{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gate Execution Quality Metrics\n",
    "\n",
    "This tutorial covers benchmarks for measuring quantum gate performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qcmet import CliffordRB, InterleavedRB, OverUnderRotationAngle, CycleBenchmarking\n",
    "from qcmet.devices import NoisySimulator, IdealSimulator\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gate execution quality metrics consist of:\n",
    "\n",
    "- Gate set tomography based process fidelity (GST)\n",
    "\n",
    "- Clifford randomised benchmarking (CliffordRB)\n",
    "\n",
    "- Interleaved Clifford randomised benchmarking (InterleavedRB)\n",
    "\n",
    "- Cycle-benchmarking composite process fidelity (CycleBenchmarking)\n",
    "\n",
    "- Over- or under-rotation angle (OverUnderRotationAngle)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clifford Randomized Benchmarking (RB)\n",
    "\n",
    "Clifford Randomized Benchmarking measures the average error rate of a gate set by applying random sequences of Clifford gates.\n",
    "\n",
    "### How Clifford RB Works\n",
    "\n",
    "1. Generate random sequences of Clifford gates of varying lengths\n",
    "2. Append an inverse gate to return to |0⟩\n",
    "3. Measure success probability\n",
    "4. Fit decay curve: P(success) = A × p^m + B\n",
    "5. Extract average gate error from decay parameter p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'m_list': [25, 50, 100, 150, 200, 250, 300, 400, 500, 650], 'circs_per_m': 10, 'interleaved_clifford': None}\n",
      "Generated 100 circuits\n",
      "Total circuits: 10 lengths × 10 samples\n"
     ]
    }
   ],
   "source": [
    "# Create simulator\n",
    "noisy_device = NoisySimulator()\n",
    "\n",
    "# Setup CliffordRB benchmark\n",
    "rb = CliffordRB(\n",
    "    qubits=2,\n",
    "    m_list = [25,50,100,150,200,250,300,400,500,650],\n",
    "    circs_per_m=10\n",
    ")\n",
    "\n",
    "# Generate circuits\n",
    "rb.generate_circuits()\n",
    "print(rb.config)\n",
    "print(f\"Generated {len(rb.circuits)} circuits\")\n",
    "print(f\"Total circuits: {len(rb.config['m_list'])} lengths × {rb.config['circs_per_m']} samples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Example RB circuit:\n",
      "              ░         ░       ░ ┌────────┐ ░       ░       ░ ┌───┐ ░        »\n",
      "   q_0: ──────░─────────░───────░─┤0       ├─░───────░───■───░─┤ Z ├─░────────»\n",
      "        ┌───┐ ░ ┌─────┐ ░ ┌───┐ ░ │  Iswap │ ░ ┌───┐ ░ ┌─┴─┐ ░ └───┘ ░ ┌─────┐»\n",
      "   q_1: ┤ Z ├─░─┤ Sdg ├─░─┤ Y ├─░─┤1       ├─░─┤ Z ├─░─┤ Y ├─░───────░─┤ Sdg ├»\n",
      "        └───┘ ░ └─────┘ ░ └───┘ ░ └────────┘ ░ └───┘ ░ └───┘ ░       ░ └─────┘»\n",
      "meas: 2/══════════════════════════════════════════════════════════════════════»\n",
      "                                                                              »\n",
      "«         ░       ░ ┌───┐ ░ ┌───┐ ░       ░     ░ ┌──────┐ ░       ░ ┌───┐ ░ »\n",
      "«   q_0: ─░───────░─┤ Y ├─░─┤ X ├─░───────░──■──░─┤0     ├─░───────░─┤ X ├─░─»\n",
      "«         ░ ┌───┐ ░ └─┬─┘ ░ └─┬─┘ ░ ┌───┐ ░  │  ░ │  Ecr │ ░ ┌───┐ ░ └───┘ ░ »\n",
      "«   q_1: ─░─┤ X ├─░───■───░───■───░─┤ Z ├─░──■──░─┤1     ├─░─┤ Z ├─░───────░─»\n",
      "«         ░ └───┘ ░       ░       ░ └───┘ ░     ░ └──────┘ ░ └───┘ ░       ░ »\n",
      "«meas: 2/════════════════════════════════════════════════════════════════════»\n",
      "«                                                                            »\n",
      "«              ░       ░ ┌──────┐ ░ ┌───┐ ░       ░ ┌──────┐ ░       ░ ┌───┐ ░ »\n",
      "«   q_0: ──────░───────░─┤ √Xdg ├─░─┤ X ├─░───────░─┤ √Xdg ├─░───────░─┤ Y ├─░─»\n",
      "«        ┌───┐ ░ ┌───┐ ░ └──────┘ ░ └───┘ ░ ┌───┐ ░ └──────┘ ░ ┌───┐ ░ └─┬─┘ ░ »\n",
      "«   q_1: ┤ X ├─░─┤ I ├─░──────────░───────░─┤ I ├─░──────────░─┤ I ├─░───■───░─»\n",
      "«        └───┘ ░ └───┘ ░          ░       ░ └───┘ ░          ░ └───┘ ░       ░ »\n",
      "«meas: 2/══════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«        ┌──────┐ ░       ░       ░ ┌────────┐ ░       ░ ┌───┐ ░       ░      »\n",
      "«   q_0: ┤1     ├─░───────░───────░─┤0       ├─░───────░─┤ Y ├─░───────░──────»\n",
      "«        │  Ecr │ ░ ┌───┐ ░ ┌───┐ ░ │  Iswap │ ░ ┌───┐ ░ └─┬─┘ ░ ┌───┐ ░ ┌───┐»\n",
      "«   q_1: ┤0     ├─░─┤ S ├─░─┤ Z ├─░─┤1       ├─░─┤ I ├─░───■───░─┤ Z ├─░─┤ I ├»\n",
      "«        └──────┘ ░ └───┘ ░ └───┘ ░ └────────┘ ░ └───┘ ░       ░ └───┘ ░ └───┘»\n",
      "«meas: 2/═════════════════════════════════════════════════════════════════════»\n",
      "«                                                                             »\n",
      "«         ░ ┌──────┐ ░ ┌────┐ ░ ┌───┐ ░ ┌────┐ ░ ┌──────┐ ░       ░     ░ ┌───┐»\n",
      "«   q_0: ─░─┤0     ├─░─┤ √X ├─░─┤ I ├─░─┤ √X ├─░─┤1     ├─░───────░──■──░─┤ Z ├»\n",
      "«         ░ │  Ecr │ ░ └────┘ ░ └───┘ ░ └────┘ ░ │  Dcx │ ░ ┌───┐ ░  │  ░ └───┘»\n",
      "«   q_1: ─░─┤1     ├─░────────░───────░────────░─┤0     ├─░─┤ I ├─░──■──░──────»\n",
      "«         ░ └──────┘ ░        ░       ░        ░ └──────┘ ░ └───┘ ░     ░      »\n",
      "«meas: 2/══════════════════════════════════════════════════════════════════════»\n",
      "«                                                                              »\n",
      "«         ░ ┌───┐ ░ ┌──────┐ ░ ┌───┐ ░       ░ ┌───┐ ░       ░ ┌────────┐ ░ »\n",
      "«   q_0: ─░─┤ Y ├─░─┤0     ├─░─┤ Y ├─░───────░─┤ Z ├─░───────░─┤0       ├─░─»\n",
      "«         ░ └───┘ ░ │  Ecr │ ░ └───┘ ░ ┌───┐ ░ └───┘ ░ ┌───┐ ░ │  Iswap │ ░ »\n",
      "«   q_1: ─░───────░─┤1     ├─░───────░─┤ Y ├─░───────░─┤ X ├─░─┤1       ├─░─»\n",
      "«         ░       ░ └──────┘ ░       ░ └───┘ ░       ░ └───┘ ░ └────────┘ ░ »\n",
      "«meas: 2/═══════════════════════════════════════════════════════════════════»\n",
      "«                                                                           »\n",
      "«              ░       ░         ░ ┌──────────┐ ░ ┌─┐   \n",
      "«   q_0: ──■───░───────░─────────░─┤0         ├─░─┤M├───\n",
      "«        ┌─┴─┐ ░ ┌───┐ ░ ┌─────┐ ░ │  Inverse │ ░ └╥┘┌─┐\n",
      "«   q_1: ┤ Y ├─░─┤ S ├─░─┤ Sdg ├─░─┤1         ├─░──╫─┤M├\n",
      "«        └───┘ ░ └───┘ ░ └─────┘ ░ └──────────┘ ░  ║ └╥┘\n",
      "«meas: 2/══════════════════════════════════════════╩══╩═\n",
      "«                                                  0  1 \n"
     ]
    }
   ],
   "source": [
    "# Look at circuit structure\n",
    "print(\"Example RB circuit:\")\n",
    "print(rb.circuits[10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RB Results:\n",
      "  qubits: 2\n",
      "  alpha: 0.9996772896169319\n",
      "  AverageGateError: 0.00024\n",
      "  fit_result: {'popt': array([0.99967729, 0.67568573, 0.32379839]), 'pcov': array([[ 2.18584749e-08,  4.11562949e-05, -4.12954106e-05],\n",
      "       [ 4.11562949e-05,  7.75766023e-02, -7.78317533e-02],\n",
      "       [-4.12954106e-05, -7.78317533e-02,  7.80885979e-02]])}\n"
     ]
    }
   ],
   "source": [
    "# Run benchmark\n",
    "rb.run(noisy_device, num_shots=1024)\n",
    "\n",
    "# Analyze\n",
    "results = rb.analyze()\n",
    "print(\"\\nRB Results:\")\n",
    "for key, value in results.items():\n",
    "    print(f\"  {key}: {value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing RB Decay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sf49ytGrlhOPHj6ptr169+hr9Av/44xowNjbGihVB8PDwVIWOggiFQrVAVbNmLQCAo6OTakwkEqF69Rp4/vxZoevJz/Pnz7Bp03pcvvwrEhJeIuc57XZ2BT8T8+rVK2jRwlEVkgCgdu06+OST+rh27apaUGrTpm2hf3aW9s/Y2NgYZGVloUOHzmrjnTp1QWTkMTx48A/q1KmrGnd2ds21fosWLVUhCQBatmyl1pf3+e9768GD+3j69AmmTvVVe182b94CQqEQN2/egI1NPdjaNsD33+9EWNhGtG3rCjs7+yI9KqQgtrYNcPToYVhaWqFNG2fY2HxS8ErFgEFJh70bkv744zL69u2Orl17YPXqdWpXVhBR3kJCpKqQJJPJEBIiLbWwtHTpAsTEXMOIEWNQt249GBsbY//+PYiKOqFaJinpNW7duon27dvkWv+/86gsLCw0+voSiQQrV65DWNgmLFnyJeRyOZo2dYCPz0y1U3r/ZWBgAH19fdXnOR+/+0sYyL6BblHnUCoUCsyaNR2pqakYM8Yb1avXhJGRETZvDsWzZ08LXD8lJTnPU0vm5pZITk5SGytM/6ytrQGgUF+7OKWkJAPIXaO5efbDXN/dF0NDw1xXySUkvESNGjVzbbcwwTivr5szp2jOnBl5Lp/Tn+HDR0EgECAi4gi2bv0GZmbmGDBgEEaOHFsiYdPHZyYkko348cdvsX79alSpUhXDho3Ep596FPvXeheDUhlx585tKJVKHD58AH//HYstW75FgwYF/8VFVFH9d05SzucASjwsZWRk4MKFc5g82UftqEbO0ZIcEokp6tWrj9mzA/67iVw+5BdPw4aNERLyNTIy3uKPPy5j3brVmD3bF7t3H9B4WwURiw1yPb+yoPlQDx8+wK1bNxEUtEJ1IQuQ3b/CkEgkSEx8lWs8MTFBddrrXwX3r0qVqqhevQZ+/fUSxo2bWKgaioNEkv2Hb2LiK1hbV1GNJyYm/P/r/x4Zyut9YGlplU8fEgv19f+7zZyv5+MzE40aNc61vJVVdqAUi8UYPdobo0d74+HDBzhy5CC2bNmEjz+uju7de0EsFgMAsrL++75ILlRd/2ViYoJp03wxbZov7t69g59++gEhIctgY1MPzZo1/6BtFgaveisjBg/+DAcOHMXHH1fHnTu30b17B+zdu1ttmeDgpXxuHBGA5cuX5Zq47evrD3//uXleDVfcMjMzoVAo1I7MvHmThnPnotWWc3RsjcePH8HKyhoNGjTM9V9xMTAwhLOzK/r3H4gnTx4XOohookqVKqrL4XO871J64N9ApKf3b5+ePn2C69evqi2X87pMpl5306YO+P3335Cc/O8v3n/+uYe7d++gadMPmzs1ZMjn+PvvWLWrA3MoFIoSmTxsb98Yenp6OHXqpNp4VFQkzM0tVKc/81+/Ef7443fV1WYA/r8vSe9ZK3+1a9dBlSpV8fjxozzflzlB6V01atRUTS6/f/8eAMDaOvuCg3v34lXL3bsXX+Ap2/z+vd9Vr94nqmenvrv9ksAjSmWIo2NrREaehbf3KJw9exoTJozBr79ewqJFQTAwMFBdEg2o/8X87l/WRBXBfy+SyJHzec58oZJiYmICe/uG+PbbbTAzM4NIpIdvv90GY2MTvH7971/+3bv3woED+zB5sjc+++x/qFmzFlJTU3H79s3/n1Q9+YNruHDhHA4fPgB39/aoWrUaXr1KwJ49u9GkSTMYGBgUx26qad++Ew4fPoCVK4Ph5tYeMTHXcPr0yfeuk/MLOTR0LRQKBdLT3yAsbKPaURUAqFOnDgBg376f4ObWHoaGhqhX7xMMHjwUR44cwvTpkzF8+CjIZBn45psNqFq1Gnr27JPHVyzYp5964OrVP7Fs2WJcu3YVbm7tYGRkhPv37+HAgb2oVu1juLq6FrwhDZiZmWHgwCH4/vsdEIvFaNSoCS5ePI8TJyLg4+NX4O0sBg8eiv37f8KMGVPxv/95ISUlBWFhG9Xmw2lCIBBg8mQfLFw4F2/fpsPZ2RVGRkZ4+vQJLl48h3HjJqFWrdqYPdsXdnb2qF/fDkZGRjh/PhopKcmq+0M1atQYVapUxZo1X0Eun4Lk5BR8++32AuvK7997woRRcHPrABubehCJhIiIOAJ9ff0SPZoEMCiVOVZWVti9ez+WL1+Kr75ajq1bN6NZs+YYOnSY2lU+gHYuiSbSBbNmzUVWliLP10rr+2D+/EAsX74UgYELIJGYwsPDE+npb7Br17eqZcRiMb7+egO2bNmEHTu2ICHhJUxNzWBra4dPPx30nq0XrEaNGhAKBdi0aT1ev06ERGKK1q3bwNt7UlF3LU9t2rTFxIlTsWfPjzh69DDatHHBjBmz8cUX+Z/CEovFCAwMxldfSREQMAtVqlSFl9co/PHHZfz9d6xqOVvbBhg1ahwOHz6A77/fgSpVqmLPnkOoWrUa1q7dhHXrVmHRonkQCkVo1ao1pkyZrnZrAE0IBAIsWBCIo0edcejQzzh58jgyM2WoVu0juLq2g6fn5x+03YJMmjQNlStXxqFDP2P79jBUq/YxZsyYjf79Bxa4rpWVFVas+BqrVi1HQMAsVK9eA9On+2PTpvUfXE/Hjp1RubIJtm/forqwoFq1j+Dk1BYWFtlzp5o0aYaoqEjs2vUt5HI5atasjS+/XIxWrbIn/uvp6WHp0hUICQnCnDn+qFGjBqZMmY61a1e992vn9+/dpEkzHDt2BI8fP4ZQKICNzSeQSleqTXQvCQLlf0+a0wdJTEzL9wdzSYmMPIYDB/Zj9er1alca5ISjnAmsuhSS9PSEMDc31kq/yqKK1q/MTBkSEp7A0vIj6OuLP3g7enrCCtGv4sJ+aYb90pw2elbQzxMLC+NCPcKHQamY6MIvsrS0NHz//Q6MGjUOtWtXVV3t8/DhS63W9a6K9ou/qCpavxiUtIP90gz7pbmyHJQ4mbscmTnTB3Pn+sPZuUWuS6KJqHyRy+XIysrK9z8iKh6co1SOdOjQCT//vBf37sXDxKQydu3ah7NnT5faJdFEVHqGDOmPp0+f5Pv6uXP5P1+NiAqPQakcuX//HjIzM2FhYYlXrxLQv38PzJ+/GDNnzmFYIipnpNKVRXqmFhEVDoNSOZJzSbS390T4+EzBgQP7EBAwG337foovvphR4pdEE1Hped/dtYmo+HAydzHRtcm2SqUSYWEbMX/+XJiamuHkybOqhzJqU0WbnFxUFa1fnMytHeyXZtgvzZXlydw8olROCQQCjBkzHg4O2RO7dSEkERERlTW86q2cc3RsjbZt/72L7KFDB+Dn54O3b99qsSoiIqKygUeUKpCkpNeYPn0KkpJe48qVPxAWtgO1av33wZFERESUg0eUKhBTUzNs3LgFFhYWuHr1T3Tu7IYTJyK0XRYREZHOYlCqYDp27IzIyLNo2dIRr1+/xuefD8bSpYt4RRwREVEeGJQqoBo1auLAgQiMHj0OALBq1QoMHtwfMhnvyUJUXMLCNsLV1THXf8OGDQYAuLo64vvvd6qWDw8/hOPHcx/hzW+8KGbP9sXkyeOKdZul5fbtmwgL25hrnmV4+CG4umb/AUhUnDhHqYISi8UIClqB1q3bwMdnCho2bASx+MMvxyai3AwMDLB6dajamKGhIQAgNHQrqlX7SDUeHn4IlSpVQteu3dWWz2+8orp9+xa2bv0GAwcOUfUSAJydXREauhUmJiZarI7KIwalCu7TTz3QrJkDatb8d1J3SkoyTEwqQyAQaLEyorJPKBSiceMmeb6W3zh9GHNzc5ibm2u7DCqHGJQINjb/3uE3MzMTQ4cOgpWVNVavXgeJxFSLlRGVX66ujpg4cRqGDh2GyZPH4cqVP1TjADBy5Fj8+efveY6PHu0NALhw4Ry2bv0Gd+/eQaVKRmjfvhMmTfoCRkZGqq9z7148VqwIQmxsDKysrDFy5NhC1xgTcw2bNq1HbGwMRCIRnJ1dMW2aL8zNLVTLvHz5AsuXL8Xly7+icmUJBg3yxMuXL3H27Gns2XMIQPZpyF27vsWJE2fVtt+9e3sMGvSZ2v7s3v097ty5DZlMhtq162D0aG+0adMWQPbRtaVLFwIAevfuDACoVu0j7NlzSPXa4cORMDMzAwAkJydh7dpVOH8+Gunpb2Fra4fx4yfDwaGFqobJk8ehUqVK6NGjNzZtWo+XL1/A3r4R/P3noXr1GoXuFZVfDEqk5o8/fscff1xGZmYmYmNjEBa2k3/5kk5IS0vL9zWRSKR2GiYtLf87mQuFQrUg8b7t/nfZD5GVlZWr1v8erfX1nYXFiwNgYGCISZO+AABUqVIFHTt2yXMcAE6disT8+XPQs2cfjB7tjYSElwgNXYuUlGQsXBgEAMjIyMD06ZNhaGiIefMWAQDCwkKRlpaGGjVqvrfumJhrmDLFG23auGDhwiC8fZuOb77ZgFmzfLFx41bVcrNm+eLFi2eYMWM2TExM8O232/H8+TOIRCKNe/XkySO4uLjjs8+GQSgU4NKlC/Dzm4bVqzegRQtHODu7wstrNLZvD0NIyBoYG5tALNbPc1tyuRy+vlPx5MkjTJgwBebmltizZxd8fCZhw4YtaNDAXrXs7du3kJi4E+PHT4FCIceaNSuxaFGA2n5SxcWgRGqcnNrg0KFjGDPGC/HxcejZsxOCg1fC0/NzbZdGFVzduh/l+1rnzl3x/fd7VJ/b2dXFmzdv8ly2bVtX/PxzuOpzR8fGSEhIyHNZB4fmOH78zAdWDKSnp6N9+zZqYwEBi9CtW0+1sbp1bVCpkjEqVaqU6w+TvMaVSiXWrVuNjh27YNasANW4paUV/PymwctrDGxs6uHo0UN4+fIFvvtuD2rWrAUAsLW1w9ChAwsMSqGha9GggT2WLl2uCnY2Np9g+PAhuHjxHJydXXHp0gX8/XcsVq/egJYtWwEAmjd3xIABvSCRSDTsFjBw4BDVxwqFAs2bOyI+Pg4HD+5HixaOMDc3Vx3lsbOzVx05ysvFi+dw48ZfCAlZAycnZwCAk5Mzhgzpj507tyAwcLlq2dTUFGzZ8p3q1F16ejqWLl2I58+foUqVqhrvB5UvDEqUS4sWjoiMjMakSeNw8uQJTJ06Ab/+egmBgcFF/uuaqCIxMDDAunXfqI19/HH1Im/3wYP7ePr0CaZO9VU7YtW8eQsIhULcvHkDNjb1EBv7F+rWracKSUD2Va+ffFL/vdt/+/Ytrl+/ikmTpqndOqRmzVqoUqUqbtyIhbOzK2JjY2BiYqIKSQBgYmICR8fWuHXrb4336/nzZ9i0aT0uX/4VCQkvkfMoUjs7+wLWzO3q1SswNjZWhSQA0NPTQ7t2HXDixDG1ZT/5xFZtflOdOnX/v57nDErEoER5s7CwxHff/YRVq1ZAKg3Et99ux5s3aQgN3aLt0qiCio9/ku9r/z3Nc/Nm/HtPvb3r8uWYfLf732U1JRQK0aBBwyJtIy85l8DPmTMjz9efPXsKAHj58mWeE5zNzS2RkZH/Y4xSUpIhl8vx9ddf4euvv8r1+vPnzwAACQkvYWaWe/sWFha5xgqiUCgwa9Z0pKamYswYb1SvXhNGRkbYvDlUtT+aSElJVptLlcPc3BLJyUlqY5UrV1b7XF8/+3SeTJah8del8odBifIlFAoxffpMtGzZCjNmTIOv7yxtl0QVmLGxsUbLFvZJ5ZpsV1fkXGTh4zMTjRo1zvW6lZX1///fCjdv5j6yk5iYgEqV8t/vnKtehw0bCXf39rleNzU1A5B9qu/168Rcr7969Urtc7HYINdcraysLKSnp6s+f/jwAW7duomgoBVwc/v3a2ZkfFhYkUgkSEx8lWs8MTGBF6mQRnjDSSpQu3YdcPHiH6hf31Y1Fh19mjeoJCpG+vr6yMjI/T2V13jt2nVQpUpVPH78CA0aNMz1X05QsrdvhPj4u3j48IFq3YcPH+DOndvvrcXIyAiNGzfB/fvxeW7/o48+Vm0/NTUVv//+m2rd1NRUXL78q9r2qlSpgszMTDx69FA19vvvv6md1ssJRHp6/07Ofvr0Ca5fv6q2rZzXCzra07SpA9LS0vDrr5dUY1lZWYiOPo2mTZu9d12id/GIEhWKnt6/b5ULF85h8OD+aN68Jb75ZluBk0KJqGC1a9dFRMRhnDsXDSsrK1hZWcPKyjrf8cmTfbBw4Vy8fZsOZ2dXGBkZ4enTJ7h48RzGjZuEWrVqo2fP3ti+PQwzZ36BMWMmAMi+6s3CwrLAeiZOnIZp0ybgyy9no1OnrqhcuTJevHiO3377BT179kGLFo5o06YtbG0bYNGieRg/fgoqV66MnTu35TpK16ZNWxgZGUEqXYLPP/fCixfP8NNPuyAWG7yz/9nhLzR0LRQKBdLT3yAsbCOsrauobatOnToAgH37foKbW3sYGhqiXr1P8F/Ozq6wt2+ERYsCMH78ZFhYWGLPnh+RkPASw4aN0vSfhyownTuidPfuXYwcORIODg5wcXFBcHBwoY5cpKSkICAgAE5OTmjWrBmGDRuGGzdu5Fru1q1b8Pb2Rps2beDo6IjPP/8cly5dymOLlJ/09DeoXFmC33//DZ06ueLkyePaLomozPv88+Fo0qQZliyZjzFjhuPAgX3vHe/YsTNWrFiN+/fvYeHCuZg1azp27foW1ap9rApCBgaG+OqrtTA3t8DixQHYsGENhg4dDnv7gudNNWnSDOvXb0Z6+hsEBS2En980bN26GYaGhqo/jgQCAZYtC4GdnT2WLw/C8uVBcHV1R/v2ndS2ZWpqhiVLgpGY+AqzZ8/AoUMHMG/eQrVL+8ViMQIDgyEW6yMgYBY2b96I4cNHqd3zCABsbRtg1KhxOH78KCZMGAV/f5886xeJRFixYjXatnXF+vVfY968mXjzJg1ffbVW7dYARAURKHMuK9ABSUlJ6NWrF+rUqQNvb288e/YMy5YtQ9++ffHll1++d92xY8ciJiYGvr6+sLKywrZt2xAbG4sDBw7go4+yLyt+9eoVevfujZo1a2LcuHHQ19fHzp07cenSJezZswd2dnYfXHtiYv73bSmP7t+/h7FjvXDlyp8AgC++mIGZM+eoHXnKi56eEObmxhWuXx+qovUrM1OGhIQnsLT8CPr6H/5IHT09YYXoV3Ep7n6tXh2idsPJ8obvL81po2cF/TyxsDCGSFTw8SKdOqK0a9cupKWlYe3atXBzc4OHhwf8/Pywa9cuPHv2LN/1rly5gujoaAQGBsLDwwPt27fHhg0boKenh7CwMNVyFy9eREJCAkJCQtCpUye4u7tjzZo1EAgEiIyMLI1dLDdq166DQ4eOY9So7Lv8rlq1Ah4efT/o6hQiIiJdpVNBKTo6Gs7Ozmo3EevRowcUCgXOnz+f73qxsbEQCARwcXFRjRkZGcHR0RGnTp1SjWVmZgJQvxTUwMAA+vr60KEDa2WGgYEBli0LwaZNW2FsbIILF84V+1POiYiItEmnJnPHxcVh4MCBamMSiQTW1taIi4vLdz2ZTAahUJjrXir6+vp49OgR3r59C0NDQ3To0AFWVlZYtmwZfHx8oKenhy1btkAgEKBfv35Fqr0wh+/KKw+PQWjWrBl27/4BI0aMfO/DdHP6VJH7pYmK1i+FougPYs55+wkEAP/+KVhJ9GvaNF9Mm+ZbPBvTMXx/aU7bPROJBNDT+/CfoToVlJKTk/O87b2pqSmSkpLyWCNb7dq1IZfLERsbi6ZNmwLIvnlZTEwMlEolkpOTYWhoCFNTU3z33Xfw9vaGm5sbAMDMzAzffPMNatYs2pVbEknFvmN169bN0bp1c9Xnr1+/hp+fH5YuXQpra+tcy1f0fmmqovTr7VsRXr4UFvkHG1BxwmVxYb80w35prrR7plAIIBQKYWpaSe1ZkJrSqaD0oVxcXFCrVi3Mnz8fUqkUlpaW2LRpEx48yL53SM4RjoSEBEyePBm1atXCnDlzIBKJsHv3bkyYMAHfffcd6tWr98E1JCenQy7n5L4c48Z5Y8+e3ThyJBxhYdvRpk32YwREIiEkEiP2q5AqWr9kMhkUCgWyshQQCj9sfwWC7L7J5Qr+xV8I7Jdm2C/NaatnWVkKKBQKJCWlIz1dnut1icSoUOFNp4KSRCJBSkpKrvGkpCSYmuZ/J1WxWIyVK1fC19cXffr0AQDY2trCy8sLO3fuVM152rx5M5KSkrBv3z6Ixdkz4J2dndGrVy+sX78eISEhH1y7XK7gVRDvmDJlOq5evYLbt2+hT5/umDdvISZOnKJ6nf3STMXpV/YfNTJZhto9djSR84OYv8QKh/3SDPulOW317N+bkhbtijudCko2Nja55iKlpKTgxYsXsLGxee+6jRs3RkREBO7fvw+lUok6depg0aJFaNSokeq5PXfu3IGNjY0qJAHZ99qws7PDP//8U/w7VIHZ2zfEsWOnMWPGVOzbtwcLF87DL79cwPr1G2FuXvYeGUGlQygUwcjIBKmp2Y/FEIsN3jvnLT8KhQByOX+TFRb7pRn2S3Ol2TOlUgmZLAOpqYkwMjIp8jMbdSooubu7IzQ0VG2uUkREBIRCodoVbfkRCASqu7a+evUK4eHh8PPzU73+8ccf4+TJk8jIyICBQfZfq3K5HH///Tfs7XkDsuJmYmKCDRvC4OzsirlzZyIiIhzt27siPPwIPv64jrbLIx0lkWQ/yDQnLH0IoVAIhaIiHIErHuyXZtgvzWmjZ0ZGJqqfJ0WhkzecrFu3rtoNJ/v06aN2w0kvLy88fvwYJ06cUI1t2LABtWvXhqWlJeLj47Fx40bY2Njgm2++UaXJmJgYDBkyBG3atMHnn38OkUiEH3/8EVFRUdi5cydatWr1wbVXlBsCfqhr165g9OjhyMzMxNWrVyASGbFfhVDRbjj5LoVCAbk8q+AF/0MkEsDUtBKSkt7wr/5CYL80w35pThs9E4n0CjySVNgbTurUESVTU1Ns374dixcvxqRJk2BsbAwPDw/4+Kjfoj77B6j6xKzk5GRIpVIkJCSgSpUq6Nu3LyZOnKjWqMaNG2Pz5s1Yv349Zs+eDYVCgU8++QSbNm0qUkii9wsOXgqRSITIyGg8e/YEVlZWSExMAwBIpYEQCASYOXOOlqskXSMUCiEUan53bj09IQwNDZGeLq9w4fJDsF+aYb80V9Z7plNBCQDq1auHbdu2vXeZnTt35hrz9/eHv79/gdt3dnaGs7Pzh5ZHH0AkEkEqDQQA+PvPVo2PGDEU4eGHMXLkGG2VRkRE9F46F5So/PH1zQ6wUmkghEIBli5dDKl0KcLDDwMAfvjhWzRr1hxDhw7TZplERES5MChRqcgJS0FBSxASEgyZTIYpU3wQGxuDkydP4IsvJuHSpQtYtiwElSpV0nK1RERE2XhrUSo1vr7+EIvFkMlkEIvFCAhYiO+++wlz586HUCjErl3foUePjrh9+5a2SyUiIgLAoESlKCREqgpJMpkMISFSCIVCTJvmi717D6FKlaq4cSMW3bp1wMuXL7VdLhEREYMSlY6QECmk0kDMnj0PGRkZmD17HqTSQISESAEALi5uOHnyHFxd3TFu3HhYWVlpuWIiIiLOUaJSkBOS/P3nws9vFgDAz28WFAql6mo4X19/VK1aFT/9dEBt3X/+uQ+5XI66dd9/Z3YiIqKSwKBEJU4ul8Pff65qQneOnM/fvSeWSCRSfZyRkYHRo4cjLu4uVq1ahz59+pVOwURERP+PQYlK3PtuJvnf8PSulJQUiMVipKQkY/ToYRg9ehwWLAhUPX6GiIiopHGOEuksKysr/PxzOCZP/gIAEBa2Cb17d0V8fNz7VyQiIiomDEqk0/T19fHll4vw/fc/wdzcHFev/onOnd1x6NDP2i6NiIgqAAYlKhM6d+6GqKjzaNXKCSkpyVizZmWu5/0REREVN85RojKjevUa+PnncISESOHp+bnaxG8iIqKSwCNKVKbo6+tj1qx5qFOnrmps1aoVOHhwvxarIiKi8opHlKhM++WXS1i6dBEAYNSoc1iwIBCGhoZaroqIiMoLHlGiMq1lS0dMnTodALBlyze8Ko6IiIoVgxKVaXp6epg3bwF++GEPLCwscO3aFXTu7M5TcUREVCwYlKhc6NSpK6KizsPJyRkpKckYM8YLCxbM03ZZRERUxjEoUbnx8cfVsX//EUyb5gsAaNDAXssVERFRWcfJ3FSu6OnpYe7c+ejffyAaNWqsGk9MfAVzcwstVkZERGURjyhRufRuSHr58iXat2+LmTN98PbtWy1WRUREZQ2DEpV7UVEn8OTJY2zbFoaePTsjLu6utksiIqIygkGJyr3Bgz/Drl17YWlpiZiYa+jc2R0//7xX22UREVEZwKBEFULHjl0QFXUebdq0RWpqCsaNG8lTcUREVCAGJaowPvroY+zbdxg+PjMgEAiwbVsYli8P0nZZRESkwxiUqELR09PD7NlfYteufWjZshWmTZuu7ZKIiEiHMShRhdShQyeEh0dCIjEFACiVSuzcuY2n4oiISA2DElVYAoFA9fHWrZvh6zsVPXp0wt27t7VYFRER6RIGJaqwgoOXIiRECgCoW9cGVlZW+Ouv6+jcuR1Gjx6O4OClWq6QiIi0jUGJKiyRSASpNBAhIVJ06NAJUVHn0batK9LSUnHo0M84ceIY0tPTtV0mERFpEYMSVVi+vv7w95+rCkvVqn0EFxc31etXr/6J7t074tatm1qskoiItInPeqMKzdfXHwAglQZi5crlkMlk8PefC0fH1pg4cSxu3fobr1690nKVRESkLQKlUqnUdhHlQWJiGrKyFNouQ+fp6Qlhbm6sc/2qUcMKMpkMYrEYDx++BAA8e/YMFy6cxaefeqiWUyqVapPAS5qu9kuXsWeaYb80w35pTld7ZmFhDJGo4BNrPPVGFV5IiFQVkmQymWqCd9WqVdVC0q1bN9G5szuuX7+mrVKJiKiUMShRhRYSIoVUGgh//7l4+PCl2pyl/1qwYC6uX7+Knj07ISxsE3gwloio/GNQogrr3ZCUM1fpvxO837V27UZ069YDGRkZmD17BkaNGoakpNdaqJyIiEoLgxJVWHK5XC0k5cgJS3K5XG3cwsISO3bswuLFQdDX18eRIwfRsaMrLl/+tTTLJiKiUsTJ3MVE1yap6SpdndSnqStX/sDYsSNw//496OnpYd++w2jTpm2xf53y0q/SxJ5phv3SDPulOV3tGSdzE5UgB4cWOHnyLPr3H4CWLVvB0bG1tksiIqISwPsoEX0gicQUGzduRVpaGvT0sr+VMjIycP36VQYnIqJygkeUiIpAIBDAxMRE9fmSJfPRu3dXLF8elGuOExERlT0MSkTFRKFQIDk5GQqFAsuXB8HDoy+ePn2i7bKIiKgIGJSIiolQKMTq1euxbt0mVKpkjPPnz6JDh7aIijqh7dKIiOgD6VxQunv3LkaOHAkHBwe4uLggODgYMpmswPVSUlIQEBAAJycnNGvWDMOGDcONGzfyXPbKlSsYMWIEmjdvjhYtWmDw4MH5LkukqUGDPHHyZDQaN26KhIQEeHoOxMKFAcjMzNR2aUREpCGdCkpJSUnw8vJCZmYm1qxZAx8fH+zevRvLli0rcN3p06cjMjISfn5+WL16NUQiEby8vPDkifqpj4sXL2LYsGGoU6cO1q5di5UrV8LNzQ3p6ekltVtUAdWrVx/h4ZEYNWosAGDHjq08DUdEVAbp1FVvu3btQlpaGtauXQszMzMA2TcFXLhwIby9vVG1atU817ty5Qqio6OxYcMGdOzYEQDg5OSETp06ISwsDPPmzQMAZGVlYe7cuRg+fDj8/PxU67dr165kd4wqJENDQyxbFgJX13YQCASoWbOWtksiIiIN6dQRpejoaDg7O6tCEgD06NEDCoUC58+fz3e92NhYCAQCuLi4qMaMjIzg6OiIU6dOqcYuXLiAR48eYfjw4SVSP1Feevfui169+qg+P306CrNm+eLt27darIqIiApDp44oxcXFYeDAgWpjEokE1tbWiIuLy3c9mUwGoVAIkUikNq6vr49Hjx7h7du3MDQ0xNWrV2FmZobr169j+PDhePDgAWrWrIkJEyagf//+Raq9MHf3pH/7VFH7lZaWhsmTx+H58+f49ddL2LJlBz75pH6+y1f0fn0I9kwz7Jdm2C/NlfWe6VRQSk5OhkQiyTVuamqKpKSkfNerXbs25HI5YmNj0bRpUwDZl2rHxMRAqVQiOTkZhoaGePHiBdLT0zFnzhxMnToV9erVw+HDh+Hv7w9LS0u4ubl9cO0SidEHr1sRVdR+mZsbY9u2bRg+fDhiYq6jQwdXhIaG4n//+99716uo/SoK9kwz7Jdm2C/NldWe6VRQ+lAuLi6oVasW5s+fD6lUCktLS2zatAkPHjwAkH1TQABQKpXIyMjAjBkzVL+YnJ2dERcXh9DQ0CIFpeTkdMjluvMMG10lEgkhkRhV6H61aeOOM2cuwtt7FM6dO4thw4bh6NHjkEpXwNjYWG1Z9ktz7Jlm2C/NsF+a09WeSSRGhTrKpVNBSSKRICUlJdd4UlISTE1N811PLBZj5cqV8PX1RZ8+2XNBbG1t4eXlhZ07d6rmPOUcrWrTpo3a+s7Ozvjuu++KVLtcrtCph/3puoreL2vrqvjpp4P46qtghIRI8f33O3H58q84cuQETE3Nci1f0fv1IdgzzbBfmmG/NFdWe6ZTJwxtbGxyzUVKSUnBixcvYGNj8951GzdujIiICBw7dgwRERE4ePAg3r59i0aNGkFfXx8AUL9+/nNBMjIyir4DRBoQiUTw85uNvXsPoWrVanBwaJFnSCIiIu3RqSNK7u7uCA0NVZurFBERAaFQqHZFW34EAgHq1KkDAHj16hXCw8PVbgPg6uoKfX19XLhwAba2tqrxCxcuoFGjRsW7M0SF5OLihlOnLsDQ0FA19upVAoRCIaysLLVYGRER6VRQ8vT0xM6dOzFp0iR4e3vj2bNnCA4Ohqenp9o9lLy8vPD48WOcOPHvoyE2bNiA2rVrw9LSEvHx8di4cSMaN26MAQMGqJaxsrLCsGHDsHr1aggEAtSrVw9HjhzBlStXsHnz5lLdV6J3WVlZqT5WKpWYMmU8btyIxTffbEX37p20WBkRUcWmU0HJ1NQU27dvx+LFizFp0iQYGxvDw8MDPj4+asspFIpcT2ZPTk6GVCpFQkICqlSpgr59+2LixIkQCtXPLvr6+qJSpUoICwvDq1evUK9ePaxbtw6urq4lvn9EhTF//lz89tuveP06Eb17d/v/G65OASBASIgUcrkcM2fO0XaZREQVgkCpVCq1XUR5kJiYViYnqZU2PT0hzM2N2a/3CAmRQioNRMOGjREbGwMAcHNzR5MmDli//mv4+8+Fr6+/lqvUXXyPaYb90gz7pTld7ZmFhXHZu+qNiKAKQVJpIHr16oPTp6Nw9mw0zp6NhofHYIYkIqJSxKBEpIPeDUs5V20CwOXLv0Emk0EsFmurNCKiCkWnbg9ARP/y9fWHWCxGZmYm9PX14e09CaGhYQxJRESliEGJSEeFhEhVR48yMzNhZmaGFi0cVa9/++12/Pjj91qskIio/GNQItJBORO6Z8+eh4yMDMyePQ9SaSBCQqQAgDt3bmP27BmYMmU8Jk4ci9TU3He0JyKiomNQItIxOSHJ338u/PxmAQD8/GbB33+uKizVrWsDHx8/CIVC7NnzIzp1csPVq39quXIiovKHQYlIx8jl8jxvAeDr6w9//7mQy+UQiUSYPn0mDhyIQI0aNREfH4eePTtjw4a1UCh05/JbIqKyjvdRKia6dn8IXaWr99PQVYXp1+vXifDxmYIjRw4CALp164Ht23/IdbPVioLvMc2wX5phvzSnqz0r7H2UKuZPUqJyxMzMHFu27ERw8EoYGBigRQvHChuSiIiKG++jRFQOCAQCjBgxGm5u7qhTx0Y1/vTpE1haWqndi4mIiAqPf3YSlSP16tWHSCQCAKSnp2PIkE/Rt293/PPPfS1XRkRUNjEoEZVTN2/ewKNHj/D777+hY0dXHDy4X9slERGVOQxKROWUg0MLREWdg6NjayQnJ2HMGC/4+k7FmzdvtF0aEVGZwaBEVI7VqlUbBw4cxRdfzIBAIMDOndvQrVt73LgRq+3SiIjKBAYlonJOX18fc+Z8iZ9+OoAqVari5s2/MX/+HG2XRURUJjAoEVUQ7u7tcfr0RQwY4IGVK9dquxwiojKBQYmoArGyskJo6BZUr15DNbZy5XL88sslLVZFRKS7GJSIKrCoqBMIClqM/v17YMWKZZDL5douiYhIpzAoEVVgrVu3gYfHEMjlcgQHL8Wnn/bCw4cPtF0WEZHOYFAiqsBMTCpj/fpvsG7dJhgbm+DSpQvo0MEFhw79rO3SiIh0AoMSEWHQIE9ERZ1DixYtkZT0GqNHD8f8+XO1XRYRkdYxKBERAKBuXRscOnRcdc+lli0dtV0SEZHWMSgRkUrOPZfOnfsNfft+qhq/dy8eCoVCi5UREWkHgxIR5VK/vq3q42fPnqFnz04YOtQDz58/12JVRESlj0GJiN7r2rU/kZqaiqioSLRv74yoqBPaLomIqNQwKBHRe3Xp0h3Hjp2GvX1DvHz5Ap6eAxEQMBsZGRlqy4WESBEcvFRLVRIRlQwGJSIqkL19Q0REnEKLFtkTvDduXIeePTvjzp3bALJDklQaCJFIpM0yiYiKHYMSERWKkZERIiKiMHDgIADA9etXERq6ThWS/P3nwtfXX8tVEhEVLz1tF0BEZcuGDWGoWvUjrF//NX74YScyMzMZkoio3OIRJSLS2IIFSyAWi5GZmQmxWAwfHz9Mnz4Fly5d0HZpRETFikGJiDQWEiKFTCaDWCyGTCaDl9dQfPvtdvTv3xNSaSCysrK0XSIRUbFgUCIijbw7J+nhw5fw95+LY8fC0bhxUygUCoSESNGvXw/88899bZdKRFRkDEpEVGh5Tdz29fWHv/9cxMRcQ58+/VG5sgS//fYLOnZ0xc8/79VyxURERcOgRESFJpfL85y4nROW7OwaICrqHBwdWyM5OQnjxo3EsmVLtFQtEVHR8ao3Iiq0mTPn5Pvau+Hp4MEIrFgRhHXrvkb37j1LozQiohLBI0pEVOz09PQwa1YAfvvtGhwcWqjGr127wofrElGZwqBERCWmWrWPVB9fv34NPXt2xpAhn+LZs6darIqIqPAYlIioVNy7FweRSIQzZ06hfXtnnDgRoe2SiIgKxKBERKWiT5/+OHEiGo0aNUFCQgI+/3ww5szxw9u3b7VdGhFRvhiUiKjU2Nra4ejRk/D2nggA2Lx5I7p1a4/Y2L+0XBkRUd4YlIioVBkaGmLx4mX44Yc9sLKyxo0bsTh58oS2yyIiypPOBaW7d+9i5MiRcHBwgIuLC4KDgyGTyQpcLyUlBQEBAXByckKzZs0wbNgw3Lhx473rTJw4EXZ2dggLCyuu8omokDp16oozZy5h+nQ/TJw4RTWuVCq1WBURkTqdCkpJSUnw8vJCZmYm1qxZAx8fH+zevRvLli0rcN3p06cjMjISfn5+WL16NUQiEby8vPDkyZM8lz9z5gyuXr1a3LtARBqwtrbGrFkBEIlEAIA3b95gwIDeOH78qJYrIyLKplNBadeuXUhLS8PatWvh5uYGDw8P+Pn5YdeuXXj27Fm+6125cgXR0dEIDAyEh4cH2rdvjw0bNkBPTy/Po0UymQyBgYGYPn16Se4OEWlo48Z1OH/+LP73vyHw95+ON2/eFGq94OClCAmR5vlaSIgUwcFLi7NMIqpAdCooRUdHw9nZGWZmZqqxHj16QKFQ4Pz58/muFxsbC4FAABcXF9WYkZERHB0dcerUqVzLh4WFQSKRYMCAAcVaPxEVzYQJU+DtPQkAsHXrZnTt2g4xMdcLXE8kEkEqDcwVlnKeTZdzxIqISFM6FZTi4uJgY2OjNiaRSGBtbY24uLh815PJZBAKhbl+GOrr6+PRo0dqlx8/fvwYmzZtwrx58yAQCIp3B4ioSLInegdh1659qFKlKm7duonu3TsgNHTte+/onfOsOak0EMuXZ5+qX758Wa4H+BIRaUqnnvWWnJwMiUSSa9zU1BRJSUn5rle7dm3I5XLExsaiadOmAACFQoGYmBgolUokJyfD0NAQABAUFIQuXbrAwcGhWGsXiXQqc+qsnD6xX4VTUfvVtWtXnDt3CdOmTcbRo0fw5Zdz8Pr1K8ybtyDfdfz9Z0MoFCAoaAlCQrIvApk9ex78/GaVXuFlUEV9j30o9ktzZb1nOhWUPpSLiwtq1aqF+fPnQyqVwtLSEps2bcKDBw8AQHXk6Ny5czh37hwiIor/jsASiVGxb7M8Y780UxH7ZW5ujCNHDmHTpk1YsmQJfHymwdzc+L3rLF26WBWSxGIxli5dXErVln0V8T1WFOyX5spqz3QqKEkkEqSkpOQaT0pKgqmpab7ricVirFy5Er6+vujTpw8AwNbWFl5eXti5c6dqztOSJUswfPhwGBkZITk5WbV+RkZGvkezCis5OR1yOR/2WRCRSAiJxIj9KiT2Cxg8+H/o128QDAwMkJiYBgDYu3c3unfvBWNj9eC0fPkyVUiSyWSYMyeAR5QKwPeYZtgvzelqzyQSo0Id5dKpoGRjY5NrLlJKSgpevHiRa+7SfzVu3BgRERG4f/8+lEol6tSpg0WLFqFRo0bQ19cHAMTHxyM0NBShoaFq665evRqrV6/GtWvXYGBg8EG1y+UKZGXpzhtA17Ffmqno/RKJ9FX7HxERjrFjR+GTT+ojNDQMTZs6APh34vbs2fOwdOlizJkTgKCgJVAolJyjVAgV/T2mKfZLc2W1ZzoVlNzd3REaGqp2dCciIgJCoVDtirb8CAQC1KlTBwDw6tUrhIeHw8/PT/X6jh07cq0zfPhweHp6omfPnqpARUS6y8TEBNWqfYQ7d26jR49OmD37S7x9m47g4KXw95+rOoLk5zcLCoUSUmkgADAsEdEH0amg5OnpiZ07d2LSpEnw9vbGs2fPEBwcDE9PT1StWlW1nJeXFx4/fowTJ/597MGGDRtQu3ZtWFpaIj4+Hhs3bkTjxo3VbgHg5OSU59etVatWvq8RkW5xdXXH6dMXMH36VISHH8KiRQGoVas2Jk6ckisM5Xwul8u1USoRlQM6FZRMTU2xfft2LF68GJMmTYKxsTE8PDzg4+OjtpxCocj1gy85ORlSqRQJCQmoUqUK+vbti4kTJ0IoLJuz7IkofxYWlti69Vt8990OzJvnj3/+uY/vv9+JNm1c0Lt3b7VleSSJiIpCoOSDlYpFYmJamTz3Wtr09IQwNzdmvwqJ/SrY3bu3MX78GFy9+ie2bv0O/fr1Y880wPeYZtgvzelqzywsjMveZG4iIk3Vq1cfR46cwPHjEejVq49qPC0tDQYGZfNyZCLSHTwvRURlnlgsRu/efVWfP3nyBK1aNcPq1SGcn0RERcKgRETlzo4dO/D06VMEBi7EwIF98OjRQ22XRERlFIMSEZU7M2fOxNq1oahUyRgXLpxD+/ZtcfDgfm2XRURlEIMSEZU7AoEAQ4f+D1FR59CiRUskJb3GmDFemDp1AlJTc9/9n4goPwxKRFRu2djUw6FDxzF9uh+EQiF27foOX3+9UttlEVEZUuSr3pKTk3Hy5Encvn0bb968QaVKlVC/fn106tSpSM9OIyIqDvr6+pg1KwDt23fCV18FY9o0X22XRERlSJGOKF28eBFdunTB/v37IZPJYGpqCplMhv3796Nr1664dOlScdVJRFQkbdq0xe7dP6sepKtQKDB//lzEx8cVsCYRVWRFOqK0aNEiBAUFoWPHjrleO3XqFBYsWICIiIiifAkiohKxeXMoNmxYgx07tmLp0mB4en4OgUCg7bKISMcU6YjS06dP4erqmudrbdu2xdOnT4uyeSKiEtOjR284O7sgLS0V06ZNxKhRw/DqVYK2yyIiHVOkoNS6dWssWrQIz58/Vxt//vw5lixZgtatWxepOCKiklKzZi3s23cY8+YthL6+Po4cOYh27Zxx6tRJbZdGRDqkSEEpKCgIKSkp6NixI5ycnNCpUyfV/1NSUrBs2bLiqpOIqNiJRCJMneqDo0dPon59Wzx79hRDhnyKtWtXa7s0ItIRRZqjZGFhgdWrV+PNmze4f/8+0tLSYGxsjNq1a6NSpUrFVSMRUYlq2tQBJ05EY/HiL7Fz5za4u7fTdklEpCM0DkpnzpzBoUOH8PTpUxgZGaFBgwbo2rUrmjRpUhL1ERGVikqVKiEoaAUmTpyKmjVrqcb/+OMyHBxaQCjkbeeIKiKNvvO3bduG8ePHIzIyEm/evEFCQgJ27NiBwYMHY9y4cXjx4kVJ1UlEVCreDUnXr19Fnz7d+Lw4ogpMo6C0Y8cO2NvbIyoqCvv27cO+ffvw22+/ISAgALdv38agQYPw7NmzkqqViKhU3bt3D/r6Ypw/fxbt2jlj//492i6JiEqZRkEpISEBHh4esLCwUI2JxWIMHToUe/fuhUAgQHBwcLEXSUSkDX369ENU1Dm0bOmI5OQkeHuPwoQJY5CU9FrbpRFRKdEoKNWtWxcJCXnfZ8TCwgKfffYZoqOji6UwIiJdkPO8uBkzZkEkEmHv3t1o374tLlw4p+3SiKgUaBSUxowZg2+//Rb37t3L83UjIyPe2ZaIyh09PT3MnDkHBw9GoE6dunj06CGuXPlT22URUSnQKCht2bIFIpEIgwYNwjfffKM2H+mff/7Bd999h+7duxd7kUREuqBVKydERZ3HggWBGD9+kmpcLpdrsSoiKkkaBaUqVarAyMgIqampCAkJQfv27dGmTRu4uLigW7duMDQ0xODBg5GZmVlS9RIRaZWJiQkmTpyiul1AWloaunRph7CwjVAqlVqujoiKm0b3UQoNDQWQ/YPhzp07uHXrluq/27dv4++//8agQYMgEolQo0YN1KtXD5988gl8fHxKpHgiIm3btetbxMRcw+zZfjhx4hhWr16PqlWrabssIiomAmUx/gmUkJCQKzzduXMHf/zxR3F9CZ2VmJiGrCyFtsvQeXp6QpibG7NfhcR+aa60e6ZUKrFlyyYsXBiAt2/fwsLCAiEha9CrV58S/9rFge8xzbBfmtPVnllYGEMkKvjEWrEGpYpM194AukpXv2F0FfulOW317ObNvzFhwhjExFwDAHz++XAsXrwMJiYmpVbDh+B7TDPsl+Z0tWeFDUq8Jz8RUTGws2uAiIgoTJniA4FAgO++24GAgFnaLouIiohBiYiomIjFYgQELMT+/UfQpEkz+PvP1XZJRFREDEpERMWsbVtXREZGo1q1j1Rj69Z9jbi4u1qsiog+BIMSEVEJePfmu0ePHsHChfPQsaMrdu7cxtsIEJUhDEpERCWsSZOmcHFxw5s3afD1nYphw4bg+fPn2i6LiAqBQYmIqITVqFETe/cewvz5SyAWi3H8eATatXNCePhhbZdGRAVgUCIiKgVCoRCTJk3F8eNn0LBhYyQkJGDEiKFYsGCetksjovdgUCIiKkUNGzbCsWOnMGWKD4RCIdq0aavtkojoPRiUiIhKmYGBAQICFuLChcvo3r2navz69WvIyMjQYmVE9F8MSkREWmJj84nq4ydPHmPgwN7o3r0jbtyI1WJVRPQuBiUiIh1w//59iEQi/PXXdXTp4o7169dAodCdxz0QVVQMSkREOqBNG2ecOfMLunbtDplMhgUL5mLAgN548OAfbZdGVKExKBER6YgqVapg584fERLyNSpVMsaFC+fQvn1b/Pjj99oujajCYlAiItIhAoEAw4aNQFTUOTg6tkZKSjL++OOytssiqrD0tF0AERHlZmNTDwcPRmDbts347LNhqnGZTAaxWKzFyogqFh5RIiLSUXp6ehgzZjyMjY0BAAqFAp6eA+Dn54O0tDQtV0dUMTAoERGVERcvnse5c9HYvj0MnTq54vfff9N2SUTlHoMSEVEZ4eLihj17DuLjj6sjLu4uevfuCqk0EJmZmdoujajc0rmgdPfuXYwcORIODg5wcXFBcHAwZDJZgeulpKQgICAATk5OaNasGYYNG4YbN26oLXPt2jXMnj0bXbp0QbNmzdC1a1eEhITgzZs3JbU7RETFyt29Pc6cuYiBAwdDLpcjJESKXr064/btW9oujahc0qmglJSUBC8vL2RmZmLNmjXw8fHB7t27sWzZsgLXnT59OiIjI+Hn54fVq1dDJBLBy8sLT548US1z9OhR3L9/H2PGjMGmTZvg5eWF3bt3Y/z48SW5W0RExcrU1AwbNmzGpk1bYWZmhitX/sSkSWOhVCq1XRpRuaNTV73t2rULaWlpWLt2LczMzAAAcrkcCxcuhLe3N6pWrZrneleuXEF0dDQ2bNiAjh07AgCcnJzQqVMnhIWFYd687Kdzjx07FhYWFqr1nJycIJFIMGPGDMTExKBx48Ylu4NERMWof/+BcHJyxowZ0zBr1jwIBAJtl0RU7ujUEaXo6Gg4OzurQhIA9OjRAwqFAufPn893vdjYWAgEAri4uKjGjIyM4OjoiFOnTqnG3g1JORo2bAgAeP78eTHsARFR6froo4/x3Xc/oUmTZqqxb77ZgJ9/3qvFqojKD50KSnFxcbCxsVEbk0gksLa2RlxcXL7ryWQyCIVCiEQitXF9fX08evQIb9++zXfd33//HQByfV0iorIoNvYvzJ8/F+PGjcT48aPw+nWitksiKtN06tRbcnIyJBJJrnFTU1MkJSXlu17t2rUhl8sRGxuLpk2bAsi+30hMTAyUSiWSk5NhaGiYa71Xr15hzZo16NSpE+rUqVOk2kUincqcOiunT+xX4bBfmqvoPbO3bwAfnxn46qvl2LdvDy5evIB16zaiffsOeS5f0fulKfZLc2W9ZzoVlD6Ui4sLatWqhfnz50MqlcLS0hKbNm3CgwcPACDP8/aZmZmYPn06AGDBggVFrkEiMSryNioS9ksz7JfmKnLPgoODMHBgfwwbNgy3b9/GgAF9MHXqVCxbtgxGRkZYsGABRCIRAgICVOvk9Gvx4sWQy+XF8nOxPKvI768PVVZ7plNBSSKRICUlJdd4UlISTE1N811PLBZj5cqV8PX1RZ8+fQAAtra28PLyws6dO9XmPAGAUqnEnDlzcO3aNXz//feoUqVKkWtPTk6HXK4o8nbKO5FICInEiP0qJPZLc+xZNlvbxoiKOof58+diy5bN+Prrr3Hq1GlERZ2FTCZHUNBCpKfLMGvWHFW/li1biqCgJZg9ex4SE3nn77zw/aU5Xe2ZRGJUqKNcOhWUbGxscs1FSklJwYsXLwqcQ9S4cWNERETg/v37UCqVqFOnDhYtWoRGjRpBX19fbVmpVIqjR4/im2++QYMGDYqldrlcgaws3XkD6Dr2SzPsl+bYM8DAwAjLln2Frl17YNq0SRg8+DMolQL4+MyEQqFEUNASAMDSpYtVIcnffy58fGZW+N4VhO8vzZXVnulUUHJ3d0doaKjaXKWIiAgIhUK1K9ryIxAIVHONXr16hfDwcPj5+akts2nTJmzbtg0rVqyAs7Nzse8DEZGu6dixC86d+xWVK/87B7RLl2548eIFgoKWICQk+8a+/v5z4evrr8VKiXSPTgUlT09P7Ny5E5MmTYK3tzeePXuG4OBgeHp6qt1DycvLC48fP8aJEydUYxs2bEDt2rVhaWmJ+Ph4bNy4EY0bN8aAAQNUyxw6dAghISHo27cvatSogStXrqheq1WrVp63DyAiKg9MTc1UH6elpWHcuJF49OghRCIRZDIZxGIxQxJRHnQqKJmammL79u1YvHgxJk2aBGNjY3h4eMDHx0dtOYVCAblcrjaWnJwMqVSKhIQEVKlSBX379sXEiRMhFP57/jHnXkwHDx7EwYMH1dYPCgpSC1VEROXV27dvYWNTD3FxdwFkH42XyWQICZEyLBH9h0DJe94Xi8TEtDJ57rW06ekJYW5uzH4VEvulOfascFasWIbg4KUQi8WqI0oymQwzZ87BjBmztF2ezuL7S3O62jMLC+NCTeYumzc1ICKiDxYSIkVw8FL4+8/FpUu/w83NTfXw8eDgpQgKWqzlCol0B4MSEVEFI5fLVRO369Spi1OnTmHhwkCIxWLY2NRTm7JAVNHp1BwlIiIqeTNnzlH7XCQSYcqUaejQoTPMzMxQrdpHAICUlGRkZWXB3JwXulDFxT8biIgIANCggb0qJAHAvHmz4O7eBlFRJ96zFlH5xqBERES5pKQk4/LlX/Hs2VN4eg7EjBlfIDU1VdtlEZU6BiUiIsqlcmUJIiPPYty4CQCAHTu2oEOHtrh06aKWKyMqXQxKRESUJyMjIyxZIsXevYdQo0ZN3L9/D/36dcfChQF4+/attssjKhUMSkRE9F5ubu1w+vQFeHp+DqVSiR9//J6n4ajC4FVvRERUIInEFF9/vQE9e/aBvr4erKysVK/J5XKIRCItVkdUcnhEiYiICq17957o1Kmr6vP9+/egd+8uuHPntharIio5DEpERPRBsrKyEBi4CL//fhmdOrli8+ZQKBS684gKouLAoERERB9ET08PBw6Ew929A9LT0zFnzkwMGtQfjx491HZpRMWGQYmIiD5Y9eo1sHv3fgQFrYCRkRHOnj0Nd/c2+PHH78FnrlN5wKBERERFIhQKMXr0OERFnUPLlq2QkpKMKVPGIybmmrZLIyoyXvVGRETFol69+jh06BjWrVuNly9fokmTZtouiajIeESJiIiKjZ6eHqZN88XixUGqsfv378HHZzJev07UYmVEH4ZBiYiIStT06VPx3Xc74ObmhMjIY9ouh0gjDEpERFSi5swJwCef1MezZ08xdOgg+PhMRkpKsrbLIioUBiUiIipRLVu2wsmT5zB+/GQIBAJ8990OtGvnjOjo09oujahADEpERFTijIyMsGjRUhw4cBS1a9fBw4cP4OHRFxER4doujei9GJSIiKjUtGnTFqdOXcDIkWNgb98IHTp00nZJRO/FoERERKXKxMQEUulXOHr0JAwMDABkPw4lNHQt0tPTtVwdkToGJSIi0opKlSqpPl6zZiW+/HIOOnd2wx9/XNZiVUTqGJSIiEjrmjRpiqpVq+H27Vvo2bMzli5dhIyMDG2XRcSgRERE2te5czdER1/CwIGDoVAosGrVCnTt2h7Xr/MxKKRdDEpERKQTzM0tsGHDZmzZ8i2srKxw48Zf6NatPXbt+k7bpVEFxqBEREQ6pXfvvoiO/hW9e/eDSCRCixaO2i6JKjAGJSIi0jlWVlYIC9uB06cvwNbWTjV+4cI5yOVyLVZGFQ2DEhER6SSBQIB69eqrPv/tt18wYEBv9OnTDXfv3tZiZVSRMCgREVGZ8OzZM1SqZIzLl39Fx46u+OabDVAoFNoui8o5BiUiIioTsucuXYK7ewekp6dj7lx/DBzYB/fv39N2aVSOMSgREVGZUaNGTfz008+QSr9CpUrGOH/+LNq3b8sr46jEMCgREVGZIhAIMHLkGJw+fQHOzi5IS0tFZmamtsuickpP2wUQERF9iDp16mL//iM4cuQgevfupxp/9uwpqlSpCoFAoMXqqLzgESUiIiqzhEIh+vTprwpFKSnJ6N69I4YP98SzZ8+0XB2VBwxKRERUbvz66yU8f/4Mx44dhbt7a+zduxtKpVLbZVEZxqBERETlRqdOXXHiRDSaNGmGxMRETJgwBiNGfI7nz59ruzQqoxiUiIioXGnYsBEiIqIwc+Yc6Onp4ejRw3Bza4V9+37i0SXSGIMSERGVO/r6+pgxYxaOHz+Dxo2bIjExEeHhhznBmzTGq96IiKjcaty4CY4dO4X167/G0KHDVeMZGRkQi8UMTlQgHlEiIqJyTV9fH9Om+cLa2lo1NnHiWIwePRwvXrzQYmVUFjAoERFRhXLr1k0cPXoYhw8fgJtbKxw4sE/bJZEO07mgdPfuXYwcORIODg5wcXFBcHAwZDJZgeulpKQgICAATk5OaNasGYYNG4YbN27kudycOXPQunVrNG/eHFOnTuXVEEREFYitrR2OHTuFhg0b49WrVxg7dgSPLlG+dCooJSUlwcvLC5mZmVizZg18fHywe/duLFu2rMB1p0+fjsjISPj5+WH16tUQiUTw8vLCkydP1Jb74osvcP78eSxYsAArVqxAfHw8xo4di6ysrJLaLSIi0jFNmjTD8eOn4evrDz09PRw69DPc3Vvj4MH92i6NdIxOBaVdu3YhLS0Na9euhZubGzw8PODn54ddu3a99w6rV65cQXR0NAIDA+Hh4YH27dtjw4YN0NPTQ1hYmGq5P//8E+fOnUNgYCB69uyJTp06YfXq1bh58yaOHz9eGrtIREQ6QiwWw99/Lo4dOwV7+0ZISEjA/Plz8ebNG22XRjpEp4JSdHQ0nJ2dYWZmphrr0aMHFAoFzp8/n+96sbGxEAgEcHFxUY0ZGRnB0dERp06dUtu+RCJRW87Gxgb29vaIjo4u3p0hIqIyoUmTZjhx4gymT5+JlSvXolKlSgDAey4RAB27PUBcXBwGDhyoNiaRSGBtbY24uLh815PJZBAKhRCJRGrj+vr6ePToEd6+fQtDQ0PExcWhbt26uS4HtbGxee/2C0Mk0qnMqbNy+sR+FQ77pTn2TDPsVzY9PUPMm/el2tj27Vtx5swpBAeHwMoq+4o59ktzZb1nOhWUkpOTIZFIco2bmpoiKSkp3/Vq164NuVyO2NhYNG3aFACgUCgQExMDpVKJ5ORkGBoaIjk5GZUrV85z+zExMUWqXSIxKtL6FQ37pRn2S3PsmWbYL3WpqalYtOhLJCYm4vz5s1i/fj08PDxUr7NfmiurPdOpoPShXFxcUKtWLcyfPx9SqRSWlpbYtGkTHjx4AAClckOx5OR0yOWKEv86ZZ1IJIREYsR+FRL7pTn2TDPsV34E2Lv3ICZN8saNG7EYNGgQ+vcfgK++WoW6dWuyXxrQ1feYRGJUqKNcOhWUJBIJUlJSco0nJSXB1NQ03/XEYjFWrlwJX19f9OnTBwBga2sLLy8v7Ny5UzXnSSKR4OnTpxpvvzDkcgWysnTnDaDr2C/NsF+aY880w37l1rhxMxw/fgZffSXF11+vxM8/78O5c9EIDQ1Fx47d2S8NldX3mE6dMMxrrlBKSgpevHgBGxub967buHFjRERE4NixY4iIiMDBgwfx9u1bNGrUCPr6+qrtx8fH55qgFx8fX+D2iYio4jEwMIBIpIfPPx+OBg3s8fLlSwwePBh37twGAISESBEcvFTLVVJJ0qmg5O7ujgsXLiA5OVk1FhERAaFQqHalWn4EAgHq1KmDunXr/v8DEMMxaNAgte0nJSXh4sWLqrH4+HjExsbC3d29eHeGiIjKBZFIhB07tqJXr76YPn0G/P398ckn9RESIoVUGpjrQiIqX3Tq1Junpyd27tyJSZMmwdvbG8+ePUNwcDA8PT1RtWpV1XJeXl54/PgxTpw4oRrbsGEDateuDUtLS8THx2Pjxo1o3LgxBgwYoFqmefPmcHV1xZw5c+Dv7w8DAwOsXLkSdnZ26Nq1a6nuKxERlQ2+vv4AAKk0ELNnz8PSpYsxZ04ApNJAjBnjjbi4u0hISIClpaWWK6WSoFNBydTUFNu3b8fixYsxadIkGBsbw8PDAz4+PmrLKRQKyOVytbHk5GRIpVIkJCSgSpUq6Nu3LyZOnAihUP2g2apVqxAUFIQvv/wSWVlZcHV1xbx586Cnp1OtICIiHZITloKCliAkJPvRWjNnzsHp01H49ddLOHXqJJYvX4VevfpouVIqbgIl76hVLBIT08rkJLXSpqcnhLm5MftVSOyX5tgzzbBfmqlRwwoymQxisRgPH77En3/+jqlTJ+Dmzb8BAAMGeGDp0uWwsODRpRy6+h6zsDAu1FVvOjVHiYiISFeFhEhVIUkmkyEkRIrmzVvixIloTJ06HUKhEPv27YGbmxPCww9ru1wqJgxKREREBciZuD179jxkZGRg9ux5kEoDERIihaGhIebNW4Dw8EjY2trhxYvnGDFiKMNSOcGJOURERO+RE5L8/efCz28WAMDPbxYUCiWk0kAA2XOYWrRwRGTkWaxYsQznz0eja9fu2iybigmDEhER0XvI5XL4+89VTejOkfP5uxcX5RxdyszMVF0klJGRgSVLFmDKFB9UqVKl9AqnYsHJ3MVE1yap6SpdndSnq9gvzbFnmmG/NPMh/QoKWoSVK1fA3NwcgYHBGDhwcKk8WktX6Op7jJO5iYiIdEDv3v3RuHFTJCYmYuLEsRg+3BNPnz7RdllUSAxKREREJahJk6Y4duwUZs2aB319fRw7dhRubk7Yteu7XI/UIt3DoERERFTC9PX1MX36TERGnkXz5i2QlPQaU6dOgFS6RNulUQEYlIiIiEqJvX1DHDkSiYCARbCwsMBnnw3TdklUAAYlIiKiUqSnp4cpU77A5csxqF27jmo8LGwT7t+/p7W6KG8MSkRERFpgYmKi+vjs2TOYPXsG2rVzRljYRigUunN1WEXHoERERKRl1avXgLOzC968ScPs2X7o378n4uLuaLssAoMSERGR1tnY1MP+/UcQFLQClSoZ49KlC+jQwQUbNqxVu6EllT4GJSIiIh0gFAoxevQ4nDlzEW5u7ZGeno758+dgxIih2i6tQmNQIiIi0iG1a9fBnj0HEBLyNUxMKuPTTz20XVKFxme9ERER6RiBQIBhw0age/desLKyUo1HR5+GlZU1GjZspMXqKhYeUSIiItJR1tbWqufCvXqVgPHjR6NLF3esWLEMmZmZWq6uYmBQIiIiKgPkcgUcHVshMzMTwcFL0bVre1y/flXbZZV7DEpERERlgLW1NbZv/wGhoWGwsLDAX39dR7duHbBs2WJkZGRou7xyi0GJiIiojBAIBBgwYBCio39Fnz79kZWVha++Wo6uXdshNTVV2+WVSwxKREREZUyVKlUQFrYDYWE7YGVlDQeHFmp3+qbiw6veiIiIyqg+ffqjbVs36OmJVGOPHj3EgwcP0KaNsxYrKz94RImIiKgMs7S0hKmpGQBAqVRixoxp6NevO2bPnoHU1BTtFlcOMCgRERGVEzKZDFWrVoNSqURY2Ca4u7fBqVMntV1WmcagREREVE4YGBhg1ap1+OmnA6hVqzYePnyAIUM+xdSpE5CY+Erb5ZVJDEpERETlTLt2HXD69EWMGzcBAoEAu3Z9B1fX1oiJua7t0socBiUiIqJyyMTEBEuWSHHo0HHUr28LExMT1Kv3ibbLKnMYlIiIiMqx1q2dcPLkOfzww14YGRkBAORyOSIiwqFUKrVcne5jUCIiIirnDA0NYWNTT/X55s2hGD7cE599NhAPHz7QYmW6j0GJiIioAjIwMEBUVCTc3JywZcs3UCgU2i5JJzEoERERVTDe3pMQFXUerVu3QVpaKmbN8kX//j1x9+5tbZemcxiUiIiIKqD69W1x8GAEgoKWo1IlY1y6dAHt27fFTz/t0nZpOoVBiYiIqIISCoUYPdob0dGX0L59R8jlcjRs2FjbZekUBiUiIqIKrlat2vjxx/04duw0GjX6NyidOXMKGRkZWqxM+xiUiIiICAKBAE2aNFV9fv36NXh6DkCnTq64fPlXLVamXQxKRERElMurVwmwsLDErVs30atXFwQEzEJaWpq2yyp1DEpERESUS7t2HXDu3K8YMmQolEolNm5cj3btnBEdfVrbpZUqBiUiIiLKk7m5BdasCcWuXXtRo0ZN/PPPPXh49MW8ef7aLq3UMCgRERHRe3Xs2AXR0ZcwatRYAECdOnW1XFHp0dN2AURERKT7TEwqY9myEHh6fo4mTZqpxmNirqNq1WqwtrbWYnUlh0eUiIiIqNAcHFpAJBIBAN68eYORIz+Hm1sr7NnzY7l8yC6DEhEREX2QFy+ew8SkMl69eoWJE8fi888HlbuH7OpcULp79y5GjhwJBwcHuLi4IDg4GDKZrMD1EhMT8eWXX6J9+/ZwcHBA79698cMPP+Ra7vLlyxg2bBhatWoFJycnjBkzBjdu3CiJXSEiIirXateug+PHT2P27ACIxWJERh6Hm5sTwsI2lpuH7OpUUEpKSoKXlxcyMzOxZs0a+Pj4YPfu3Vi2bFmB606bNg1RUVGYOnUqNmzYADc3NyxYsAC7d+9WLRMXF4fRo0ejUqVKCAkJQWBgIJKSkjBixAi8ePGiJHeNiIioXNLX14ePj5/aQ3Znz/ZD795dkZKSrO3yikynJnPv2rULaWlpWLt2LczMzAAAcrkcCxcuhLe3N6pWrZrnei9evMAvv/yCoKAgDBgwAADg7OyM69ev48iRIxg8eDAAIDIyEkqlEqtXr4ahoSEAwM7ODp07d8b58+fRv3//Et9HIiKi8sjW1g4HD0Zg27YwLF48H5aWljAxqaztsopMp44oRUdHw9nZWRWSAKBHjx5QKBQ4f/58vutlZWUBACpXVv8HMTExUZtYlpmZCbFYDAMDA9XYf9chIiKiDyMUCjFq1FicO/crli9fBYFAAABISEjAb7+Vzceg6NQRpbi4OAwcOFBtTCKRwNraGnFxcfmu99FHH8HV1RWhoaGoW7cuqlWrhujoaJw/fx4rVqxQLderVy9s3rwZq1atwogRIyCTyfDVV1/ho48+QqdOnYpUu0ikU5lTZ+X0if0qHPZLc+yZZtgvzbBfhVO7di3VxyKREF98MR07d+7E2LHjMW/efJiYmGixOs3oVFBKTk6GRCLJNW5qaoqkpKT3rpszp6lXr14AAJFIhHnz5qFbt26qZerUqYNt27Zh4sSJCA0NBQBUr14dW7duLfKRJYnEqEjrVzTsl2bYL82xZ5phvzTDfhWeXC6HUCiEUqnEpk0bEBFxBBs3bkT37t21XVqh6FRQ+lBKpRKzZ8/GvXv3EBISAmtra1y4cAFLly6FqampKjzFx8djypQpcHFxQf/+/ZGRkYEtW7Zg7Nix2LVrF6ysrD64huTkdMjl5WOGf0kSiYSQSIzYr0JivzTHnmmG/dIM+6U5kUiIrVu3ol+/gZg2bTL++ec+evTogUGDhmDpUiksLT/8d29RSCRGhToyqFNBSSKRICUlJdd4UlISTE1N813v9OnTiIiIwMGDB2FnZwcAcHJyQkJCApYtW6YKSitXroSVlRWCg4NV67Zu3RodOnTAjh07MH369A+uXS5XICuL3zSFxX5phv3SHHumGfZLM+yX5tq164AzZy5BKg3Epk3r8dNPPyIqKhI7duxCq1ZO2i4vXzp1ktXGxibXXKSUlBS8ePECNjY2+a53584diEQi2Nraqo3b29vj+fPnSE9PVy3XoEEDtWWMjY1Rq1Yt/PPPP8W0F0RERJQXY2NjLFq0FOHhkbC3bwSRSA/169sWvKIW6VRQcnd3x4ULF5Cc/O99FyIiIiAUCuHi4pLvetWrV4dcLsfNmzfVxv/66y9YWlrCyCj7XPLHH3+MGzduqF0Jl5qaivv376N69erFvDdERESUlxYtHBEZGY29ew/BzMwcQPY0msOHD0Iul2u5OnU6FZQ8PT1hbGyMSZMm4dy5c9i7dy+Cg4Ph6empdg8lLy8vdOnSRfW5u7s7Pv74Y0ydOhUHDhzAxYsXsXz5cuzfvx//+9//1LYfGxuLGTNmIDo6GpGRkRg3bhxkMhkGDRpUqvtKRERUkenr68PO7t+zPHv2/IhRo/6H3r274O+/deeJGToVlExNTbF9+3aIRCJMmjQJISEh8PDwwKxZs9SWUygUaonTxMQE27ZtQ8OGDbFixQpMmDABZ86cwaxZs+Dt7a1arnPnzli1ahXu378PHx8fzJs3D4aGhtixYwfq1KlTWrtJRERE/6FUKlG5sgS//34ZnTq5QioNREZGhrbLgkBZHh/1qwWJiWmc2FcIenpCmJsbs1+FxH5pjj3TDPulGfZLc5r07MmTx/D3n46IiHAA2Xf7/uqrtWjduvgne1tYGBfqqjedOqJEREREFddHH32M7dt/wObN22FlZY1bt26iT5+u+Prrr7RWE4MSERER6QyBQIC+fT/F+fO/YejQYQCg1dsHMCgRERGRzjE3t8CqVetw/vxlODv/e+V7ZOQxvHjxotTqYFAiIiIinfXJJ/VVH9+7F4/Ro4fD1dURP/74PUpjmjWDEhEREZUJb9++hY3NJ0hMTMSUKeMxZMin+Oef+yX6NRmUiIiIqExo0MAex4+fxrx5C2BgYIDTp6Pg7u6EjRvXldiNKhmUiIiIqMzQ19fH1KnTcfr0BbRt64o3b94gIGA2+vfvWSJhiUGJiIiIypx69epj377DCAn5GhKJKVxd3SESiYr96+gV+xaJiIiISoFQKMSwYSPQpUs31TPjAOD69Wt4/ToRbm7tiv41irwFIiIiIi2qVu0jGBoaAgCysrLwxReTMHBgH0ybNhGJia+KtG0GJSIiIio3ZDIZWrZ0BAD88MO3cHFphf3793zwrQQYlIiIiKjcqFSpEoKDV+LQoeOws2uAly9fwNt7FD7/fBDmzfNHSIhUo+1xjhIRERGVO05ObRAZeRZr1qzEqlUrEBl5HPr6+sjMzAQABAYuKtR2eESJiIiIyiUDAwPMmDELUVHn4eTkDAeHFpg5cw6k0kC8fv26UNvgESUiIiIq12xt7XDgwFG8fp0ICwtLCAQCJCW9RnJyEurWrfvedXlEiYiIiMo9oVAICwtLAICvrz8AFGqCN4MSERERVSg5E7oFAkGByzIoERERUYUREiKFVBoIU1OzAk+7AQxKREREVEHkhCR//7kwMzMr1DoMSkRERFQhyOVy+PvPVc1RKgxe9UZEREQVwsyZczReh0eUiIiIiPLBoERERESUDwYlIiIionwwKBERERHlg0GJiIiIKB8MSkRERET5YFAiIiIiygeDEhEREVE+GJSIiIiI8sGgRERERJQPBiUiIiKifAiUSqVS20WUB3K5QtsllBkikZD90gD7pTn2TDPsl2bYL83pYs+EQgEEAkGByzEoEREREeWDp96IiIiI8sGgRERERJQPBiUiIiKifDAoEREREeWDQYmIiIgoHwxKRERERPlgUCIiIiLKB4MSERERUT4YlIiIiIjywaBERERElA8GJSIiIqJ8MCgRERER5YNBiYiIiCgfDEof6O7duxg5ciQcHBzg4uKC4OBgyGQybZdV6u7fv48vv/wS/fr1Q8OGDdG7d+88l/vpp5/QrVs3NGnSBH379sWpU6dyLZOSkoI5c+agdevWaN68OaZOnYrnz5+X9C6UqqNHj2LChAlwd3eHg4MD+vXrhz179kCpVKotx35lO3PmDP73v/+hTZs2aNy4MTp16oSgoCCkpKSoLRcVFYW+ffuiSZMm6NatG/bu3ZtrWzKZDFKpFC4uLnBwcMDIkSMRFxdXWruiFWlpaXB3d4ednR2uX7+u9hrfY9n27dsHOzu7XP+tWLFCbTn2S93+/fvRv39/NGnSBE5OThgzZgzevn2rer1cfU8qSWOvX79Wuri4KD///HNldHS08qefflK2bNlSuXDhQm2XVupOnDihdHd3V06ZMkXZu3dvZa9evXItc/jwYaWdnZ1y5cqVyosXLyoDAgKUDRs2VP75559qy40aNUrp7u6uPHLkiDIyMlLZu3dvZd++fZWZmZmltDclb/DgwUofHx/lkSNHlBcuXFCuWLFC2aBBA+WaNWtUy7Bf//r555+VUqlUGRERobx06ZJy586dytatWytHjhypWua3335T2tvbKwMCApQXL15Urly5UmlnZ6c8evSo2rYCAgKULVu2VP7000/K6Oho5dChQ5Vubm7K5OTk0t6tUhMcHKxs27at0tbWVnnt2jXVON9j/9q7d6/S1tZWGR0drfzzzz9V/z1+/Fi1DPulbv369crmzZsrN27cqPzll1+UERERyvnz5ytTU1OVSmX5+55kUPoAoaGhSgcHB2ViYqJqbNeuXUp7e3vl06dPtVeYFsjlctXH/v7+eQalrl27KqdPn642NmTIEOWYMWNUn//xxx9KW1tb5dmzZ1Vjd+/eVdrZ2SmPHDlSApVrR0JCQq6xefPmKVu0aKHqJfv1fj/++KPS1tZW9b02atQo5ZAhQ9SWmT59urJHjx6qz588eaK0t7dX7tq1SzWWmJiodHBwUG7atKl0Ci9ld+7cUTo4OCh/+OGHXEGJ77F/5QSlvL43c7Bf/7p7966yYcOGytOnT+e7THn7nuSptw8QHR0NZ2dnmJmZqcZ69OgBhUKB8+fPa68wLRAK3/8WevDgAe7du4cePXqojffs2RMXL15Una6Mjo6GRCKBi4uLahkbGxvY29sjOjq6+AvXEgsLi1xj9vb2SE1NxZs3b9ivQsj5vsvMzIRMJsMvv/yC7t27qy3Ts2dP3L17Fw8fPgQAnDt3DgqFQm05MzMzuLi4lNt+LVmyBJ6enqhbt67aON9jmmG/1O3btw81atRAu3bt8ny9PH5PMih9gLi4ONjY2KiNSSQSWFtb6+b5VS3K6cd/f1jXq1cPmZmZePDggWq5unXrQiAQqC1nY2NT7nv6+++/o2rVqjAxMWG/8iGXy5GRkYG//voL69atQ8eOHVGjRg38888/yMzMzPX9WK9ePQD/vv/i4uJgaWkJU1PTXMuVx35FRETg1q1bmDRpUq7X+B7LW+/evWFvb49OnTph48aNkMvlANiv/7p69SpsbW2xfv16ODs7o3HjxvD09MTVq1cBoFx+T+ppu4CyKDk5GRKJJNe4qakpkpKStFCR7srpx3/7lfN5zuvJycmoXLlyrvVNTU0RExNTwlVqz+XLlxEeHg5/f38A7Fd+OnTogGfPngEA3NzcEBISAqDo/ZJIJOXuezY9PR3Lli2Dj48PTExMcr3O95g6a2trTJkyBc2aNYNAIEBUVBRWrVqFZ8+e4csvv2S//uPFixeIiYnBrVu3MH/+fBgZGSE0NBSjRo3C8ePHy+X3JIMSkZY8ffoUPj4+cHJywvDhw7Vdjk7btGkT0tPTcefOHWzYsAHjx4/H1q1btV2WTtqwYQMsLS0xcOBAbZdSJri5ucHNzU31uaurKwwMDLB9+3aMHz9ei5XpJqVSiTdv3mD16tVo0KABAKBZs2bo2LEjvv32W7i6umq5wuLHU28fQCKR5Lo8GchOyv89jFjR5fTjv/1KTk5We10ikSA1NTXX+uW1p8nJyRg7dizMzMywZs0a1Vwv9itvDRo0QPPmzTFo0CCsX78ev/zyC06cOFHkfiUnJ5erfj169AhbtmzB1KlTkZKSguTkZLx58wYA8ObNG6SlpfE9Vgg9evSAXC7HjRs32K//kEgkMDMzU4UkIHtuUcOGDXHnzp1y+T3JoPQB8jrnnJKSghcvXuQ6L1vR5fTjv/2Ki4uDvr4+atasqVouPj4+1/2E4uPjy11P3759C29vb6SkpGDz5s1qh5/Zr4LZ2dlBX18f//zzD2rVqgV9ff08+wX8208bGxu8fPky1yH9vOYblmUPHz5EZmYmxo0bh1atWqFVq1aqoyLDhw/HyJEj+R7TEPul7pNPPsn3tYyMjHL5Pcmg9AHc3d1x4cIFVUIGsidPCoVCtSseCKhZsybq1KmDiIgItfHw8HA4OztDLBYDyO5pUlISLl68qFomPj4esbGxcHd3L9WaS1JWVha++OILxMXFYfPmzahatara6+xXwa5evYrMzEzUqFEDYrEYTk5OOHbsmNoy4eHhqFevHmrUqAEg+3SKUCjE8ePHVcskJSXh3Llz5apf9vb22LFjh9p/s2fPBgAsXLgQ8+fP53usEMLDwyESidCwYUP26z86dOiA169f48aNG6qxxMRE/PXXX2jUqFG5/J7kHKUP4OnpiZ07d2LSpEnw9vbGs2fPEBwcDE9Pz1y/+Mq79PR0nDlzBkD2Yf/U1FTVD5TWrVvDwsICU6ZMwYwZM1CrVi04OTkhPDwc165dw7fffqvaTvPmzeHq6oo5c+bA398fBgYGWLlyJezs7NC1a1et7FtJWLhwIU6dOoVZs2YhNTUVV65cUb3WsGFDiMVi9usdkydPRuPGjWFnZwdDQ0P8/fffCAsLg52dHTp37gwAmDBhAoYPH44FCxagR48e+OWXX3D48GGsXLlStZ1q1arBw8MDwcHBEAqFqFq1KjZu3IjKlSvD09NTW7tX7CQSCZycnPJ8rVGjRmjUqBEA8D32jtGjR8PJyQl2dnYAgJMnT2L37t0YPnw4rK2tAbBf7+rcuTOaNGmCqVOnwsfHBwYGBti0aRPEYjGGDh0KoBx+T2r1Lk5l2J07d5ReXl7Kpk2bKp2dnZXLli1TZmRkaLusUvfgwQOlra1tnv9dunRJtdzu3buVXbp0UTZq1EjZu3dvZVRUVK5tJScnK2fPnq10dHRUOjg4KCdPnlzubuDZoUOHfPv14MED1XLsV7aNGzcq+/Xrp2zevLnSwcFB2atXL+WqVauUKSkpasvl3AW5UaNGyi5duih/+umnXNvKyMhQLlu2TOns7Kxs2rSpcsSIEco7d+6U1q5ozaVLl3LdcFKp5Hssx+LFi5Vdu3ZVNm3aVNm4cWNl7969ldu3b1cqFAq15divfyUkJChnzJihbNmypbJp06bKUaNGKW/fvq22THn6nhQolf85oUpEREREADhHiYiIiChfDEpERERE+WBQIiIiIsoHgxIRERFRPhiUiIiIiPLBoERERESUDwYlIiIionwwKBERERHlg0GJiIiIKB8MSkRERET5YFAiIiIiygeDEhERgJEjR2LIkCH4888/MWzYMDg4OKBLly44c+YMAODMmTMYPHgwHBwc0K9fP8TExGi5YiIqDXwoLhERgLZt28LMzAxv3ryBh4cHKleujI0bN0Imk2HGjBkICwvDoEGDoFQqERoaipo1a+LgwYPaLpuISpietgsgItK2hIQEJCQkQCAQYP/+/ahSpQoAQCgUYsmSJdi+fTv2798PExMTAEBiYiK2bdsGmUwGsViszdKJqITx1BsRVXg3b94EAEyePFkVkgCgUqVKAICZM2eqQhIAmJiYQCgUQiAQlG6hRFTqGJSIqMK7desWAKBjx45q4/Hx8TA0NISLi4va+L1791CzZk3o6+uXWo1EpB0MSkRU4d28eRPW1taoWrWq2vjff/+N+vXr5zq9dvPmTdjZ2ZVmiUSkJQxKRFTh3bx5Ew0aNMg1/vfff+caz8zMRHx8PIMSUQXBoEREFZpcLsedO3dyBaJXr17hxYsXucbv3r2LzMxMBiWiCoJBiYgqtHv37iEjIyNXIMqZ4J3fOIMSUcXAoEREFVrORO7/Bp/8AtGtW7dgYmKCGjVqlE6BRKRVvOEkERERUT54RImIiIgoHwxKRERERPlgUCIiIiLKB4MSERERUT4YlIiIiIjywaBERERElA8GJSIiIqJ8MCgRERER5YNBiYiIiCgfDEpERERE+WBQIiIiIsoHgxIRERFRPhiUiIiIiPLxf5EAbI1G38fGAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "rb.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing Gate Quality\n",
    "\n",
    "Let's compare gate quality between ideal and noisy simulators:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Comparison:\n",
      "Average gate error ideal: -0.00000\n",
      "Average gate error noisy simulator: 0.00024\n"
     ]
    }
   ],
   "source": [
    "# Run RB on noisy simulator\n",
    "ideal_device = IdealSimulator()\n",
    "\n",
    "rb_noiseless = CliffordRB(\n",
    "    qubits=2,\n",
    "    m_list = [25,50,100,150,200,250,300,400,500,650],\n",
    "    circs_per_m=10\n",
    ")\n",
    "\n",
    "rb_noiseless.generate_circuits()\n",
    "rb_noiseless.run(ideal_device, num_shots=1024)\n",
    "\n",
    "results_ideal = rb_noiseless.analyze()\n",
    "\n",
    "print(\"\\nComparison:\")\n",
    "print(f\"Average gate error ideal: {results_ideal.get('AverageGateError', 'N/A')}\")\n",
    "print(f\"Average gate error noisy simulator: {results.get('AverageGateError', 'N/A')}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What the Numbers Mean\n",
    "\n",
    "**Average Gate Error**: Average gate error of a set of single- and multi-qubit Clifford gates\n",
    "- The lower the Average Gate Error, the better the quality of Clifford operations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interleaved Clifford Randomized Benchmarking (RB)\n",
    "\n",
    "Interleaved Clifford Randomized Benchmarking measures the average error rate of a target Clifford gate in a gate set. This is done by interleaving a target Clifford gate through random sequences of Clifford gates.\n",
    "\n",
    "### How Interleaved RB Works\n",
    "\n",
    "1. Generate random sequences of Clifford gates of varying lengths\n",
    "2. Append an inverse gate to return to |0⟩\n",
    "3. Measure success probability\n",
    "4. Fit decay curve: P(success) = A × p^m + B\n",
    "5. Extract average gate error from decay parameter p\n",
    "6. Generate random sequences of Clifford gates of varying lengths interleaved with target Clifford gate\n",
    "7. Repeat steps 2-5 to extract the decay parameter p_i for the interleaved circuits.\n",
    "8. Calculate interleaved gate error using the decay parameters p and p_i."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'m_list': [25, 50, 100, 150, 200, 250, 300, 400, 500, 650], 'circs_per_m': 10, 'interleaved_clifford': <qiskit.circuit.quantumcircuit.QuantumCircuit object at 0x7f1403d07380>}\n",
      "Generated 200 circuits\n",
      "Total circuits: 10 lengths × 10 samples\n"
     ]
    }
   ],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "\n",
    "# Create simulator\n",
    "device = NoisySimulator()\n",
    "\n",
    "# Create circuit with target Clifford gate\n",
    "circ = QuantumCircuit(1)\n",
    "circ.x(0)\n",
    "\n",
    "# Setup interleavedRB benchmark\n",
    "irb = InterleavedRB(\n",
    "    qubits=1,\n",
    "    m_list = [25,50,100,150,200,250,300,400,500,650],\n",
    "    circs_per_m=10,\n",
    "    interleaved_clifford=circ\n",
    ")\n",
    "\n",
    "# Generate circuits\n",
    "irb.generate_circuits()\n",
    "print(irb.config)\n",
    "print(f\"Generated {len(irb.circuits)} circuits\")\n",
    "print(f\"Total circuits: {len(irb.config['m_list'])} lengths × {irb.config['circs_per_m']} samples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "IRB Results:\n",
      "  qubits: 1\n",
      "  alpha: 0.9999235760656404\n",
      "  alpha_g: 0.9995476221471704\n",
      "  AverageGateError: 0.00004\n",
      "  InterleavedGateError: 0.00019\n",
      "  Clifford_fit: {'fit_result': {'popt': array([0.99992358, 1.        , 0.00125025]), 'pcov': array([[ 6.44838319e-08,  8.23109620e-04, -8.23263413e-04],\n",
      "       [ 8.23109620e-04,  1.05072126e+01, -1.05091647e+01],\n",
      "       [-8.23263413e-04, -1.05091647e+01,  1.05111175e+01]])}}\n",
      "  Interleaved_fit: {'fit_result': {'popt': array([0.99954762, 0.51257069, 0.48753614]), 'pcov': array([[ 3.74777624e-08,  3.65497812e-05, -3.67946455e-05],\n",
      "       [ 3.65497812e-05,  3.57284630e-02, -3.59581700e-02],\n",
      "       [-3.67946455e-05, -3.59581700e-02,  3.61909435e-02]])}}\n"
     ]
    }
   ],
   "source": [
    "# Run benchmark\n",
    "irb.run(device, num_shots=1024)\n",
    "\n",
    "# Analyze\n",
    "results = irb.analyze()\n",
    "print(\"\\nIRB Results:\")\n",
    "for key, value in results.items():\n",
    "    print(f\"  {key}: {value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing InterleavedRB Decay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "irb.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What the Numbers Mean\n",
    "\n",
    "**Average Gate Error**: Average gate error of a set of single- and multi-qubit Clifford gates\n",
    "- The lower the Average Gate Error, the better the quality of Clifford operations.\n",
    "\n",
    "**Interleaved Gate Error**: Average gate error of a target Clifford gate in a gate set\n",
    "- The lower the Interleaved Gate Error, the better the quality of the target Clifford operation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Over/Under Rotation Angle\n",
    "\n",
    "This benchmark detects systematic over-rotation or under-rotation errors in single-qubit gates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generated 41 circuits\n",
      "\n",
      "Rotation Analysis Results:\n",
      "  success: True\n",
      "  OverUnderRotationAngle: 0.03146251398870455\n",
      "  fit_result: {'popt': array([ 0.50052081, -0.5020418 ,  0.02107131,  0.12585006,  1.5753996 ]), 'pcov': array([[ 4.51268404e-06,  5.94109362e-06, -2.59998197e-07,\n",
      "         9.94502958e-08, -2.85527367e-06],\n",
      "       [ 5.94109362e-06,  1.81765069e-04, -7.86083103e-06,\n",
      "        -9.72212447e-07,  5.47409729e-05],\n",
      "       [-2.59998197e-07, -7.86083103e-06,  6.01151691e-07,\n",
      "         3.84869866e-08, -2.25924771e-06],\n",
      "       [ 9.94502958e-08, -9.72212447e-07,  3.84869866e-08,\n",
      "         4.30265278e-07, -8.18183895e-06],\n",
      "       [-2.85527367e-06,  5.47409729e-05, -2.25924771e-06,\n",
      "        -8.18183895e-06,  3.98614943e-04]])}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>,\n",
       " <Axes: title={'center': 'Fitting with error amount = 0.031$\\\\pi$'}, xlabel='$m$', ylabel='$p_0$'>)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "overrotation_amount= np.pi/100\n",
    "device = NoisySimulator(t1=0, t2=0, overrotation_amount=overrotation_amount)\n",
    "\n",
    "rotation_exp = OverUnderRotationAngle(\n",
    "    qubits=1,\n",
    "    delta_m=5,  # Maximum gate repetitions\n",
    ")\n",
    "\n",
    "# Generate and run\n",
    "rotation_exp.generate_circuits()\n",
    "print(f\"Generated {len(rotation_exp.circuits)} circuits\")\n",
    "\n",
    "rotation_exp.run(device, num_shots=1024)\n",
    "results_rot = rotation_exp.analyze()\n",
    "\n",
    "print(\"\\nRotation Analysis Results:\")\n",
    "for key, value in results_rot.items():\n",
    "    print(f\"  {key}: {value}\")\n",
    "rotation_exp.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What the Numbers Mean\n",
    "**Over/Under Rotation Angle** (in radians): The amount of over/under- rotation per gate\n",
    "- A positive value represents an over-rotation by the target gate.\n",
    "- A negative value represents an under-rotation by the target gate.\n",
    "- The larger the magnitude of over/under- rotation, the lower the accuracy of the gate rotation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Further benchmarks\n",
    "\n",
    "Additional gate quality metrics implemented in QCMet are\n",
    "\n",
    "- Gate set tomography based process fidelity (GST)\n",
    "- Cycle-benchmarking composite process fidelity (CycleBenchmarking)\n",
    "\n",
    "These also follow the standard workflow:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'composite_process_fidelity': {'m=2_to_m=4': 4.03307128518151,\n",
       "  'm=2_to_m=8': 1.1263552467649778,\n",
       "  'm=2_to_m=10': 0.5437854647893269,\n",
       "  'm=4_to_m=8': 0.49965640854839666,\n",
       "  'm=4_to_m=10': 0.5190481243612284,\n",
       "  'm=8_to_m=10': 0.40691147471081385},\n",
       " 'method': 'ratio',\n",
       " 'success': True,\n",
       " 'ptm_elements': {2: {'XX': 0.99765625,\n",
       "   'XY': 0.0185546875,\n",
       "   'XZ': 0.00625,\n",
       "   'XI': 0.015234375,\n",
       "   'YX': 0.998046875,\n",
       "   'YY': 0.0009765625,\n",
       "   'YZ': -0.016015625,\n",
       "   'YI': 0.99921875,\n",
       "   'ZX': 0.9974609375,\n",
       "   'ZY': -0.019140625,\n",
       "   'ZZ': -0.0017578125,\n",
       "   'ZI': -0.0140625,\n",
       "   'IX': 0.998828125,\n",
       "   'IY': 0.0033203125,\n",
       "   'IZ': -0.007421875},\n",
       "  4: {'XX': 0.9947265625,\n",
       "   'XY': -0.9947265625,\n",
       "   'XZ': -0.9947265625,\n",
       "   'XI': 0.994921875,\n",
       "   'YX': 0.996875,\n",
       "   'YY': -0.9943359375,\n",
       "   'YZ': -0.9951171875,\n",
       "   'YI': 0.9962890625,\n",
       "   'ZX': 0.9958984375,\n",
       "   'ZY': -0.9955078125,\n",
       "   'ZZ': -0.994140625,\n",
       "   'ZI': 0.99375,\n",
       "   'IX': 0.99765625,\n",
       "   'IY': -0.994921875,\n",
       "   'IZ': -0.9947265625},\n",
       "  8: {'XX': 0.9927734375,\n",
       "   'XY': 0.9880859375,\n",
       "   'XZ': 0.989453125,\n",
       "   'XI': 0.99296875,\n",
       "   'YX': 0.9931640625,\n",
       "   'YY': 0.9923828125,\n",
       "   'YZ': 0.9880859375,\n",
       "   'YI': 0.99140625,\n",
       "   'ZX': 0.992578125,\n",
       "   'ZY': 0.987109375,\n",
       "   'ZZ': 0.990234375,\n",
       "   'ZI': 0.991796875,\n",
       "   'IX': 0.9935546875,\n",
       "   'IY': 0.98828125,\n",
       "   'IZ': 0.9890625},\n",
       "  10: {'XX': 0.9896484375,\n",
       "   'XY': -0.003515625,\n",
       "   'XZ': 0.0013671875,\n",
       "   'XI': 0.01484375,\n",
       "   'YX': 0.9890625,\n",
       "   'YY': -0.001171875,\n",
       "   'YZ': -0.005859375,\n",
       "   'YI': 0.9908203125,\n",
       "   'ZX': 0.9904296875,\n",
       "   'ZY': 0.0138671875,\n",
       "   'ZZ': 0.0025390625,\n",
       "   'ZI': 0.0025390625,\n",
       "   'IX': 0.991015625,\n",
       "   'IY': -0.00078125,\n",
       "   'IZ': 0.01875}},\n",
       " 'cycle_fidelities': [0.37357177734375,\n",
       "  0.0007446289062499958,\n",
       "  0.99130859375,\n",
       "  0.37459716796875]}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = NoisySimulator()\n",
    "\n",
    "# gate layer to benchmark\n",
    "circ = QuantumCircuit(2)\n",
    "circ.h(0)\n",
    "circ.cx(0, 1)\n",
    "circ.x(1)\n",
    "\n",
    "cyclebm = CycleBenchmarking(circ, [2, 4, 8, 10])\n",
    "\n",
    "cyclebm(device)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}