code_camp_II.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import *\n",
    "import numpy as np\n",
    "import pylab as pl\n",
    "import networkx as nx\n",
    "from qiskit.visualization import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1]), array([0, 1]))"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "V = np.arange(0,2,1)\n",
    "E =[(0,1,1.0)] \n",
    "\n",
    "G = nx.Graph()\n",
    "G.add_nodes_from(V)\n",
    "G.add_weighted_edges_from(E)\n",
    "\n",
    "nx.draw_networkx(G)\n",
    "np.array(list(G.nodes)), V"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createCircuit(x,G,depth):\n",
    "    V = list(G.nodes)\n",
    "    num_V = len(V)\n",
    "    q = QuantumRegister(num_V)\n",
    "    c = ClassicalRegister(num_V)\n",
    "    circ = QuantumCircuit(q,c)\n",
    "    circ.h(range(num_V))\n",
    "    circ.barrier()\n",
    "    for d in range(depth):\n",
    "        gamma=x[2*d]\n",
    "        beta=x[2*d+1]\n",
    "        for edge in G.edges():\n",
    "            i=int(edge[0])\n",
    "            j=int(edge[1])\n",
    "            w = G[i][j]['weight']\n",
    "            circ.cx(q[i],q[j])\n",
    "            circ.rz(w*gamma,q[j])\n",
    "            circ.cx(q[i],q[j])\n",
    "        circ.barrier()\n",
    "        circ.rx(2*beta,range(num_V))\n",
    "        circ.barrier()\n",
    "    circ.measure(q,c)\n",
    "    return circ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 769.356x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "createCircuit(np.array((np.pi,np.pi)),G,1).draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1130.56x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "createCircuit(np.array((np.pi,np.pi,1,2)),G,2).draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cost(x,G):\n",
    "    C=0\n",
    "    for edge in G.edges():\n",
    "        i = int(edge[0])\n",
    "        j = int(edge[1])\n",
    "        w = G[i][j]['weight']\n",
    "        C = C + w/2*(1-(2*x[i]-1)*(2*x[j]-1))\n",
    "    return C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def listcosts(G):\n",
    "    costs={}\n",
    "    maximum=0\n",
    "    solutions=[]\n",
    "    V = list(G.nodes)\n",
    "    num_V = len(V)\n",
    "    for i in range(2**num_V):\n",
    "        binstring=\"{0:b}\".format(i).zfill(num_V)\n",
    "        y=[int(i) for i in binstring]\n",
    "        costs[binstring]=cost(y,G)\n",
    "        maximum = max(maximum,costs[binstring])\n",
    "    for key in costs:\n",
    "        if costs[key]==maximum:\n",
    "            solutions.append(key)\n",
    "    return costs, maximum, solutions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'00': 0.0, '01': 1.0, '10': 1.0, '11': 0.0}, 1.0, ['01', '10'])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listcosts(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def expectationValue(data,G):\n",
    "    E=[]\n",
    "    V = list(G.nodes)\n",
    "    num_qubits = len(V)\n",
    "    for item in range(0,len(data.results)):\n",
    "        shots = data.results[item].shots\n",
    "        counts = data.results[item].data.counts\n",
    "        E.append(0)\n",
    "        for key in list(counts.__dict__.keys()):\n",
    "            c=getattr(counts, key)#number of counts\n",
    "            binstring=\"{0:b}\".format(int(key,0)).zfill(num_qubits)\n",
    "            y=[int(i) for i in binstring]\n",
    "            E[item] += cost(y,G)*c/shots\n",
    "    return E"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simulate the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aer.backends()\n",
    "backend_sim = Aer.get_backend('qasm_simulator')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuits=[]\n",
    "n=16\n",
    "for gamma in np.linspace(0,np.pi/2,n):\n",
    "    for beta in np.linspace(0,np.pi/2,n):\n",
    "        circuits.append(createCircuit(np.array((gamma,beta)),G,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "val=expectationValue(job_sim.result(),G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.99658203125"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl.imshow(np.array(val).reshape(n,n))\n",
    "pl.colorbar()\n",
    "np.max(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import optimize as opt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getval(x, backend, noisemodel=None):\n",
    "    j = execute(createCircuit(x,G,1), backend, noise_model=noisemodel, shots=1024*2*2*2)\n",
    "    val=expectationValue(j.result(),G)\n",
    "    return -val[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: -1.000000\n",
      "         Iterations: 21\n",
      "         Function evaluations: 42\n"
     ]
    }
   ],
   "source": [
    "out=opt.minimize(getval, x0=(1, 1), method='Nelder-Mead',\\\n",
    "                 args=(backend_sim,None),\\\n",
    "             options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.57497864, 1.1747406 ])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "j = execute(createCircuit(out.x,G,1), backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(j.result().get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#IBMQ.save_account('yourAPItoken')\n",
    "IBMQ.load_account()\n",
    "provider = IBMQ.get_provider(hub='ibm-q')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "backendnameibm = 'ibmqx2'\n",
    "backendibm = provider.get_backend(backendnameibm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.providers.aer.noise import NoiseModel\n",
    "from qiskit.providers.aer.noise.device import basic_device_noise_model\n",
    "\n",
    "properties = backendibm.properties()\n",
    "ibmqx2noisemodel = basic_device_noise_model(properties)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_sim_noise = execute(circuits, backend_sim, noise_model=ibmqx2noisemodel, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_noise=expectationValue(job_sim_noise.result(),G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.955322265625"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl.imshow(np.array(val_noise).reshape(n,n))\n",
    "pl.colorbar()\n",
    "np.max(val_noise)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: -0.959229\n",
      "         Iterations: 21\n",
      "         Function evaluations: 47\n"
     ]
    }
   ],
   "source": [
    "out_noise=opt.minimize(getval, x0=(1,1),\\\n",
    "                       args=(backend_sim,ibmqx2noisemodel), method='Nelder-Mead',\\\n",
    "             options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "j = execute(createCircuit(out_noise.x,G,1), backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(j.result().get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "V = np.arange(0,5,1)\n",
    "E =[(0,1,1.0),(0,2,1.0),(2,3,1.0),(3,1,1.0),(3,4,1.0),(4,2,1.0)]\n",
    "\n",
    "G = nx.Graph()\n",
    "G.add_nodes_from(V)\n",
    "G.add_weighted_edges_from(E)\n",
    "\n",
    "nx.draw_networkx(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.0 ['01100', '01101', '10010', '10011']\n"
     ]
    }
   ],
   "source": [
    "l,m,maxcost=listcosts(G)\n",
    "print(m,maxcost)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1694.03x806.68 with 1 Axes>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "createCircuit(np.array((0.4,0.1)),G,1).draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uzYzadyefVF3HWvJr4GmlZFVPQECAtSMAAAAAAIAagOIqUE38dOmU2nt4y97Wzqh9z8WT6ti4hWxt+ONcYMWKFdaOAFiFg4ODateube0YAAAAAFBjUI2pZM8//7xFh+3cuHFDBw4ckKenp5ycnOTp6anBgwfrhx9+MOq3detW2djYFPt1586dIuOmpqbqqaeekoeHh2rXrq2uXbtq+/btZco2d+5chYSEKC8vr8zzgvl+Sj6l0CYti7TvTj6pTsW012R/+9vfrB0BuCsuLi56/PHH9f7772vbtm36+eef9dNPP+lf//qX/vznP8vf37/IPQ4ODlq6dKnWrl1LgRUAAAAAKgnF1UqUmJio9957T6+88kqZ783OzpaLi4veffddbdy4UfPnz9fVq1cVERGhnTt3FukfExOjH374wejLycnJqI/BYNCQIUO0cuVKxcTEaPXq1WrUqJEefPBB7du3z+xsU6dO1YULF7Ro0aIyzwvm23vptDo18TVqyzPkad+lRIU2aalLGamK+HK2+ix9VV3/+VdtTjpopaTWt2zZMmtHACxSr149xcbG6sKFC1q8eLGmTJmibt26KSgoSB07dtSIESM0d+5cHTlyRJs3b9YDDzwg6dfC6rBhwxQcHKwWLVpYeSYAAAAAUDPYWztATTJ//nz5+PioZ8+eZb7Xw8NDHh4eevTRRwvbBgwYIHd3d3322WeF/8Au4Ofnp/Dw8FLH/OabbxQXF6e1a9dqwIABkqSIiAgFBgbqpZde0tq1a83K5uLiojFjxuitt97SuHHjyjgzmOP8zetKzkhRx8bGBZMDl5OUnn1HnT1bq1GtutoSNVt2trY6lXJJj615Tz+Mec1KiQGUVa9evfT555+rWbP8fZW3b9+uVatWae/evbp69aqcnJwUEBCg7t27a+TIkerZs6e2bdumd999V97e3nr44Yd148YN9enTR4cOHbLybAAAAACgZmDlaiXJzMzUokWLNHr06CLXDAaDzp49q9atW8vZ2Vnt27dXXFyc/Pz89OSTT5Y4Zp06deTk5CQHBweLMq1atUoNGzZU//79C9scHR0VFRWlb7/9VhkZGWaP9dhjj+nIkSP6/vvvzeqfl5enmJiYMs+5pjqffl2S5OZk/FHfpUd2qrNnKzWr11B2trays83/I52aeUtB7s0rPScAyzzyyCNav369mjVrpvj4eHXs2FHdu3dXTEyMNm/erJ9//lm7d+/WokWLNHHiRDVt2lTR0dHKy8vT9OnTjQqre/futfZ0AAAAAKDGoLhaSXbt2qWUlBT16NGjyLVjx44pKSlJkyZN0rp16zRixAiNGjVKp06dUqdOnYz65ubmKjs7W0lJSZoyZYoMBoOeeuqpImOOHz9e9vb2ql+/voYNG6ajR48W6XPw4EEFBgbKxsbGqL1du3bKyckp9p6ShISEqG7dumavdp0wYYJeffVVs+YMyb/BfXJ1qq23flytlDsZun47XQv2f6f/3f+tXo8YVdjvdMplRS55WYOWv6EhrUOtmNi64uLirB0BMFvnzp315ZdfysHBQTExMeratavJrVnS0tL08ssvG+2RHRcXR2EVAAAAACoZ2wJUkl27dkmSOnToYNS+ZMkSXbp0Se3bt9dzzz0nSerZs6f27t2rr7/+Wh07djTq36NHD+3YsUOS1LhxY61du1bBwcGF111dXfXMM88oMjJSbm5uOnjwoKKjoxUeHq49e/aoVatWhX2vX7+ugICAIlkbNGhQeN1ctra2at++fZEDtoqzZMkSff7559q6dWthsbm0OUOq51Rb/374Oc36fqlafDxVte2d1N7DW9888oK6N2tb2K+Fm4e2jnpZp1Iuqd9Xr2uQb818LQ8dOiQPDw9rxwBMcnZ21qJFi+To6Kj33ntPzz//vFn3FeyxGhkZqbS0NDk6Omro0KEaOHCg2W9yAQAAAADuHsXVSnLhwgU5OTmpXr16Ru3R0dGqX7++3NzcjNpbtWolBwcHo8KpJH3yySdKTU3V+fPntXDhQg0cOFBr1qxRZGSkpPzi7W8LuBEREerXr5+CgoIUHR2tTz/91OI5LFiwQJMmTdKyZcs0fPjwItfd3d2VkJBgcpzo6Gj179+/yCrekuZs6rnl5fcreEuT9dyXFZajJF29/BU3+uUSr2fmZMvJPn+LiHqOteTi4FxJyYyV5XW0xDPPPGOyz7x580z2mzdvXnlFuisvvPGxpPzX7bffV2XVMbNUNXNPnTpVfn5+OnToUOEbbKb89vCqgq0AIiMj9fbbb+vdd9/VunXrZDAYCvtbY45V8bUGAAAAAHP99t9UplBcrSR37tyRk5OTUdu5c+d08OBBtWnTpkj/M2fOKDAwsMg9fn5+hd8PGTJEXbp00bRp03TgwIESn+3r66vw8HDFx8cbtTdo0EA3btwo0r9gxWrBClZJOnHihD777LNSD8mqVauWbt++XeJ16dc5F1f4Km7O5jwX+fYkn9Rft38lOxtbZeflKLbXH6wdCUApbG1tNXnyZEnSCy+8oKysLJP3FFdY3bt3r/bv36+pU6fK19dX/fr10/r16ys6PgAAAABAFFcrTcOGDXXz5k3l5ubKzs5OUn6hUco/ROq3bt++rbi4OA0YMKDUMW1tbRUaGmrWalSDwVBk1VBgYKBWr15d5NqhQ4dkb28vf39/SVJOTo7Gjx+vjz76SNOnTy/xGdevX1ejRo1KzVEw5yZNmhi1Fzdnc59bXsryrkT280sqMIllunr5a3PU36wdo0yvoyXM2Qt43rx5Jg9Gi42NLa9Id2Xm3AWS8l+3335flVXHzFLVyP3bv2vDwsLUsmVLJSUlad26dSbvLamwKuUfErhgwQLNmTNHo0aNMiquWuO/TVV4rQEAAACgMnCgVSXx9/eXwWDQ6dOnC9sKCpG/X+355ptv6uLFiyYPdsrOztb27duN9lEtzokTJxQfH6/OnTsbtQ8ZMkRXr17Vhg0bjMZcunSp+vTpIxcXF0nSq6++qgEDBigkJKTU55w+fbqwIFuSgjkfP37cqL24OZv7XOD3XnnlFWtHAEwKDc0/dG7Tpk3Ky8srtW9phdUC3333ndG4AAAAAICKx8rVShIRESFJ+vHHHwuLoS1btlRwcLCOHDkie3t7bdq0ScuXLy88jOS3hcaDBw+qTp06WrlypRo0aKAzZ85owYIFOnjwoL7++uvCfqNHj5aPj486deqk+vXr6+DBg3rjjTdUq1YtzZo1yyjTQw89pO7du2vcuHF688035enpqffff19nzpzRkiX5KzPj4+O1efNmbd26tdT5paSk6Pjx45o2bVqp/QrmHB0drQYNGqhp06bFztnc5wLFGTFihLUjACYVHChY2rYuknmFVUlKSEhQXl6e/P39ZWdnp9zc3ArJDQAAAAD4FcXVSuLj46Pw8HCtXr1ao0ePlpT/sf5ly5YpLCxMJ06c0Lhx4zR27FhNmTJFs2bNMjrYqV69erp69aomTJigmzdvqkGDBurSpYvi4uLUrVu3wn7BwcFaunSpPvzwQ2VkZMjd3V19+vTR7Nmz5evra5TJxsZGq1ev1gsvvKAZM2YoPT1dHTp00MaNGwuLnFu2bNHJkycL701OTtbhw4eVlJSkZ599tnCsNWvWyMHBweSBUwVznjRpkiZPnqyGDRsWO2dznwsUp23btjpy5Ii1YwClWrduna5evaodO3aU2m/69OkmC6uSlJmZqddee005OTkcHgUAAAAAlYTiaiWaMmWKnnzySaWkpMjNzU2S1KZNm8KPvRes0hwzZowCAgJUq1atwnubN2+u5s2bm1zJOXPmTM2cOdPsTG5ubvr444/18ccfmzVeZGSkpk6dWqSI+sUXX2jEiBFyd3c3+cw2bdpoy5YtRm2/n7O5z63qntuyWD8ln1KHxj6K7TW2sP3Hi7/ouS2LZWtjo9AmvorpOabcnnn+5nXF7v5GI9s+cFfPOH/zup7a8A+lZt2qkJxATbdmzRqtWbPGZL933nlH7dq10zvvvFNiYbXA7NmzyyseAAAAAMAM7LlaiUaPHq1WrVpp/vz5pfbbs2ePyf1Wq5Ldu3dr27Ztd7XPZXWbszn2XTqt9Kw72jJqtrJyc7Tn4snCa83rNdLGES9p66iXdflWqhKunCm3525KSlBv76C7fsampASNCuhaYTkBmCcrK0tjx441WVgFAAAAAFQ+Vq5WIltbW3366afatm1biX3S09N1/PhxPf3005WYzHzFrZy9fPmyPv/8c7Vs2dKiMc2Zc3XcezX+wi/q7R0kSerlHaRdF08o1DN/m4MmLm6F/Rxs7WVnU/b3OeLOHNajq2IV7O6txNQrCvbw1tcPP6vvzx7R/N5PqI6js1nPMDWOs73jXeW0hsjISGtHAAAAAAAANQDF1UoWGhpa6knOderUqXaHkAwaNOiu7q+OczZHSmaGWrh5SJJcnWrp8NVbRfr8fOWMrt5KU0AjrzKP372Zv+739NV/hr+ocWs/1Gvdo2QwGJSRnWlUWDX1DHPGuZuc1vDRRx9ZOwIAAAAAAKgBKK4CFcTVqbbSMm9LktIyb8vNubbR9eu30zV90+f68qE/lThGckaKHl/znlFbYxdX/d9Df9KplMtq4ZpfvD1387qa1m2g/ZcTFezhXaZnmBrHnDGqmsmTJ1NgBQAAAAAAFY7iKlBBwu9rrX8c2KRH/cO1Oemg/tAuovBaTl6unlj7geb2GF24RUBOXq6u3U5XYxfXwn5NXNz0XdRfix3/8LVzCmjopdy8PNn+92TwTYkJ6uPdrkzPKG2c4saoDqrjNhIAAAAAAKD6qR4bKALVUIfGLeRs76CeS16Rna2t7vdspeSMFM3Z9W8tPxavPcmn9GLcEvVZ+qp2XTiuxNQrmr39K7PHP3z1nAIaeSkzN1uXb6XpYvoN/XTptDo1yd/71txnlDZOcWMAAAAAAAAgHytXgQoU22us0c9NXNz0YvhQSVJU2weMrn19/EeN/F1baWb+dxxJ2vfEXEn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AAAAAMEZxFQAAAAAAAAAswLI5AAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwAMVVAAAAAAAAALAAxVUAAAAAAAAAsADFVQAAAAAAAACwwP8Df6tjj38k6EsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1791.55x806.68 with 1 Axes>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transpile(createCircuit(np.array((0.4,0.1)),G,1),backend=backendibm).draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuitsp1=[]\n",
    "n=8\n",
    "for gamma in np.linspace(0,np.pi/2,n):\n",
    "    for beta in np.linspace(0,np.pi/2,n):\n",
    "        circuitsp1.append(createCircuit(np.array((gamma,beta)),G,1))\n",
    "circuitsp2=[]\n",
    "n=8\n",
    "for gamma in np.linspace(0,np.pi/2,n):\n",
    "    for beta in np.linspace(0,np.pi/2,n):\n",
    "        for gamma2 in np.linspace(0,np.pi/2,n):\n",
    "            for beta2 in np.linspace(0,np.pi/2,n):\n",
    "                circuitsp2.append(createCircuit(np.array((gamma,beta,gamma2,beta2)),G,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_simp1 = execute(circuitsp1, backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.7784423828125"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "val=expectationValue(job_simp1.result(),G)\n",
    "pl.imshow(np.array(val).reshape(n,n))\n",
    "pl.colorbar()\n",
    "np.max(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_simp2 = execute(circuitsp2, backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.09130859375"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val=expectationValue(job_simp2.result(),G)\n",
    "np.max(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getval(x, backend, noisemodel=None):\n",
    "    j = execute(createCircuit(x,G,1), backend, shots=1024*2*2*2*2)\n",
    "    val=expectationValue(j.result(),G)\n",
    "    return -val[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: -3.903015\n",
      "         Iterations: 17\n",
      "         Function evaluations: 40\n"
     ]
    }
   ],
   "source": [
    "out=opt.minimize(getval, x0=(1, 1), method='Nelder-Mead',\\\n",
    "                 args=(backend_sim,None),\\\n",
    "             options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.67109375, 1.2171875 ])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "j = execute(createCircuit(out.x,G,1), backend_sim, shots=1024*2*2*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(j.result().get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3.9129638671875]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expectationValue(j.result(),G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4.0, 4.0)"
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     },
     "execution_count": 59,
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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