problems/week3/week3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Week3: Groverアルゴリズムを用いたMAXCUT問題の解決\n",
    "この週では、Week2で学んだGroverアルゴリズムを用いて単純なMAXCUT問題を解決します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AccountProvider for IBMQ(hub='ibm-q', group='open', project='main')>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit\n",
    "from qiskit import IBMQ, Aer, execute\n",
    "\n",
    "IBMQ.load_account()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MAXCUT問題\n",
    "\n",
    "MAXCUT問題とは、与えられたグラフG(V,E)の頂点Vを二つの部分グラフS,Tに分割（カット）する際に、  \n",
    "S-T間に存在するエッジ（カットエッジ）の本数が最大となるような分割(最大カット)を見つける問題です。\n",
    "\n",
    "### 量子アルゴリズムによる解決\n",
    "量子アルゴリズムによるMAXCUT問題の解法は、  \n",
    "[Quantum Approximate Optimization Algorithm (QAOA)](https://qiskit.org/documentation/aqua/optimization/qiskit_optimization.html) を用いたものや  \n",
    "[Variational Quantum Eigensolver (VQE)](https://medium.com/qiskit/the-variational-quantum-eigensolver-43f7718c2747)を用いたものも知られていますが、  \n",
    "ここでは、Week２で学んだGroverアルゴリズムを用いて解いてみましょう。\n",
    "\n",
    "とても簡単な例として、  \n",
    "頂点が（0,1,2）の３個  \n",
    "辺が（0,1),(1,2)の２本からなるグラフのカットを考えてみます。  \n",
    "<img src=\"maxcut.png\" width=\"320\">\n",
    "\n",
    "\n",
    "２つのゾーン、０と1に頂点を振り分けて（カットして）、  \n",
    "境界線を横切る辺（カットエッジ）の数(value)を  最大化することで最大カットを求める事ができます。  \n",
    "(最大カットはもちろん２です。)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 量子回路でカットエッジを判定する\n",
    "まずはオラクルの設計をしてみましょう。  \n",
    "グラフをカットした時、ある辺(a,b)がカットエッジかどうか判定する回路を考えてみます。\n",
    "\n",
    "辺の両端a,bが同じ部分グラフに入っている場合に0、  \n",
    "異なる部分グラフに含まれている場合に１と判定します。  \n",
    "１量子ビットを１頂点に対応させ、二つの部分グラフを0と1で表すと、  \n",
    "真理値表はXOR回路と同等のものになります。\n",
    "\n",
    "|頂点a|頂点b|判定|\n",
    "|--|--|--|\n",
    "|0|0|0|\n",
    "|0|1|1|\n",
    "|1|0|1|\n",
    "|1|1|0|\n",
    "\n",
    "対応する量子回路を以下に示します。  \n",
    "全ての組み合わせを同時に入力するため、頂点に対応した量子ビットにアダマールゲートを作用させています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 347.956x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(3)\n",
    "qc = QuantumCircuit(q)\n",
    "\n",
    "#cutedge checker\n",
    "def ccheck(a, b, c): \n",
    "    qc.cx(q[a], q[c]) \n",
    "    qc.cx(q[b], q[c])\n",
    "\n",
    "qc.h(q[0])\n",
    "qc.h(q[1])\n",
    "ccheck(0,1,2)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## カットエッジを数え上げる\n",
    "この判定回路とWeek1の(半)加算器を組み合わせることで  \n",
    "入力に対応したカットエッジの本数を数え上げることができます。\n",
    "\n",
    "今回のグラフは3頂点と２辺を持つので、  \n",
    "q[0],q[1],q[2]に頂点が含まれている部分グラフの情報を、  \n",
    "q[3],q[4]にカットエッジの判定結果を、  \n",
    "q[5],q[6]にカットエッジの本数をそれぞれ格納します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648.956x505.68 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(8)\n",
    "qc = QuantumCircuit(q)\n",
    "\n",
    "#half adder\n",
    "#入力: a,b\n",
    "#出力:和s,キャリーc\n",
    "def hadder(a,b,s,c):\n",
    "    #XOR\n",
    "    qc.cx(q[b], q[s])\n",
    "    qc.cx(q[a], q[s])\n",
    "    #AND\n",
    "    qc.ccx(q[a], q[b], q[c])\n",
    "\n",
    "qc.h(q[0:3])\n",
    "ccheck(0,1,3)\n",
    "ccheck(1,2,4)\n",
    "hadder(3,4,6,5)\n",
    "\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "これでカットエッジの本数を数える回路が出来上がりましたが、  \n",
    "Groverのアルゴリズムのためのオラクルとして用いるためには\n",
    "YesかNoで答えられる質問を用意する必要があります。\n",
    "\n",
    "## MAXCUTのためのオラクル回路\n",
    "そこでしきい値を2に設定し、桁上げ出力(q[5])が1であるかを確認することで  \n",
    "”カットエッジが2本（またはそれ以上）であるかどうか”を判別するオラクル回路を作ってみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1': 24957, '0': 75043}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 769.356x565.88 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(8)\n",
    "c = ClassicalRegister(1)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "qc.h(q[0:3])\n",
    "ccheck(0,1,3)\n",
    "ccheck(1,2,4)\n",
    "hadder(3,4,6,5)\n",
    "qc.cx(q[5],q[7])\n",
    "qc.measure(q[7], c[0])\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=100000)\n",
    "result = job.result()\n",
    "count =result.get_counts()\n",
    "print(count)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "約25％の結果が1となりました。\n",
    "今回の場合、カットエッジが2本となる入力は010と101なので、このオラクルは妥当なようです。  \n",
    "\n",
    "q[7]の初期状態を|->状態へ設定し、cx(q[5],q[7])を適用することで  \n",
    "010と101に対して符号反転を行うことができます。\n",
    "\n",
    "符号反転を行ったあとはここまでの逆順の操作を行うことでq[3]からq[6]を初期状態へと戻します。\n",
    "この操作は、入力Qubit(q[0]からq[2])とオラクル計算のためのQubit間の不要なエンタングルメントの消去に必要です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'0000000': 130, '0000010': 114, '0000001': 119, '0000100': 122, '0000011': 130, '0000110': 123, '0000111': 135, '0000101': 127}\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1612.16x565.88 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(8)\n",
    "c = ClassicalRegister(7)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "#inverse operations\n",
    "def iccheck(a, b, c): \n",
    "    qc.cx(q[b], q[c])\n",
    "    qc.cx(q[a], q[c]) \n",
    "def ihadder(a,b,s,c):\n",
    "    qc.ccx(q[a], q[b], q[c])\n",
    "    qc.cx(q[a], q[s])\n",
    "    qc.cx(q[b], q[s])\n",
    "\n",
    "qc.h(q[0:3])\n",
    "qc.x(q[7])\n",
    "qc.h(q[7])\n",
    "\n",
    "ccheck(0,1,3)\n",
    "ccheck(1,2,4)\n",
    "hadder(3,4,6,5)\n",
    "qc.cx(q[5],q[7])\n",
    "ihadder(3,4,6,5)\n",
    "iccheck(1,2,4)\n",
    "iccheck(0,1,3)\n",
    "qc.barrier()\n",
    "qc.measure(q[0:7], c[0:7])\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=1000)\n",
    "result = job.result()\n",
    "count =result.get_counts()\n",
    "print(count)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "等確率で８種類の出力が得られていることと、q[3]~q[6]が初期状態に戻っていることが確認できます。  \n",
    "符号反転の状態は確率分布から確認することはできません。  \n",
    "（測定されないq[7]は常に|->状態です。）\n",
    "\n",
    "# 回路の完成\n",
    "Diffusion回路を付け加えることで、MAXCUT問題に対するGroverのアルゴリズムが完成します。  \n",
    "高い確率で正解を得られるか確認してみましょう。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'010': 5009, '101': 4991}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1672.36x1167.88 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(8)\n",
    "c = ClassicalRegister(3)\n",
    "qc = QuantumCircuit(q,c)\n",
    "\n",
    "#diffusion operations\n",
    "def diffusion(a,b,c):\n",
    "    qc.h(q[a])\n",
    "    qc.h(q[b])\n",
    "    qc.h(q[c])    \n",
    "    qc.x(q[a])\n",
    "    qc.x(q[b])\n",
    "    qc.x(q[c])\n",
    "    qc.h(q[c])  \n",
    "    qc.ccx(q[a],q[b], q[c])\n",
    "    qc.h(q[c])  \n",
    "    qc.x(q[a])\n",
    "    qc.x(q[b])\n",
    "    qc.x(q[c])\n",
    "    qc.h(q[a])\n",
    "    qc.h(q[b])\n",
    "    qc.h(q[c])\n",
    "\n",
    "#initialization\n",
    "qc.h(q[0:3])\n",
    "qc.x(q[7])\n",
    "qc.h(q[7])\n",
    "qc.barrier()\n",
    "\n",
    "#oracle part\n",
    "ccheck(0,1,3)\n",
    "ccheck(1,2,4)\n",
    "hadder(3,4,6,5)\n",
    "qc.cx(q[5],q[7])\n",
    "ihadder(3,4,6,5)\n",
    "iccheck(1,2,4)\n",
    "iccheck(0,1,3)\n",
    "qc.barrier()\n",
    "\n",
    "#diffusion part\n",
    "diffusion(0,1,2)\n",
    "qc.barrier()\n",
    "qc.measure(q[0:3], c[0:3])\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=10000)\n",
    "result = job.result()\n",
    "count =result.get_counts()\n",
    "print(count)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 今週の問題・・の前にTips\n",
    "### $C^{\\otimes n-1}$NOTゲートの実装について\n",
    "$ n $ Qubitに対する拡散変換を行うには、  \n",
    "$C^{\\otimes n-1}$NOTゲートが必要となります。  \n",
    "Qiskitには以下の関数が用意されています。  \n",
    "\n",
    "**mct(q_controls, q_target, q_ancilla, mode='basic')**\n",
    "\n",
    "MCTゲートを用いることで複数のControl 量子ビットをもつToffoli gateを呼び出すことができます。  \n",
    "なお、MCTゲートを1〜2量子ビットゲートに分解する手法としては[1]や、補助量子ビット(ancilla)を用いない[2]などが知られています。  \n",
    "[1]A. Barenco (Oxford), C. H. Bennett (IBM), R. Cleve (Calgary), D. P. DiVincenzo (IBM), N. Margolus (MIT), P. Shor (AT&amp;T), T. Sleator (NYU), J. Smolin(UCLA), H. Weinfurter (Innsbruck),**Elementary gates for quantum computation** , arXiv:quant-ph/9503016 (1995)  \n",
    "[2]Mehdi Saeedi, Massoud Pedram, **Linear-Depth Quantum Circuits for n-qubit Toffoli gates with no Ancilla**,  arXiv:1303.3557 (2013)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 今週の問題（ラーニングチャレンジ演習 ⅡI）\n",
    "\n",
    "頂点　V:　(0,1,2,3)  \n",
    "辺　E:　（0,1),(0,2),(0,3)  \n",
    "となるグラフG（V,E）が与えられた時にカットエッジ数が３となるような入力を  \n",
    "Iteration = 2回のGroverアルゴリズムを用いて求め、回路の量子コストを算出せよ.\n",
    "\n",
    "**求めてほしい結果:**<br/>\n",
    "(a)問題を解くために設計した量子回路.<br/>\n",
    "(b)シミュレーターの実行結果から、最も確率振幅が高い量子ビット列を求めてください.<br/> \n",
    "(c)Unrollerを用いて、作成した量子回路の量子コストを算出するのに必要なゲートカウント. <br/>\n",
    "\n",
    "**提出物:**<br/>\n",
    "今週のチャレンジでは、以下２つのファイルの提出をお願いします.<br/>\n",
    "1.上記 (a)の量子回路をpythonファイル (.py) または ipython notebook (.ipynb)で保存したもの.<br/>\n",
    "2.textファイルの1行目に上記(b)、2行目に上記(c)の結果を貼り付けて保存したもの.<br/>\n",
    "\n",
    "txtファイルはご自身のパソコンのメモ帳またはテキストエディターを開いて作成いただいても良いですし、下記のサンプルコードを使ってtxtファイルを生成いただいてもかまいません.生成したファイルには(c)の結果が自動的に貼り付けられますので、ご自身で(b)を1行目に追加して保存してください.\n",
    "```sample_output.py\n",
    "import json\n",
    "dct = qc.count_ops()\n",
    "with open('wk3_output.txt', 'w') as f:\n",
    "    f.write(json.dumps(dct))\n",
    "```\n",
    "Example output:<br/>\n",
    "1000, 0111<br/>\n",
    "{\"u3\": 46, \"cx\": 31, \"barrier\": 3, \"measure\": 3}<br/>\n",
    "\n",
    "作成した量子回路をUnrollerを用いてu3とCXなどのエレメンタリーゲートに分解する方法については、[量子回路のコスト計算について](https://github.com/quantum-challenge/2019/blob/master/problems/how_to_calculate_quantum_cost.ipynb)を参照してください.\n",
    "\n",
    "ラーニングチャレンジⅠからⅢまでの結果ファイルは [提出フォーム](https://angelhack.typeform.com/to/AakobE)から送信をお願いします."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 解答例\n",
    "|1000>もしくは|0111>の確率が最大となる回路を構成します。   \n",
    "- q[7]は補助量子ビットになります。\n",
    "- Adderを用いずにカットエッジが3であるかどうか判定しています。\n",
    "- Iterationの回数を1や3に変更すると正解確率が変化します。（2で最大となる）\n",
    "\n",
    "**注意：**\n",
    "|1000>もしくは|0111>を観測すると、古典ビットがc[3],c[2],c[1],c[0]の順番で並んだものが得られるため, それぞれ観測結果は0001,1110になることに注意してください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1000': 41, '1101': 41, '1100': 53, '0011': 30, '0111': 37, '1110': 4602, '1111': 52, '0000': 32, '0110': 36, '0010': 41, '0001': 4844, '0100': 41, '1001': 31, '1011': 33, '1010': 44, '0101': 42}\n"
     ]
    },
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      "text/plain": [
       "<Figure size 1683.19x4659.48 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#from qiskit.aqua.circuits.gates import mct\n",
    "q = QuantumRegister(11)\n",
    "c = ClassicalRegister(4)\n",
    "qc = QuantumCircuit(q,c)\n",
    "ite = 2 #number of iteration\n",
    "\n",
    "#initialization\n",
    "qc.h(q[0:4])\n",
    "qc.x(q[8])\n",
    "qc.h(q[8])\n",
    "qc.barrier()\n",
    "\n",
    "for i in range(ite):\n",
    "#oracle part\n",
    "    ccheck(0,1,4)\n",
    "    ccheck(0,2,5)\n",
    "    ccheck(0,3,6) \n",
    "    qc.mct([q[4],q[5],q[6]], q[8] , [q[7]], mode='basic')\n",
    "    iccheck(0,3,6)\n",
    "    iccheck(0,2,5)\n",
    "    iccheck(0,1,4)\n",
    "    qc.barrier()\n",
    "#diffusion part\n",
    "    qc.h(q[0:4])\n",
    "    qc.barrier()\n",
    "    qc.x(q[0:4])\n",
    "    qc.barrier()\n",
    "    qc.h(q[3])\n",
    "    qc.mct([q[0],q[1],q[2]], q[3] , [q[7]], mode='basic')\n",
    "    qc.h(q[3])\n",
    "    qc.barrier()\n",
    "    qc.x(q[0:4])\n",
    "    qc.barrier()\n",
    "    qc.h(q[0:4])\n",
    "    qc.barrier()\n",
    "\n",
    "qc.measure(q[0:4], c[0:4])\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=10000)\n",
    "result = job.result()\n",
    "count =result.get_counts()\n",
    "print(count)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WFStW5Pzzzz/gGOVyuZjht2HDhhx33HGpqakpjk+aNCm/+MUvMm3atC6sfM8aAAAAjlRtbcnHvpFs3b7/flWl5MH7fpRjB/dMXQBHsxkzZiRJWlpaDnssMww7eDXYW79+faf2a6+9Nps3b05DQ8N+779hw4asWrUqjY2NSZIXX3wxw4YN69Rn2LBh2bp1axdWDQAAcHSpqkqm1e6/TynJ5JMjLASoADMMOxg3blwmT56c5ubmjBo1KmPGjMmyZcty2223JUmnHZLnzJmTcePGpaGhISNGjMiaNWtyzTXXZMiQIVmwYEGS5JhjjskLL7zQ6Xs8//zzGTp0aM+dFAAAwBHo3NOTn/0qefLZ13ZGflUpyTEDk/8ypRKVAWCGYQdVVVW56aabMnHixFx66aWZO3duampqcvnll6e6ujqTJ08u+k6aNCm33npr5s6dm6ampixevDhNTU1ZvXp1xo4dm6T9moZPP/10tmzZUtxv7dq1OeOMM3r83AAAAI4kg/onf/225Myx7UuPO6o7MbniT5LjzLUAqAi7JB+Eiy66KA888EB+9rOfve77vuc978kpp5ySa665Jl/5ylfS3NycDRs27HeX5INZc96V69IBAAAq6YXtyT98vf3zf3inoBDgUHRlVmRJ8kFYvXp1cV3C1+tzn/tcPvCBD2TkyJGpra3N17/+9f2GhQAAAH3NsYNe+1xYCFB5AsMD2Lp1a9avX5/LLrvskO5/wgkn5Pvf/34XVwUAAAAA3UNgeABDhw7Nrl27Kl0GAAAAAPQIm54AAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgCAAAAAAWBIQAAAABQEBgeopaWlpRKpb3etm/fXunyAAAAAOCQVFe6gKPdkiVLMm3atE5tAwcOrFA1AAAAAH3HyzuSex9Lnno+qa5KzhiTnFqTlEqVruzoJjA8THV1dWlsbKx0GQAAAAB9ysqHk5tXJ6/sTEpJykm+//Pk5FHJvOnJyGMqXeHRy5LkvWhra8uSJUtSW1ubQYMGpb6+PitWrEhdXV0uvvjiSpcHAAAA0Kfd80jytZXtYWHSHha+qvW3yf/4fvLSyxUprVcQGO7FvHnzsnDhwlxyySVZvnx5Zs2aldmzZ2fjxo0588wz9+hbXV2dkSNHZubMmVm3bl2FqgYAAADo/draklvu2/fxcpItL7bPQOTQCAx3s3Tp0tx444255ZZbctVVV+Xcc8/NggULMnXq1OzcubMIDIcPH54rr7wyN9xwQ26//fZcffXVueuuuzJ16tQ8/PBrP5Ef//jHc8YZZ6SqqirLli2r1GkBAAAA9Aobfp08t+3A/e58qPtr6a1cw3A3ixYtynnnnZdzzjmnU/v48ePTv3//TJo0KUkyZcqUTJkypTg+ffr0NDU1pb6+Ps3Nzbn++uuTJLW1tfnMZz6Tf/iHf+ixcyi5sicAAHCU+fBX2hcUej8DHMgZ0z+YP774iwfs9+SWbSmVhvRARUeWjs+j5XJ5Pz33zQzDDlpbW7N27dpccMEFexzbtGlTJk6cuN8dkGtra9PY2JiVK1cWbR/4wAfyx3/8xxk0aFC31AwAAADQl7z80nNd2o89mWHYQWtra5Jk9OjRndq3bduWFStW5Pzzzz/gGOVyueL/ETvU9BgAAKBSrvhq+0fvZ4ADeXln8g9ff23Dk305v3F0vtCHnlNmzJiRJGlpaTnsscww7KCmpiZJsn79+k7t1157bTZv3pyGhob93n/Dhg1ZtWpVGhsbu61GAAAAgL5sYHUy4837Pl5K0r9fcvaEHiup1zHDsINx48Zl8uTJaW5uzqhRozJmzJgsW7Yst912W5J02iF5zpw5GTduXBoaGjJixIisWbMm11xzTYYMGZIFCxZU6hQAAAAAer3zJiXPb2vfCbmU9p2RXzWgOvnQOUnNsZWq7uhnhmEHVVVVuemmmzJx4sRceumlmTt3bmpqanL55Zenuro6kydPLvpOmjQpt956a+bOnZumpqYsXrw4TU1NWb16dcaOHVvBswAAAADo3aqqkvf9fnLFnyS/N+619ndMST72rqR29L7vy4GZYbibCRMm5I477ujUdtFFF+X000/P4MGDi7b58+dn/vz5Bxxvx44d2bVrV9ra2rJjx45s3749AwcOrPh1DgEAAACOZqVScmpN++0/Nra3/dEZla2ptzDD8CCsXr2603Lk1+Mv//IvM3jw4Pz4xz/OhRdemMGDB+exxx7r4goBAAAAoGsIDA9g69atWb9+/QE3PNmXL33pSymXy51up556atcWCQAAAABdxJLkAxg6dGh27dpV6TIAAAAAoEeYYQgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGh6ilpSWlUmmvt+3bt1e6PAAAAAA4JNWVLuBot2TJkkybNq1T28CBAytUDQAAAAAcHoHhYaqrq0tjY2OlywAAAACALmFJ8l60tbVlyZIlqa2tzaBBg1JfX58VK1akrq4uF198caXLAwAAAIBuIzDci3nz5mXhwoW55JJLsnz58syaNSuzZ8/Oxo0bc+aZZ+7Rt7q6OiNHjszMmTOzbt26ClUNAAAAAIfPkuTdLF26NDfeeGNaWlpyzjnnJEnOPffc3Hvvvbn55puLwHD48OG58sorM2PGjAwbNixr1qxJc3Nzpk6dmrvvvjunnXZaXn755VxyySX5/ve/nxdffDENDQ35n//zf+b000+v5CkCAAAAwD4JDHezaNGinHfeeUVY+Krx48enf//+mTRpUpJkypQpmTJlSnF8+vTpaWpqSn19fZqbm3P99ddn586dGT9+fD75yU9m9OjRWbx4cd73vvflZz/7WbeeQ6lU6tbxAQAAutqHv1JO4v0McGg8h7ym42NQLpcPaQxLkjtobW3N2rVrc8EFF+xxbNOmTZk4ceJ+d0Cura1NY2NjVq5cmSQ55phj8tGPfjRjxoxJv3798td//ddZs2ZNtm/f3m3nAAAAAACHwwzDDlpbW5Mko0eP7tS+bdu2rFixIueff/4BxyiXy/tMs++8886ceuqpGTRo0OEXe4AaAAAAjiZXfLX9o/czwKHwHJLMmDEjSdLS0nLYY5lh2EFNTU2SZP369Z3ar7322mzevDkNDQ37vf+GDRuyatWqNDY27nHsmWeeyeWXX55PfvKTXVcwAAAAAHQxMww7GDduXCZPnpzm5uaMGjUqY8aMybJly3LbbbclSacdkufMmZNx48aloaEhI0aMyJo1a3LNNddkyJAhWbBgQadxt23blne84x153/velwsvvLBHzwkAAAAAXg8zDDuoqqrKTTfdlIkTJ+bSSy/N3LlzU1NTk8svvzzV1dWZPHly0XfSpEm59dZbM3fu3DQ1NWXx4sVpamrK6tWrM3bs2KLfzp07M2vWrNTW1ppdCAAAAMARzwzD3UyYMCF33HFHp7aLLroop59+egYPHly0zZ8/P/Pnzz/geB/60IfS1taWz3/+811eKwAAAAB0NYHhQVi9evVer0t4II899lhuvPHGDBo0KCNGjCjaf/GLX+SUU07pyhIBAAAAoEsIDA9g69atWb9+fS677LLXfd83velNfXp3HgAAAACOPgLDAxg6dGh27dpV6TIAAAAAoEfY9AQAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwBAAAAAAKAgMAQAAAICCwPAQtbS0pFQq7fW2ffv2SpcHAAAAAIekutIFHO2WLFmSadOmdWobOHBghaoBAAC6ws5dyc9+lTy4OdnVlpwwPPn905LhgytdGQB0P4HhYaqrq0tjY2OlywAAALpI62+TL7Qkz21LSqWklKStnPz7z5L/MiU59/RKVwgA3cuS5L1oa2vLkiVLUltbm0GDBqW+vj4rVqxIXV1dLr744kqXBwAAdJNnX0r+1w+T5393laFyuT0sTNo/fuveZOVDlasPAHqCwHAv5s2bl4ULF+aSSy7J8uXLM2vWrMyePTsbN27MmWeeuUff6urqjBw5MjNnzsy6desqVDUAAHC4frQueemV9qBwX5b/LGlr67maAKCnWZK8m6VLl+bGG29MS0tLzjnnnCTJueeem3vvvTc333xzERgOHz48V155ZWbMmJFhw4ZlzZo1aW5uztSpU3P33XfntNNOS5LMmTMnP/jBD7J9+/bU1dXlM5/5TKZOnVqx8wMAAPbtPx4+cJ/ntiUPPZVMGN399QBAJQgMd7No0aKcd955RVj4qvHjx6d///6ZNGlSkmTKlCmZMmVKcXz69OlpampKfX19mpubc/311ydJFixYkC9+8YsZMGBAvvOd7+S9731vnnjiiW49h1Kp1K3jAwBAb/X//d+dKVX1O2C///Ke2Vl/19d6oKK+48NfaZ/W6f0McCg8h7ym42NQ3t+U+f2wJLmD1tbWrF27NhdccMEexzZt2pSJEyfudwfk2traNDY2ZuXKlUXbGWeckQEDBqRcLqd///558skns3379m6pHwAAODzbtv72oN5cbXv+Nz1QDQBUhhmGHbS2tiZJRo/uvLZg27ZtWbFiRc4///wDjlEul/dIs+fMmZOvf/3refnll3P55Zdn0KBBXVf0PmoAAABev2/dm9zxy/33OXZQ8sjPfpB+pl90qSu+2v7R+xngUHgOSWbMmJEkaWlpOeyx/InroKamJkmyfv36Tu3XXnttNm/enIaGhv3ef8OGDVm1alUaGxs7tX/1q1/NCy+8kG9+85t7HAMAAI4cZ09IBvVP9rei7U8mRVgIQK9mhmEH48aNy+TJk9Pc3JxRo0ZlzJgxWbZsWW677bYk6bRD8pw5czJu3Lg0NDRkxIgRWbNmTa655poMGTIkCxYs2GPs/v37553vfGfq6+tz1llnZcKECT12XgAAwMEZNTS57D8nn78j2fpy52OlJH86OZlWW5HSAKDH+L9YB1VVVbnpppsyceLEXHrppZk7d25qampy+eWXp7q6OpMnTy76Tpo0Kbfeemvmzp2bpqamLF68OE1NTVm9enXGjh27z+/xyiuv5NFHH+2BswEAAA7FKcclH3tXcuHU19qa3tLe1jRp/7MPAaA3MMNwNxMmTMgdd9zRqe2iiy7K6aefnsGDBxdt8+fPz/z58/c71pYtW3L77bfn7W9/e6qrq/OFL3whTzzxxAGXNgMAAJU1oDo5a1yy9K72r8+vr2w9ANCTzDA8CKtXr+60HPn1+OxnP5sTTzwxJ5xwQr72ta/lO9/5TnGtRAAAAAA40phheABbt27N+vXrc9lll73u+x533HH50Y9+1A1VAQAAAED3EBgewNChQ7Nr165KlwEAAAAAPcKSZAAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACgIDAEAAAAAAoCQwAAAACOOuVy8uxLyc9bX2t75DfJKzsrV1NvUV3pAgAAAADgYD33UnLXQ8nKh9sDw44+872kVEpqT0im1SZveWPSz3S5101gCAAAAMARr62c/Hhd8u37kx279t2vXE7WP9l+e+Oo5MLG5KSRPVdnbyBjBQAAAOCI9srO5AstyTfu2X9YuLvW3yb//O/JPY90W2m9ksAQAAAAgCPWrrbk+hXJL5849Pt/5c7k/se6tq7eTGB4iFpaWlIqlfZ62759e6XLAwAAAOgVvv/zZN2T++/z6Tntt30pJ/mXlclvt3Zpab2WaxgepiVLlmTatGmd2gYOHFihagAAAIDe7rltyfMvJYMHJMcNbd/ko7d68rnke2u6ZqyXdyb/9h/JX/1R14zXmwkMD1NdXV0aGxsrXQYAAADQy23akiz/WeeluWNGJk1vSepPqVxd3WnFg+2bnXSVBzcnTzxjE5QDsSR5L9ra2rJkyZLU1tZm0KBBqa+vz4oVK1JXV5eLL7640uUBAAAAfcyGJ5PPfK898OroiWeSL/44aXmwMnV1p+07umezkjs3dP2YvY3AcC/mzZuXhQsX5pJLLsny5csza9aszJ49Oxs3bsyZZ565R9/q6uqMHDkyM2fOzLp16ypUNQAAANAb7WpL/u9Pk7a2pLzbbLtXv/zmPclvnu/x0rrVr7Ykr7yOHZEP1sNPdf2YvY3AcDdLly7NjTfemFtuuSVXXXVVzj333CxYsCBTp07Nzp07i8Bw+PDhufLKK3PDDTfk9ttvz9VXX5277rorU6dOzcMPP7zHuP/6r/+aUqmUZcuW9fQpAQAAAEexNa3JC9tfCwf35ae9bOZc6zPdM+6Tzyev7OyesXsL1zDczaJFi3LeeeflnHPO6dQ+fvz49O/fP5MmTUqSTJkyJVOmTCmOT58+PU1NTamvr09zc3Ouv/764thLL72UT37yk5k4cWKPnEOpN1/tFAAAetCHv9L+9txr7O7nsYZ9+8PZ16bhT69MqWrf877K5XKWfuunefdbz+7ByrrXtPcvzlv/7G87te1vJ+T9Hb/iq699Xi4nx51wcrb+tvUwKzwydXweLe8+JfUgmWHYQWtra9auXZsLLrhgj2ObNm3KxIkT97sDcm1tbRobG7Ny5cpO7YsWLcoHP/jB1NTUdHnNAAAAQO9WLpeTg8jSywecg3iUOcSw6yAH78axj35mGHbQ2tqeLI8ePbpT+7Zt27JixYqcf/75BxyjXC53SnIfffTR3HLLLVm9enVuueWWri14PzUAAACH79UZKV5jdz+PNezb2tbk/6zYf59SqZQ/f/fZuekfe8/vUMsvk2/e27mt40zBjl6dWbiv4x1VlZLfPtWa/v0Or74jzYwZM5IkLS0thz2WGYYdvDoDcP369Z3ar7322mzevDkNDQ37vf+GDRuyatWqNDY2Fm0f+chHsnDhwvTv37/rCwYAAAB6vTNOSkYMSfa3Yr9USv6gtudq6gknj+qecUePSK8LC7uaGYYdjBs3LpMnT05zc3NGjRqVMWPGZNmyZbntttuSpNMOyXPmzMm4cePS0NCQESNGZM2aNbnmmmsyZMiQLFiwIEly++235/nnn8873vGOipwPAAAAcPSrqko+eHbyv36Y7NjZeTFtqdS+cvd9ZyXHDa1Yid3i5OOSgdXJy128QUntCV07Xm9khmEHVVVVuemmmzJx4sRceumlmTt3bmpqanL55Zenuro6kydPLvpOmjQpt956a+bOnZumpqYsXrw4TU1NWb16dcaOHZsk+dGPfpSVK1empqYmNTU1+elPf5p58+Zl0aJFlTpFAAAA4Ch0ak3ykfOShlOTfh1mGo4/Prn0j5LG8RUrrdsMqE7OGtf14/a2mZjdwQzD3UyYMCF33HFHp7aLLroop59+egYPHly0zZ8/P/Pnz9/vWB/5yEfyoQ99qPj6ggsuyNy5c/P+97+/a4sGAAAAer3Rw5OLpiUXnJXM/7f2tsvfVtmauts5b07uejjZuatrxpt8cnLCsK4ZqzcTGB6E1atXd7ou4cEaNmxYhg177adw4MCBGTVqVKc2AAAAgNdjUB/aJqHm2OTt9cm37j1w3wMZPCB57+8d/jh9gcDwALZu3Zr169fnsssuO+yxumKXGgAAAIC+5Jy65JHfJD/71b77HGh35KpSctEfJMMH778f7QSGBzB06NDs2tVF814BAAAAeF2qqpI/n5Z89a7kvsde//0HVCd/8YfJGWO6vrbeSmAIAAAAwBGtul97aHj6Sck3Vifbdhzc/cafkMxu7H07SHc3gSEAAAAAR7xSqX3X5Le8Mbl7Y7Ly4eTJZ5Pybv0GVidvPjH5wwntgWGptNfh2A+BIQAAAABHjSED2ndPPufNyfYdyRPPJC+90n6dwuOGJm8Y1v45h05gCAAAAMBRaVD/ZNzxla6i96mqdAEAAAAAwJFDYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGAAAAAEBBYAgAAAAAFASGh6ilpSWlUmmvt+3bt1e6PAAAAAA4JNWVLuBot2TJkkybNq1T28CBAytUDQAAAEezl3ckqx9N1rYmr+xMjh+WTB2fnHJcpSsD+hKB4WGqq6tLY2NjpcsAAADgKLdpS3LdHcmLLyelJOUkG59K7noo+f3TkvedlVRZJwj0AE81e9HW1pYlS5aktrY2gwYNSn19fVasWJG6urpcfPHFlS4PAACAXub5bcn/vj156ZX2r8vp/HHVw8l3HqhEZUBfJDDci3nz5mXhwoW55JJLsnz58syaNSuzZ8/Oxo0bc+aZZ+7Rt7q6OiNHjszMmTOzbt26ClUNAADA0erODe1hYbm87z4/Wpdse6XnagL6LkuSd7N06dLceOONaWlpyTnnnJMkOffcc3Pvvffm5ptvLgLD4cOH58orr8yMGTMybNiwrFmzJs3NzZk6dWruvvvunHbaaUmSGTNmZNWqVenXr1+SZObMmfnSl77UredQKpW6dXwAAOgrPvyV9vTGa+zu19cf6z9fsj4jTjgtpdK+5/Xs2JVMOXdO1t25tAcr40jV139n2LeOPxPl/f0XYj8EhrtZtGhRzjvvvCIsfNX48ePTv3//TJo0KUkyZcqUTJkypTg+ffr0NDU1pb6+Ps3Nzbn++uuLY1/+8pczc+bMnjkBAAAAjjqDjhm537DwtX6jeqAaoK8TGHbQ2tqatWvX5m/+5m/2OLZp06ZMnDhxvzsg19bWprGxMStXruzOMg/oUNNjAACgsyu+2v7Ra+zu19cf68XfSZ589rVrFu7Ljf/ns6k/5bM9UhNHtr7+O8OeZsyYkSRpaWk57LFcw7CD1tbWJMno0aM7tW/bti0rVqzY4/qFe1Mul/eYDnzppZfm+OOPz9vf/vZs2LCh62ou91EAACAASURBVAoGAACgV2g87cBh4ZABycQxPVIO0McJDDuoqalJkqxfv75T+7XXXpvNmzenoaFhv/ffsGFDVq1alcbGxk73ffTRR/Poo4+moaEh73jHO7Jz586uLx4AAICj1u+fltQMTfZ3Nbo/nZxU9+uxkoA+zJLkDsaNG5fJkyenubk5o0aNypgxY7Js2bLcdtttSdJphuGcOXMybty4NDQ0ZMSIEVmzZk2uueaaDBkyJAsWLCj6nXXWWcXn//iP/5jrrrsu69evzxlnnNFzJwYAAMARbVD/5PK3JdevSFqf6XysX1Xy9vrk7LrK1Ab0PWYYdlBVVZWbbropEydOzKWXXpq5c+empqYml19+eaqrqzN58uSi76RJk3Lrrbdm7ty5aWpqyuLFi9PU1JTVq1dn7Nixex2/VCrZvQgAAIC9GnlMcuWfJn/9x6+1vevM5B/fk/yROSdADzLDcDcTJkzIHXfc0antoosuyumnn57BgwcXbfPnz8/8+fP3O9azzz6bu+++O9OnT0+5XE5zc3NGjBiRCRMmdEvtAAAAHN1KpeS041/7esabK1cL0HeZYXgQVq9efVAbnuxux44dmT9/fmpqajJmzJisXr06t9xyS6qr5bQAAAAAHJkkVwewdevWrF+/Ppdddtnrvu8b3vCG3HPPPd1QFQAAAAB0D4HhAQwdOjS7du2qdBkAAAAA0CMsSQYAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACgJDAAAAAKAgMAQAAAAACtWVLgAAgL5tx3/9l0qXUHH9/2l2pUsAACiYYQgAAAAAFASGAAAAAEBBYAgAANBBuZxs2Zrcv+m1trseSn61Jdm5q3J19UZt5eSp55N7Hn2tbdXDyRPPJLvaKlYWQJ/nGoYAAABJtu9oD6t+uqE9xOroX1e1fxxYnfze2OQP65LRw3u+xt7ixZeTOze03555qfOxf1nZ/nHIgKTxtGTahOS4oT1fI0BfZoYhAAB9xlMvPpcBSy7M/U892qn9sed+kwFLLswvtzxemcKouAc3J9d8O/nGPXuGhR29vDP5yYbk2u8ktz1gxuGhuO+xpPnW5DsP7BkWdvTSK8ntv0wWfTtp+WXSZsYhQI8xwxAAgD5j9ZMbM6i6f95Sc3Kn9ruffDjHDhiculEnVqgyKukHP0++ff/ru09bOfne2mTDr5OLZySDB3RLab1KuZx8895kxYOv7347d7Xfb8Ovkw+enfTv1z31AfAaMwwBAOgz7vn1xvyn409NdVXnxGH15ofTcMLYVJW8PO5rWh58/WFhR4/8Jvn8HWYaHoxv3//6w8KOfv54cuNP2sNaALqXV0SHqKWlJaVSaa+37du3V7o8AAD24p4nN+ato8ft0X73kw/nzL2007u1/ja55d799/n0nPbb/jzydPLva7qurt5o3ebkh7/Yf5+DeazXtiY/Wd91dQGwd5YkH6YlS5Zk2rRpndoGDhxYoWqgcl58Odm0pX2pyRtHJcMGV7oi4Gjy1PPJb15oX2Y29g2Wmz37UvsOoaVS8qbjkiFeWnSZ+379SC5489RObW3lttz360dz6ZSmPP3S83n3N5ZkQL/qvLTjlSw8+31526mTKlRtz9u6PfnVb9s/f+Oo5NhBla2nO5XLyddWdd1stR/+PGl4U3LSyK4ZrzfZuSv52squG+/W+5LJJycjhnTdmAB0JjA8THV1dWlsbKx0GVAxL76cfOve5J5Hk12/uxB1Van9Rdy7z0yGeyEH7MemLck370k2/ua1tsH9k7Prkj+ZlPTrY2shnnmxfcOFNa3tYUaSVFclbx2bvLPBNdIO1+Mv/DabX3w2DSeM7dT+wFOPZeuO7fn9E2szctDQtMz+RPpVVeWhZ57MRd/+H30iMNy6vf1n777HXgvQqkrJlDcl7zqzdwaHDz3VPsOwq5ST/Ghd8n5vDfbwwK/2v7nJ67VjV/vuyufXd92YAHTWx16GH5y2trYsWbIktbW1GTRoUOrr67NixYrU1dXl4osvrnR5cMTY9kry2e8nd298LSxM2t9oPLAp+fR3k+e3Va4+4Mj26NPJf/9++/W/Otq2o30jgS//tG9dp+rZl9qfN9f86rWwMEl2tiUrH07+xw+Sl3dUrr7e4PGt7enQiIGd/5v1tV/emd8/cXxOHnZc+lVVpV9V+0vkF17ZnsnHn9Ljdfa0F19OPvO95N5HO//OtZXb2z7zvfZAsbdZ+VDXj3nPo35P96Y7HuuVD3V+rgSgawkM92LevHlZuHBhLrnkkixfvjyzZs3K7Nmzs3Hjxpx55pl79K2urs7IkSMzc+bMrFu3rkJVQ8/74S+SJ59r/4/67sppf/N72wM9XRVwNCiX25en7Wrb+3NIkty/qf1aVX3Frfe1/5NlX4/H48+0b87AoXvzqJMyfOCQ/NN/3JJnt7+Y327bms/f/4P87/u/n09On130e+TZpzLjXz6Rty9blHeMf2sFK+4Z313TfkmAff09f/qF9hC/t9n4VNePuWNX0vpM1497NNvV1n6Nx672/Pbk6a1dPy4A7QSGu1m6dGluvPHG3HLLLbnqqqty7rnnZsGCBZk6dWp27txZBIbDhw/PlVdemRtuuCG33357rr766tx1112ZOnVqHn744WK8crmcj3/84znxxBMzbNiwvO1tb6vUqUGX2vm7pSD7U06y+pH2mYgAHT3ym9/9w2E/s0NKpb5zYfut29uXgh5ossxP1idtbQfoxD4NGzgk33z3VbnnyUcy9rr/N5NuuCrf3HB3vv3ev8v0k08v+o0dcXxaZn8id37g6lzxwy9VruAe8MrOZNXDB+638uH2vr3Fiy937RLZjrpymXNv8NTz3beDtMcaoPu4huFuFi1alPPOOy/nnHNOp/bx48enf//+mTSp/Ro2U6ZMyZQpU4rj06dPT1NTU+rr69Pc3Jzrr78+SfLP//zPue+++3L//fenpqYmDzzQ/dOtSqVSt38POPa4kzPvM5sO2G9nW3Lqm9+apx65pweqAo4Wk/7zX+WP5n5uv33K5eSBDU+n9LY39FBVlXPShGm54GM/OWC/F7YnQ0cen23P/+aAfY8mr1y1tMe+17Q3vjkrLvzEPo+/vHNHBlb3T5IMGzA4Qwf0zC5elXr9NvLEuvz5Px146uorO5MT33RGfvvEL3ugqu43YnRt/mJJ5/9IHGh33n0dv+Krnb+e/9F/zMqvf/wwqutdxrx5emZ+dEWntq56rP/i/7k0a374vw+juiPbh7/S/m8k7+/YFz8j7EvHn4nyIV6/QWDYQWtra9auXZu/+Zu/2ePYpk2bMnHixP3ugFxbW5vGxsasXNm+BdiuXbvyqU99Kvfcc09OOOGEJElDQ0P3FA89rG3XwU8zaNvlYj5AZwf7HNJXnj9e13Pqzr7xmFTKfU89kr//0dfSr1SVnW278s/nXlTpkrpVW1vf/HteLnffVN3uHPto5LEGODoJDDtobW2/UNLo0aM7tW/bti0rVqzI+eeff8AxyuVykeRu2rQppVIpn/3sZ/P5z38+J5xwQq6++uq8613v6vrid6sBulu5nCz6dvKb5/e/hG7ooOTJRx7oczudAvv39AvJ1bfsv08pybkNJ+YLfeDv2o5dycdu3v8lHEpJThqZbNv6THrbRIId//VfKl1CofGkCbn9/R/r8e9bqddvbeVk4TcPvDx35JBkyxMbUtVL/p6/sjP5u3/rfFmE3WevverV2W77Or5H/8WfSOPXP3FY9fUmW7YmC7/Vua2rHut//b/X5Ywx1x16cUe4Vx8H7+/YFz8j7G7GjBlJkpaWlsMeq5f8ye8aNTU1SZL16zsvT7j22muzefPmA84O3LBhQ1atWpXGxsYkyRNPPJHHH38827ZtS2traz73uc/lL/7iL/Loo492S/3Qk0ql5Jw3H/h6W2dPiLAQ2EPNsckZJ7WHYPtSTvKHE3qqosrq3y/5w9r99ymn/Xm3t4WFVFbV7/6eH8j0N6fXhIVJMqA6OWFY94z9xlHdM+7RatQxyZAB3TP2yR5rgG5jhmEH48aNy+TJk9Pc3JxRo0ZlzJgxWbZsWW677bYk6bRD8pw5czJu3Lg0NDRkxIgRWbNmTa655poMGTIkCxYsSJIMGTIkSfLRj340AwcOzNlnn51zzjknLS0t+eAHP9jj5wddber45LGnk//Y2P6m/9Xw8NXPJ45J3jaxcvUBR7bZjcl//3777qwdlUrts37e+9bklOMqU1sl/MmkZNOWZN2Tuz2n/u7x+IPa5PfGVrJCeqvpde1/z+/btPe/5//plOScusrV113qTmzffKkrDRucnDiia8c82pVK7Y/1fY917bgnjUiO7ZlLjAL0Sb3o/4SHr6qqKjfddFMmTpz4/7N35/FR1ff+x98z2UMISYgh7CQkhC1JA4JBJATESMFqqWvEpdCrXkrttagtt/6sWm5ZFNve9va22urVUgUrVSsKtS5JRBEksoU1IEsIBMIOgQRCMr8/TnPIQPacWTLzej4eeRDO+Z5vvnPm8z0z85nv+X41Y8YMTZs2TbGxsZo5c6YCAwOVlpZmlk1NTdWyZcs0bdo05eTkaMGCBcrJyVFhYaESEox388nJyQoKCvLUwwFczm4zPvDfc63zN7zxUdIdI6XpWYwuBNC4zmHSjyZKk9KMD9l1BveQZl4vjfHBBEVTAgOkB8dJt42Q4uqNfOrbVbpvtHT7CEYXwjXsdune64zX9B7Rl7b3iJbuyjTiz5dGF9a5tplRvW0xKon3Pg1pbgR1W4z2kxHoAOApvJxdZsCAAcrLy9PZs2dVUlKiOXPmqKioSIMGDVJY2KVPM7Nnz9aGDRt08uRJVVdX68CBA3rllVfUr18/s0xERIRuueUWzZs3T9XV1Vq9erU+/fRT855ywBfYbNLVCdKsb17a9pPJxptw3jADaE54sJSTKj0z5dK2B7Kl5PhGD/FpAXbjNuz//NalbY/cKA3rR7K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fkl7+RPpwh9EJvd+hanslLMQ/0Kn9rZ2f67rIGA0LHiAfq1U+VvvH15nztUoKN39FoqlJeuNT++WiB4/ZC9eNTfZLbP+zUHrnS8nWmUXnurnPStww5h5znquu+myPd4wJAAAAwP0oGLbgvvvu07x583T//fdrzZo1ys3N1ZQpU7R//36NGzfusr6+vr7q37+/cnJytHu3ubbi/Mvn0ndnLm+3yV48fOPTlo+b1XtfSbu/XwOteb3hQvHhg61XtqsoLjcmdLD6+Qfq+S9W62TtWR2vqdYrX32sP3z1kZ7JmOLod+BkpbKWPalbV87X7THXGJjYM9bulLZ8X6BvXuy68GXhLnPuTruzwvVjHjklnTzn+nG9WWOTfYahq+09Kp1vcP24AAAAsCssLDQ6AkyKguElli5dqtdff12rV6/W448/rokTJ2r27NkaP368GhoaHAXDfv366bHHHtNrr72mtWvX6umnn9aGDRs0fvx47du3zzGezWbTnDlzFBkZqeDgYN18881GPbUrduSUffZSWxNxGm3S5z1kBkldvfT53rb7WCz2wg06L9g/UO/89HFtPnJAUX98UImvPa539hTpvTv+VRnD4h39okLCVTDlSX3+86f18Cd/Ni6wBzQ2tf+6skgq2OmROB5zts5+CbE7XLikG3ZHT9l3OHa1Jpt0+KTrxwUAAIDd119/bXQEmBRrGF5i/vz5mjRpkjIzM53aY2Ji5Ofnp8RE+zppKSkpSklJcRzPyMhQdna2kpOTlZ+fr1dffVWS9MILL2jLli366quvFBYWpq1bt7r9OVhctJBZyj88ooypi9rsY7PZtPLjnfrxuASXPGZ3Nvyqm/XTWR+12cdmk3YebpLV6iebzVyr/Z9/fKnHHmvC0DEqvPvJVo/XNdTL39dPkhTcq7eCevX2SC5Xvbeu1MARV+vuZ7a02ccm+5pxgcEDVXPGhQvRGSh8ZKqmPL3Zqa29nZBbO/7wm87f3zvjEW3524tdSGcuUVffqtsff8+pzVXnOvu2u7Rn0/IupOvefvkX+5/VjPp8QPfHawRt4fUBoC2PPPJIu30WL17cZr/Fixe7MhK8RPOfK7ZOrsdEwbCZ8vJy7dixo8U3W1lZmRISEtrcATk2Nlbp6enauHGjJKmxsVGLFy/W5s2bNWjQIElSamqqe8K7gY9v+7s9WyyWDvUzg44+T4vFKquPrxobXLStKy6zpfKAfr3+LflYrGpoatQLE6cZHcmtruQ9ZvXt5cYknmWx+rhzcPeN7YXcea6t7vz/CAAAAMAtKBg2U15eLkmKiHDe6rampkaFhYW65ZZb2h3DZrM5KrllZWWyWCx66aWX9Morr2jQoEF6+umn9ZOf/MT14S/J4Ao7yu2bKbTFYpEmjBul/+oBOwh8d0Z6enX7/fr3kRrq69wfyMPqf7XM6AgO6YNHa+3kJzz+uK56b12p6lrpibftl3e2JbCXdLLqkHxNUp9p6T136ey1Cy7Mdmvt+KVefukFpY96ofPhTGZfpfTSJROoXXWu/2flUsUP9twMZU+7cB6M+nxA98drBG3h9QGgLbt2tb/e1eLFi9vcnHXRoravGoS5ZGVlSZIKCgq6PBZTLJoJCwuTJJWUOG/L+dxzz6mioqLd2YF79uzRpk2blJ6eLkk6fPiwDh06pJqaGpWXl2vJkiW65557VFpa6pb8rhY/WArubV8brTU2mzQh1mORDBXWVxodYS+StuWG0Z7Jg54jKEBKGdH2e1GSxsfINMVCSQoNkvzd9Getof3dM663GhzivrE51wAAAO4zd+5coyPApJhh2Ex0dLSSkpKUn5+v0NBQDRkyRCtXrtQHH3wgSU47JE+dOlXR0dFKTU1VSEiItm/frmeffVaBgYGaPXu2JCkwMFCS9Jvf/Eb+/v664YYblJmZqYKCAt17770ef35Xyscq3XWt9J/rJYut5c1PUoZLcZEej2aYn46TXvxQOl/f8vkY2l+aQMEQbnBrsn0X27N1l7/2LJIG9JVuHGtEMvexWqSRA12/e2+AnxTRz7VjervevaTIEKnCxRuUDAiS+npmiVEAAIAeKTc31+gIMClmGDZjtVq1YsUKJSQkaObMmZo+fbrCwsKUl5cnX19fJSUlOfomJibq3Xff1fTp05Wdna0FCxYoOztbxcXFioqKkmRf09DPz8+op+MSCUOlGVlSeLBzey9f6aax0s8n2H+p7ykiQ6Rf/lCKGujcbrVIaVFS3s3umxGFni00SHr4R/ZZrs1ZLFLSMOmX2VIfEy4nOn6U68dMizbXTExXSXfDuXbHmAAAALgoPj7e6AgwKUoblxg9erTWrVvn1DZt2jTFx8erd++L0yRmzZqlWbNmtTlWUFCQfvzjH2v+/PnKz8/X5s2btX79ev3ud79zS3Z3iR8sjYmUDh6TXvxfe9u8O3puYWxwf+n/ZktHTknPfr+p6FM/s182CrhTWF9p5k1S1Rnpme/X9pvzEykk0Nhc7pQ4zL4u6ImzrhnPapF+wCzgFqVFS3/bLtW4aL8mf18pPcY1YwEAAADwLGYYdkBxcbHT5chXYsmSJdq5c6f69++ve+65R3/+8581cuRI1wb0AItFGhl28fueWixsrvkljRQL27ao6D1tOVoqSXp83RuauGyuHl37epv36Wi/lhw6c1yPrf3/JEkvFr+vrGVPOo5trTyoF75494rH7E4G9r34tZmL7fWifAAAIABJREFUhZJ9aYTJ17luvB9eJQ0Kbr9fTxTYS7rjGteNd3uq1JfPRgAAAMArUTBsR3V1tUpKStrd8KQ1YWFheu+991RdXa3du3e7fYdkoLtpsjXp80MlShk0UluOHtDZ+lqtmzJH5xsbVFyxr8X7dLRfaz45uF03jUhUXUO9tlWWOR1LDh+hDYf3qMnW1OnnBM+Ki5RubOdKi4ffbH/X3uiB0g8TXJfLjMaNlK4Z2XafjpzrpGHS9cwuBAAAcLsLu+ICrkbBsB1BQUFqbGzUQw89ZHQUwCttrSzT0L6hkqSNh/foxuGJkqQbRyRqU8XeFu/T0X6FZd8o/KVf6Oa35inmj/9Xd7zzgr39253KGBav17av07SrMi67X0z/CG2tPNjl5wbPuS2la5cSRw2U/iWLtQvbY7FIU8ZLVw/v/BgJQ6RpE9rfUR4AAABdt2TJEqMjwKQoGAJwq70njmhEsH2XmJN15xTsb18LtJ9/b52obXlhuo72u2HYGKVFjtLHk/9dNwwbo9/dNF02m03n6uvk7+Or9d/u1MThl08pi+4Xrl3HD7vi6cFDrBb75bI/v96+o++V3O+HCVLeTVd2v57Mxyr90w+kn10j+V1BgdXXKt2eIv1zxpXdDwAAAJ03c+ZMoyPApFiJDoBb2WRzfB3iH6jTdTWSpNN1NQoJaHkBvo7223+yUlH9wiVJ5WeOa0jfUH1VWaqk8BF685tPNTn++lYzWcT0J29jsUjXRNl3iv60RNqwVzpT23JfPx/75bUZcfaNinBlrBb7uUsYYj/XG/e1vhlKgJ90bbR0Q5zz+poAAABwv4KCAqMjwKQoGAJwq9j+kfr80G5JUvrgWP1p6ye6c0y61h7coX+6KkMNTY06VlOtQX0u7iLT0X7fHCvX2AFD1djUJOv31z9+XLpdN4+4Sm+XFGlbVan+tPUTffNduX7/5f8qL/VHkqQDp6p01xgWWPNWwb2lW5KlHyVKFSelb49LJ89JTU1SnwBpWKg0tL/k72d0Uu83IEj6cap0a7J06IT9XJ+21/LVN0AaNkAaHCL14l8TAAAAgKnwT3wAbpUcPlzfnjkmSUoZFKUAXz9NXDZXSQOHKy0yRntPHNHCL97VH370L477dLTfN9+VK31wrOoa61V57rQqqk/oy6MH9GjarUqLvFgQzFr2pKNYKEklxyuUHD7CA88e7uRjlYaG2m9wL18faUSY/QYAAADA/CgYAnArq8WqCUPitOVoqVIGjdSiG+9xOr6tqkx3tXDpcEf6zUq/uOv4lnsXSJJ+GnutrBbn5VkLpjzp+Hpr5UGNHxx7WR8AAAAA8DY7d+40OgJMioIhALd7NO22Vo/9bPS1HRqjo/3uHJPe5vHk8BHMLgQAAABgCsuXL1dubq7RMWBCFAwBdIjf81OMjgAAAAAAaGbOnDkUDOEWXJMHAAAAAAAAwIGCIQAAAAAAAAAHCoYAAAAAAABe6OWXXzY6AkyKgiEAAAAAAIAXSkhIMDoCTIqCIQAAAAAAgBfKzMw0OgJMioIhAAAAAAAAAAcKhgAAAAAAAAAcKBgCAAAAAAB4obS0NKMjwKQoGAIAAAAAAHihoqIioyPApCgYAgAAAAAAAHCgYAgAAAAAAADAgYIhAAAAAACAF1q5cqXREWBSFAwBAAAAAAAAOFAwBAAAAAAA8EI5OTlGR4BJUTAEAAAAAAAA4OBrdAAA3qH+V8uMjmA4v+enGB2hW+M14rnXCOea92NbeH3w+mgLrw9eH+3hNeKZ1wjnmfci0N0xwxAAAAAAAMAL5eXlGR0BJkXBEAAAAACA/5+9O4+Pqr73P/6e7ImYBIhhXxIIIYQkTRANIklwiRbsQoupgdIW7lUvBW9dqKXyq2y9ATQ1tr9Wqr9itZSlErSKwtWqJOICElkMa9gxEEhkDxDIMr8/powZCFln5mTOvJ6PRx7ime985zPf+Z7JzDvfcw7ggaZOnWp0CTApDkkGWsBqlY6ckvZXSKUnv9m+cqPUq7M0oKsUHmJcfTC3Y2ekvccd595rn0u9O0n9u0gRNxpXG+BNzl6USo5JX9XbF5d8KvXoJEVFSL07SxaLcfXBWDW10p7j0uETUtnpb7av3mqbGwO6SgF8AvdqR09J+8ql0lPfbMv/3PZZMqaL1KmDcbUB8DxpaWn66KOPjC4DJsTHFaAZrFZp00GpYJfjF8Qr1pXY/muRNLindPdg25cCwBm2lUof7JAOVFx726d7pE///e+B3aS74m3hIQDnO3pKem+b9OVXUp3V8baNB2w/ktQtTEofKN3ST/IhOPQaVdXShzukz/ZK56quvf29bbb/Bvvb5sbd8VKHIPfWCONYrdLWr6S1O6RDJ669/eM9kvbYPksO6mH7fR51k7urBOCJKioa+JIAOAGHJANNOHNBeqlAWvxpw2FhfVZJxaVS3v9KqzbbVhmg5crPn1FA7jhtKT/osP3QmQoF5I7TzhNHjCnMzc5fkl5ZJ/2lsOGw8Gq7yqQ/vi+t+Fy6VOP6+ozC/HAfxtqmtk56t1j63Rppy+Frw8KrlZ2Rlm+Q/vS+dKLSPTUagfnxjT3HpAXv2ELBhsLC+i5WS4W7pPlvS1sPu6c+IzA/vnHuorToI9vv9IbCwvqskrYfkf7wnvTGF9Jlfp/DCRhrAK1BYAg0ouKclPeutPNoy+5nlW1F2F8Kzf1Bz1WKju1XkJ+/Bkf0cti+8dg+3RgQrNhO3QyqzH3OXJB+/54tnGipT/ZIL3wgXbzs/LraA+aH+zDWtrDwbx9La76UapsICq+2r9z2B6Sjp5pu64mYHzZfHJAWfiidOt+y+1Vekv66TirY6Zq6jMb8sDlZKT3/nu1ogZawyhYsv7jWvH8EZI64D2NtboMGDTK6BJgUgSFwHecv2UKX0xda38euMtt5rawt/JLp7b44vl/fiuwrPx9fh+1FZfuU0iVKPhZzv3VdrrF9+Sw/2/o+Dn0tvfyRVFfnvLraC2+fH+7EWNtW7G79qvX3r7xk25/PtOF3SXvF/JB2l0lLPmt61Wlj/rlJ2rjfeTW1F8wP22HqCz9s20rjfeXSq+vM+VmSOeI+jLW5rVy50ugSYFK8M7RSQUGBLBZLgz9VVU0ciwKP8EZR06sFnh9v+2nM1q++Oa8VmueLY/t1c9foa7ZvPLZPQxrYbjbvbLVd4KQxzZl7e45LhbudV1d74e3zw528fay3lUrr9zXepjn74rkq2wWKzPaF39vnx4XL0tJmhIXNmSMrm/GZw9N4+/yQpDc32Y5WaUxz5seOo7ZzFpsNc8R9GGtze/rpp40uASbFRU/aKDc3V8OHD3fYFhgYaFA1cJZ95VLRQef198YXUlJvKZA9rlk2Hz+g+wcOc9hWZ63T5uMHNTk5U19fOKsxb+QqwNdPF6ova+6IH+muvgkGVetcZaelj3Y5r793tko3R0k3mujE+t48P9zNm8e6tk7K3+i8/rYfsf0M7um8Po3mzfNDkt4rls5cdE5fVdXSW5uln97unP7aA2+fH4dP2C6A4yxvbZaS+0ohAc7r02jePkfcibE2txUrVmjOnDlGlwETIr5oo9jYWKWmphpdBpxsnZNXZV28bLvK8rD+zu3XjI6cO6my86eV0iXKYfvW8kOqrK7Srd1i1DGogwqyZ8nXx0d7Tx3ThLf/aJoPNZ+U2M5b5Cw1tdKGfbarLZqBt88Pd/L2sS4ubdspKRqyrsQ8gaG3z49LNU2vPm2prYdtAWRYsHP7NYK3zw9J+rjEuf1dqrEdup4+0Ln9GoU54j6MNYDW4pDkBtTV1Sk3N1cxMTEKCgpSUlKSCgsLFRsbq4ceesjo8uBiVdXSl204X9X1mPH8RK5wpNJ2KerwwBCH7ct3fqpbu/VXr9DO8vXxka+P7e3r3OUqJUb2dnudrlBX59yVrVd8bqK5583zw928faxd8Z69u8x5K9KM5u3zY3up7fOCM9VZbX9cNANvnx81tdKmQ87v10ynuPH2OeJOjDWA1iIwbMCkSZM0d+5cPfzww1qzZo2ysrKUnZ2t/fv3a8iQIde09fPzU8eOHTV27Fjt3m3CE4Z5mSMn23by8uspPWnOC1A428BO3RUWGKJnP39Lp6vO6+TFSr205X39ecu/9D9p2fZ2B06XK2PZLI3On6fv9r/ZwIqdp/yc87+ASraLp7iiXyN48/xwN28ea6vVdjihK3zlon7dzZvnhyQdctHr6Kp5527ePj+OnraFhk7v95RU7YJ+jeDtc8SdGGvzKywsNLoEmBSHJF9l6dKlevXVV1VQUKD09HRJ0siRI7Vp0ya9/vrr9sAwLCxMTzzxhDIyMhQaGqri4mLl5ORo2LBh2rhxo/r166fDhw87XOLcarXqwoULKioquiZ4RPtx9LRr+r1cK31dKUWGuqZ/swgNDNE/x0zTUx8tV9SLUxXiF6ikyD56+4e/0ohecfZ2UeGRKsiepYNnKnT3P+ZqdL8UA6t2jqOnXNd32Wkp6ibX9e8u3jw/3M2bx7ryku1CJa5w9JQ5Dkv25vkh2d5TXcGVvwfcifnhmn7rrNLxM1LPTq7p3528fY64E2Ntftu3b1dkZKTRZcCECAyvMm/ePN177732sPCK/v37y9/fXwkJtnM5JCcnKzk52X57WlqaMjMzlZSUpJycHC1atEi9e/dWZWWlvc1bb72lRx55RCkprn3ztVgsLuv7F3+3uvwxjHbzd36l4T+a77CtqavXXe/2R5c4/n9C0hCVH9zUhuqMc3naUrc91vCeA1U4btZ1b79UU61AP39JUmhAsDoEuOeET66e9/EZ/6G7/vMvDtucNfcy7rxHh4vfa0N1TXPXHGmv80Ny33sjY+3asQ69KUoT8xyPSXbWvjjnf+brnn/8ug3VNY354fp9MWvWZ+rW3/Ec1q2ZI1fPj70HvpLF4tpDAZkfrp8fSZmPKOMnf3DY5qz3kFtvG6Gjuz9uQ3VNY4645/c5n63N/Z3SWR577LEm2+Tl5TXaLi8vz5klwUPU37+s1tYdQklgWE9paam2bdvW4M52+PBhxcfHN3oF5JiYGKWmpmr9+vUN3r5kyRKNGzeON8Z2rrbmsgv7vuSyvr3J5vIDeuqj5fK1+Kimrla/GznB6JKcgrnnHGadH+2RWce6rtaV+6Lr+m5vzDo/JKnORa8j79Xm4Kr5IUm11cwROB9jDaAhFmtro0YTWr9+vYYNG6Z33nlHo0aNsm+/ePGi+vXrp1GjRukvf/lLIz3YDl+uqKjQtm3bHLafO3dOXbp00eeff67Bgwc32kdGRoYkqaCgoE1tXOHKXzmb+iupJ9teKv2/Zp4G4so4XP3X34ZYLNKCLCnAQ2P66l8uM7oEw/k/m910ozY4+LX0/LvNa9uSuSdJs8dIYSFNt2sL5ojr58gVjLVrx7quTpq+Qrpc03Tblu6LP75Nujmq6XZtwfxw/b64fH3zr5LckjkS1116eGTr62oO5ofr50fJMemFD5rXtqXvITljpZDrr19wCuaIe36fM87u+9zkyXbt2tVkm7i4OO3cufO6tw8caJLLq6NZnJkVcdGTeiIiIiRJJSUlDtufeeYZlZWVNXko8Z49e7RhwwalpqZec9vrr7+umJiYJsNCGK9nZ9f02zXUc8NCuEf3cMnHBQuQQ4NcHxYCZuLjI/Xs6Jq+zXDuMUi9XPQ6uqpfuJer9vPOHVwfFgLwPLNnzza6BJgU8UU90dHRSkxMVE5Ojjp16qQePXooPz9fq1evliSHC5WMHz9e0dHRSklJUXh4uIqLizV//nyFhIRoxowZ1/S9ZMkSjR9v4mV5JhIWLPWNsK32cqZE156SCCYQ4GdbXbL9iHP7Tezl3P4Ab5DYS9pf4dw+u4TafuD54ntKK4tsF6FwJt6vzSEkQBrQ1bbS0JmYHwAakpWVZXQJMClWGNbj4+OjFStWKD4+XpMnT9bEiRMVERGhKVOmyM/PT4mJifa2CQkJWrVqlSZOnKjMzEwtWLBAmZmZKioqUlSU47FGx44dU0FBgbKzWXLtKW4f4Nz+fCzSsP7O7RPm5Oy5J0nDXdAnYHa3REv+vs7tc/gA2+kp4PnCQ6QEJ1/tuk8EK1DNZHiMZ/QJwPPFxcU13QhoBQLDqwwYMEBr167V+fPndfjwYc2dO1fFxcWKi4tTcPA3V4uaPn26tmzZotOnT6u6ulpHjhzRK6+8or59+17T5/Lly3XbbbepVy/+LOgpkvs490N7+kDblwtv8dzGt7X5+EFJ0rS1izVy2Ww9/uGrjd6nue1a4si5k3riw7/Z///5oneUsWyWJGlr+SH97vNVTnssZxnYTYrp4rz+hkZL3cKd158r1J8vV7vyGn5etldpS2dq5LLZmrZ2caP9tXYutdc54Uzu3jfr74P19z+p/Y93SKB0d7zz+rvpRim1n/P6cxber1vv20mSn5M+SVskfTfZOX25Cu8fLZPQU4qKcF5/w2OkiBud158z8P5hHD47AXAHAsNmKCoqcjgcuaU4HNnz+PpI41Jt/22ryFDp24lNtzOLOmudPj1SouQufbX5+AGdr67S2uyZulxbo6Kyhs8Q39x2LfXBoWLd2SdBknSpplpflh+235YU2UefHd2jOmudUx7LWSwW6YFUKdAJJ4wIC5bGNH7qVcPVny8NufIa9g6N0HtZM7Q2e6bKL5xRccXhBtu3ZS611znhLEbsm1dev6v3P8kzxvvOeOecU84iadyw9nceW96v26ZrmPN+v4+IlfpFOqcvV+D9o+V8fKTsYc5Zqdy5Q/sLlHn/MA6fnQC4C4FhEyorK1VSUtLkBU8as3HjRj344INOrAru0L2j9NPbG78IxaNLGr+qXViw9FBG+/uS6Epbyw+r5422b9jrj+7RHb1tH+Du6JOgDWV7G7xPc9s1pvDwDkX+3//UXcvnqv+L/60f/vN3Kvxqp9J62Zbov1y8VhMGpzncp3/HrtpafqjFj+VqnTtI/5ne+JeMpuZeSIDtSpvt/eTo9edLY69h1xvCFeQXIEnys/jK19Lwr6/mzqWGHktqv3PCGVy5b15vPK+8fg3tf1L7H29fH9u+GNHh+m2a2hctsoUGUTc5vbw24/267e4Y1PQpR5qaI4N7St9r53/c4f2jdSJDpYkjGv8DdFPzo0Og7bNkoL/Ty2sT3j+Mw2cnXO3KVXEBZyMwbEKHDh1UW1urRx55xOhSYIDEXtKDGVKHoJbft3dn6b8z29/hI66299Qx9Qm1fTM+femCQgNth/KHBQbrVNX5Bu/T3HaNGdFroIZ266f3H/iNRvQaqD/cOVEXqi+pQ0C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\n",
      "text/plain": [
       "<Figure size 1683.19x7789.88 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.transpiler import PassManager\n",
    "from qiskit.transpiler.passes import Unroller\n",
    "pass_ = Unroller(['u3', 'cx'])\n",
    "pm = PassManager(pass_)\n",
    "new_circuit = pm.run(qc) \n",
    "new_circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('u3', 126), ('cx', 72), ('barrier', 13), ('measure', 4)])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_circuit.count_ops()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "dct = new_circuit.count_ops()\n",
    "with open('wk3_output.txt', 'w') as f:\n",
    "    f.write(json.dumps(dct))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}