTAz9uzZU5OHQkQkLnEN/Wdm/c1shpktifw7II7PDjKz98xsq5ndGfL+bWa20czeMbPXzOz0eGoLE8t0gaeddhozZ87kJz/5SZn1AwYMYO3ataxdu5alS5fStGlTzj//fL799lvGjBlDTk4O69ev5/TTT2fWrGDajIEDB7Ju3TrWrl3LjBkzuO6664DKpx78wQ9+wKuvvsrppx/1rysiUq1iDggzuw6YC/wd+BOwC5hjZj+N4bMNCbrIDgbSgSvMLL1cs7eBbHfPBOYBv4m1torEMl1gamoqmZmZlQ6TO2/ePAYPHkzTpk359NNPady4MZ06dQLgvPPOY/78+QA0b94cs2CajK+//jq6XNnUg127diU1NfVof1URkWoXzxnEHcB57v7v7v6Eu98FnB9ZX5WewFZ33+buRUAOcFHpBu7+urv/I/JyJcGDeEclbLrAnTt3xr2dnJwcrrjiCgBatmxJcXExJaPIzps3r8yEIgsWLOCss85i6NChzJhx+CMiFU09KCJS28QTECcT3Jgu7T3gX2L4bBuCnk8lCiPrKjIOeDmO2mrMrl27ePfdd7ngggsAMDNycnK49dZb6dmzJy1atKBhw+8GtL344ovZvHkzCxcu5O677z5sW1dddRV//OMfq31iDxGR6hbPt9QKYJqZNQUws2bAFOAv1VmQmV0JZEe2Hfb+9WaWb2b5JZdpKhLrdIGVmTt3LhdffDHHHXdcdF2fPn1Yvnw5q1evpl+/ftHLTaX169ePbdu2RW88Vzb1oIhIbRRPQNwIZAJfmtnHwBfA2cANMXx2J8FzEyVSIuvKMLMfAXcBw9z9QNiG3P1Jd8929+xWrVpVutPS0wUWFRWRk5MTne0pVnPmzIleXirxySefAHDgwAEmT57MjTfeCMDWrVspmYDprbfe4sCBA5x88smVTj1YnxxpjzGADz/8kPPPP5+0tDTS09MpKCgAgmkX27Vrd9iMXABvvPEGWVlZZGRkcM4555TZ3qFDh+jatSsXXnhhdF1Fvc9EJFxMAWHB3dZ/AgYC7QieoG7n7ue4+0cxbCIP6Ghm7cysMTAKyC23j67AEwTh8Ekcv0OFYpkuMC8vj5SUFJ5//nluuOEGMjIyop8vKChgx44dh335TJkyhbS0NDIzM/nxj3/MueeeC8D8+fPp3LkzWVlZjB8/nueeew4zq3Tqwd///vekpKRQWFhIZmZmtOdTXXM0PcYArr76am6//XY2bdrE6tWry8ztO2XKlGiPsqysLAC++OILbrrpJnJzc9mwYQPPP/98me1Nnz6dtLS06OvKep+JSLiYxmKKjLv0LtDC3QsJ7iHEzN2LzexmggfrGgIz3H2Dmd0D5Lt7LsElpebA85HePx+6e3x/7ocYMmQIQ4YMKbOu9JytPXr0oLAw/NdJTU0Nvak9ZcoUpkw5/ArYxIkTmThx4mHrr7zySq688srQfdxyyy3ccsstlf4OdUHpHmNAtMdYevp3ndVKemuVv/+yceNGiouLOe+884CgN1hVnn32WUaMGMFpp50GUCZQCgsLeemll7jrrruYNm0aQGjvs/vvv59x48Yd4W8sUv/Fc4npbYIB+46Iuy9y907ufoa73xdZNykSDrj7j9z9e+6eFfk56nCQxDmaHmNbtmzhpJNOYsSIEXTt2pXbb7+dQ4cORd+/6667yMzM5NZbb+XAgQPRz3z++ef079+f7t278/TTT0fbT5gwgd/85jdlgqiq3mcicrh4AuINYLGZ/dLMxpnZ2JKfGqpNjhHFxcUsX76cqVOnkpeXx7Zt25g5cyYA999/P5s3byYvL4/PPvuMyZMnRz+zZs0aXnrpJZYsWcK9997Lli1bePHFF2ndujXdu3cvs4+qep+JyOHiGe77B8B24Jxy6x3NCXHMO5oeYykpKWRlZUUvTw0fPpyVK1cybtw4TjnlFACaNGnCtddey9SpU6OfOfnkk2nWrBnNmjWjX79+rFu3jrfeeovc3FwWLVrE/v372bt3L1deeSXPPPNMtPcZwCuvvMKWLVuq8xCI1DtVnkGYWVMz+zWwD1gGDHL3AaV+zq3xKqXWO5oeYz169OCLL76IPl2+dOnS6L2LXbt2AeDuLFy4kM6dOwNw0UUXsWLFCoqLi/nHP/7BqlWrSEtL4/7776ewsJCCggJycnI499xzeeaZZ4CKe5+JSLhYLjE9QtBraRMwEphaoxVJnXQ0PcYaNmzI1KlTGThwIF26dMHd+elPgxFcRo8eTZcuXejSpQt79uzhF7/4BQBpaWkMGjSIzMxMevbsyXXXXRcNj4pU1PtMRMJZSb/9ChuY7QK6ufsuM2sLLHP3dgmprgrZ2dlectMxXsfCbFBy7NF/14lTl4+1ma1x9+yq2sVyBtHM3XcBuPsO4MQjrkpEROqMWG5SN4oM620VvMbdl9ZEcSIikjyxBMQnlO2l9Gm51w60r86iREQk+aoMCHdPTUAdIiJSy2jMaRERCRXPg3IiR6Qu9/YQOZbpDEJEREIpIEREJJQCQkREQikgREQklAJCRERCKSBERCSUAkJEREIpIEREJJQCQkREQikgREQklAJCRERCKSBERCSUAkJEREIpIEREJJQCQkREQikgREQklAJCRERCKSBERCSUAkJEREIpIEREJJQCQkREQikgREQkVMICwswGmdl7ZrbVzO4Meb+fmb1lZsVmdkmi6hIRkXAJCQgzawg8AgwG0oErzCy9XLMPgWuAZxNRk4iIVK5RgvbTE9jq7tsAzCwHuAjYWNLA3Qsi732boJpERKQSibrE1AbYUep1YWSdiIjUUnXuJrWZXW9m+WaWv3v37mSXIyJSbyUqIHYCbUu9Tomsi5u7P+nu2e6e3apVq2opTkREDpeogMgDOppZOzNrDIwCchO0bxEROQIJCQh3LwZuBpYAm4C57r7BzO4xs2EAZtbDzAqBS4EnzGxDImoTEZFwierFhLsvAhaVWzep1HIewaUnERGpBercTWoREUkMBYSIiIRSQIiISCgFhIiIhFJAiIhIKAWEiIiEUkCIiEgoBYSIiIRSQIiISCgFhIiIhFJAiIhIKAWEiIiEUkCIiEgoBYSIiIRSQIiISCgFhIiIhFJAiIhIKAWEiIiEUkCIiEgoBYSIiIRSQIiISCgFhIiIhFJAiIhIKAWEiIiEUkCIiEgoBYSIiIRSQIiISCgFhIiIhFJAiIhIKAWEiIiEUkCIiEgoBYSIiIRSQIiISKiEBYSZDTKz98xsq5ndGfJ+EzN7LvL+KjNLTVRtIiJyuIQEhJk1BB4BBgPpwBVmll6u2Tjgc3fvAPwOmJyI2kREJFyiziB6AlvdfZu7FwE5wEXl2lwEzIoszwMGmpklqD4RESknUQHRBthR6nVhZF1oG3cvBr4ETk5IdSIicphGyS4gXmZ2PXB95OU+M3svSaW0BPYc6Yft9ueqsZR6T8c6cXSsEyeZx/r0WBolKiB2Am1LvU6JrAtrU2hmjYATgU/Lb8jdnwSerKE6Y2Zm+e6enew6jgU61omjY504deFYJ+oSUx7Q0czamVljYBSQW65NLjAmsnwJsNTdPUH1iYhIOQk5g3D3YjO7GVgCNARmuPsGM7sHyHf3XOAPwGwz2wp8RhAiIiKSJAm7B+Hui4BF5dZNKrW8H7g0UfVUg6Rf5jqG6Fgnjo514tT6Y226iiMiImE01IaIiIRSQIiISCgFhIiIhFJAxKFk6A8NASIixwIFRBzc3c2suZ7PEJFjgXoxxcjM0oAfA5cTPOW9CHgJWOHuXyeztmONmTV090PJrqO+MLN/ARw4CBzn7p8nuSSpJRQQMTKzN4CPgeeAFgRPe3cH/g5McvcXzcx0dnF0zOxBgvFpnnH3glLrG7j7t0krrJ4ys3HAMOBHwPvAcuCvwGvu/nEya6tvIkH8lbsfTHYtsVJAxMDMWgPb3L15ufUnAD8neOr7Wnf/czLqqy/M7HvALmAb0A5YDTwF/Knkr1ozexZ43t0XJK3QesLMTgXWA/8KLAX6A+cBZwP7gLvdfZn+8Dl6ZtYKeJFgSKH/BbYAe0v/0WNmzWrb1Qjdg4jN8UCemV1YeqW77408DT4P+KmZHZeU6uqPcwn+z9OJYLTJN4B7gY/MbIGZDSMI4/VJq7B+uRxY4+7/7e673H2Ou48FhgB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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb0781b7fd0>"
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "plot_histogram(job_exp.result().get_counts(qc))"
   ]
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   "source": [
    "# Reference\n",
    "[Basic Circuit Identities and Larger Circuits &#8212; Experience Documentation 2.0 documentation](https://quantumexperience.ng.bluemix.net/proxy/tutorial/full-user-guide/004-Quantum_Algorithms/061-Basic_Circuit_Identities_and_Larger_Circuits.html)\n"
   ]
  }
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