Challenge4_CircuitDecomposition.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercise 4: Circuit Decomposition\n",
    "Wow! If you managed to solve the first three exercises, congratulations! The fourth problem is supposed to puzzle even the quantum experts among you, so don’t worry if you cannot solve it. If you can, hats off to you!\n",
    "\n",
    "You may recall from your quantum mechanics course that quantum theory is unitary. Therefore, the evolution of any (closed) system can be described by a unitary. But given an arbitrary unitary, can you actually implement it on your quantum computer?\n",
    "\n",
    "**\"A set of quantum gates is said to be universal if any unitary transformation of the quantum data can be efficiently approximated arbitrarily well as a sequence of gates in the set.\"** (https://qiskit.org/textbook/ch-algorithms/defining-quantum-circuits.html)\n",
    "\n",
    "Every gate you run on the IBM Quantum Experience is transpiled into single qubit rotations and CNOT (CX) gates. We know that these constitute a universal gate set, which implies that any unitary can be implemented using only these gates. However, in general it is not easy to find a good decomposition for an arbitrary unitary. Your task is to find such a decomposition.\n",
    "\n",
    "You are given the following unitary:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What circuit would make such a complicated unitary?\n",
    "\n",
    "Is there some symmetry, or is it random? We just updated Qiskit with the introduction of a quantum circuit library (https://github.com/Qiskit/qiskit-terra/tree/master/qiskit/circuit/library). This library gives users access to a rich set of well-studied circuit families, instances of which can be used as benchmarks (quantum volume), as building blocks in building more complex circuits (adders), or as tools to explore quantum computational advantage over classical computation (instantaneous quantum polynomial complexity circuits)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "from qiskit import *\n",
    "from may4_challenge.ex4 import check_circuit, submit_circuit\n",
    "from qiskit.transpiler.passes import Unroller\n",
    "from qiskit import Aer\n",
    "from qiskit import Aer, QuantumCircuit, execute\n",
    "from qiskit.visualization import plot_histogram\n",
    "from IPython.display import display, Math, Latex\n",
    "\n",
    "from may4_challenge import plot_state_qsphere\n",
    "from may4_challenge.ex1 import minicomposer\n",
    "from qiskit.compiler import transpile\n",
    "from qiskit.transpiler import PassManager\n",
    "from may4_challenge.ex4 import get_unitary\n",
    "import numpy as np\n",
    "from math import pi\n",
    "import pandas as pd\n",
    "import matplotlib.pylab as plt\n",
    "from qiskit.aqua.components.optimizers import AQGD,ADAM,SLSQP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Using only single qubit rotations and CNOT gates, find a quantum circuit that approximates that unitary $U$ by a unitary $V$ up to an error $\\varepsilon = 0.01$, such that $\\lVert U - V\\rVert_2 \\leq \\varepsilon$ !** \n",
    "\n",
    "Note that the norm we are using here is the spectral norm, $\\qquad \\lVert A \\rVert_2 = \\max_{\\lVert \\psi \\rVert_2= 1} \\lVert A \\psi \\rVert$.\n",
    "\n",
    "This can be seen as the largest scaling factor that the matrix $A$ has on any initial (normalized) state $\\psi$. One can show that this norm corresponds to the largest singular value of $A$, i.e., the square root of the largest eigenvalue of the matrix $A^\\dagger A$, where $A^{\\dagger}$ denotes the conjugate transpose of $A$.\n",
    "\n",
    "**When you submit a circuit, we remove the global phase of the corresponding unitary $V$ before comparing it with $U$ using the spectral norm. For example, if you submit a circuit that generates $V = \\text{e}^{i\\theta}U$, we remove the global phase $\\text{e}^{i\\theta}$ from $V$ before computing the norm, and you will have a successful submission. As a result, you do not have to worry about matching the desired unitary, $U$, up to a global phase.**\n",
    "\n",
    "As the single-qubit gates have a much higher fidelity than the two-qubit gates, we will look at the number of CNOT-gates, $n_{cx}$, and the number of u3-gates, $n_{u3}$, to determine the cost of your decomposition as \n",
    "\n",
    "$$\n",
    "\\qquad \\text{cost} = 10 \\cdot n_{cx} + n_{u3}\n",
    "$$\n",
    "\n",
    "Try to optimize the cost of your decomposition. \n",
    "\n",
    "**Note that you will need to ensure that your circuit is composed only of $u3$ and $cx$ gates. The exercise is considered correctly solved if your cost is smaller than 1600.**\n",
    "\n",
    "---\n",
    "For useful tips to complete this exercise as well as pointers for communicating with other participants and asking questions, please take a look at the following [repository](https://github.com/qiskit-community/may4_challenge_exercises). You will also find a copy of these exercises, so feel free to edit and experiment with these notebooks.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAGKCAYAAADE29x1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOy9eZxU1Zn//75L7dU7NM2+2kBAFEEWQwL5GTRq0EjUGKPRCUnGYIJJTKISFxyN22hGHUfML06MiTG/mC8qfF/BkZEYkrii0sgmi2w2S0N3dXdtXctdfn9U16Wru6u6qqt65bx59avpOvfce27VrfM5z/Oc8xzJNE0EAoFAICgEcl83QCAQCASDByEqAoFAICgYQlQEAoFAUDCEqAgEAoGgYAhREQgEAkHBULsoF1PDBAKBQNAeKV2BsFQEAoFAUDCEqAgEAoGgYAhREQgEAkHBEKIiEAgEgoIhREUgEAgEBUOIikAgEAgKhhAVgUAgEBQMISoCgUAgKBhCVAQCgUBQMISoCAQCgaBgCFERCAQCQcEQoiIQCASCgiFERSAQCAQFQ4iKQCAQCAqGEBWBQCAQFAwhKgKBQCAoGEJUBAKBQFAwhKgIBAKBoGAIUREIBAJBwRCiIhAIBIKCIURFIBAIBAVDiIpAIBAICoYQFYFAIBAUDCEqAoFAICgYQlQEAoFAUDCEqAgEAoGgYAhREQgEAkHBEKIiEAgEgoIhREUgEAgEBUOIikAgEAgKhhAVgUAgEBQMISoCgUAgKBhCVAQCgUBQMISoCAQCgaBgCFERCAQCQcEQoiIQCASCgiFERSAQCAQFQ4iKQCAQCAqGEBXBacmqVatYtWpVXzdDIBh0CFERCACfz8fll1+Ox+Nh7NixvPDCC1mV5Vt3/Pjx1NbW9uzNCQS9iBAVgQC46aabsNvt1NXV8Yc//IHvfe977Nixo8uyfOsuWbKEdevW9e7NCgQ9iGSaZqbyjIUCwUAl6fpatWoVoVCIsrIytm/fTnV1NQDXXXcdI0eO5M4770xb9uCDD+ZVF+D111/n4YcfZsOGDb38DggEeSGlKxCWiuC0Z8+ePaiqanX8AGeddRY7duzIWJZvXYCFCxdSU1NDc3NzT96iQNBrCFERnPYEg0GKi4tTXispKSEQCGQsy7cugM1m4/zzz+fVV18t5C0JBH2GEBXBaY/X68Xv96e85vf7KSoqyliWb90kM2bMYNu2bYW6HYGgTxGiIjjtqa6uRtM09u7da722detWpk2blrEs37pJNmzYwAUXXNBTtycQ9CpCVASnPR6Ph6VLl3LXXXcRCoV48803Wbt2Ldddd13GsnzrAjQ2NrJr1y4WLFjQV7cvEBQUISoCAfDUU0/R0tJCZWUlX//611m9erVlUWQqy7fuX/7yFy688EIURendGxYIeggxpVhwWtJ2SnFfcuWVV3LNNddw+eWX92k7BIIcEVOKBYL+iNvtFvEUwaBCWCqC05K//e1vACxatKhP2yEQDFDSWipCVAQCgUCQK8L9JRAIBIKeR4iKQCAQCAqGEBWBoA1dparP9dj33nuPJUuW8Oijj/ZkswWCfoMQFYGgDV2lqs/12BdeeIEXX3yR3bt390bzBYI+RwTqBYJWMqWxT6aqz/XYLVu2sGrVKs4//3xWrFjRezcjEPQsaQP1am+2QiDoz6RLVb9p06ZuHztz5kzWrl3bc40WCPoZwv0lELSSTar67hwrEJxOCFERCFrJNlV9rscKBKcTQlQEglayTVWf67ECwemECNQLBG24+uqrkSSJZ555hpqaGi6++GLeeuutTsUil2MFgkGGWFEvEGRDplT1F110Effff39WxwoEpyvCUhEIBAJBrghLRSAQCAQ9jxAVgUAgEBQMISoCgUAgKBhCVAQCgUBQMISoCAQCgaBgCFERCAQCQcEQoiIQCASCgiFERSAQCAQFQ4iKQCAQCAqGEBWBQCAQFAwhKgKBQCAoGGLnR4EgB0zTJLBrF5+++CIN77yDEYsh2+1UzJvH6K99jaIpU5CktGmRBIJBj0goKRBkiaFp7Lr/fhrefhsjGoW23x1JQnY4qJg/n6krVyKrYrwmGNSIhJICQT6YppkQlLfewohEUgUlcQBGJELDW2+x6/776WKwJhAMWoSoCARZENi165SFkgEjGqXh7bcJfPxxL7VMIOhfCFERCLLg0xdf7FJQkhjRKJ/++c893CKBoH8iREUgyIKGd97p6PJKh2nS8NZbPdsggaCfIqKJAkEaTNNE13UAoqEQpmFgtL5uShLIMoZhIJkmMqBIEiaJCKakaYkySRKzwQSnFUJUBKctmqYRi8XQNI14PE48HkeWZXRdtwLtkiRhmiZ+WcaIx6FVUCTTtATDNIzEa63HmoaB5HBw/PhxzDbHSZKEqqrIsozNZsNms2G325Fl4TAQDB6EqAgGPaZpWqKRFJGkcCQ7/aSI6LqeYlkkXy+fNctygUkArceYgCnL1vxKSZKQVJWKuXOtv5PnMU2TWCwGQCQSAUCWZUzTtARGVVXrt0AwEBFPrmBQYRgGmqYRjUaJx+OWgABpp/m2t0o6Y8SSJTRu2ZKYTtwOKXESS2hku50RS5akvVZSaCRJwjAMAGKxmCU4yTIhNIKBiHhKBQMewzAIh8NEIhHi8XinwtBWOJK0tSKSv9PFP7zV1ZTNmkXj++93OgvMiqU4HJTNno130qROz9OZFdT2um0tp/ZCI8syTqcTt9uN3W5P93YIBH2KWFEvGJAYhkFLSwstLS0pHW97MglFztfUNPY+8QS+99/HjMVSZoOZkoRis1E+Zw6TfvCDHl9RL8syLpcLl8slBEbQF6T9UglREQwYNE0jEokQiUQyCkkuJF1QnQlPZ4JkmibBvXupfeUVmrZswYjHke12ymbNYuSll1J0xhlZXbf9uTuzVrIlacG4XC4cDkfW9QSCPBCiIhiYZBKSTJ1vpvhIIdBjMaInTiDb7TgrK3vsOulId++KouBwOITACHqatKIiYiqCfkkkEiEYDGa0SDJZF32Re6uQrrauSHcdXdcJh8OEw2FkWcbr9eJ2u8W0ZUGvIURF0K8Ih8MEg0E0TcvqeGttSJv1IOmO6Wl6SlC6Eqt092cYBn6/n2AwiMfjwePxCHER9DhCVAT9gnA4jN/vt6bYJmnbWaazTNKVtT+mNy2JQtJVm7sSzPbi4vV6hbgIegwhKoI+IzkVOBgMdhCTJIUUgYEoKIUiac0Eg0GCwSButxuv1yvWvggKjniiBL1ONmLSk6SzWPKZgZUkk6st0zm7W5YryXMl4y5CXASFRjxJgl7DMAyCwSDhcDijZdLT8Y9MM8YykU3nnqntXcVFulOWK23f36S4tLS04HA4KC4uFuIiyBvxBAl6hWAwSCAQADJ3vL01ayub4Hc2rw1E2t+HYRjWtG2v1ytiLoK8EKIi6FE0TaOpqanD1OBsLJKeDKwPFoHojGwtqrY5yJJ/B4NBIpEIJSUlYp2LoFsIURH0GMkZR+3J1hpJt+K8/TG5xjDyESurbus05r5eHdx2XU5bkch0bGfHtP1b0zQaGhpwu90UFxcLq0WQE0JUBAUnFovR1NSUdq1JdwPgndGdGEY+VopVN7lHSpo25S1aWZ6nKyHp7NhsCYfDRKNRSkpKcDqdOdUVnL4IUREUjGQgvjPrZKDyyCOPAHDLLbcAuXXe3RGXzrIoZ0tPuAt1Xcfn8wmrRZA14gkRFIRYLEZ9fX2PCUo28ZdMx3Z3AkDbXRslSaKxsZFly5Yx+TOfYeFll7Hu1VetY5NlkyZNYs6cObzyyisp52pf/vLLL1tlzz77LBdddBHjx4/nhz/8YYd2zJs3j6NHj3Z7dlm+dcLhMCdOnLA2FxMI0iEsFUFeJFdrh8NhoOsAfD7rP7It78mZWz//+c+x2Wx8uHkzNW++yXduuYWz5s1j8uTJVtnWrVvZsWMH3/zmN/nMZz7D5MmTU+p2Vj5s2DBuvvlm/va3v3XacS9evJgNGzZwww03FOQ+kuSSK80wDHw+Hy6Xi5KSEmG1CDpFPBWCbhONRqmvryccDqekQslET8+66skpyeFwmPXr1/PTn/4Uj8fD7LPP5osLF7JmzZqUMrfbzZw5c1i8eDFr1qzptG778osvvpgvfelLlJWVdXrtxYsX89prr/XIfeX6nrW0tHDixAlaWlp6pD2CgY0QFUG3CIfD1NfXW8H4QopFPsLQk6K1f/9+FEVh4sSJ1mtTqqvZvXt3SlmyDdOmTWP37t1p67Yt74r58+ezY8cO/H5/Ae+o+xiGQWNjI42NjX3dFEE/Q4hKF6xatYpVq1b1dTP6FX6/n6amptNuDUkoFKKoqCjltSKvl1Ao1HlZURGhUCh93Tbl7WkvrDabjQULFvDGG2/kextdkouot7S0UF9f3yfpdgT9EyEqOeLz+bj88svxeDyMHTuWF154IasygCeffJLZs2fjcDg6+Ma7qjt+/Hhqa2t77L6ywTRNfD5fSjC+L/Yt6YxCB7A7O4fH47GyAiS3Em6bVt4qa21PIBDA4/EAdCgHUsqzafPUqVPZtWtX3vfSFbmmoklO0sh2uwLB4EaISo7cdNNN2O126urq+MMf/sD3vvc9duzY0WUZwIgRI7jjjjv41re+ldN5AZYsWcK6det6/gbTYBgGDQ0NHYLI3Vk/0hNkk/o+H0zTZMKECei6zv79+6H1erv27GHy5MmpZa3t2blzpxWkb18OpJRnw6ZNm1i4cGHe95IvbadMJ9E0jfr6+oJt85wPwrvQtwhRyYFQKMSaNWu499578Xq9LFiwgEsvvZTf//73GcuSLF26lK985StUVFRkfd4kl156aYcpqr2FpmmcPHkypw6jv7qw8sHtdnPRRRfxyCOPEA6H+WDrVl7ftImvfvWrHco2b97Mhg0b+OpXv9pp3fblyW2TDcNA13UikUjKyL+pqYl9+/YxZ86cHr/P7mQ8gMTAo76+vt8F8PPxEOTjmegP3oW+QIhKDuzZswdVVamurrZeO+uss9ixY0fGsnzOm2ThwoXU1NTQ3NxcoLvJjmg0ysmTJ9F1Heg/7q4k7Tu2fNeoJHeRTMf9999PJBJh5uzZ/OjOO7l35UrL2kiWzZgxg+XLl/PAAw8wefJk63ydlSc/88cff5yJEyfy5JNP8tJLLzFx4kQee+wx67obN25k4cKFKIqS9b1kusdM5DsgaGxs7ODq60vy8RDk45noa+9CXyHWqeRAMBikuLg45bWSkhICgUDGsnzOm8Rms3H++efz6quvcvXVV+dxF9kTDodpampKea2zTjyb13qK9h1kvmtUujq2rKyM3/zmN+ixGNETJ5Dt9g5l6c6ZrhwSK/aTq/Y747XXXuPyyy/P5ha6pCtXYSE+u0AggK7rlJaW5n2ufFm6dCkA77//forlkPQQbN++vYOH4MEHH8xYfuedd2asCwnvwsMPP8zy5cv75L77CmGp5IDX6+0wpdPv91NUVJSxLJ/ztmXGjBls27atm63PjeQMr64YzCni86HQFp3L5eqVeEo+n137ew6Hw/h8vn47M6wrD0G+nom+8i70NUJUcqC6uhpN09i7d6/12tatW5k2bVrGsnzO25YNGzZwwQUXFOBOMtPU1DSo8nflw/z585k/f37O9QotrI8//jhut7ug5+wNIpFIv50Z1pWHIF/PRFvvwumEEJUc8Hg8LF26lLvuuotQKMSbb77J2rVrue666zKWJUkGY3VdTwnGZlO3sbGRXbt2sWDBgh69R7/f3+8Crdny6KOP8uijjxb0nOeddx7nnXdeQc85WEknpJqm9UuLpSsPQSE8E73pXegvCFHJkaeeeoqWlhYqKyv5+te/zurVqy2LIlMZwH333YfL5eLBBx/k+eefx+Vycd9992VV9y9/+QsXXnhhQQK16UhmGO5vwfjukk8Cx0x1Gxsb+c6//iszFi7kcxddlFIGp5I/DibyfSaSU477k7B05SEohGeit7wL/QkRqM+R8vLytFN7M5VB5vnzXdVdu3Yt11xzTU5tzYVwONxh5NXdoG1vBuozkU8Cx0x1k2Vvv/oquw8c4Ns335ySOLKnkj8Wku7u25IPSYtlyJAheZ8r1+tqmpbiIVBVNcVD8Mwzz1BTU8PatWt56623ADKWd1UXes+70N8QlsoAwe1299iIJxKJpATlk6PS7nYkXc0u6g1LqDsJHJPt6qzuvHnzuO6665g8eTJr165l7rnn4na5mDVzJgsXLkyxatxud8bkj01NTWmtoCRbtmzh+uuv5+mnn+72e5BtloFsP+dCfG7RaLTX84Xl4yHIxzPRG96F/oiwVLpg0aJFfd0EAJ577rkeOW8sFuvwJe9JK6MQ585mZJ0ugePbb7/dZdva19U0jQ8++ICKigp+/etf85WvfIX7H3qIudOmMXHSJA4cOEA4HLasmuuuuw5VVfH7/R2CuQArV67MmCIf4OWXX+bpp5/m7rvvzum+O7ufQlGodDctLS3IskxJSUkBWtU1+XgI8vFM9LR3ob8iLJUuWLRoUb8RlkKTdEf0Zgwl12t1dnymfTySx+eawLEt7evu27ePYDBIRUUFkUiEkpISZs+axSt/+QvhcJiPP/6Y4cOHW1bNBRdcwNChQ3njjTc6nWabyYJK3sNVV13F8uXLU4Sm7X0P9LhXKBQa9DMMe9K70J8RlsppSnLDpd4MnKYbaWcagac7vityTeDYVV3TNPF6vVaZaZrsPXCAA4cPI0lSSpxg2rRpbN26lV27dnHZZZelnCcbC0qSJKZPn86zzz6b9r67azW0f6+7sn46K892U6+u8Pv9yLJc8KnS/WUQ2FPehf6OsFROQ5KC0t21A/lszZvL6/lcI58Eju3rTpw4EZvNRigUYvTo0cTjcd55911aIhHC4TCKoqSct6ioiJMnT3a6WDEfC6oQdCYQuRwP6VPhdOe5aGpqIhqN5lwvE4PZuzAQEKJyGtLU1EQsFut2nqz+MLOrK/JJ4Ni+bk1NDZAQhPPOO4/y8nKqhg1jSHk5Bz/9lGg0ap0XsPZy7yz5Yz4WVH9GkqRuPxeNjY3E4/ECt0jQVwhRSUM0GmXZsmWMHTuWoqIizj777JSVsZkyn0JitOR0OvF6vXi93owj5GuvvZbhw4dTXFxMdXU1zzzzTKfHvffeeyxZsiSvBX7Nzc1EIpG0bo+eEIy+8v+nS/AInSdwfPzxx9PWffjhh3n11VfZsWMHb7zxBoFgkL+8/jqPrV6NoijYbDar7qZNmxg/fnyns34KkQK/UPSXuExyW4Vk0lLBwEaISho0TWP06NFs2rSJ5uZm7rvvPq666ioOHjwIZM58muTJJ5+0FhRm2jb29ttv5+DBg/j9ftatW8cdd9zBBx980OG4F154gRdffDHrLWjbE4lELDdLb1obfWXZJBM47tu3j82bN6ckZLzllls4cuRIyk/bhI7t606ePJlIJEJLSwt/+tOfKC4qYstf/8qb//M/XHLJJSkW0ZYtW7jmmms67bS7sqB6k/5kcSZdsvkI3WAdCA40hKikwePxsGrVKsaNG4csy3z5y19m/PjxVmefbm+U7jBt2jQcDgdwyo3wySefdDju+uuv5+qrr2b69Ok5X8MwjNMusV0hWbNmDeeccw4zZszgn//8J3/4/e9xtGYobm/VnHPOOVxzzTVWp33ttdfyxBNPWOfKZEGdTrQXkHg8nlfK/ME4EByIiNlfWVJXV8eePXuyShCZ5Pbbb+e2225j8uTJ/OIXv8gYPFy+fDm//e1vaWlpYebMmVx88cUdjpk5cyZr167tTvNpamoa9O6F7iR+zJY777yTO++80/o7mfoeMqe0B3j++edT/u7q+IGOaZrIstytfVuCwSBOpxN7my0FsiU5EEzSdiA4bty4tCnwu0PbfqDtQHDWrFkpxyUHgueff35e1xtICEslC+LxON/4xje4/vrrmTJlSlZ1HnroIfbv38+RI0f47ne/y5IlSzq1PpI89dRTBAIB/vGPf7B06VLLcikEkUikQyqS/uJPLyT9KfljXI8SjYeI64Wd2dRfaT/duavnK1N5Y2NjQaa6d3cgOGTIED772c/yt7/9LeOxy5cvx+12M2XKFIYPH55xILhixYpcmz9gEaLSBYZhcN1112G323nyySezrjd37lyKiopwOBxcf/31fPazn2X9+vUZ6yiKwoIFC6itrWX16tX5Nh1ItL/9vij9JTdXrvQrIWydQttZi/wRHw2hWnwtx2kI1eKP+Hq9eb1Nrs9TpuN1Xe+Qhy5XBvpAcCAjRCUDpmmybNky6urqWLNmTcoMn1zJZcGYpmkZH+ZcaGpq6jDqK+RGTIXANE10Xcc0TaLRKNFoFF3XaW5uJhqN0tLSwokTJ9B1nbq6Onw+H9FolMOHDxMMBvH5fHzyySdomsa+ffs4duwYoVCIXbt20dzczLFjx9i+fTvxeJyamhqOHDlCU1MTH374IU1NTRw6dIjNmzcTj8fZvHkztbW11NfX8+677+L3+9m7dy+bN28mFovxzjvvUFtby4n6ej7YtYtgOMzOnTupqakhEonw1tv/5NPaTwg0Rtiz7QBmXGbb9hq27/iIcDjM+++/z4kTJzh+/Dgffvgh0WiUHTt2sH//fkKhENu2bcPn83HixAl27txJPB5nz549HDt2jHA4bK3u9/l8HDp0CF3XrfuJRqOcOHGCWCxGOBy2RvzBYJBYLIau68Tj8f4lzmkIh8OdJvrMhoE+EBzoiJhKBr73ve+xa9cuXn/9dVwuV0pZusynqqrS1NTEu+++y8KFC1FVlT/96U/8/e9/T5mymuTEiRP89a9/5ctf/jIul4vXX3+dP/7xj/zxj3/Mu/1dfTG7s5oaEiNJWZYJBoOoqookSTQ2NlJeXk5zczOBQIAxY8awZ88eKioqUFWVAwcOMGXKFA4ePEg4HGb69Ols3bqVqqoqFEWhtraWGTNm8PHHHyPLMlOmTGHHjh2MHz8egNraWkpKSqivr8fpdOJ0Oq39KyKRCA888AAfffQRPp+P0aNHc+uttzJlyhRUVeWll17ipZdeYv/+/SxevJiHH34Yp9PJiBEjcLlc3HDDDWzduhVVVTFNk6qqKjZu3MikSZNwOp1UVVVRUVGBoij85je/4b333iMcDlNRWsp3/uVfuPLaa9F1HZvNxvgJ44gpAfbtPMjT//UM8z87l0u/+iWKHEOx2WyMHTsWr9eLYRiMGDECRVEYMmQINpsNm81GWVkZDofDWmkuSRKqqqIoCqZpYhgGpmkSj8cJBoPWdNzk53X48GHsdjs+n4+6ujpmzZrFRx99RFVVFS6Xi/379zNlyhQ+/fRTQqEQs2bN4sMPP2TkyJE4nU4OHDjAmWeeydGjRzEMg3HjxnHo0CGGDh2KoigEAgEqKysJhUKoqorb7UbTNFRVzZg+pzvPX1NTE5WVlTmdt+1AcP369QNyIDjQkbp40/r/kKaHOHToEOPGjcPhcKCqp7T3V7/6Fd/4xjdYtWoV99xzT0qdu+++m1WrVnHy5EkuvvhiPv74YxRFYcqUKdx7770sXrwYgIsuuojPfe5zrFy5kpMnT3LFFVewdetWDMNg7NixrFixgu985zs5t1nTDd7e2cDRhhaGldqYOMRAkTNbJcmOKhQK4XA4aGlpwefzMXbsWHbu3ElxcTHFxcXs2rWLSZMm0dDQgM/n49xzz+X9999n+PDhlJSUcOjQISZOnGjldBo/fjxHjx6lpKQEh8NBIBCgtLTUGim73W7i8bglSvlYT+FwmNWrV3PVVVcxcuRINm7cyE033cTGjRsZPXo069evR5ZlK839Y489llL/iiuuYOnSpVkl/9u9ezfjxo1DlSR2vvce1y5fzu+ff54ZM2YAiVhKQ7iWXz7wFCt+ciP/ft/j3H7Pj6hwj8Km9B/3iGEYGIaBLMvWgMg0TWtHw+bmZnRdp6ysjMOHD1NRUYGmaRw7dozJkyezc+dO7HY7o0aNYvv27YwdO5ZIJMKJEyeYNWsW27dvp6ysjGHDhnHs2DGqqqosMSwtLbWC+V197m63O6d97m+88UZqamp4/fXX8Xq9KWXJgeA999xDbW0tv/71rzMOBL/73e+yZcuWlC2DofOB4NKlS/njH//IpZdemv2HMLBJ+8EJURkk7D8W5JZfbSWmGcQ0A2IBFDRWfXMaIyucNDc3Y7fbicVi1NbWcsYZZ7B161Yrxcj27duZMGECkiTh8/mYNGkSJ0+exO124/F4iEajOJ1OFEXJSgD6Om7zxS9+kR/96Edccskl1msPPfQQx44dy0tUkuixGLs2b+ba5cv5t3vvTelMAlEfmz98k18/9TvmzJvNt7/9HYoc5fnfVD9H13VisRgOhwOfz2dZX7W1tVRVVeH3+zly5AgzZ87kvffeY8iQIVRUVHDo0CEmT55MNBolHo9bApScQVZSWsaW/SGONrQwcoiLeVMrUJWO1stAHAgOYISoDGY03eDKe9+mKZRIdSHHm4hGIpQofiocLdzxvUv4aGsNEyZMwO124/f7GTZsGKZpdstt0d85efIkc+fOZcOGDUyaNMl6PZOo7N69G9M0mThxIrfeemvGWWS33347L774IpFIhGlTpvDyunUpaVZM0ySqBdFNDbvi7lcWSn8hmStM0zQaGxspKyvj2LFjBAIBJkyYQE1NDWPGjKEpLPH0/91NxDGSuCFjVxM/v7zxLMZXebu+kKCnEKIymPnn9pM88P99TDiqYzeClMb3UBcdAoqKw6Zw46VTmTu1d3fb6yvi8TjXXnstY8eO5eGHH04pSycqH374IdXV1dhsNtauXcsdd9zBhg0bGDduXNrrxFpaeGfjRt7bupWbf/azFN+9aRropoaEhCJ336d/OqPrOnFN54f/+TZKrB4fIyj22AkaiWScpR4bf75zfqcWi6BXSCsq4hMZBBypbyGmGSjolJqHqYtXEpXdRE07YU3lmO/0WCthGAYrVqzAbrfzi1/8Iut655xzDl6vF4fDwVVXXcW5557LX//614x1FEVh9tlnc7yujt/97ndpjhp407b7C4qi8NGBACHdyTGtijLzCMXGEas8phm8s6uhD1soSIeY/TUIGDnEhV2VCcYNGilLWnsAACAASURBVFucKJJOGY245TA+eSROAgSCIbwe94Bdn9JVu03T5JZbbuHkyZP8/ve/77VZP7quc+jQodS2tBr4khCVnEi6xHw+H3a7nU8OHWOoeQBdriSKm6ZwMVLr1isxzeBoQ/emHAt6FmGpDALmTa3ArsrosSgBigmbHprNYpqMUuyqRLES4Nix4xw8XMs/33yT5uZmDh06xL59+9A0jePHj1up37u7x0pPko0Q3nbbbezdu5fnnnuu0+nf6dLcNzc3W7PCNE3jpZde4p133uk0pU59fT1r164lFAqh6zr/eOcd/u///A8LFixIPTCpR0JTLEzTtLZbaGhooKmpiVAoxM6dO2lubuaTTz7hrbfeQtM09u7dh6/JT+WQEhoZTtR00KiXEtVltFhCSOyqzIgKZx/flaAzRExlkLC3tonv/3ITmp6Y/WVXZWyqzN3XfoaRQ1zE4gYmJtFIFKfTTnOjD02LU1lZyfbt2xkxYgTxeJza2lrOPPNMPv74YxwOBxMnTmTv3r2MGTMGSZJobm5m1KhRNDU14XA4cLlcxONx7Ha7FfDvbWuotraWuXPn4nA4UtLNP/TQQyxdupRHH32UX/7ylyl1fvzjH3PLLbfQ0NDAddddx759+6wdGX/2s5/x+c9/Hkgkg5wzZw4rVqygoaGB7373u+zcuTOxzmTYMK6/5hpuuPHGlHPrhoaJgSKpSNLgGbcl+4p4PI6u69jtdhobG621KvX19YwaNcqy3Kqqqti2bRvjx48nFApZ0423bdvGkCFDGDZsGHV1dVRWVibW4SCBpGC0XscwDFb811aaW+LJBiDLKnZPGaVeG3++Q8RU+hARqB/sNDU14Q8E+XBvI8cbo1SVOTjnjDIUWbLcOXHdRNNPra5XFRmbkrpGJPk8tLS0YJomNpuNkydPUlJSYq1DOOOMM/joo48oKSmhoqKCXbt2MXHiRBobG/H5fMyePZv333+fyspKysvL2bt3L1OmTCEQCNDY2MjUqVM5cOAA5eXlOJ1OGhoaGDZsGOFwGE3TrEWUbrcbRVGIxWI4nU50XbcWAyZdYj0lYJ+eDLPzoJ/PjCtm9NCO290mE0rKdjvOysrUMiOOiYki2XpUYJOfVfK3pmkoimJN7XW73dZUcpvNhs/no7S0lJaWFvx+P6NGjeLAgQOUlJRgt9s5dOgQ48eP5+TJk/h8Ps4880w++OADRowYgd1u5+DBg0yZMoXDhw8TjUaZMWMG27ZtY8yYMdjtdk6cOMH48eNpbGxEVVVKS0sJh8O4XC5rPVJnGEbiudSMpNuw9dlUZQ6fCLLqd7uI6wZRTceuyni8JTzxg7li9lffIkRlMKNpGidaM+Z2RWdfYJsqF2TEl1xIKcsy4XDY6kiam5spLi62FkaOGDGCgwcPUlpaiqqqfPrpp0yYMIG6ujr8fj9Tpkxhy5YtjBo1CkVROHjwIGeeeSZ79uwhFosxffp0tm3bxogRIwA4evQoM2bMYPv27djtdiZNmsT27dsZP348mqbx6aefcs4557Bt2zaKi4upqqpi9+7dTJgwgUgkwrFjxzj77LPZunUrQ4YMIWI6Wf2nt2jUy3AoUb6+oJzPzzuH7du3M3ToUDweD/v37WNkcTGBSISQaTJ16lR27NhBVVUVql3m8KFPmVw9hbq6OsLhMNXV1Wzbto2RI0eiqioHDx5k6tSpHDx4EMMwmDRpEh999BFjxozBNE0OHTrEWWedxc6dOxMr9cePZ8eOHYwbN45IJMLx48eZOXMmW7Zswe12M2bMGD7++GMmTJhAOBzm+PHjzJ49mw8++ICqqirKysrYt28fkyZNIhwO4/P5mDJlCgcOHKCsrAy3201DQwOVlZVEo1FisRjl5eXWotjkuo9CTj83TZO4dupZhM4HOppuWIOlylIb8z4zjBHDqwrWDkG3EKIymGlqaiIcDudURzcSX+ikq0GWJGyq3OUK/P5EMrBrGAaKolhb0iqKQktLCw6HA8MwiEQieL1eAoEAqqpit9utFC/xeJxwOMyQIUM4ceIELpeLt3Y1s+aN3QTidlw2uGxuBZcunEpdXR0ejwe73U59XR0eXSdmmuguF1VVVVa5pIC/2U/l0GEEg0Hi8TgVFRXU19dTVFSELMv4/X7Ky8sJBoNAYp96v99vrXdJtjkajSJJEg6Hw8pAkLz3pKtvIE6+iGsGmm5YHYwqS6iKjJzl81daWorb3dGCFPQaQlQGK7lYKZ3W1w3iWve/3O3p65X0heDTk2FufeYjTAMkGR769owOLrB07q9Ta1RkZCm77AODkXTPgaYnxEQ3QJJAkSTUbgxmVFWlsp3bUdCrCFEZrHTHSoFTX3prZbOBFW8xzVaXmFxYd8dAIhFTaWbKmGLGDvN0KE8nKoapY5g6Mgqy3HGP+tOVhJiYlmUsmSZ2m4KSh9tVWCt9SlpREetUBjCaptHS0pLxmLbi0fZ3chSZ/L9dTlgpmm5YAX1dB5vKoJ1hk8mqGj3UzYhyZ+6WhphOnEKmIHxb2n8W2Vi8wWBQiEo/RIjKACYYDGa9ZWv7350hyxJ2WUFRTsVbYlpihDnQ4i3Z0FWnJcsSppmbS08sfEyQbRA+SfvXsnm/NU0jHA4LYelnDM4h6GmAYRhdWindRZElnHYFuyojAYZpEo3rxOI6hiE8opkRpkpcM4jEdEtQVFnCaWt9ngocYwoEAgU9nyB/hKUyQAmHwz2+g5+qJKyTpDtMM0w0Q8844jzdsSyV0/C9SQbhk+OO7gbhk2SziZyu68Ja6WcIS2WA0p3gfHeQJAm7KuO0KaitnYOmt45EdaOL2gObZIeWrXYnRf50c33phkkkphPTEoIiS+BQZRx2pUddpsnPp7e+C4LsEJbKAKQvcnRZ8Rajk3iLIuU1i2fwcHq5vrINwneXthNLMhGLxawtjQV9j+gJBiA9FUvJhrbxFllqjbdohoi3MPiC9Oncq6ZpEovrROI6cb01bqLIOO1KwQQlSbZuxEhEZCzuLwhRGYAUSlTyicmoiozDpqAqiWC+ZphEWoP5PR3r6U2SfVpW9zR4bhvovEPvEIRXJFz2roPwPf1MCFHpPwh7cYARj8cL5vrKN5iciLdImIpkucLiuoluGKiKVPBRa29gxUW68d4kLZW2hspgyDAApzIvGK1TrJNurmxjJj2dWFO4wPoPA+9bf5rTl66vdEiShMOm4GwNzBqmSbw1mK8XOJif64g31+OTi0Hbd4IdTpNYwNLOOOno/sqmM816DUwn95LtBmbdtRTaBuFNQJHBZT/1WfcHkvcvrJX+gRCVAUZ//OIkO6xkvMVhOxVvicR1orHCxVtyHfF2d4TcpcUiSSClRk/Mbgbqs+3w0y0aNIzMwt2dLQIMIxE3icZ1DNNMZLNWZJx2td9OyhCzwPoHwlYcQCRN/Pbk4rJJN7LNx+3Tvo6qJFLpxzQDXTfQTRM9rqPKCZdYPu3sLfK5fq718r3XQr5P7VfCm6aJTVV6fF1SIT7v5KxI4QLrW/rnkEPQKelcX7mMRNMd1xMbXtnVxIwga31LqyslrnXtEutpQck2vU3i/13XyWeNSm+JZ1f33NlKeLdD7ZGV8O3pbKO4dOWZENZK3yNEZQBRyHhKb83QkiQJu03BYVOQJQkTWuMtWsHjLbm2q7B07vrqTzPh0t2z1vp5xFv3N1FaY2R2W2FT9+fj5ku6+LoS9v7oHj7dEHbiACEWi3XpO8+F3nYtKbKEYldSUnlENQOlNVlld/dv6S+kW6PSn2d+ddyoLRE36amYSbaLGdPVbfs73TGaphGLxbDb7d1upyA/hKgMEPrjrK/uUIh4S29zat+ZU66wDgygxfRGq5jolsuucFtK9wcikYgQlT5kcDxFpwG9nZalp8kn3tIfGQir6duuhNdbZ3QlV8IPBEHJ1n02WAZgAxVhqQwQkvuvDyaS8RbFMNFaR85x3UA3jB51w/QMfWeqZONSsvaENwGJPrMMe2OWm67rGIZx2u5a2teId30AoGlaxnhKf3QZ5YIiSzjsCg4rn1gi3lLI9S350tUMsL5MeZ/pmu2D8LLcM0H4/kYsFuvrJpy2CEtlANDVFyRT4r/+vragLUqrdZIcVQ+EeAv0z5T3vR2E7w1yed5isRhOp7OHWyToDCEqA4Duur7y7YQfffRRAG655ZYeOX86EkFjyVqEpxkmekwvaFr17tJ5sL7/ROkHcxA+l+dtsMUgBxID/0k7DeireEp7C+jZZ5/loosuYvz48fzwhz9MKWtsbGTZsmVMmjSJOXPm8PLLL2dd3tl5k/EWuyrzhc8v4OixY8S0nl3fkilHVtoOzTQzBuk75hDrnjuvq3o9FYR/9NFHrcFFrvTlGh3h/uo7hKgMAPpKVNp3iMOGDePmm2/ma1/7Woeyn//859hsNrZu3cqTTz7J7bffzu7du7Mqb3ve9qiKzAUXLObvb7xe0HhLulXbOVtfkpTRUGl/nZ5I/RLrbE/4LNLRZyKdIOQysHjllVe6Xbf9oGTevHkcPXo067YbhlHQdV2C7BGi0s/RNK3frMq++OKL+dKXvkRZWVlKm8LhMOvXr+enP/0pHo+HOXPmsHjxYtasWZNVedvzdsbixYvZsGEDbqcNmyIjmYmYQUtM6/b+LV11tp0nb0z8NttkKE789E1MRdMNIlENTTu1Et5ZoCB8uvqZBgDJgUNNTU2nA4ts6qYblCSfgVzaLqyVvkGISj+n0F+MnoiD7N+/H0VRmDhxovXatGnTrE6hq/L2tBeJ+fPns2PHDpqbm7GpMk6Hgtqa4LCn1rd0KVStGYpbd7FPvljQNqQjZU94Wmd0te4J3xOZCdq+F+kGAG0HDl6vt8PAIdu6nQ06ICEqr732Wk7tFqLSNwhR6efkGnDMxvdeaEKhEEVFRSmvFRUVEQqFsipvT3vhs9lsLFiwgDfeeMMqt9sUnDYFpR/kE8s0nbiQ77dhmERjqenok4tIe3JWVzYDkVwHDrnWTQ4s/H4/kN37KoL1fYMQlX5OrqOtvph26/F4CAQCKa8FAgE8Hk9W5dkwdepUdu3alfKa3MvrW5Lvbdv+rDdckwNhJXyuA4dc63Y2sOjqvReWSt/QP55IQVoGwkr6CRMmoOs6+/fvt17buXMnkydPzqq8PZ11Fps2bWLhwoWdHq+0bh5lU2QkQG/dHKy78ZbcyBxPyVfkeyII3xPkM3DItm77gUVXlqEI1vcNQlT6MYZh9JsgPSTcCZFIBMMw0HWdSCSCpmm43W4uuugiHnnkEcLhMJs3b2bDhg189atfBeiyvP15o9FoiuuiqamJffv2MWfOnIzts/ViPrGOn0thO/jkSnhNL3wQvidIDhw++eQT67VMA4fO6nY16Mg0sEjSfl8WYa30PoNWVFatWsWqVav6uhl5oet6Xzchhccff5yJEyfy5JNP8tJLLzFx4kQef/xxAO6//34ikQgzZsxg+fLlPPDAAymdQqbyTOcF2LhxIwsXLkRRlC7bmG28pbti3b4/PxWiL0xHr+vGqSC8CbLUs0H4TMRjBpEWHX9TjMP7gxw5FKLhRJhAIJx2YPHoo492OnCA7g9KIPuBRXuEqPQ+g1ZU2uPz+bj88svxeDyMHTuWF154IasygCeffJLZs2fjcDi44YYbsi4DGD9+PLW1td1qc3+yUiCxsv7IkSMpP8nV9mVlZfzmN79h3759bN68mcsvvzylbqby9uetra1NWcX/2muv8aUvfSmntmaKt+hGIdPLtH5GeZ7OCsK3plbprSB8Z5imSbMvxtHDYaIRHVmRcLoUVLvM4088zpQpZ3RrYJHPoCSXgUUSSZKE+6sPOG3StNx0003Y7Xbq6uqoqanhkksu4ayzzmLatGkZywBGjBjBHXfcwWuvvdYhrXamMoAlS5awbt06li9fnnObT9cvRPsO3+Vyden2SEeh84m13VsF8rdUknvCx3UTSUpok6LIPb4nfCb8jXEaG6O4PSqqLSFoUusU6h98/0d8/6YfEg5plJU7KCk/tW9JcuCQjltuuSVtyp+u6r722msdBirZkM93KOnpGOgej97mtLBUQqEQa9as4d5778Xr9bJgwQIuvfRSfv/732csS7J06VK+8pWvUFFR0eHcmcoALr300g4ri7Olr0Vl/vz5zJ8/v0/bAIkRrtvtzuscPR9vyV0A+mMQPh4zaPLFcLvVtG2QJAm3R6XJFyMe651nNJ+BRaHIx2ORj6ckH29HX3BaWCp79uxBVVWqq6ut18466yw2bdqUsawQLFy4kGuuuYbm5mZKSkpyqptJVHo6AzHAeeed1+vXN+IGekxDsavINtlyAZqmaQXvJUkiFoths9mIx+PE43HcbjfBYDARU7HbCYVCeDwewuEwmqZRWlqKz+dDVVVsNhu+xmaKSkoI+AMYepzKykoa6k/icrmw2Ww0NzczdOhQGhoa0DSN4cOHc/z4cbxeLwDNvkbKbSrHm3w4mpsZXjWC48ePU1xcjGmaBINBqqqqOH78OKqqUlFRQX19PUVFRURjccItLZSXD8Hna8Bms1FeWkJjwI/X6yUej6NpGmVlZYkFnzYbTqeTlpYW3G438Xgc0zRxu93EYjEURUFRFEzTtNxDstw9YQoHNWTllLU4e9bcTo+TJAlZSRzf1lopNEnLsG2MLRcKOTDLx2ORj6ckH29HX3BaiEowGKS4uDjltZKSEgKBQMayQmCz2Tj//PN59dVXufrqq3Oqmymm0tczgDq7fnJzJEmSiEQiyLKMYRiEw2GKi4vx+Xzouk5ZWZnVQWuaRnNzMyNHjuTg/oNEmyJUlQ3j0xO1VI0bTjQepam5ierqag4cOIDD4aCqqoqjR49SWVlJOBwmGo0yevRojh07hsvlori4mKamJhRFIRKJEI/HKSoqIh6PW52tw67iUBUiqoImSeiGhGJzYrPZsdtteDwebDabNa3VZrNRXFyMw+EAwCzWUaIRSoqKsBcVY7fbKSkpwel0WhtE2Ww2vF4vsiyjqioOhxMDBSQDWbEhKzIOm4rNpgCm9f7FYjEikQherxe/34+qqui6zsmTJxkyZAhNTU1Eo1FGjRrFwYMHcblcuN1ujh8/zujRozl69CiRSITq6mr2799PcXExbrcbn8/H6NGjOXHiBACjRo2irq6OoqIiVFUlEokQCTmJxoIEQgpOh5fq6im4XC40PZ4QEunU7DO7UyEYiPeoqOQbVyykqCxduhSA999/v4PlkKks6Q3Zvn17B2/InXfembbswQcfBBLejocffliISn8i+eVsi9/vp6ioKGNZoZgxYwbbtm0rqKj0FMlrRqNRa/ZZOBzG6XTi9/uJRCIMHTqUTz/9FLvdjsvl4siRI4wZM4YjR46g6zqTJk2itrbW6oQDgQBOp5NoNGqNqj0eD06n0/q/2+1m3OixaK4YrhIPRa4iPFVebF671YkNqRhitbOystL6f7K8rSU4ZEji2LZuyaSVAVipQkpLS6x4i8vtAhJuqOLi4oSbp43bLbk/h2maeJwuoieO4/C6cVVWoshqp/t3DB8+3EpHXzYk0ea26ejLS049Z51Zsm2fw6FDh3a497YpT8aMGWNdM/k5lpaWWm0eMmQINpsNCZlYXEeLyyiSm2hYIqjHCAVDhAIGLS2NIJkUeXSa/MepGl5BNBrDH/AxetR4amsP4nA4GVJRxfG6YyiO0WiaRjyesPgCgQAOhwO3242maTgcDhSlb6ZC97ULGfL3lOTj7egLTgtRqa6uRtM09u7dyxlnnAHA1q1bmTZtWsayQrFhw4ZuBfsK/YXQNI1oNIrNZqOxsRHDMHA6ndTV1VFSUkJTUxPNzc1MnDiRm2++mW3bthGNRikrK2PZsmUsWbIEt9tNOBzmwQcf5O2336asrIyf/vSnnHvuuQwfPhyAK664gg8//NByxVRVVfGPf/wjxSJ0uRId+A9+8AP++c9/Eg6HGTp0KMuu+hZXXvJV7C4HNrcdqTUGsmXLFh5//HHmz5vPv/7rv56KkNNOfFv7rVw6sE73b4nqKKqMPcP+La0786YN0ieD8MmYSW8E4Q3dRNMNDN1E10w0zUQ3DAwNNE3GMDTACZhENHA6EqJjs4HHVcJxLUJJsRebTUZSZIaPGIrTJbe2fiKmaVJUVIph6JgGVFUqFBcXp7h8gsEg4XCYSCTCsWPHLDegpmlMmjSJY8eOUVxcjMfjIRKJUFZWhq7rrdaco6DvTX8QlXw9Jfl4O/qC00JUPB4PS5cu5a677uKZZ56hpqaGtWvX8tZbb2UsS6JpGpqmoeu6Nb9eVVVUVc1YBomU3rt27WLBggU5tzvXmIphGLS0tGCz2WhoaKClpYWysjIOHjyI1+vFNE0CgQATJ06kubkZp9NJaWkpQ4cOxeVyUVFRYblq7r77bsaNG4fD4WDfvn1cccUVzJs3z5ry6fF42Lp1Kzt27OCb3/wmZ511VsoU0Pvuu49rrrmmy3v8/ve/zyOPPHLqOl+9grPnnc1ZM89Gtp3q0NeuXcvTTz/N3XffjSS3S9HR1qBLzsrqRGigbaqV1Pcvub5FNUximoFmGBiaga4bHTa5kiQJTBMDExmzQ4zeNE3iumllDwawKYXZvVLXDXTNRG8VDV030HUTLW5iGFg7Paa7iiQntm9WFBlZlVEVUFUZRZWQFQmXWyXQHEdWdO5/8C7effdNmv3NjBo1hhXf/wkLPrsIVVFZ9r1vsm3bFhRFRZJODRwAJk2aRGNjIz/5yU/YtGkT5eXl3HrrrSxZssTaXiA53TcSifD1r3+dmpoay5opKyvjz3/+Mw6Hg2g0yrBhw4jFYuzevZv/+q//Yv78+dx4441Zv2d9vV99ITwl3fV29AWnhagAPPXUU3zrW9+isrKSiooKVq9ebVkjmcog0UHec8891t/PP/88d999N6tWrcpYBvCXv/yFCy+8MKf59UkyiUokEiEQCOB2uzl8+DCKouBwOGhsbGTMmDHE43FcLhcej4fJkydjt9stoYNTbhE4ZTW0pf1qZkmSOHjwIJMmTWL9+vVs3LixQ0bZlStX5nyPHa4jS3x6vJaZtnNSXr/yyitZvny5Jc4pnXNn+8d3IjTtj+ksEaTcOgNL1yXiemIBYkwz0HQTmyqjyJYpBJhIrf+SaHrClWa0mjGqlBCTbBYummZCLCwrQzfQtVbro9XioAuPqCxJKIqEorb+Tv7f+jtz5+rx2mj2xTFMjWHDhvPMr/9IVdUI3vzn3/jZbSv485/WM3LEKDBNfnzzXdy4/Hps9o7nbJvKPjnwmD59OpMnT05x2ZWXl6OqKvfffz/XXHONtQreNE0rHqZpGocOHeK3v/2t9Z1bunQpiqIgyzLFxcXd+n71FoXwlHTX29EXnDaiUl5ennZqb6YyyLw6v6uV+2vXrs1qxN4ZSVExTZNQKISu6xw5cgSv10s4HMY0TbxeL1VVVbhcLlwuF+PGjQNSYwl2e/cCqbfffjsvvvgikUiE6dOnc/7551sZZSdMmGAdN23aNN5+++2Uug888AD3338/EydO5NZbb804k6yz67Rn+vTpPPvssxnb25nQQNdi05lVI8sSTkW14i2GaRJts74l9dwSup5Ya3JqT3gJW7tO3DBaBUM3LYtD08FoY3F0hSRLqIqErEoosoTaKhiyIqEqMrKSnyVks8uUlttpbDS58bsrErOvgM9//v9h5IhR7Nq1nRHDR2IYJm6P0qmgJFPZd2fgIUmSNRkiaUkDloV8zz33cO655+L1eqmvrycQCKDrOocPH6ayspKysjJsNlvKM18oS6W7Hot8PSX5eDv6gtNGVPoKt9vNBRdckHO90MEAB/66D9dED4f8CUvk1VdfRdM0br31Vmw2m3Vs0tLIeSvcLnjggQe47777+OCDD3jrrbesqbpFRUUp52yfUXblypVUV1djs9lYu3YtN9xwAxs2bLAEL5vrFJJ8rBpVllAkGU03iBsmmgF6TEc24URDA8d8jYyJmVRWVWHoJoZhIgOmKRHVWl1gBmi6iZkhc3IyPiMrpywKRQFFTQiHLLe6qHohVUtxWeLZavLFkBWwORUaG+o5dPgAo0aOpyWko6oyjz3x7/zH4w93GDikS2XffuDRlmwGIdOnT+e3v/2t9XdyYoJpmjidTjRNo76+nuPHj3PGGWcQjcaoP2qjyRdi8tRyZswuz+v9y8djkY+nJB9vR18waEVl0aJFfd0EAJ577rmc64QOBvjHDzeyz76fkkAR59w+n9IJZbz++uvYbDZsqg3MxAjmJz/9CX//+98pLy/ntltvs1YdP/vbZ/nzi3/m490fc9mll/Ef//EfKdfIte6aNWt47rnnmDtnLvX19Rw5coQRw0cAEPAnMsomO82ZZ8+0rnPlFVfyyiuvsHHjRr71L99Ke8+yJHPu7HOt6yz71rKc37esad+vZGHVqIqMhEFUT6R5qa+rY/3f30TXdT7ctpPPnncxQyqGY1PTd1qSBLKSmBSQdEcl/58Uk4wDADPhCuvyftLwy18m9pr/8Y87X9Xetp3FZTZcXoVwUKPJF+a2lT/i4osu58wZU3B7Ve686+fWwGHdunXccMMNvPbaa4wbN45gMJhTGvxcByEd2ytZM/tKS0sZPXo00WiM3/3qA+qOtBBumIDbfYzJM0q57YEzuy0s+Xgs8vGU5OPt6AsG7Yr6RYsW9RthyZXa9w8TtUUZcqQMT4uLyCeh1I6jdcvBO+68A7vdTk1NDf/5n//Jyp+vZPee3SAltm5dcfMKvnZVx61bAe644w7sNjs1W2r4zyda67bZM37FitS6Sb/2hAkTkCSJP77wR6ts566dKVMi25PN3hftr9OjmJ3/GIaBYRrohk7c0IgbcWJGjIgeIay3ECWKSZxoOMLhw4fQdb01DqJz8uSnqKaGjIGqgtMh4fYoFJfaKK+wM3SYg8oqF0OGOigtt1NUbMPtUbE7FZTWAL5h0Ooay/FH79cnngAAIABJREFUy+7HMEhco/Xvhnofy5Yto7r6DObNnctLa15KuOTiJv/9zLNceuklnH3OZL72jS/hLXLy7//+AB6vDQmJLR9u5corr2Tq1Kn8859vMmvWbF7/37+ixU3iMY2GhobEfvPnzuH//HkNzU1+3C4P8ZjB3LnzOHzoCPGYQTxmcOb0s3HY3ciSjcu/cgWzZs3mfzdstMqTP1o8ux9Dh73bQ+zfXkTAV4Sn/CSRiMHuj5r46H1fzz5bPUB3vR19xaAVlYHMsLOH4ytqxnQn+ruSz5SlzJqRJImWlpaU7Vvnzp3L4sWLeemll5AkiUsuuYSLLrqIsvIykBK++ORPS6SF9a+u56c/+yneIi9z57XWffklJFli7ty5xOIxPF4PJiab/r6JtWvX8rnPfQ6P18PcuXN5/g/P0xJp4f0P3mfDhg1cccUVSLKEP+Bn0983EY1F0Q2dl195mXfffZcvfOELKW2QZIkGXwPr/u86wi1hDNOwrrNgwYIOx+b7gwSmZKKjEzfjxM1WwTCiRIyEaESMKFEjRsyMo5kaGjo6BqaUEMZ4i06wXkMLmQwrHWHNVlJUhcqJw3BUQsVQG0MqbJSWqhR7ZdwOsNtMFNlExkCWTCQZZKUwP5Kcw4/U+tP6911334HdbuODD7bw+BNPcMedP2fv3t1IEgyrGsb3b/pB66g/yq+e/hV2u806x7CqYfzg+yu46sqrEmOc5MQFCX73u+cwTZM1/+dlHnsscd53332HM1oHHl88/4u8/nr6/ebTDUJMM/ufwwfDaHENV7HfMjhjMYMDe4NZfw/7y8D0ueeey2lDu75m0Lq/BjKlk8pZ8rOv8MHG9wmVtNDijqJEbSnTYD/55JOc/dZJuvJ5S5LE7373Oz788EMMw2D79u3cc8891mhp9erVnHvuucyYMYOysrKUjLKapvHwww+zb98+6xq/+c1vrGtde+21zJkzhxUrVljXue222zAMg1GjRnHPPfdw4YUX5vyemaaJQWJ2lMGpfWgMTEzT6GrSlJUwUZJkZCRrD3oZGS1qEG7WMDQVuwSKS6a8agwXF1/M8aPHqBw9Cu/QcqKmyUmzhSLJgUexIyd7uEQLEz8mSMmXZNm6Dt1Mq5ILSbePqsqEw2FeffVVNm7cSElJEfPnz2Px4sW8svZlVq5cyZIll3DrrbcSCoVYsGAB3qJTnVpzczNFRR7mzZvHR9u28t5777Ft2zbuvfffiMUj/O/r/8sXvvAFfvX/ruaRRx7hnHPO4e//+Dsrf74Sm13mwi9dwOrVq/nWsn+hubmZLVu2MG/ePFRVZd26dbz33rvce++/dZgEkI21a5omzc3NuIp9OD0xDF0h1FyBIoPdLjP+DG+X50jSHwRlIDIoReXaa69l48aNhEIhqqqq+NnPfsa3v/1tIJG8bdmyZWzYsIEhQ4bwwAMPpPgrFy1axDvvvGNNvx05cmTafbYzXact7733Hvfeey+LFi1Km6W1PUOmVDK96CwrTcfOnTs5evQoQ4cO5fjx4zQ1NfXY9q0VFRWsWbOGhx56iGPHjvHYY4+lHDt06FAuvvhiLrzwQi677LKUsoqKCtavX5/22s8//3zKsWvWrOmyvXBKNEzTxMTs+DuLc8i0WnqtoiEnJwRLErLU0WjXYgYhf5x4JJFZQFIkPMU2HB4VzdAYNryKEcOrcNs96JJJsxahRYsT0GOEDY1imxOPzZ7oDI1WYWs7nE7O7gPQ9cTvVlNAssyKnlko2dXAora2lueffx5FUVi3bh2vvfYaAA899BALFy60Bg7xeByv12sNHLZv346iKDzxxBPccsstzJgxA5vNRnV1tTXwePrpp9m8eTN+v7/LQUhbOnsf4vE4wWAQm83GgQMHUBSF0tJSzphaztiJMvt3hZBkGadTZvKMUmbMLi/4eylIZVCKyu23385///d/43A4+Pjjj1m0aBEzZ85k1qxZXSZvg0TG0c7EIZfrtOWFF17gxRdf5Oabb87pPhRFsdIynH322WzYsAHDMPD7/cRiMfx+PzU1NUyYMIFAIMCJEydwu91dTqEs1J7xO3buYNiC4dRF6hnurOScsrNR5e49UoZpWCJhkOh0U/7uguTK9vaiAYlJALIkZ50EU9cNWprjRMKtYiJJuItUnEWnMveaZptFkKaBqqhU2D1ElTiN8QiaodMYCxPUopTZXNgVNSUsZrYRF7MT/02HCWkFtmq6GliMGjWKI0eOpB1YJAcOyfLPf/7zKedtm8r+D3/4Ay+//LJV94UXXmD58uW88cYbXHbZZRkHIUDrVgOJJJ3xeBxFUThy5AilpaU0NTVhGAYTJkxg5MiRFBcXWwPCH6wcxa6tjTTVuzhjamnes78E2TEoYyrTpk2z5ronYxCffPJJVmnuC3Gd9lx//fVcffXVTJ8+PafztxUGSZJQVRW73U51dTXz58/HMAwURcFutxONRtm+fTsjRozg3Xff5fjx4/z/7L15nBTVuf//rqWr11l6ZpgFBsYZ9lUFRFEM/jQYIVGjMbgSvPK6fNW45EKiAbOYbyZuX03iDVFyc+/LGDWJyUXFRI2aRNCIxI1FNmUdh232tfdafn80XXTP9Mx0z/RsUG+YF0OdU1WnejnPOc9zzuf57LPPaGxsRFVVamtraW9vJxwOU1ZWllbO+GS88dYbvF+8jV/u/TW/+/xP/GLfr1j+0d187qtOWv9kADxCWI8Q1sIEtRBBNYhfDRDUQoS0MGE9gqqrqIaGZugnDYphIAoikiAiCxI2UUYRbdglBafkwCk7ccgO7JIdRVJQRBuyKCOLsjkL6akj1nUDf2uYluMhQj4NAXC4ZbzFDpzZts7nC5w0YiewSzaKHVl4bS4kQSCia9SG2mkI+1D1k5k8BUFAEEUESUKUZUSbDVFREGw2BEkCSTINyYnGRWczmoYRiaCHw+iRCLqqRo/1kHq6Y1kmBhbJ6E2+ecMw0HWd9vZ2Ghsb8fv9HDx4kKNHj3Lw4EHef/99GhsbOXDgAA0NDdjtdkpKShgxYgRTpkxh+vTpuN1ucyNlDFEUmHp2Hl9bUs5Zc/JTNiihUIhly5ZRVlZGVlYWZ511Fq+99ppZftFFF+FwOPB4PHg8nk7fm56k7OPp6Vox3n//fS6//HIee+yxlJ5hMDkljQrA7bffjsvlYtKkSZSUlLBo0aIuxdt27tyZcO6qVasoKCjgggsuYMOGDWnfpyNnn30269ev56677krrGbqbbcRSsD755JPouk5DQwPvvvsu//Zv/8a5556L1+slJycHm82GpmnU1tZSW1tLdXU1O3bs4OKLL+a+++7jww8/ZOPGjfz1r3/li1/8Is3NzdTV1dHW1kY4HDZTwMbnjG9obGDHpzsRx9nw6QEiuopfDdISbuX+nQ8RiARMo+GP+E8aDT1MRFdNo6HHGQ2B6IxCFiRkUcYmythFBYdkxyk5cNlcOCS7aTRsJ4yGJGRGqDDoi9BcEyTQqmIYBjaXRE6RA49X6XpDYey+STpzt02hyJFNluxAAAJqhJpgGy3hoLlBMvklhaihiTM2gs2GIMtRYxNvaGJuNU3DUNWTxkZV0WMGKCbbEvcaGbpOTmsraiTClr/8BeOEGy5+YJGumGmsfnyu+kgkQjgcZtu2bVRUVFBXV0d1dTXt7e289tprjBs3jurqajZv3kxNTQ1VVVUcO3YMXddRFAWXy0VJSQkzZ86koKCAs846iwkTJuB0OsnLy0NRlJTe+3Q3PqqqyujRo9m4cSMtLS1UVlayePFiDh06ZNZZs2YN7e3ttLe3d3KPx3tDnnvuOW677bZOfUw83V0rRszb0VX5UOKUdH9BdEPRL37xC9577z02bNiA3W5PSbzt4YcfZsqUKSiKwh/+8Acuv/xytm7dmtTH29V9MkVPX4YHHnjA9Ft3DJivWbOGn/70p2bdl19+mRUrVrBy5UoqKiqYMGEC//Ef/8F1111Hbm4u9957L2PHjqW9vZ1f/OIXCbGPF198kWuvvZYVK1YQDAb5zQu/JX/6CHJbs1BtGhFFxRaRCNlVDE1n07H3mVM8C+PE7EKMxS/SiGcMFOGghq85gn4iWZdkE3Hl2lDsPW80i85QTrqwOnZwoiCQozhwy7aT8RY1iF8LkW1z4pZT2+RpxlegswstjViNoetgGOx+4AFadu9mTm4uD37/+9z7wQdoixbxxhtvsH79egBTdVhVVdPVGstp4/F4qKmpIRKJ4Pf7aW5u5vPPP8fv9+P3+7n44otZtWoVK1asoLm5mb/97W/85je/IRQKmTOSw4cPs2DBAtxuNyNHRlfSxQRJIVFROh06vg+92UnvdrsT9px85Stfoby8nI8++qjHvTPdydzHpOx7Q8zbkUxtYqgh9DAiGVpJ0nvJrbfeypQpU7jwwgu54IIL8Pv9Ztljjz3Ghg0b+POf/5z03Msuu4wvf/nL3HnnnSnfJ90ZSVc0Nzd3aiuQcrA/U+i6TiQSMfOkXLf8BtRzYNS0UnQMNEnDFXDidwTICrg5N2sWX56+kH379kWn9W4PdXV1lJeXc/z4cQzDoKysjKNHj5KdnY3NZsPn81FYWEhzczOCIJCXl0draytOpzO6nDcSwe12m/L5iqKgaVqCpHqsA0ll9BoJawRa1cQgfI4Nu6vncZZhGKi6RlgPIxjgwIYgSwg9dGAhLUJzJEjkhBtMESVyT8RbUiEWWwDMPTKSJBEKhaLGWRQJBALYFYVAIBDNI+N209zcjCzL/Oq//ou248dZFAjQLoq06Tq/+/hjdjQ3k5OTw+133snZZ59NeXk5lZWV/OlPf0q4/7Jly7j++uspLS3l4Ycf7iSbc+edd3LXXXcRCAT4zne+w9tvv43X62X16tUJqYDXrVvH22+/bSbe6s+Ec7IsJ6QK6A01NTWUlZWxdetWJk2axEUXXcTOnTsxDIOJEyfyk5/8xFwptmXLlk59zKOPPsrGjRuT9jHdXWuI0+UbdsrOVOJRVZX9+/ezbNmytGXu0924lyym0lt6GmUNRPbHWDtiMzBFUfDm5mLMttFqi600Ewi4wtHfsgWmjJvCiPwRjCiI5v/QdZ1Ro0YhiqKZY8PpdFJYWIgsy6a7I2Y8DMMgEonQ3Nxs6im1tLRQWlpKVVUVoihSXFzMoUOHKCwsxOfz0dLSwrhx49i7dy92u52RI0fy+eefM2rUKFpbW/H7/VRUVHDw4CEkQ8GhuGlsrKcgv5CQ5sMQVcY4x7D3wGEzv0t9fT0lJSU0NDQQiUTM4LXT6USyydQ31VNcVMTntU0YAow6Ue7xeBAEwWzzkSNHMAyDUaNGUVtdjSPLRWsoSFtrO8WlJTQcOY5bsVM6chRVVVUUFBQQCARobW1l7NixfPbZZyiKQklJCYcOHaK0tJTW1lYCgQBjx47l4MGDuN1ucnNzqa2tpaSkxFxZ5XK7CYTDOEQRQRTR/X5QVeyShB34zqRJqHY7Y664gjFXXhmVppFlfvazn3UKzsdTWVlJZWVl0jKXy5VWvvnuPsMdP+Ppfub7qvkViUS48cYbWbp0KZMmTQK692akm/QvXc/IcOCUMyq1tbX84x//4Ctf+QpOp5O//e1v/P73v+f3v/99j+Jtzc3N/Otf/2L+/PnIsszzzz+fMKJK9T6ZouMXYijkiwd4+onfsPyjuwmFW4lGq0+W2USFmd6zEuqLomjqecUHUuNFL2PKtWeccYbZccSvTho9ejSQqK4cS1oVT0FBgZl9sqCgAEEQKCwsRFU11CAU55RF3W6SQG5+Nrl5HlQt6uZxuVyMGjUKSZKicjg2Gy6XyxxYOBwO0xAaGAhSVPRQKShAI/p7UVFRNBGWEE3w5XQ6KS4uNg3q6NGjsdvt6IZBS9BHRBIoPGN0NKbkdjB5yhRssmwOZGRZ5pxzzkEURURRZOTIkZ2eOS/v5DLZ4uLiTq9N7HV0ulwwYgSOY8dQ4paeK7pO3rhxSTXX+mPgkk6++Y73TrctfWm7russWbIERVFYs2aNefzcc0+mWF66dCm///3vefXVV7nzzjvTTvrX3bWGK6ecUREEgSeffJJbb70VXdcpKyvj5z//OVdccQXQvXhbJBLhe9/7Hnv27EGSJCZNmsRLL71kBvYXLlzIhRdeyOrVq3u8TyboaFQ6iuwNVkphWZS5f8p3uX/nQ0T0MGFDRRFlbKLC/VO+2+tlxZlAEISEPO0QDcIHW8HQDBwOJzanhCvbhmzmazkZB4vvWGNCnfEZHfPz8033l82lIAoidrsnGieyyQkdPEQ75fhj8dd3u1youmbGW/yGSkjQyBYk3LaT9TKVC2Tu3LkYhkH2W2/RumsXeiSCqChkT56M98wzk57TH5+x3uab74pkixFi9Lb9hmGwbNkyampqePXVVxMEXJPdI9aGvib9S8czMlQ5LWIqw5VgMEhjY+a1ijI1+oxoEbY0b+V4qI5ie9/2qfQHnYLwiogrJ7UgfHfouoFmROVeREFE0aKdvqh03fH02FZNpTkSIHwi3mITJXJtDuxS76/ZFYau07RtG/6DB3GVl+M988wu40ED5WLtL1wuV8LsNlVuvfVWtm7dyt/+9reERQPJvBnLly9ny5Yt5uDzuuuuQxAE0xuyaNEiNm3a1MmwpHKtIUyXHwrLqAxhQqEQDQ0Ng92MYYca1vG1RFBD6QfhU6GTUdElMAwEm9znDtinhmmNBNBOfC+dso0c2YEsDg/Z8xhDxRh5PJ5OMY6eqKqq4owzollP4921v/rVr7j00ktZtGhRgjfjxz/+MQsWLDDrNTY2csstt/Dmm2+Sn5/PQw89ZKp2xHs76urqerzWEMYyKsORcDhMfX09AE899RR//OMf2bNnD1deeaUZRA2FQqxevZp33nmH5uZmysrKWLVqFRdffLF5na5yxiejY87422+/Pans9pYtW/j5z3+edmrX/iS6E14l5I/uqREEAWeHnfCZoJNRMWTQdQRJQughs2JK1zcM2iMh2tSgmWfFLdvJtjkQh0BHPZzIzc3F5XINdjNORbr8IJ6ymx9PBeJHSUVFRdx9991ce22ilL2maYwcOZJ169axZ88e7rnnHm699VaqqxN3tldWVrJ371727t3bpUGBaM74zZs38+mnn/Kb3/yGRx55hO3bt3eq9+KLL7J27dqEXfmDha4b+FtO7IT3qyBEd8LndrUTvg+c9N+fPGZKt2RoDCYKAtmKgyJHFi5ZwQDa1RA1wVZ8kXBG7tGRpqYmli1bFpWrnzMnQValN3W3bNnC0qVLWbt2bb+0N1Xiv0MWA4NlVIYwsRU/AIsWLeKyyy5LyO8NUZ/xypUrGT16NKIosmDBAsaMGZPUEKTCxIkTEzZwxnLTd2Tx4sXcfvvtaUm79AfmTvi2EzvhnRI5hQ7c3e2EzzSx22R4Xi+LEnmKi0K7B0WU0AyDpoifmmAbIS2S0XvF55Rfs2YNq1at6nL3dip1B3PQEe99sYzKwGMZlSFOV6tOunJb1tXVceDAgU6d/YMPPsi0adO48sorE/JfJ2PVqlWMHTuW+fPnU1hY2G3O+GXL+jFDYzeEgxpNx4P4miLomoGkiGSNsJOdb49b1ZVI/GvWmxU28ZsPE4jX5+rm3O7+3x02UaLQkUWe4kISRCK6Rl3IR33IZ26k7AuxnPLf+c53OuWU723dwRx0xGaOsixnbOWcRepYZnyIY7fbCYVCnY53JQN+xx13cM011zBu3Djz+FDLGd8XkgXhPSkG4eNfs964xOIVijseN7OmdBGg7st+i1hdl6zglGy0RUK0aUGCWoSQFuky3pJqsDydnPKp1o0NOgaTofS5PZ2wzPgQJ9Xpu67r3HXXXSiKwk9+8pOEspkzZ+LxeLDb7SxevJhzzjmHf/zjH91eT5Ik5syZw7Fjx/jtb39rHk824u7LKDxVNE2nvTFMS20QNaRFNxdm2/AWOzK2qisVYo/WqbOOjYj7eY+BcCLeUmzPToi3HE8Sb0nVcPUkg9/buoONZVQGB2umMsRJ5Yuh6zorV66krq6OZ555ptuNWpDeBitN0xJyxqcy4s70SqtgW4RgmxYNhAvgcMk4s20DFzNJhX6Kq3SFJIrkKS48kmLub2mK+GnTQuTaHDjS2N+Sjgx+KnW7miH1lOcn01hGZXCwZipDHFEUkSTJlKDXdR1N0xLk6FetWsXevXt5+umnzV3gMVpaWtiwYYNZ/4UXXmDz5s1JRevq6+tZv349Pp8PTdPYsGEDL730EvPmzRuIR03AMIyhEYRPkVhOlYHeDa1IckK8RdU16kM+GtKIt8Tk6lPJr5NK3a4MRyoGJZOvnxWkHxysfSrDgKamJiorKxOk7AFWrFjBtddey7nnnovdbjf3oUBUqO7qq6+moaGBJUuWJKRrveeee8xMffE54xsaGli+fDm7du0yc8bfcsst3HjjjQP6vKGgir9ZRY1oiIKApIi4c2zY+rgTPhPoevQrYQg6IS2MKIg4JHvUDRhRTbmWwcAwDNrUMG1qIJqZEnDJdrJtdqQO6QU6ziZuu+02BEHg0UcfZefOnSxZsoT169cnNSzp1B0sFEWhoKBgsJtxKmNtfhzOtLe3dxKpOxWJhDX8LWpCEN6VY8PhktPeod3XHd3Jzo/Gj6KLvXR0gloIURBxSlFtMD0cXebbF7mW3rYr/pim67REgvi1aIxFFASyZSduues9O01NTaxcuTKpXH38wKOnukOF3uykt0gLy6gMZ+J31g9F+tqBd9oJL57YCe/J7E74vtLRqMTPVAD0iJoxuZZMENZUmtUgYS36uson9MTSibcMV6yd9P3O6Z1PZbjTX77hTOkz9fYasSB8oF0lpkcyJIPwqSIIJzIvGjAE2q9IMoWSh4AapjkSNOMtDtFGjuLANsz0xHoi/vNsBekHD8uoDANEUcRmsxGJZHYXdWwVWCYMSzrXMQyDkF/F36piaNHJcGc5+qFHTzHk2H4VA6PrYdwg4JQVHJLNjLcEtAihYKTLeMtwJT4DqBWkHzysV36Y0B9GBTK3/DfV64SDKr5mNUGO3p1rw6YMn1GzIAjJHcMdlhUPhFJvqvcQBIFsmx23ZKMlEsCvRfCpIQJauMd4y3CjpyX1Fv2LZVSGCYqiJOS9Hm4kC8JnUo5+SJAg1yINSCed7j0kUSTP7sYTF29pjvhp1yRyZQcOeXh2yPHGteOyeouB5RT6Rp/aOByOYZkVTlN1/K0q4SEehM8EgiAQnX8ZZic3VPKKxGMYRmK8RT0Rbwn7cGg2sm0OlGEUb+n4+sZn6rQYeCyjMkwQRRG73U4wGMz4tTPR8XW8xlAOwne1LBe6Hvknk7xPhiCK0ZnKiWVifUln211b+vJ+xZ/bMd4S1CIE1DAem2PYxFt0XTefyeFwWCKSg4xlVIYRDoeDQCCQVCqlLzOYTK0Ai7Uh5FPxt6noJ4LwdoeMM0dGknvfyWaSfpWWyZBcS3ftyfRrGB9vaVVDtKshM96SJTvwyMqQeN+6Ir5t1jLiwccyKsOI2ChsIAQce0MkpCUE4eVhGITvKwInVoAZQ2sFWCpIoohXceKWFVoiAUKaSkskQLsWwis7sUvJXZZDxcUXm81bDC6WURlGiKKI0+nMWMA+2QynNx1ENAgfIRLSERg+Qfh+6QxFATT6Xa24P1FEiRF2D0E1QpMaQNN16sM+7JJMjs3ZKd4yFAwKnIw7WgwuQ/tbb9EJh8ORMaMSk63vbZ6RhCC8AaJ06gbhu5S874CZW2UYG5UYDtlGsSTTroZpVaMzl1qt7UT+lqEXb7EC9EMDy6gMM2IuML2bLIPp0JvOv1MQHgO7x4YrjSD8UHCZ9NvqrBM76w1djwbuhymx1ybLZscl22gNB2lXw7SrIdrVILk2Jx7Z3i/vY7rviyiKllEZIlhGZRjS02ylvzpswzDMIHxsJ7zilHHlyEhyep1nbzMvZjp+1C+GTRRAM/pVOS/V97hjvXQ+G/H1JEHEa3fhttnj4i1B2rUwXtmZ8f0t6b4vVoB+6GAZlWGIy+Xq1qj0R0cZDqr4mlR0bfB2wmfCoKS6VDfegHV1X+PEn46Ywfo05FrSHQj0xjD0dF4qbegy3qIlj7dkmq7aaM1Shg6WURmGKIqCLMtompbRkXuyL2wkrEVzm4SjO+FFScSdK6M4BzKFb+ZmXqku1U32unY8VTjxp3PF2EUy066BIp02xMdb2tQgQU0lNADxlmRtlGXZEpAcQlhGZZjicDhob2/P6DUTcnIMoZ3wQ6HDTQtBQAtFMFQVyeVAsp+aHV5CvCUSxKeG8akh/FqILNlJ1gDtb7FcX0MLy6gMU1wuF+3t7RmPn+i6QaA1QtA39HbCDxfCTS0E61sRDBBkCcXrxp6X2+05Q2HhQm+RBBGv4sIt22mNBAloEVojAXxaiFzZgVPuP6MqCIKl9TXEsJJ0DWPq6+sJh8Pd1kknoBvyReXodT0aC+htEH4wiF8eHVNzFgSBQCCAy+UiEAgQiUTIzs6moaEBt9uNIAg0NTVRWFhIU1MTuq6Tn5/PkSNH8Hq9/PKXv8Tv9/P97/+A48ePIcsyBQUFVFdXk1+QTyASpLmpmfHl46iursblcpHlcHFo5x4Ki4tRVZVWXztF2V4ajTC5+V5cLhf19fXk5+cTiUTw+/0UFhbS0NCAy+VCURR8Ph8ejwdN09A0DZfLRSQSQZKkhJTRQ5WgGjH1xCCa1yVXdqBImR/DulwucnO7N9gW/UKXncrQ7y0suiQrKysj1wkFVJqPh/A1RzB0A9kmkl1oJytf6VeDYhgG4XAYVVUJBoM0NDSgaRqHDx+moaEBn8/Hp59+SktLC0eOHOGjjz4iHA6zadMm9u/fT21tLZs2baKuro6dO3fy3nvvEYlE+OCDD6iurqahoYEdO3bQ1tbGsWPHOHjwILquc+TIEdra2ggEAjQ2NqKqKn6/35z5hUIhM14VH6z/05/+xJVXXsmCBQu47777osZQ9x21AAAgAElEQVT6xFerra2Nb3/725w1exZLvrmc1/72BoZhoGrRbJDPP/8Hrr32WiZPnsz3v/99IpEI7e3t1NbW8tRTT3HNNdcwbdo07r77bvbs2UN7ezuff/4527Zt47zzzuOvf/0rBw4c4PDhw7z77rs0NjbyySefsHnzZgKBAJs3b+bYsWPU19fzySefEAgEqK6uprq6mnA4zLFjx/D7/YRCIdra2tB1HV3X+0WNwSHbKLJ7yLW5EAWBsKZSG2qnMexH6+NS+I6DJI/H09fmWmQYy/01jLHb7SiK0u1spbtZSkIQ3gBR7lsQXtM0BEGgvb2dSCRCVlYW1dXVeL1eIpEI1dXVTJ06le3bt2Oz2SgvL2fXrl2Ul5ejaRpHjx7l7LPPpqWlBYhKmNtsNmRZxuPxUFpaiizLTJ482SzLycnBZrNRUFBgPusFF1xgtqm4uBgAr9drHps5c6b5e35+PoIgUF5ebh6bNGmSeX+n04miKJSVncHEiROZPHkyGzZsIBAMkOvNJS8vD0VS+K//+i+ysrL4+IMP+HjjJv7PvSs4e/oMxleMQ/UHmTFjBjPPmc2GDRsIBoPk5OSQk5PDqFGjOHLkCKtXrzbL5s6da7Z5woQJXHrppTQ2NjJ+/HgMw6CkpARBEPB4PKiqiqIoTJgwAYfDgWEY5OXlmTMaXdfRNI3a2lpEUURVVaqqqjj77LP5+OOPcTgcjB07lp07dzJu3Dh0XaexsZEJEyZw9OhRsrKyyMrKIhgM4nK5EEUx5fwtHpuCU5ZpjYTwqyH8aviEnljv4y3xMkUul8tKxjUEsd6RYU52dnbS/PXd7elIFoR3eGScWV0H4TVNIxAIYLfbaW1tpampiTFjxrBt2zaKiooQRZGqqiqmTp3KkSNH0HWdiRMnoqoqoiji8XgYM2YMNpuNM888E0mSsNlsCQZg9OjRAEydOtU8VlFRYf6ek5MDJBqIvrqD0unYFi1aBMC2bdsIHAuYx/1+P6+++ip///vfyc7zMnf+BVx8wYW88NJLrLz1DhSvm69ceYV57rFjx7q8bscygAULFvDkk09y8803IwiC+cyKopirnvLy8sz6brcbOPl6Apx55pnm76NGjQKixtcwDDRNY8aMGdjtdkKhEKoa/Vz4fD6z096zZw/jx4+nrq6O5uZmZs+ezc6dOykpKcHj8dDW1kZ+fj4QTZIVe12j8RYnHlmhJRIkGIu3qCFybenHW+I/09nZ2WmdazEwWEZlmKMoCna7nUPb6/ngz0c5+HETkbCOTREon5nHOVeOpHicJ5rrIxaEb4+YbgSHx4YzKxqEj7l8fD4fdXV1lJWV8dFHH5GbGx2R7927l0mTJhEOhzEMA0mSKC8vx+PxYLfbGTVqFIIgJPi4J06caP4e6+yGw+iy4x6V7mzPgQMHkCSJsWPHAmDPy2X6rLPYvHkzrtIRfV79NXfuXO644w5aW1sz3pEKgoAsy6YrVVEU8/cpU6aY9c4//3wgOrMLh8NIkkRxcTEOh4NwOExNTQ0ej4f9+/fj8/mYOXMmO3fupKysDIfDQSgUwuv1EpZstKghIrpGfdiPXQ2Ra3OmHW/xeDyWxP0QZeh/uy26RVN13nj8c7a+cxA1pGEY0d4vEjLYu7mBg1uaqJjl5eJbygn5NQw9uqRLtBl48hSOHTtKqDZESUkJ27dv54wzzsBms5kyMBMnTsTlcmG32yksLOx0/4KCgm7bN1xXNaXTZp/P1ym+leP14g8GM7Kc2GazMW/ePN566y2uvPLKPl+vL8TLoZSUlJjHYzOls846y4zXjBkzxlR/qKqqYvr06WzZsgWv10vByBIO1x0nJz+PoKriUezkyA6kOENhGAZ72+t5+ehOPmw8gmqoKKLM7PzR/NuZ85liZA3Lz9apjmVUhjGGYfDCA7s58H4bRljGMPQO5RAJ6uz/oJFQQGXyZTbsLgd2t8Tn+w8xzTkNm82G3W7H4/Ewd+5cc/QXMyDxrqbecDp86d1uN21tbQnH2trazJlZJpg8eTK7d+8edKOSCqIoIoqi+RnKysqiqKgIgNmzZ6OqKrquIwbCSBGVQwcPEfQFmHTWNIRghJF5IzAE+M+9/+SjpsOEdC362RYEQrrK+21H2bn9L8zNL2P15EuQh1GWytMBy6gMY47sbuOz9xqIhHQcsov2cBhzcwlEf3cGUPMa+HxPCQUz7UyfMw6v10vp6JEIgmDGKeD0MADJ6OtsqqKiAk3TOHDggBkD2rVrV4Lrr69s3LiRlStXZux6MTI1k0z1OvFxoDOnz8AwDIpyCzje3EA4HGHf7t3UFzfyZksVe5uOE3IL6HEZNAVRQHDZCeoqmxqqeGD33/n+lAWn7Wd3KGI5JYcxm/5YjRqKzk5EUUYWlajiuqBDyXHIawRNgqZ8jIBE2+5c8vPzU17BM5xJZ6lsqquZYkufYyuqQsFoUNvlcrFw4UIeffRR/H4/H3zwAW+88QZf+9rXzPM7nhsMBs2AeHdlAM3Nzezbt485c+Zk9LkzSW8/T4Ig4FAUzigsoTQ3n7PmzKY918Ge1uMo7SFETSenOWSmEpAcdnM2HdJV3muoYk9bbcaew6LvWEZlGLN3c0NC2g6H7EKwRzDkELR6oDkXwnbwuzAMgQMfNg1eYweYvhrNZOc//vjjjB07ljVr1vDiCy8ybeJUfvmfawB44IEHCAajS4dvv/12HnzwwYSZSvy5L7zwAmPHjuXxxx/vsQzg73//O/Pnz09ppVu6zz2UBhcOyUaxI4tNDYdodYocL3YCAm6fRpZPQxAFREdijCqka/ypetvgNNgiKdaO+mHM/Rdv6PQOBUt2Eap3ILQlWSUkwLf/9/wBaVs8wzVY/9hjj2EYBitWrEQUE9uvGRohLYwoiDik/k1hu3z5cq666ioWLlzYr/cZKtyw+TlC+kmZIAwDt19F8LhQ8zvHqeyizF+/8O8D3s7THGtH/amITen89im15QgRGwaddy4nqz8QDEeDAqktJx4InE4n8+fPz/h1B8tV1tO9w3rM9Xfi9TcgrymCXUmes+VkfYuhgBWo74H7778/4d+hxPjz8tn9dl2CC0zEhlLSRrhWB78DjKjLRBCgYnbfVnINZ1LNoxJPbGd7qtfpTb1UrhNzhWU6SdlgGvvu7q2IMiEtqt/m8qlEbCJaUQ4+T3KjoohWNzaUsGYqadLY2MhVV12F2+2mrKyM3/3ud2bZmjVrmD17Nna7nZtvvrnTud2V93RueXk5hw8fTjh2/uLRyPYOb6Em46iZiBhyw8jjUFgLgo6kGMy+fGRC1cEcqWaSVJ4j1Twq8Zx//vnMnXt+SnXTuV869JTj5VTDMAxmKgW4ggZZ7RHyG8PITjuNJe6kU0YBgfPzywahpRZdYRmVNPnmN7+JoijU1NTw3HPPcdttt7Fz504ARo4cyfe+9z1uueWWpOd2V97TuZdffjkvv/xywrFRk7OYMDcfW0fDoks4xRw4VgytOchZYXJm1SPlBKitraWmpqbXI+mh2LENV/faYNJlNssBfn8Nw4iqObe2sn37dgKBAFN8DpxhnTaPjSPl2Rjervf7KKLE10eflKC5//77h6RX4XTCMipp4PP5WLduHT/+8Y/xeDzMmzePK664gmeeeQaAq6++mq9+9aumBlJHuivv6dwrrriCl156KeGYIAhcvXoyE87Px+YQEwZykmjDIWVhM5yMnTaSm+78simxUVNTg8/nY9OmTRw7doyWlhZqa2tTyiTZUwc+FI1Ob4k9yqlmtLobUPSUbrgvaJqGqqo0Njby2WefEQqFeO+996iqqkJVVXJzc7HZbCyc9wUmVYzDLtmQPV2nCbaLMufnlzEpq7PSQ4y+eAf64pVI5lk4XbCMShp89tlnyLLMhAkTzGNnnnmmOVPpT+bPn8/WrVtNBd8YkixyzfensPSnZzH5CyOisxYBbHaRsy8p46YHzuLylZOwKTKSJFFaWsqMGTNwuVxMnz6d3NxcQqEQVVVVRCIR3nvvPT799FPa2trYt28ffr+fQCBAMBhMyFnSFadSB3zXXXcya9ZMJk6cyLx58xI6lRgHDx6koqKCO++8M+F4U1MTy5YtY9y4ccyZM4cXX3yxy/tcc801VFRUMH78eMaPH8+FF16YtN6WLVtYunQpa9eu7fUz9SXWk2osKRwOU19fj6qq7NmzhwMHDlBfX8/mzZtpaGggGAwiiiKyLHPOOecwduxY8vLyTMFRQRC4a/w8Lhg9Hpfi6JSyWUAwDcrqyZd0266+eAf64pVI5lk4XbAiXGnQ3t7eSdAvJyenk0RHf2Cz2bjkkkt47bXXuO666xLKBEGgdHI2i++f2uk8VVWpr683tbxiiKJo6lU5nU5TUmP27NmmdpOu66iqSm1tLbW1tcycOZOPP/6Y0tJSsrKyaGhooLS0lFAoFE0te+J6w9GwJOtsv/nNO/h//+9RnE4H+/btM3OezJgxw6xz//d+mKAAHOO+++7DZrOxbds2du7cyTe+8Q2mTJnS5S77yspKbrjhhm7b+OKLL7J27Vp++MMf9uIJo/T2vYm5qQBTHj8/P5+jR48SDAYZPXo027Zto6SkBJvNxrFjx5g+fTrZ2dkoioLX6+X888/vdP+u9t54XG4qZ1/JnrZanq/exuaGKsJ6VPtrbn4Z144+i0nZXc9QYlx99dUAfPjhh51mDt2VxbwSO3bs6OSVeOihh7o9F6KehUceeYTbb7+9xzaealhGJQ08Hg+tra0Jx1pbWzOWLKsnZsyYwSeffNLJqHSHLMtkZ2fT3Nzcbb3YyqKYhAZgzsiys7PNXBvTp09HlmWzgzEMw0wANW7cOHbs2MGoUaOQZZkjR44wY8YMMyviiBEjaGhoIDc3F0mS0DTNFCccbEOU7P4dDYAgCBw6dMg0Kn95+S9kZ2czaeIkDh06ZNaLl8J3u93MmTOHBQsWsG7dOlavXp1222IGb/Hixdx+++3Mmzcv7Wt0vFZskBHLPpmdnc3x48dxOBwoikJVVRWjR4+mtraWuro6c0AxYsQIvF4vx44dIzs72xQbdTqdzJo1C0WJ5kkpLS0FoiP67tqRDFEUyc3NRRAEJmcXcf/US3v9vL2lK6/Exo0bUzp//vz53HDDDbS0tCRIIZ0OWEYlDSZMmICqquzdu5fx48cD0RwY8fk/+pM33nijV0FIl8tFMBgkGAx2WScVf3n87MYwDPP3WFIrgPPOO88c1drtdmRZNjuaSCTC8ePHsdlstLa2cvz4cWbNmmXK6xcXF7Nnzx4mTZqEz+ejsbGRKVOmcOjQIXJzc3G73TQ2NlJQUEA4HCYcDpOXl4fP58Nut5uGymaLLj3ti6GqrvOz81ALrzz3U1798wsEg0GmTZvGJZdcAkQFIx//6c959g/P8cLz6xLO7SiFD9EcMe+9916X93vwwQd54IEHGDt2LPfee68pNR8vwT9hwgTWrl2LLMu0tLRgt9sxDIOWlhby8/PNvDper5eDBw9SVFREOBymurraVAjOysqipKSETz/9lDPOOINgMEhNTQ2zZs2ivr6ewsJCnE4nOTk52O12SktLKSkpwW63m22Ck+rU8aKZdntmNoHm5uYOuqx9X70S3XkWTnUso5IGbrebq6++mh/84Af893//N1u3bmX9+vVs2rQJiLqaVFU1c4sHg0FkWTbzh3RX3tO5TU1N7N69u9ej1NzcXGpraxNS5PaF7kaZEHVrxDqZsrKTSz7PPvtsINopxcQXzzvvPHPkPHXqVJxOJ7IcjQEJcWKCkUiEpqYmcnJyqK+vp66ujqysLD755BNKSkrMEfakSZPYv38/kUiEM888k23btlFaWookSaYE+6FDh9B1nXHjxrFr1y7GjBmDruscPXqU3KJyfvbcP4loEoGiy/n1b65BD7Xxr3/9i08//ZRp06axetVqvnTZl8jyZFFTU0M4HObo0aPU19fT1taG0+mkurqa7Oxs08g0NDTw4YcfMmPGDLZs2UJxcTFut5vLL7+cn//85zQ2NvKXv/yFm2++mYceeogZM2bgcDioqqpi8uTJfP7556YUzI4dOzjjjDPMGWFOTg5+v9/UdXM4HNhsNhRFMdMZTJ8+HUVRsNlszJ0713xdY+9DvBvP5XJ1em8zqYwQf53YzEkQBFwulzl7HUwy4ZXojWfhVMAyKmnyxBNPcMstt1BYWEh+fj5PPvmkOVOprKzkRz/6kVn32Wef5Yc//KE5u+iuvKdzX3nlFb70pS/1OtNhzKXQ2Ng45GRTYlLpcDK7o6Io5khx3LhxZt3p06cDUTn1iooKDMNIGEHHshp6vV7zOWfNmpVwfafTSVlZGYIgYLfbKS8vx+12mx3b1s/9+HUXEQ2QRVoiLi6dO41XXnmFt956C0mS2L5tO/esvhfZJuN0Omlra8PlcpGfn49hGPj9frKysrDb7RQXFxMOh8nJyWHMmDHIssy4cePMjv+rX/0qbrebgoIC/uM//oMdO3ZQX19PeXk5oiiayc/iszvGZ8yMycrHz4zi0yPH8rj3NZ97f31mYu9TzFU7FMiEV6K3noXhjmVU0iQvL6/T0t4YPa2R7668p3PXr1/fYyC3JxwOBy6XC7/f36frdGQwjVR3S2NjZfFumZhrLL7zik805na7mSr5CeLBkKICR7Onj8XtdiFJEi0tLbz//vscP36cK78cTRHs9/nRdZ0DBw7w+uuv4/V6zWB2RUWF6W6aOnWquSAiful4LI4Vm5WKoogkSX1OlTwUSFXJIJYxNNNur956B/rqleirZ2E4Yy0pHia4XC4uvbTvAcucnJyEYHxXZFo6vj9J1taO6YDTuc7oES7uvXoUkxx7+OENYxmZZ2fDhg289NJLzJs3j5tuuol33n2Hl1/9M3957RWWLFnCxRdfbC45TkUKP0ZLSwsbNmww5e5feOEFNm/ezEUXXZS0/cNtH1Cqy8+9Xm9Kn8t0qaysxOl08tBDD/Hss8/idDqprKzssQyiXolAIEBhYSHXX399J69Ed+f21bMwnLFUintgw4YNAOaX/FRA13Xq6+uJRCKDbhAgfU2rjqPf/pgpNTQ0sHz5cnbt2oWu65SWlnLLLbdw4403Aokqxb/8+RoOHTrEL37xC/P8pqYmVq5cydtvv43X62X16tVcddVVANx0003MmTOHu+66i4aGBpYsWcK+ffvM4P4999zDF77whYw+z1AmNzc3aQynNwwVrb6vf/3r3HDDDeZ7fgrS5RfOMiqnKZqmUVdXZwbIMy1WGE+yTn+oxXXSZSCl709lsrOz+xzriWeoGJWlS5fyxBNPZDSl9BDDMioWnelqY2Q86Xb+w91YpMqpblR6MxtM9733eDwZD8yfip6FIYplVCySEw6HaWxs7NawxDMUjcZgtOl0Myo91RVFMa2ZrsvlIjc3t7fNsxh8rCRd6RIKhVi2bBllZWVkZWVx1lln8dprr5nlHo8n4UeSpAT9p+7E6DqSat3333+fyy+/nMceeyxjz6koSkpf7pMJq3p2kw10MDnW+T322GMZfW1OZ9Ix0um6Th0Oh2VQTmEso9IFqqoyevRoNm7cSEtLC5WVlSxevNiU42hvbzd/jh8/jtPp5Otf/7p5fndidB1Jte7vfvc7/vjHP/Lpp59m9FkdDoe5B6KrzqHjZrXuGOhZQ1crvZ566ikWLlxIeXk53/rWt1Iu66m8qamJf1/278yYNJ0L587rJBZ53nnncfTo0Uw8Wq8ZqqvEFEVJ2G9jcephGZUucLvd3H///ZxxxhmIoshXvvIVysvL+eijjzrVXbduHYWFhaa6bE8S+fGkU3fp0qVcd911TJs2LePPGxs9DuWkUD0ZvI7GrKioiLvvvptrr7220zndlfVUft9992FTbLz30WZ+9vjPWLVqVYKhX7BgAW+88UbKz9WRvrzu8TPKoUKsTbIs96tB6UmO/g9/+AOTJ0/G7XYzduxY3nnnHbMsHc/CRRddhMPhML0UXYmE9odnYThgGZUUqamp4bPPPku6o/bpp5/mG9/4hvlFTkciP526Z599NuvXr+euu+7KxCN1wuVyJQROh1LHBOm3Z9GiRVx22WV4vZ3TKHdXFl/esROMiUV++zvfxuV2MWvObFMsMsaCBQt4/fXXu21bd4ajL6/7UHvPAHO3fEFBQb9qenUnR//mm29y77338tRTT9HW1sbbb79tytNAep4FiBqwmKeiK89Bf3kWhjqWUUmBSCTCjTfeyNKlSxPEEwGqqqrYuHEjS5cuNY+lI0Y3mHL6yYiNvjLFYGQS7M/rxXS8ysvLEU78mTp1akLHMXfuXHbu3GlqR8VfYyjOJDJNx9dMlmXy8/P7XSSyu0R3P/zhD/nBD37AeeedZ0rfxCR90vEWpEN/ehaGMpZR6QFd11myZAmKorBmzZpO5c888wzz5s3rpLWUqhjdYMvpJ6Pj3oG+dNQD3Xn29/18Ph9ZWVkJ98nKysLn85n/t9lszJs3j7feeqtTm/qjfUPNTRn/jIqiUFBQMKg7yzVN48MPP6Suro5x48ZRWlrKHXfcQSAQAHqXfG/VqlUUFBRwwQUXmMuYO9LfnoWhimVUusEwDJYtW0ZNTQ3r1q0zdaPi+e1vf5swS4FEMboYXYnRpVN3IMnOzjZX6AykYeg4qu/qZ7Bwu92dZpFtbW2dNrlNnjyZ3bt3p3393jxb7P3pTd75/nwtYyKZgy1jX1NTQyQS4X//939555132Lp1K1u2bDFlVdL1Fjz88MMcOHCAI0eOsHz5ci6//HL279/f788xXLCMSjfcdttt7N69mz//+c84nc5O5Zs2beLIkSMJq74gUSLf5/Px7rvvsn79epYsWdLpGunUHWhcLldCp9Bfu+7jr9lxVN/Vz2BRUVGBpmkcPHDQPLZr165OwdqNGzcyf/78tK/fH/GUZMf70w0nCALZ2dlDJjlV7Lt75513UlJSQkFBAStWrODVV18F0vcWnHvuuaYC9dKlS7ngggvMa1lYRqVLqqqq+NWvfsXWrVspLi42Yw3PPfecWefpp5/m6quvTvrh606MbuHChTzwwAMp1R1sYu4LWZb7bZNhKju1e4OqqgSDQXRdN5VkYxkruyvrrjwmFvnYY4/h9/v58IMPO4lFNjc3s2/fPubMmdOrdg8E3SkH9/bcWJnX681oXK6veL1eSktLu3RD9tVb0J8SR8MRa0e9RUrouk5zc3O32SMh9S9Yfxio2NLNlStXmv//6U9/mlBnxYoVrFy5stuyns5tampixcoVvPP2O+R6c7lv9X0JwoHr1q3j7bff5vHHH8/o8/UXmXovJEkiPz/flH8faGJy9D/60Y84fPgwv/71r005+h/84Ae89tprvPLKK9hsNq644gouuugifvzjHwNw3XXXIQiCKXO/aNEiNm3a1MmwNDc3869//Yv58+cjyzLPP/88y5cvZ8uWLQkxmdMAS6bFIjO0trbS3t4OnOyMhop0S0ejAv0n4dKdTMvy5cu56qqrWLhwYcbvO5Ck89rFNjUOZvzk/vvvT0h0B5iJ7iKRCHfffTe/+93vcDgcLF68mEceecTMMtnY2Mgtt9zCm2++SX5+Pg899JCZv2jhwoVceOGFrF69mrq6OhYtWsSePXuQJIlJkybx4x//mAULFgz48w4yllGxyBx+v5/m5mag646nN515T7Ocnq4ZMyorVqzodyPXnVG5++67efDBBzMm594dsdcslRhJfxlYS8frtMQyKhaZJV0hykzRXccYy8oXn3+9v1B1lZAeNSpOafBzqg8WOTk5p7K8u0XXWEbFIvOoqkpTUxORSGTIuMAyRU+zJlVXCeuRpDOVdBV+e/O6DcQ9ukOSpH7L1mgxLLCMikX/0d7e3mlJZm8YToZpIKXvh9rr0h95UCyGHZZRsehfVFWlubmZUCiUdm6NjsTHCTKZNjiTnfNwyKfS1evYWxRFIScnJ+kmYIvTDiufikX/EhMM9Hq9fe7Augo6d7UgIBQKsXLlSubMmcOECRNYsGAB//jHP8w6MRn7ioqKpDL311xzDRUVFYwfP57x48ebatPJuPPOOzn77LOZMmkKCy76Is///vmk9bZs2cLSpUtZu3ZtSs+cCukY6mTB+65SBCQj/rUWRZGcnBwKCgosg2LRI5ZRscgoLpeLwsLCHlc+ZWqzmCAIaJrGyJEjWbduHXv27OGee+7h1ltvpbq6GuhZ5h6gsrKSvXv3snfv3gRJ9I7ccccdbN68mV17drH2v3/FTx99jO3bt3d6phdffJG1a9dy4MCBjDwnpLb7vbtVYMlSBCR7H+INksPhYMSIEVYw3iJlLKNikXFEUSQ3NzdhJ35HMrkL2eVysXLlSkaPHo0oiixYsIAxY8aYnX1PMvfpMHHiROz2qLtLEKIqxbHEbfGd9eLFi7n99tu7zLXRX/RmGXfs33iDJIoiXq+XvLy8QRWDtBh+WEbFot9QFIXCwkJT1bejEeltB9gTdXV1HDhwIK0O/cEHH2TatGlceeWV5tLkrli1ahUTxk3gSxdfSmFRIZdcckmnOtOmTeOpp55i2bJlncrSdWP1dF4mjHN83CU220ymd2dh0ROWUbHod7KzsxkxYoQ5wu8tqXSekUiEO+64g2uuuYZx48YBPRuj1atX89577/HRRx9x4403cvPNN3Pw4MGEc+Ov8eCDD7L709387n9/z6WXXdrtstq+ztJSkc3P1OKDWFwsNzd30JWFLYYv1ifHYkCIdVh5eXn9FuzVdZ277roLRVFMWXPo2RjNnDkTj8eD3W5n8eLFnHPOOWYulNi5HTd5SpLEOeecw/Fjx/ntb3/b5bV7oxzc3Xn9hcfjobCw0Np3YtFnBkf5zeK0xeFw4HA4CIfD+Hw+M1FSuiRb2bRy5Urq6up45pln+mS40nHVaZpGVVVVr+/V1T16MoSZiEkJgoDT6SQrK8uKm1hkDGumYjEoKIqC1+tNulKsp84y5pMGX/kAACAASURBVP+P74S/+93vsnfvXp5++mmcTmdCWXcy9y0tLWzYsME89sILL7B582YuuuiiTvetr69n/fr1+Hw+NE3jnY1v8+f1f2bevHl9eCV6R7oGpeMS4aysLIqKisjNzbUMSpq0tbXxrW99i7KyMpxOJ+effz4ffPBBQp0nnniC8vJyHA4Hs2bN6nZF4amGtfnRYkigaRo+nw+/34+u62mNxA8fPsy5556L3W5P6CAffvhhrr76ah599FF+9rOfJZwTk7FvaGhgyZIl7Nu3D0mSGDt2LPfccw9f+MIXALjpppuYM2cOd911Fw0NDSxfvpxdu3ah6zojR41k6b/dzM1LEjN/Dgax16w7t5ksy7jdbpxOpxUz6QPXXnst27dv58knn6S0tJRnn32Wn/3sZ+zatYtRo0bx/PPPc9NNN/HEE08wb948nnjiCZ566il27drFmDFjBrv5mcLaUW8xPDAMA7/fT3t7O5qmDXZzumQgdtR3l1og/lhPO+YVRcHj8Zgy7xa9JxAIkJWVxbp167jyyivN47NmzWLhwoVUVlZy7rnnMmPGDH7961+b5ePHj+eaa67hwQcfHIxm9wfWjnqL4YEgCLjdboqKivB6vSnFRrrawJdO/V7VOfGnp2v0Nstid5sVk60K67j82OFwUFBQQEFBgWVQMoSqqmia1un1dDqd/POf/yQcDvPRRx9x6aWXJpRfeumlPS5VP1WwjIrFkMXpdDJixAhGjBjR7Z6J7naPJytPZWVVSnVO/OmJroxHVy6+7oxNT6l8JUnC4/FQVFREXl6etZorw2RlZTF37lwqKys5cuQImqbx7LPP8t5773Hs2DHq6+vRNI2ioqKE84qKijh+/PggtXpgsYyKxZDHZrPh9XopKSnB6/WaMYF4OZGOpLJpsL9J1Xj1tNKsJ0Nit9vJzs6msLCQoqIisrOzBy2l7+nAM888gyiKlJaWYrfb+c///E+uv/56K051AuuTZzFsiC2Bjc1awuEwwWCQUChEJBIx66WiyttX5V5N1/iwcQt14TpKHaOYlXcWspj869TTvbpzj8UrDUuSZAbkY0uz7Xa71ZkNMGPHjmXjxo34fD5aW1spKSnh2muvpaKigoKCAiRJoqamJuGcmpoaiouLB6nFA4tlVCyGLYqimO4dVVUJhUIEAgHC4XCP5/bUkXc8FpsZCYLAwbYqfrTrIcJ6BFUPI4sKimjj/infpcwzptO1uku3nCwe0rGNgiAgy7JpSCyX1tDA7Xbjdrtpamri9ddf55FHHkFRFGbNmsWbb77J17/+dbPum2++yde+9rVBbO3AYa3+sjjl0HWdcDhs/sQyU6Y6O4nv8Dt+P1RdZfmHd9ESaQNBwMCIxlUMgxxbNv81+3FzxtJRpDGZS66r1V2iKKIoimlELHfW0OH1119H13UmTZrEvn37+M53voPD4eCdd97BZrPx/PPPs2TJEp544gkuuOAC1q5dy//8z/+wc+dOysrKBrv5maLLL5L1SbU45RBF0RzVx1BVlXA4jKZp5goeVVWTxmU6zh4EQTDdTh82fEzYiJwYbRnRv4aBIBiEtDAfNW7h3IJzEoxI/L/xsxNRFBFFEZvNhiRJSJKEzWZDlmXLpTWEaWlpYdWqVRw+fJi8vDy+9rWv8ZOf/MRcqXjttdfS0NBAZWUlx44dY9q0abz66qunkkHpFmumYnFaE9tlr2kakUjE/F3X9QSjEzMELx7+C88c+gNhPRKdPRgGuqEj6CKyILLkjGu5aswVphESRRFJkpBl2TQcMeNh7WS3GMZYMxULi2TEzxaS7eXQdd38AZikjSenNQef6jeXEwtCdPTlkpxMHDWRESNGAFguK4vTEmuObWHRDaIoIsuyuShg/qgLcTld2Bw2ZIeM7JCR7DKyXcbldDF/5DxkWbYMisVpi2VULCzSQBZlfnrmT8i15eCSnMiChEtykmvL4adn/qTLZcUWFqcLVkzFwqIXqLrK5oYPOBo8xkhHCefln2MZlNOEsB6iMfw5DeFqWiN1+LRmglobqh5mhC0fTW3EJjiwyzk4JS8eWxHZymiylVEIwikzjrcEJS0sLCx6g27oHArsZo9/C/sDO2hRG8nWWpPWHWufgD/0WafjObZRZKkNeBxj8brOJM89C5cyqr+b3p9YRsXCwsIiHY6Hqnm/9e9sb3sXn96WUFYueQlqTZ3O6cqoFDsmIQT3JBxz2kZRlD2foqyLsMnZmW18/2Ot/rKwsLBIhR3+7bzStJ5WtRk9ciRpHbucn9SodIUNUDscC0SOcKT5FYINL5CVdR5e71dRlOEv5WIZFQsLCwvgYHA/zzc8x57ALvPYZNtImiNHO9U1hDTTVWstSQ/n2EaCtpu2tg20tb1Ddvb/R17e15HlnPSuP4SwjIqFhcVpTUAL8MeG59jQ+vdO+XEMKQsinc/xG8GUry8KNtRITafjAhJy+FjcEY3W1r/R3v4u+fk3kp19SZ9ETweLU2YpgoWFhUW67Ap8xn2HH2arb1vShGsHQgdRBHen4w2RupTv4ZELAb3T8Wx7OejNnY7reoC2pnc4uuMB1FBjyvcZKlhGxcLC4rRkfdPrVB75OUcjx1GkQpLFnsNGmBx757zyfr0dh+RN6T4uKSvpcafRMcoSRZJyCB2vJtD8CdVbvou/eWdK9xkqWEbFwsLitCJiRFhT8xS/b3gR/cQMoip8hLGOGUnrH1WTz0rscn5K95OTzIAcciFG+FDy+oF8jIgfAC3SytEdD9By7G8p3WsoYBkVCwuL04awHuaRo0/wz7Z/dSrbFzqGVxrR6Xi9Wk++Ut7peKrBekFr73QsS85LuibXIU8k1HCgw4006vb9N42fv5jS/QYby6hYWFicFoR1lV/WvMjRcPKZR8gId+kGCybZCe83Qgn/F5EQBVvC+SIyaiQxN70oKEihzztdT5JyCR3rfDyGr+4jGnYNfcNibX60sLA45dENg8eO/YGP/J/hlbIQaaRBq09ad6qjjP3BbQnHREQqpBx8WhOKYKfUMZZyx2TGOiootFfgknKAk0nbDDR8kTpaw4fx+7fQHjqAL1QFGHgdE7EHP+10X3u4ovMsJVbmGkfo4AHQdQrOvpnc8Zf19SXpK9aOegsLi9OXZ+pf55Xmzeb/uzMsiqBQIEGjWptw/OKsi5jmnMx0z1xUI4JNUJDFnl1gmh7EMHQMNI42v4bh/wQ1tDehjkOeSLC6s6GBRIMCgCBSMu8e3CVn9XjvfsQyKhYWFqcn/2zbzpqazm6j7gxLmTKSmvBuwGCm+xyuyvs6RbYiJEFGEnqfXE3XwwD4/dtpbPwD4fBhJCkX/XgIQw10qt/JoJxAVNyM/uJPsHkGbQe+ZVQsLOK5//77E/61ODWpiTRx7+drCRrhpOXdGZZzXFP4Ys6FTHROxiF2TuDWFwxDxzAiNDW9jL9mK6GG/Z3qdGVQzPK8cZRe/H8RBif1dJdGxQrUW1gAa9asYfbs2djtdm6++eaUy/p6bnl5OYcPH87cg1iYGIbBHxs+xNPFPhGAJq0NnTzypYKE43M9s7it+N+Z6pqecYMCIAgiomjH672SojNuR3GNTijvyaAAoOk0b3sl423rK5ZRsbAARo4cyfe+9z1uueWWtMr6eu7ll1/Oyy+/3LfGWyTlH617eLf9IK2ak0mOyXQ1uI43LAIC/z7iJv5P4TdwiU5koX+VrERRweYsofSsStwF5wI9GxTR5sLhmkBozwEa3/0j4ebjSesNFpZRsbAArr76ar761a+Sn995Q1t3ZX0994orruCll17qW+MtOhHQw/yx8UMAwobGnmAzY5TJ5Mt5Ses3aW0Y5POdkm9yQdY5OET7gLVVEEREyU7RhNvxjl7cvcsrpwIabQT3R+X1DS1Cwz+fG7C2poJlVCwsBpH58+ezdetWWlqSq9ha9I5Xmj+hRUsMfH8ebqJNc5+YtXTm+vxLmOqcMKAGJR5RsuMt/TKekXM6l8lOHM6JhPYcQG9P/Kz49n9A8NjeTucMFpZRsbAYRGw2G5dccgmvvfbaYDfllMGvhXmleXvSsrChsifYTJkyJWHWco13Pud4JmEXlYFqZlJE2U7hnNtw5I83j9lzKqDZTvBA8iXHAI3/+t+BaF5KWEbFwmKQmTFjBp988slgN+OU4a3WPQT0JHr1cVTFzVrKlCIu916AI4lB2bBhA4IgUF+ffKNkfyDKdornfgtJycbhOjE7aeusZhyPv2ob4YahseDDMioWFoPMG2+8waWXXjrYzTglMAyDTe3NTHZMwNvNqi+Izlr2Blup+t47OCQFQRCw2WxUVFTw7W9/G5/PN0Ct7oyoZJE3/jqC+7uencRQ8kZjzx5Py+a/D0DLesYyKhYWgKqqBINBNE1D0zSCwSCqqvZY1tdzm5qa2L17N/PmzRvYBz5F2R1sYH+ohd3BNpo1D2PtEyi3j+qy/jV5M7EJEl/84hc5duwYBw4coLKykieeeIJvf/vbA9jyRERZIWvCBThKJiQtF2wOHIWTkCkhvKua0Gd7afvwbQy1+xnaQGAZFQsLoLKyEqfTyUMPPcSzzz6L0+mksrKyx7K+nvvKK6/wpS99CUnq/S5ti5Nsbj+ZSdEA9ofaOBjSyZfLmewYh0c4ueckW3Lw5dwZSIKI3W6nuLiY0aNHc8MNN3DjjTcmrMrbtm0b5557Li6Xi9mzZ/Pxxx+bZQ0NDVx//fWUlpbidDqZOnUqTz31VEK73n77bc477zw8Hg85OTnMmTOHHTt2mOWbNm1i/vz5uFwuRo0axW3/f3t3Hh1VlSdw/PuqKrWlspGQBAhLiISwtAGCYUQaQWwQm6B9mm6wgYkDqCx9JixyEBuFGYcGW+weW0FHtEXbFpijIN1AS0d2TA9rgmwhBBKWEBISyF57vfkjpqCoSkAMYft9zql/7ru8LZz3e/fde393yhRqrHZaD57os5+g0BiMrZKgFGzf5uK6cOV6PbZa6vJv/2dUCSpCUD+zXlVVn9/Vs+4b2/ZD/+26det4+umnW+5C73H7awPP2Sh32Thmq8VOJInGrrQLas1jIUkBV3sEMJlMOJ1X3vrnzp3L4sWLOXDgAJGRkYwdO5aGbCQ2m40+ffqwfv16jhw5QkZGBi+88AKbN9d/jnK5XDz11FMMGDCAgwcPsnv3bqZPn+59kTh06BBDhw5l5MiRHDx4kDVr1pCTk8OECRMICo9FHx2PoXUX9IaOOPNKsB3NRbUHXs649ui+m753zUXWqBfiNjKbzdKf0kzO2qspdzW9drxT9ZBnq0JBx4iIXhgCJITcs2cPn332GUOGDPGWvfbaawwePBiAV199lQEDBlBUVERcXBzt2rVj9uzZ3rrPP/88W7ZsYeXKlQwZMoSqqioqKipIS0sjISEBgKSkJG/9N954g9GjRzNr1ixv2bvvvkvv3r25WP42ET3SKFn5xxu6B3V5B69f6RaToCLuS4MGDbrdpwDAxx9/fLtP4Z5x3FZ+w3V7m6PRKldm2H/11VdYLBZcLhdOp5OnnnqKt99+m6NHjwL1I/QatG3bFoDS0lLi4uJwu90sXryY1atXU1RUhN1ux+FweP+PtWrVimeffZZhw4YxZMgQhgwZwqhRo+jQoX6Z4v3795Ofn8/q1au9x2hoBZ0qKKRf375oDCY8dv+Ek9dyVZbjrCgjKDzqunVvFfn8Je5LgwYNumMCi2geF50K3YwdSTDEEHadfF2DQjtguqqVMnDgQHJycjh+/Dg2m401a9YQHR3t3R4UdKWu8l0w8nw3633JkiW8+eabzJ49m82bN5OTk8PTTz+Nw3ElieVHH33E7t27GThwIH/961/p2rUrmzZt8u5n0qRJ5OTkeH8HDx7kxIkT9OrVC9XtxpzUp/GLURR0EdEY2yVibNMN++nCG75nt4K0VIQQ94TD1lpO2u3U5/gKJ1SrI0qnw6io2FUb5c4qKjz1b/sJxnCff2s2m3nggQdu6ri7du0iLS2N8ePHA/WtjLy8PMLDfY+RnJxMcnIyc+bMYfjw4Xz88ccMGzaMPn36cOTIkUaPr3o8GDt0oebgN/UBJDwanTkMPBo8FXU4zpfgOl+Ki/r1X+xx3bAk972pa2kO0lIRQrS4HTt2MHLkSNq1a4eiKKxYscJnu9vt5pVXXiE+Ph6j0Uh8fDzz5s3zGY4NsGzZMm+d/xn+cy7uzfZuq3K7OGW3cdRm56RdocITRqgmjiRjZ8K1zZd5ODExkc2bN7Nr1y5yc3P59a9/TUFBgXd7QUEBL730EllZWZw+fZqtW7fy7bff0r17dwDmzJnDnj17mDx5MtnZ2eTn57N+/XpeeOEFABSNBnOXXuhN7eGSHtfREmz78rAdyMVx6gzYfJc1dpY2nWDy6nuWkpLCzp07m+1egAQVcR9qLB293W5n4sSJdOzYkZCQEHr16uWXPmXQoEEYjUYsFgsWi4WuXbs2epxx48bRpk0bQkNDSUxM5IMPPghYb8+ePaSlpfHmm282y/XdDWpqaujZsydvvfUWJpPJb/vrr7/O0qVL+eMf/0hubi5vvfUWS5cuZdGiRd46q1evJiMjg5dffpn/27+PiD4/Ysek6dSeb/yhWuVxARpsHnezXcu8efNITU1l+PDhDBw4kODgYMaOHevdbjabycvL4xe/+AWJiYmkp6czduxY5syZA9T31+zYsYPCwkIeffRRkpOTmTt3LjExMd596MJb4Sg45xdAAnFdarxv6ep7lp2dTf/+/Rk+fDhnzpz5AXfAlyzSJe47a9asQaPRsGnTJqxWq/ctuba2ljfeeINnn32WDh06sHHjRp555hkOHTpEp06dgPqgMm7cOCZNmnTd4zR80jAYDOTm5jJo0CA2bNhASkqKT73p06ezaNEiMjIyeP/995v7cu94FouFd955xyfAjxgxgsjISJ+BDOnp6ZSXl7N+/XoA+vXrx4MPPsjy5cspcdrIOH2IDY//nPZPPMaDL05r9HjDwqL5VWQcBs3dMzfIY7Nx9tU5OEtLrls3KLYNHRf/IeC2q+9Zgy5dujBq1CifgH0DZJEuIRo0lo4+ODiYBQsW0KlTJzQaDSNGjCA+Pp79+/ff1HF69OiBwVCf8VZRFBRF4eRJ/xX+0tPTGTNmDD179ryp49yLBgwYwNatW8nNzQXg6NGjbNmyhSeffBIAh8PB/v37vcOx675recQO6EfZgcDJJBuYNFqClLvr0ad63GgCtOgC8dTVBSy/9p41GDp0KFlZWT/4HBtIR70QjSgpKSEvL48ePXr4lM+dO5eXXnqJrl27snDhwiZHkU2dOpUVK1ZgtVrp3bu396F4td69e7Nu3brmPv272pw5c6iurqZ79+5otVpcLhe/+c1vmDp1KgBlZWW43W7vJyLVA601Jlq1jqYsax+tNY0/gCM0ejRKoy/adyZFQRfVBndN0/NwABSTOWD5tfesQUxMDF9//XWznCZIUBEiIKfTydixY0lPT/eZqPb666/TvXt39Ho9q1atIi0tjZycHO+ktmstW7aMt99+m3/+859s27bN23IRTVu9ejWffPIJn332GT169CAnJ4eMjAzi4+OZOHGiX31V1XKxzkidQ4dbVbhY13hHfLXlLnzsecBVYsdVdP0+FU3I7b2+u6sNKEQL8Hg8jB8/Hr1ezzvvvOOzrV+/foSEhGAwGEhPT+eRRx5h48aNTe5Pq9UyYMAAzp07x7vvvnsrT/2eMXv2bF588UXGjBnDj370I8aPH8/MmTO93/2joqLQarWUlNT3Meg09S0PW3k5xsimJ/45PSrupvuS70AKqvPGkkUqusBB5dp71qCkpITY2NgffIYNJKgIcRVVVZk4cSIlJSV88cUXPpPeAlEUhesMdvFyuVwB+1SEv7q6Or8km1qt1jvhUK/Xk5KSQmZmJgCW7+pe+L9viOrVxERBoMLlwhFgud7Lly8TExNz2/5GqampfPHFFwG3KUE63BU3tjqoNsQSsPzae9YgMzOT/v37f7+TbYIEFXHfaSod/ZQpUzh27Bh/+9vf/Ia6VlRUsGnTJm/9v/zlL+zYsYMnnnjC7xilpaWsWrWKmpoa3G43mzZt8uaCEvVDihtmj3s8Hs6cOUNOTo53aGtaWhqLFy9mw4YNFBYWsnbtWn7/+9/zs5/9zLuPmTNnsmLFCj744APOn8gje/Fr2EpLSfjlM00e+5S1YYKkr9/+9rc8+eSTJCQkUFhY6B1coSiKd/j4pEmT+PbbpgcC3KxXXnmFl156yRs4r6Y6HLgrq29oP9qw0Ea3XX3Pjh07RkZGBufPn2fy5Mk3fd5+rs2ges1PiHvO/PnzVeqHy3t/8+fPVwsLC1VANRgManBwsPf36aefqqqqqqWlpWrfvn1Vi8WihoWFqf369VP/8Y9/ePf7xBNPqAsXLvTWHThwoBoWFqaGhISoPXv2VN9///3bcr13oq1bt/r9DQA1PT1dVVVVraqqUjMyMtQOHTqoRqNRjY+PV+fOnatarVaf/SxdulTt2LGjqtfr1ajuPdXBH/1FHX3ohN9v7KET6qzDher8Q2fVBQfOqk63x2c/tbW1anh4uLpz505VVVW1oKBABdSvvvpKLS4uVk+dOqVu2LBBTUtLU3U6nbpy5cpmvycul0uNiYlR169f77fNmn9GPbvgHfXsK2+qBf/+inpizBT1xOjJAX8X3v2kyeNcfc/69Omjbt++/WZOt9G4IfNUhBD3hP8qKOJwrZUgIEYJwuLRojqhyuamtM6J+6qn2ZKHOxBnubJ88Oeff87zzz9PeXk5iqJQWFhIfHw8e/fupW9f35Qnv/rVr9i4cSOFhYXeVCxZWVnMnTuXvXv3EhERwciRI3n99dcJDa1vNdTW1jJlyhTWrFlDcHAw06dP55tvviEqKsonm8CECRNwOBx8+umn3jLV5ebS2p1c/mL7lZMw6NBHh6CxaMHtwF15GWdpGagqkeN+TsSIx5vvxgYm81SEEPe2HloTsZVBuC/AufNOci/YOF5uo7jWN6AAHL5Uh8tzpXDnzp2kpKR4k0U25cUXX6SystI7DLep9VAazJo1i+3bt7N27Vq2bNnCwYMHA6ZHSU1NZfv27T5lHocL2/FrZrzbXTjOXsZ2rAxbXhXOEi0EtUXfPglDQufrXsOtdBeOrRNCCH9tDHou1N3YCKmvz1UxuF0ouu9euE+fPu1NaX89DTm7Tp06BTS9HkppaSlms5k//elPfPLJJ/zkJz8B4MMPPyQuLs5v323btqWoqAiXy4Xuu1FcqtOJ9Ujh9U/M4cZxrhJjx8aXT24JElSEEPeEbhFGFG7sm32t3U15nYu2IfWfwKxWq9+kwMY0dBk0tGqaWg/l5MmTmM1mnE4nqamp3u3BwcEBMyiYTCZUVcVms2GxWPA4XNTszUPR61Dt1w+YhvhYNObbOxdKgooQ4p4QptfROdTAyapGJgiqEG/Uo6lTKCix87/aS7zwcDSmIA1RUVFcvnz5ho7TsHBX5871n5ka1kOZMWOGX9127dqRl5d3w9dw6dIlb8JSb9nqQ6DEYEwy47p8EVdJ4+dp7tXlho91q0ifihDintE3OtivzKxR6BZkJKpGR8FpBycv2vGosPdsDc7vOlt69+7tDRbXs2TJEsLCwnj88frO8KvXQ7n2ZzKZSEhIICgoiL1793r3UVdXx+HDh/32ffjwYfr0qZ9nozrd1O4rxFNtR7W5seVW4yoxou/YBUOXDqD1f3xbHkryK2tpElSEEPeM/jEh3mFJ7fRBdMWIqwSOnbVRVuu7FovbA8u+KcHu8jBs2DCOHTtGeblv2vjy8nIuXLhAQUEBf//73xk5ciSff/457733HmFhYcD110OxWCxMmDCBOXPmsHnzZo4ePcqkSZPweDx+AwN27tzpnffkcbopW+Gf6NFxugb7CScaS3uM3bqgDatv1QS1jcQQ3+YH38MfSj5/CSHuGTHmIAZHhXD8nI2iC06g6X6IIxfqOHHeRtekHqSmprJq1SqmTbuSNr/hAW8ymYiLi+PHP/4x+/btIzk52VunYT2UefPm8eijj+J2u+ncubPPRM0lS5ZQW1vLyJEjsVgszJgxg5KSEozGKznKioqKyMrK4tNPP8Vjc1Gx/jDuqsYTSHoqHdgqHaAJwfBAO0IG3v5PXyDrqQgh7jH7ztawZFvTqx8CtDfrsZV5qLV5eOv5jnyzPZOMjAyOHj3qlyKmudntdjp27Mjs2bO9o8Zmz55NZWUl/7P0XeoOlVH8uz0YEoy4yi7grrQ2uT/FoKPT0rFoLS3WSS/zVIQQ94c+ccG0DW08Z1uQBroZjZw75eBipYs6u4f/XneBwUOGMm3aNM6dO9fs55Sdnc1nn31Gfn4+2dnZpKenU11dzejRo711oqOj+c8F/4G7xknJuzkA2E/a8DgjMSY2Pdw5dHBSSwaUJklLRQhxz/lnYTVv7fRfJbGhdXKx0uW3rV9iMNNGxKDXNf+7dnZ2Ns899xzHjx9Hp9PRq1cvlixZ4rMKqOpR8VhdnJ27A1ep/0Jb+gQj7gCtFsWgo+NbY9CFB15H5RZptKUiQUUIcc9RVZV5fz/HyfL64cU6DXQxGMktsNHYI++BCAPRxiBeGB2NQd+yH3FUtwd3jZviN/NwlxfjKg/8uUsxazHEebDlnfeWRfy8D5G/6Buw/i0kn7+EEPcPRVH4t9TWKArEmfW0qtVx7FTTAaXguJ2sAzX8/qMLWG0eXK6Weaf22Nw4Sx2ce/kY9jwrqrsVusjAK1eqdW5seSqGhHi0oSZ0rUOISEsOWPd2kZaKEOKetXbfJf5366VGgwlcCShu95WysBAtM/41lk5xBozGW/PurXpUVJdKxYYLXPq8mKsTlGnDNSjaS422WAAUi4Y2M/pg7nFbhhFLS0UIcf/5aa9w2kXqG90eKKAAVFa7+XD5RZYvL8Vq9WC3+69x8kO4rR4cJU5OzTtHzaE6rs14XnNhGQAABuJJREFU6a7wNNliAQh9pMPtCihNkpaKEOKeVlTuYN6fz2J1+D7OGgsoAN1ijRzLrp8jEhysYfDgUJ4aGUFQkILRdHPv4h6XiupRsZ9zULbuMlX7asENikbFEmPHWew/J6WxFoshIZy4Bf1Rgm7t0OcmSEe9EOL+tT+/liVri72fwZoKKK1DdVQWuHFcE4RSk4yY9RoGjwgnvmv9pEXVoxJk0KDR+D9j3S4Vj1NFq1NwWT2U7q3hzMYKokwaHPm++cmMbRQorfBrsYB/YNFGGGm/cAC6Vo23YlqABBUhxP3tqwMVrPi6rMmAAtBer+fsaYdPWbBZoZULnFcFmi5JRtqFaWn7gJGo9np0eg0WiwZ7lRunzUNZvh1rmRPnwTqc1Vc+n0V21KO/Zv8Aod3Acawi4Dk1BBZPnZO2rz6MMT78Ju5As5KgIoQQ/9hXwceryhoNKN1ijBzL8f8MlZJkpCjXt7xbFwMVJ3xbHD0SjVzK863X3qzBVefbJ9MhWoez1HeuTFOfwQCCYnVET+2AKbFV4JNvWdJRL4QQQ/uGMzYtikALPEaH6sg/4p82XwHqyv0nSxp1118lEsAQ7Z9i0d3Kv0z1KDgxgdZ/v5pgLTHTHrhTAkqTJKgIIe4rTz4aTsa/xmLQ+z68DVYNTqf/x5nETnouX/QPKte2PhoVoGO/9LQdxeAfPGzFKvrEMJ+yoFgDca91w9jF4lf/TiRBRQhx3/mXXhb+89/jiI6sbzF0izVy9ox/PwdASICWgwJUld7Y0sW2AJMonVaVoE6Bc3VVH1cJalM/EMDcO4y4hd3QtzUGrHsnkj4VIcR9y2rzsHp9OVv+WuU32gugVbgWY5UbzzWNktZROnRl/q2XQH0qoZE6ggN8PgttoyO42L8cwNRRS+RjwYQPi/4eV9OipE9FCCGuZTJqeHZUa2bNakNsrH9m44Q2QX4BBSCy1Y3PD6kqd6Ez+z9qq4pd6Nv7T8y0JJtpPyvuTg4oTZJFuoQQ973kZDNLlnQgM7OSL7+8TGWlG60GLhcF/sRl0ipUfo/9G1rrcAUYRmw3Kd5XfmNnAzGjWxGS7L8k8t1EgooQQgA6ncLw4eE89lgo27ZVceKwlfy9tQHruq3fM21LgJYKQOkpOwl9zUQ+FkZIn7s7mDSQPhUhhGhE/lEr+3ZWc2hfDbVXTWDsZNZgDzD6K1CfCkD7RAOuvCvDlYPbBhHdz0LbR0Mwxzaem+wOJpMfhRDiZnk8KqfzbZw4bOVikYOKY1ZqLvnPoAwUVBQFYpOMxEbqCE80Efmg6W4NJFeToCKEEM3JVuOmssxFzWUX1mo3LoeKWaeASyXIpMEYqsUcqSM4SoeuhRf9agESVIQQQjQbGVIshBDi1pOgIoQQotlIUBFCiCYsWrSIhx56iNDQUFq3bk1aWhqHDx/2bu/UqROKovj9fvrTn/rsZ9myZcTHx2M0GklJSWHnzp0tfSktQoKKEEI0Ydu2bUydOpWsrCy2bNmCTqfj8ccf59KlSwDs3buX4uJi7+/AgQMoisIvf/lL7z5Wr15NRkYGL7/8MtnZ2fTv35/hw4dz5syZ23VZt4x01AshxPdQU1NDWFgYX375JWlpaX7bFy5cyBtvvEFxcTEmU/3qjP369ePBBx9k+fLl3npdunRh1KhRLFq0qMXOvRlJR70QQjSH6upqPB4PERERfttUVeXDDz9k3Lhx3oDicDjYv38/Q4cO9ak7dOhQsrKyWuScW5IEFSGE+B4yMjLo1asXDz/8sN+2zMxMCgoKeO6557xlZWVluN1uYmJifOrGxMRw4cKFW36+LU1yfwkhxA2aOXMmu3btYteuXWi1/pmKly9fzkMPPURycvJtOLs7g7RUhBDiBsyYMYOVK1eyZcsWOnfu7Le9tLSUdevW+bRSAKKiotBqtZSUlPiUl5SUEBsbe0vP+XaQoCKEENeRkZHhDShJSUkB66xYsQKDwcAzzzzjU67X60lJSSEzM9OnPDMzk/79+9+yc75d5POXEEI0Ydq0afz5z3/myy+/JCIiwtsPYrFYsFjq141XVZUPPviAMWPGeMuuNnPmTMaPH09qaiqPPPII7733HufPn2fy5Mktei0tQYYUCyFEExQl8OjZ+fPns2DBAgC2bt3KY489xu7du0lNTQ1Yf9myZfzud7+juLiYnj178oc//IGBAwfeqtO+1SShpBBCiGYj81SEEELcehJUhBBCNBsJKkIIIZqNBBUhhBDNRoKKEEKIZiNBRQghRLORoCKEEKLZSFARQgjRbK6XpqXRCS5CCCHEtaSlIoQQotlIUBFCCNFsJKgIIYRoNhJUhBBCNBsJKkIIIZqNBBUhhBDN5v8BZJma7Is/I9cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##### build your quantum circuit here\n",
    "#u = quantum_info.Operator(U)\n",
    "U = get_unitary()\n",
    "\n",
    "qc_org = QuantumCircuit(4)\n",
    "qc_org.unitary(U,[0,1,2,3])\n",
    "#qc.iso(U,q[:4],q[4:])\n",
    "\n",
    "# Run the quantum circuit on a statevector simulator backend\n",
    "backend = Aer.get_backend('statevector_simulator')\n",
    "job = execute(qc_org, backend)\n",
    "result = job.result()\n",
    "state = result.get_statevector(qc_org)\n",
    "dm = quantum_info.DensityMatrix(state).data\n",
    "plot_state_qsphere(state, show_state_labels=True, show_state_angles=1) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Theory\n",
    "\n",
    "I started by implementing this [paper](https://arxiv.org/abs/1804.00633). $7$ layers of $U_3$ gates and $CU_3$ and I varaied the targeting quibts in each layer.\n",
    "\n",
    "Then I started to decrease the number of rotations and the controlled ones till I got $U_3 = 17$ and $ CU_3= 13$.\n",
    "\n",
    "The pruning process was inspired by the shape of the sandwiched $U$ between Hadamard gates. That's why I kept the first and last 4 $U_3s$. That Approach achieved a cost of $201$ which is great but I cheated a little bit and thresholded all the absolute values below 0.01. That achieved a cost of 132 and an error of $0.006499$.\n",
    "\n",
    "The optimization process was a bit tedious since the cost funtion was the $\\lVert U - V\\rVert_2$. This means that i'm going to optimize manay parameters based on somehting like mean squared error function and that's not good at all for convergence.\n",
    "I used the unitary simulator to get the unitary matrix and just calculated the following cost function\n",
    "```\n",
    "np.linalg.norm(U-unit,ord=2)\n",
    "\n",
    "```\n",
    "and then I used Sequential Least SQuares Programming (SLSQP) as the optimizer from Aqua since it's fast and it avoided local minima vallies in our problem. Weight initialization was very small so that the optimizer would move freely to the lowest possible point and also to make the weights as sparse as possible so that we can threshold them. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "U = get_unitary()\n",
    "def qis_circuit(params):\n",
    "    q = QuantumRegister(4)\n",
    "    qc = QuantumCircuit(q)\n",
    "    \n",
    "    qc.u3(params[0],params[1],params[2],0)\n",
    "    qc.u3(params[3],params[4],params[5],1)\n",
    "    qc.u3(params[6],params[7],params[8],2)\n",
    "    qc.u3(params[9],params[10],params[11],3)\n",
    "    \n",
    "    qc.cu3(params[12],params[13],params[14],3,0)\n",
    "  \n",
    "    qc.u3(params[15],params[16],params[17],0)\n",
    "    qc.u3(params[18],params[19],params[20],1)\n",
    "    qc.cu3(params[21],params[22],params[23],0,2)\n",
    "    qc.u3(params[24],params[25],params[26],2)\n",
    "    \n",
    "    qc.u3(params[27],params[28],params[29],3)\n",
    "              \n",
    "    qc.cu3(params[30],params[31],params[32],1,0)\n",
    "    \n",
    "    qc.cu3(params[33],params[34],params[35],2,3)\n",
    "    qc.cu3(params[36],params[37],params[38],3,1)\n",
    "           \n",
    "    qc.u3(params[39],params[40],params[41],0)\n",
    "\n",
    "    qc.u3(params[42],params[43],params[44],1)\n",
    "    \n",
    "    qc.cu3(params[45],params[46],params[47],1,2)\n",
    "    qc.cu3(params[48],params[49],params[50],2,3)\n",
    "\n",
    "    qc.u3(params[51],params[52],params[53],2)\n",
    "   \n",
    "    qc.cu3(params[54],params[55],params[56],0,1)\n",
    "\n",
    "    qc.cu3(params[57],params[58],params[59],1,3)\n",
    "    qc.u3(params[60],params[61],params[62],3)\n",
    "    qc.cu3(params[63],params[64],params[65],3,0)\n",
    "    \n",
    "    qc.u3(params[66],params[67],params[68],0)\n",
    "    qc.cu3(params[69],params[70],params[71],0,2)\n",
    "\n",
    "    qc.cu3(params[75-3],params[76-3],params[77-3],1,3)\n",
    "    qc.cu3(params[78-3],params[79-3],params[80-3],2,1)    \n",
    "\n",
    "    qc.u3(params[81-3],params[82-3],params[83-3],3)\n",
    "    \n",
    "    \n",
    "    qc.u3(params[84-3],params[85-3],params[86-3],0)\n",
    "    qc.u3(params[87-3],params[88-3],params[89-3],1)\n",
    "    qc.u3(params[90-3],params[91-3],params[92-3],2)\n",
    "            \n",
    "    backend = Aer.get_backend('unitary_simulator')\n",
    "    job = execute(qc, backend)\n",
    "    result = job.result()\n",
    "    return result.get_unitary(qc),qc\n",
    "\n",
    "\n",
    "def qis_cost(params):\n",
    "    unit = qis_circuit(params)[0]\n",
    "    temp = np.linalg.norm(U-unit,ord=2)\n",
    "    print(temp)\n",
    "    return temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "opt = SLSQP(disp=True,tol=1e-13,ftol=1e-13,maxiter=1100)\n",
    "np.random.seed(70)\n",
    "x = np.random.uniform(0,0.1,90)\n",
    "data = opt.optimize(objective_function=qis_cost,num_vars=90,initial_point=x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "loss_data = pd.read_csv('loss.csv').values\n",
    "plt.plot(loss_data,label='loss')\n",
    "plt.xlabel('iterations')\n",
    "plt.ylabel('loss')\n",
    "plt.title('loss curve')\n",
    "plt.legend()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('u3', 17), ('cu3', 13)])\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2070.19x687.14 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = np.load('qiskit-challenge-weights.npy',allow_pickle=True)\n",
    "\n",
    "u = data[0]\n",
    "\n",
    "complete_circ = qis_circuit(u)[1]\n",
    "\n",
    "print(complete_circ.count_ops())\n",
    "\n",
    "complete_circ.draw(output='mpl',scale=0.85)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('u3', 31), ('cx', 17)])\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2191.97x727.56 with 1 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = transpile(complete_circ, backend=BasicAer.get_backend('qasm_simulator'), \n",
    "                         optimization_level=3,basis_gates=['u3','cx'],seed_transpiler=2)\n",
    "print(qc.count_ops())\n",
    "qc.draw('mpl',scale=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Circuit stats:\n",
      "||U-V||_2 = 3.7789372338197153e-07\n",
      "(U is the reference unitary, V is yours, and the global phase has been removed from both of them).\n",
      "Cost is 201\n",
      "\n",
      "Great! Your circuit meets all the constrains.\n",
      "Your score is 201. The lower, the better!\n",
      "Feel free to submit your answer and remember you can re-submit a new circuit at any time!\n"
     ]
    }
   ],
   "source": [
    "##### check your quantum circuit by running the next line\n",
    "check_circuit(qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('u3', 17), ('cu3', 13)])\n",
      "OrderedDict([('u3', 22), ('cx', 11)])\n",
      "Circuit stats:\n",
      "||U-V||_2 = 0.006499012124886762\n",
      "(U is the reference unitary, V is yours, and the global phase has been removed from both of them).\n",
      "Cost is 132\n",
      "\n",
      "Great! Your circuit meets all the constrains.\n",
      "Your score is 132. The lower, the better!\n",
      "Feel free to submit your answer and remember you can re-submit a new circuit at any time!\n",
      "None\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1704.86x565.88 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "threshold_indices = abs(data[0]) < 0.01\n",
    "\n",
    "data[0][threshold_indices] = 0 \n",
    "\n",
    "ff = qis_circuit(data[0])[1]\n",
    "\n",
    "print(ff.count_ops())\n",
    "\n",
    "qc = transpile(ff, backend=BasicAer.get_backend('qasm_simulator'), \n",
    "                         optimization_level=3,basis_gates=['u3','cx'],seed_transpiler=5)\n",
    "print(qc.count_ops())\n",
    "\n",
    "print(check_circuit(qc))\n",
    "\n",
    "qc.draw('mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can check whether your circuit is valid before submitting it with `check_circuit(qc)`. Once you have a valid solution, please submit it by running the following cell (delete the `#` before `submit_circuit`). You can re-submit at any time.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Send the circuit as the final answer, can re-submit at any time\n",
    "submit_circuit(qc) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# analytic solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.2134+0.3384j -0.1402-0.0884j  0.2134-0.0884j  0.0366+0.0884j\n",
      "   0.0884-0.0366j -0.0884-0.2134j -0.0884+0.1402j  0.3384+0.2134j\n",
      "   0.2134-0.0884j  0.0366+0.0884j  0.3902+0.0884j -0.0366+0.1616j\n",
      "   0.1616+0.0366j  0.0884-0.3902j  0.0884-0.0366j -0.0884-0.2134j]\n",
      " [-0.1402-0.0884j -0.2134+0.3384j  0.0366+0.0884j  0.2134-0.0884j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.3384+0.2134j -0.0884+0.1402j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.0366+0.1616j  0.3902+0.0884j\n",
      "   0.0884-0.3902j  0.1616+0.0366j -0.0884-0.2134j  0.0884-0.0366j]\n",
      " [ 0.2134-0.0884j  0.0366+0.0884j -0.2134+0.3384j -0.1402-0.0884j\n",
      "  -0.0884+0.1402j  0.3384+0.2134j  0.0884-0.0366j -0.0884-0.2134j\n",
      "   0.3902+0.0884j -0.0366+0.1616j  0.2134-0.0884j  0.0366+0.0884j\n",
      "   0.0884-0.0366j -0.0884-0.2134j  0.1616+0.0366j  0.0884-0.3902j]\n",
      " [ 0.0366+0.0884j  0.2134-0.0884j -0.1402-0.0884j -0.2134+0.3384j\n",
      "   0.3384+0.2134j -0.0884+0.1402j -0.0884-0.2134j  0.0884-0.0366j\n",
      "  -0.0366+0.1616j  0.3902+0.0884j  0.0366+0.0884j  0.2134-0.0884j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.0884-0.3902j  0.1616+0.0366j]\n",
      " [ 0.0884-0.0366j -0.0884-0.2134j -0.0884+0.1402j  0.3384+0.2134j\n",
      "  -0.2134+0.3384j -0.1402-0.0884j  0.2134-0.0884j  0.0366+0.0884j\n",
      "   0.1616+0.0366j  0.0884-0.3902j  0.0884-0.0366j -0.0884-0.2134j\n",
      "   0.2134-0.0884j  0.0366+0.0884j  0.3902+0.0884j -0.0366+0.1616j]\n",
      " [-0.0884-0.2134j  0.0884-0.0366j  0.3384+0.2134j -0.0884+0.1402j\n",
      "  -0.1402-0.0884j -0.2134+0.3384j  0.0366+0.0884j  0.2134-0.0884j\n",
      "   0.0884-0.3902j  0.1616+0.0366j -0.0884-0.2134j  0.0884-0.0366j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.0366+0.1616j  0.3902+0.0884j]\n",
      " [-0.0884+0.1402j  0.3384+0.2134j  0.0884-0.0366j -0.0884-0.2134j\n",
      "   0.2134-0.0884j  0.0366+0.0884j -0.2134+0.3384j -0.1402-0.0884j\n",
      "   0.0884-0.0366j -0.0884-0.2134j  0.1616+0.0366j  0.0884-0.3902j\n",
      "   0.3902+0.0884j -0.0366+0.1616j  0.2134-0.0884j  0.0366+0.0884j]\n",
      " [ 0.3384+0.2134j -0.0884+0.1402j -0.0884-0.2134j  0.0884-0.0366j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.1402-0.0884j -0.2134+0.3384j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.0884-0.3902j  0.1616+0.0366j\n",
      "  -0.0366+0.1616j  0.3902+0.0884j  0.0366+0.0884j  0.2134-0.0884j]\n",
      " [ 0.2134-0.0884j  0.0366+0.0884j  0.3902+0.0884j -0.0366+0.1616j\n",
      "   0.1616+0.0366j  0.0884-0.3902j  0.0884-0.0366j -0.0884-0.2134j\n",
      "  -0.2134+0.3384j -0.1402-0.0884j  0.2134-0.0884j  0.0366+0.0884j\n",
      "   0.0884-0.0366j -0.0884-0.2134j -0.0884+0.1402j  0.3384+0.2134j]\n",
      " [ 0.0366+0.0884j  0.2134-0.0884j -0.0366+0.1616j  0.3902+0.0884j\n",
      "   0.0884-0.3902j  0.1616+0.0366j -0.0884-0.2134j  0.0884-0.0366j\n",
      "  -0.1402-0.0884j -0.2134+0.3384j  0.0366+0.0884j  0.2134-0.0884j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.3384+0.2134j -0.0884+0.1402j]\n",
      " [ 0.3902+0.0884j -0.0366+0.1616j  0.2134-0.0884j  0.0366+0.0884j\n",
      "   0.0884-0.0366j -0.0884-0.2134j  0.1616+0.0366j  0.0884-0.3902j\n",
      "   0.2134-0.0884j  0.0366+0.0884j -0.2134+0.3384j -0.1402-0.0884j\n",
      "  -0.0884+0.1402j  0.3384+0.2134j  0.0884-0.0366j -0.0884-0.2134j]\n",
      " [-0.0366+0.1616j  0.3902+0.0884j  0.0366+0.0884j  0.2134-0.0884j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.0884-0.3902j  0.1616+0.0366j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.1402-0.0884j -0.2134+0.3384j\n",
      "   0.3384+0.2134j -0.0884+0.1402j -0.0884-0.2134j  0.0884-0.0366j]\n",
      " [ 0.1616+0.0366j  0.0884-0.3902j  0.0884-0.0366j -0.0884-0.2134j\n",
      "   0.2134-0.0884j  0.0366+0.0884j  0.3902+0.0884j -0.0366+0.1616j\n",
      "   0.0884-0.0366j -0.0884-0.2134j -0.0884+0.1402j  0.3384+0.2134j\n",
      "  -0.2134+0.3384j -0.1402-0.0884j  0.2134-0.0884j  0.0366+0.0884j]\n",
      " [ 0.0884-0.3902j  0.1616+0.0366j -0.0884-0.2134j  0.0884-0.0366j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.0366+0.1616j  0.3902+0.0884j\n",
      "  -0.0884-0.2134j  0.0884-0.0366j  0.3384+0.2134j -0.0884+0.1402j\n",
      "  -0.1402-0.0884j -0.2134+0.3384j  0.0366+0.0884j  0.2134-0.0884j]\n",
      " [ 0.0884-0.0366j -0.0884-0.2134j  0.1616+0.0366j  0.0884-0.3902j\n",
      "   0.3902+0.0884j -0.0366+0.1616j  0.2134-0.0884j  0.0366+0.0884j\n",
      "  -0.0884+0.1402j  0.3384+0.2134j  0.0884-0.0366j -0.0884-0.2134j\n",
      "   0.2134-0.0884j  0.0366+0.0884j -0.2134+0.3384j -0.1402-0.0884j]\n",
      " [-0.0884-0.2134j  0.0884-0.0366j  0.0884-0.3902j  0.1616+0.0366j\n",
      "  -0.0366+0.1616j  0.3902+0.0884j  0.0366+0.0884j  0.2134-0.0884j\n",
      "   0.3384+0.2134j -0.0884+0.1402j -0.0884-0.2134j  0.0884-0.0366j\n",
      "   0.0366+0.0884j  0.2134-0.0884j -0.1402-0.0884j -0.2134+0.3384j]]\n",
      " ....... \n",
      "[[ 1.    +0.j      0.    +0.j      0.    +0.j     -0.    +0.j\n",
      "   0.    -0.j      0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.    +0.j     -0.    -0.j     -0.    -0.j     -0.    -0.j\n",
      "   0.    -0.j      0.    +0.j      0.    +0.j     -0.    -0.j    ]\n",
      " [ 0.    +0.j      0.7071+0.7071j  0.    +0.j     -0.    +0.j\n",
      "  -0.    -0.j     -0.    +0.j      0.    -0.j      0.    +0.j\n",
      "  -0.    -0.j      0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.    +0.j      0.    -0.j     -0.    -0.j      0.    -0.j    ]\n",
      " [ 0.    +0.j      0.    +0.j     -0.7071-0.7071j  0.    +0.j\n",
      "  -0.    +0.j      0.    -0.j     -0.    +0.j     -0.    +0.j\n",
      "  -0.    -0.j      0.    -0.j      0.    +0.j     -0.    +0.j\n",
      "   0.    +0.j      0.    +0.j      0.    +0.j      0.    -0.j    ]\n",
      " [-0.    +0.j      0.    -0.j     -0.    +0.j     -0.    +1.j\n",
      "  -0.    +0.j      0.    +0.j     -0.    +0.j     -0.    -0.j\n",
      "   0.    +0.j     -0.    -0.j      0.    -0.j     -0.    +0.j\n",
      "   0.    -0.j      0.    +0.j      0.    +0.j      0.    -0.j    ]\n",
      " [ 0.    +0.j     -0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "   0.    +1.j      0.    +0.j     -0.    +0.j     -0.    +0.j\n",
      "  -0.    -0.j     -0.    -0.j      0.    +0.j     -0.    -0.j\n",
      "  -0.    -0.j      0.    +0.j      0.    +0.j     -0.    -0.j    ]\n",
      " [ 0.    -0.j     -0.    -0.j      0.    +0.j      0.    +0.j\n",
      "   0.    -0.j      0.7071-0.7071j  0.    -0.j      0.    -0.j\n",
      "  -0.    -0.j      0.    +0.j     -0.    +0.j     -0.    -0.j\n",
      "  -0.    -0.j      0.    -0.j     -0.    +0.j     -0.    -0.j    ]\n",
      " [-0.    -0.j      0.    +0.j     -0.    -0.j      0.    -0.j\n",
      "   0.    -0.j      0.    +0.j     -0.7071+0.7071j -0.    +0.j\n",
      "  -0.    +0.j     -0.    -0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.    +0.j      0.    +0.j     -0.    +0.j     -0.    +0.j    ]\n",
      " [-0.    -0.j     -0.    +0.j      0.    +0.j     -0.    +0.j\n",
      "   0.    -0.j      0.    +0.j      0.    +0.j     -1.    -0.j\n",
      "  -0.    -0.j     -0.    +0.j     -0.    +0.j     -0.    +0.j\n",
      "   0.    -0.j     -0.    -0.j      0.    +0.j     -0.    -0.j    ]\n",
      " [-0.    -0.j     -0.    +0.j      0.    +0.j      0.    +0.j\n",
      "  -0.    -0.j      0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.7071+0.7071j -0.    -0.j      0.    -0.j     -0.    -0.j\n",
      "   0.    -0.j     -0.    -0.j      0.    +0.j      0.    -0.j    ]\n",
      " [-0.    +0.j      0.    -0.j     -0.    +0.j     -0.    +0.j\n",
      "   0.    -0.j      0.    -0.j      0.    +0.j      0.    +0.j\n",
      "  -0.    -0.j     -1.    +0.j      0.    +0.j      0.    -0.j\n",
      "  -0.    +0.j      0.    +0.j      0.    +0.j     -0.    -0.j    ]\n",
      " [ 0.    +0.j     -0.    +0.j      0.    -0.j     -0.    +0.j\n",
      "  -0.    +0.j      0.    -0.j     -0.    +0.j      0.    +0.j\n",
      "   0.    +0.j      0.    -0.j     -1.    +0.j      0.    +0.j\n",
      "  -0.    -0.j     -0.    -0.j     -0.    +0.j      0.    -0.j    ]\n",
      " [-0.    -0.j      0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.    -0.j      0.    -0.j     -0.    -0.j      0.    +0.j\n",
      "   0.    -0.j      0.    +0.j      0.    -0.j      0.7071+0.7071j\n",
      "   0.    -0.j      0.    -0.j      0.    -0.j      0.    +0.j    ]\n",
      " [ 0.    +0.j      0.    -0.j     -0.    +0.j     -0.    -0.j\n",
      "   0.    +0.j     -0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "   0.    +0.j     -0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.7071-0.7071j  0.    -0.j      0.    +0.j     -0.    +0.j    ]\n",
      " [ 0.    -0.j     -0.    +0.j      0.    -0.j      0.    +0.j\n",
      "   0.    +0.j     -0.    +0.j      0.    +0.j      0.    +0.j\n",
      "   0.    +0.j      0.    +0.j     -0.    +0.j      0.    -0.j\n",
      "  -0.    -0.j      0.    +1.j     -0.    -0.j     -0.    -0.j    ]\n",
      " [-0.    -0.j     -0.    +0.j     -0.    -0.j      0.    -0.j\n",
      "  -0.    -0.j      0.    +0.j     -0.    -0.j      0.    +0.j\n",
      "  -0.    -0.j     -0.    -0.j      0.    -0.j      0.    +0.j\n",
      "  -0.    -0.j     -0.    -0.j     -0.    +1.j      0.    -0.j    ]\n",
      " [ 0.    -0.j     -0.    +0.j     -0.    +0.j      0.    -0.j\n",
      "   0.    -0.j      0.    +0.j     -0.    +0.j      0.    -0.j\n",
      "   0.    +0.j     -0.    -0.j     -0.    +0.j      0.    +0.j\n",
      "   0.    +0.j      0.    -0.j     -0.    +0.j     -0.7071+0.7071j]]\n",
      "......\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('u3', 18), ('cx', 13)])\n",
      "Circuit stats:\n",
      "||U-V||_2 = 7.802192551692307e-15\n",
      "(U is the reference unitary, V is yours, and the global phase has been removed from both of them).\n",
      "Cost is 148\n",
      "\n",
      "Great! Your circuit meets all the constrains.\n",
      "Your score is 148. The lower, the better!\n",
      "Feel free to submit your answer and remember you can re-submit a new circuit at any time!\n"
     ]
    }
   ],
   "source": [
    "h = np.array([[1,1],[1,-1]])\n",
    "H = np.kron(h,np.kron(h,np.kron(h,h)))/4\n",
    "U = get_unitary()\n",
    "print(np.round(U,4))\n",
    "print(\" ....... \")\n",
    "U = H@U@H\n",
    "print(np.round(U,4))\n",
    "print(\"......\")\n",
    "q = QuantumRegister(4)\n",
    "qc = QuantumCircuit(q)\n",
    "qc.u3(pi/2,0,pi,0)\n",
    "qc.u3(pi/2,0,pi,1)\n",
    "qc.u3(pi/2,0,pi,2)\n",
    "qc.u3(pi/2,0,pi,3)\n",
    "qc.isometry(U,q[:4],[])\n",
    "qc.u3(pi/2,0,pi,0)\n",
    "qc.u3(pi/2,0,pi,1)\n",
    "qc.u3(pi/2,0,pi,2)\n",
    "qc.u3(pi/2,0,pi,3)\n",
    "\n",
    "qc = transpile(qc, backend=BasicAer.get_backend('qasm_simulator'), \n",
    "                         optimization_level=3,basis_gates=['u3','cx'])\n",
    "print(qc.count_ops())\n",
    "#qc.draw()\n",
    "check_circuit(qc)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}