{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "62b94cf7-c3fa-481c-90d9-14867704c495",
   "metadata": {},
   "source": [
    "# Implementation of Freerider Detection using Quantum Computer\n",
    "\n",
    "Through this notebook, I demonstarete quantum energy teleportation and implement the verification of energy consumption algorithm. \n",
    "\n",
    "Documentation: Ikeda, Kazuki, \"Quantum Games and Economics through Teleportation\" (March 06, 2025). Available at SSRN: https://ssrn.com/abstract_id=5168193\n",
    "\n",
    "Copy right: Prof. Ikeda at UMass Boston (kazuki.ikeda@umb.edu)\n",
    "Website: https://kazukiikeda.studio.site/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "155975f4-2cf9-49d9-b037-7fab4f2255d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from QET import *"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d292b35a-e541-48b7-b2c3-50a300891ddb",
   "metadata": {},
   "source": [
    "# Chose backend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "18d5d1bb-c7e2-42fd-aba1-56069d966f46",
   "metadata": {},
   "outputs": [],
   "source": [
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "pm = generate_preset_pass_manager(backend=simulator, optimization_level=3)\n",
    "estimator = Estimator(simulator)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf4a082e-7497-4ab7-8a22-7a9418c708dd",
   "metadata": {},
   "source": [
    "# Generate the ground state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "324300bb-3dfa-4c96-b76e-eb619b1d69ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set parameters\n",
    "k=1\n",
    "h=1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "54427236-f4a0-47e5-90f4-95ab451896fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAACuCAYAAAD52tuYAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAERpJREFUeJzt3QtUVWWiB/A/B+QpiEIKCfIQVCTULmhqvsdmFNS0SdOxUWZslCnC23ixqbHRupNmw1UxxtLyLnvMArzqXYnmq2yS8RVKTiikKYI8L4EvQOR1zl3fdh0UBAQ8sM/Z3/+3Fut49t7n7G8t/O9vf4/9YWUwGAwgIuno1C4AEamD4SeSFMNPJCmGn0hSDD+RpBh+Ikkx/ESSYviJJMXwE0mK4SeSFMNPJCmGn0hSDD+RpBh+Ikkx/ESSYviJJMXwE0mK4SeSFMNPJCmGn0hSDD+RpBh+Ikkx/ESSYviJJMXwE0mK4SeSFMNPJCmGn0hSDD+RpBh+Ikkx/ESSYviJJMXwE0mK4SeSFMNPJCmGn0hSDD+RpGzULgCZjsFgQF1VNSyJjYMdrKys1C6GlBh+DRHB/3v/52FJ5l/6DN0c7dUuhpR4208kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrj/ASPUcGYsuvNRttqK6twM7sIl3YcQdbWL2Co16tWPuocDD81yN6VivzD6YCVFRwecUXA7PEY8WYkegT2xfHYzWoXj0yM4acGZRmXkb0zteH9+W0HMCs1HgN+9TOkv5OI6rKbqpaPTIttfmp1uvBP6T/CSqeDi08ftYtDJsbwN5GTk4OtW7ciKioKoaGhsLW1VR48iYyMhIycfe+Evvp6hdpFIRPjbX8TGzZsQHx8PGRk42ALu17ODW3+gQt+DrcQf6X2F51/pC0MfxPu7u4IDw/H8OHDERYWhn379mHTpk2QwePL5yo/98rZewInX/sIsqqt1eNkRgnKblTDrps1Bvn1gG9fZ2gBw9/EihUrGr0/ceIEZHH+04PISTkOXTcb9BzUD4+9NBNOnm6or65pOGb8+68AOit8s2RdwzZb1+6Y+Y/1OPXWJ8qIgRaUlFXh/e1Z2LLzPApLbjVsF0sP/GK0F6LnBSF8rLdFr0Wg+TZ/aWkpli9fjoCAANjb28Pb2xtLly5FZWUlFi1apPzyEhIS1C6mWbiZXYyi1AwUHP4OZzd9jq8WvgP3Yf0xau2ShmOOv/Yheg8fCL+ZTzZsG7n6BZR8+4Nmgn/2x6sInfs5Vr3/XaPgCwYDsP9oPqZFH0LMOyeg1xtgqTRd8585cwZTp05FcXExnJycMHjwYBQWFmLjxo24dOkSrl69qhw3bNgwtYtqln46dV6Z5BMwZwIyt36hvK+5XoFjy97H2ISlKD6eid5hA+ExOhifT3wFWnClqAJPLdmP4tKqBx6bkJgJe1tr/HXZCFginZZr/OnTpyvBX7ZsGYqKipCenq68X7t2Lfbu3Yu0tDSl5h8yZIjaxTVb/1q/A/q6ejwe+1zDtoKvzyAn5RjGJcRg5Du/Uy4G1de0MRrwRsLpNgXfKO7jDGRlX4cl0mz4Y2JikJ+fj+joaMTFxcHZ+W4njWgGDB06FHV1dfD19YWLi4uqZTVn5TnFuPz5UTw6bgh6PxHUsP3Um5/A2c9DaSLkf5UOLSi9dhvJBy63+3MfbM+CJdJk+LOyspCcnKz03K9Zs6bZY8QYviAuAqZw+fJlzJgxQ7nI9OzZEwsWLEBZWRm04Pv4ndDXN679xQSgitwSXMu6Aq1IPpCN6pr6dn/u45SLyuKplkaTbf7ExETo9XrMnz8f3bt3b/YYBwcHk4W/vLwcEydORK9evZRzV1VVKXcX06ZNw9GjR6HTdewaK4YaRTOlrboZdFiJ9rc/i4+fwzbPZ1vcf+PHAnzidTf4pjQgcABqrczjoaEbDpMBh7Ht/1x5Dfp6B0CHrl852cPDA6dOnerQZzUZ/sOHDyuvIpAtEU0CU4V/y5YtKCgowJEjR9CvXz9lm5eXF0aPHo3du3dj5syZHfpeEXzxvW1la2UNWNgs3MKiQtQY2l/bdoo+5cCdOqHdiooKAL2FLZsODcrNzVVefXx8mt0v2vqiRjZV+Pfs2YMxY8Y0BF8YNWoU/P39kZKS0uHwi6t6e4iaH+ZRibbZo56Pmk3NX2Gnx40OfM5KXwVPT3eoMeLf3v8jmg+/GMMXxO13c0R/gBgNEO1zPz+/hz5fZmYmZs+efd/24OBgZV9Htfd2rvbW7S5dt3//L1c+9Hdc+PGC2azbX3b9NryeSsLt6vbdiSxdEIb1y+/cSVoSTXb4Ga+GYmivKTHkFxsbq/xbDPGZYobWtWvX4Orqet920QdgnEtA5s/N1R5zp/i3+3NRswfBEmky/JMnT1ZexXj+hQsXGraLcX3RDyBqfYGTe6ip/3wpFH17O6Kt/rhoCAb63X/htwSaDL/oaXdzc0NeXp5y6x0SEoLAwECMGDFCaYdPmjSpxfa+6AsQQ4TGn3Xr7sxhT0pKarTd2GcgiKG969fvn+ghan1R+5Pl8PJwwqEtU+HzaPOjRPd65dfBePvlMFgqTYZf9LSnpqYiIiJCmc8vntEXIdy8ebMys894N9Bc+Gtra5XxeeOPsd+gurq60XZxnFFQUFCzbXuxTewjyxLk74rTSU9jdUwY+nk63bd/xoR+OPDBL7AudiR0Ost9sMfKYImzEx5CRUWFMqNPtPXF+LyjY9tv8VoiZhC+/vrryM7OVi48wsmTJzFy5Ejs2rULs2bNQlfo6g4/Gf5QZ329HmlnSzEt+qDyWK+Hmz2Kvp4PLdBkzd+ac+fOKbOxRDPAFMEXFi9eDE9PTzz99NPKsN+OHTswb948pZkhtpHlsrbWYeTQ3rC3s254rxWaHOprTUZGhkmn9QriTkJMLBKPCs+dOxc2NjbK7L7169d3eHafGqztumH8B6+gR6AX6m/X4HbpDRz/44fK/P6mnv12E+qra5XjhO/f+1/k7D7W5v2kPobfRPr376/U+pbu/KeHlId1hEG/mYIn/+v3LY7nfxO1HlfP5bT4XQ/aT+qynGrJzMOvBaKmNgZfEGv3dfd+RNUyUeeRruY3zvunBxv8QjiuHEhrcf+YjS8ry1r99N1FnF799/vW9X/QflKXdOGXWXjK23Dx92x23+6nYnGr8O4jyCExz8DZ1wPH5jT+M15G+2b9GZUFpbCysca/vToPY+Oj8eXzq9u8n9TH8Evki+l/atNxwVEz4BP+BA7OeRP1VXcX77yXCLZgqKtH5od78MzR99q1n9QnXZufWjd4yTT4zXoSB597CzU3Gy9eaWTjYAdbl7vDpH6zxqDs7OU27yfzwJqfGjh69sKIVZG4mVOMKTtWKdvqa+qwN+I15d+j46KQd/AUrv1wBRM/ioWVtU5p05fnluCfL9+t2e0f6dHqfjIP0s3w0zLO8Os8XpMTUVByS3noJ//LedAC3vYTSYrhJ5IUw08kKYafSFLs7dcQMcQmOtAsrcykDoZfQ8QaBZbQc07mgbf9RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSfGPdhA1o6SsCqczS3E6qxSX8spx9Ua1sv16eQ0+2nkeoYPdEBzQE7bdrGGprAwGg0HtQhCZg5raeuz6MgebkrOQmv5/Dzy+h7MtImcE4vdzBmGgnyssDcNP0jMYDNh+4DL+/d0TKC6t6tB3PPMzX/ztT6Pg4e4IS8HwE2S/vX/x7WPY+WXOQ39XTxdbvPfaKMyPCIAlYPhJWhev3MTkxfuQW1hh0u999bdDsGZpmPKHU80Zw09SupxfjjGRe1BYcqtTvv8/Fobg3T8MN+sLAIf6msjJycHWrVsRFRWF0NBQ2NraKr/AyMhItYtGJlJ1uw4R0Qc7LfhC3McZ2LrrAswZh/qa2LBhA+Lj49UuBnWiP/8tHVnZ19v1mbTEGUpnXnHpLQyft7tNn/lD3En8fHRf9PPsDnPEmr8Jd3d3hIeHY+XKlUhJScGLL76odpHIhE5+X4J1n55t9+dE8L36OLWrN7+8shYvrEpVRhPMEWv+JlasWNHo/YkTJ1QrC5neX7acgV7fdWE8dLwQJ74vwaihfWBuNF/zl5aWYvny5QgICIC9vT28vb2xdOlSVFZWYtGiRUp7PiEhQe1iUhfIKSjH3tS8Lj/vpuQsmCNN1/xnzpzB1KlTUVxcDCcnJwwePBiFhYXYuHEjLl26hKtXryrHDRs2TO2iUhf4cOd5qHEHvv3AZcS/Ogq9etjBnOi0XONPnz5dCf6yZctQVFSE9PR05f3atWuxd+9epKWlKTX/kCFD1C4udYGv04pUOW9NrR7H//Xg6cJdTbPhj4mJQX5+PqKjoxEXFwdnZ+eGfaIZMHToUNTV1cHX1xcuLi6qlpU6X12dHmfOl6l2/tOZ6p1bqvBnZWUhOTlZ6blfs2ZNs8eIMXxBXAQelvEiM2LECNjZ2Zn1xA5ZXci9garb9aqd/3RmKcyNJtv8iYmJ0Ov1mD9/Prp3b36M1cHBwWThv3jxInbu3Inhw4crk4KOHj0KUwgLC1OaKfTwqm18AJfftjqG3xoPd4eG17xDc1s8rqV5APsP/RNeXr+BqXl4eODUqVMd+qwmw3/48GHldeLEia3W1qYK/7hx45Q+BWHVqlUmC78IfkFBgUm+S3pOLoBL62P4bWFjrWvzsU0fFza336Umw5+bm6u8+vj4NLtftPWNATVF+HW6zmk9ias6mUa1jStKW6mtH0TU+CL4dfX6Vh/7bem7bLvp8EjfvjCn/yOaDL8Ywxeqqpr/JYn+ADEaIDoB/fz8YK46ejtH98stLIfvlO3N7hvehum64lZf1Pgi+N5PJbX7/LNnTsJna96COdFkh5/xaiiG9poSt+exsbHKv8UQHzvn5CDm17u5qjfOHjrYHeZGk+GfPHmy8irG8y9cuPtklRjXF/0AotYXOLlHHuIir2YAQ4PcYG40GX4xju/m5oa8vDwEBwcjJCQEgYGBylCcv78/Jk2a1GJ7X/QFiCFC48+6deuU7UlJSY22m6pTj7rO9PH9VDmve097PDGkN8yNJsPv5eWF1NRUREREKPP5xTP6vXr1wubNm5WZfca7gebCX1tbi7KysoYfY79BdXV1o+3iOLIsv54WACeHru/mWjRrAOxszW+VX012+AlBQUHYs2fPfdsrKiqUi4HooX/sscfu2z9hwgSzfQSTHo5Ybff5aQHY/D8/dNk5RZfSkmcHwRxpNvwtOXfunBLuAQMGwNHRdCut7tixQ3nNzMxs9F5MHxaTdcg8vLF4GJL2Z+NGeU2XnC/mV8Hw87o7tdycSBf+jIwMk43v32v27NnNvl+4cCG2bdtm0nNRx/Xt44T45SMR+caRTj9XQD8XrI4x3ws/w28ibCpYjgUzArD7H1ew66u2L9dtnLzTlglBxkk9H/9lHBxV6GNoK/MtmYWFnyxr2O+zNeMR8VJ1mx/zbeu6fYKNjRWS3p2I0cPMb/Wee3HpbpJ6Fd/nYr9GyjdXTPadjvY2SP7rRExTaVixPRh+kppeb1B6/2PXfYvKqrqH+q5xoR7477fGor+3ZawPwfAT4c4f8Xh1Q5rSD1Bf375I+DzaHcsjQxA1Jwg6neVMF2f4ie5RWFKprPW341AOMrOvt7jSr/i7fGMe98DvfjkQ4WO9YG1tefPlGH6iFtyqqlOW/rqUdxNV1fXKI72uzrZ4fJAbfPt2t/iHwhh+IklZ3r0KEZkEw08kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSTH8RJJi+IkkxfATSYrhJ5IUw08kKYafSFIMP5GkGH4iSTH8RJJi+Ikgp/8Hb3bqNTcGKvsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 305.525x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GS_Simulation = pm.run(minimal_model_ground_state_circuit(k,h))\n",
    "GS_Simulation.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d5bf7013-3143-41af-b5db-a6a06e2f3e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XX','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(GS_Simulation.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6e141024-fdaf-4aeb-94cc-2664bb5f6455",
   "metadata": {},
   "outputs": [],
   "source": [
    "GS_energy_Simulation = estimator.run([(GS_Simulation,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "37015a00-3d66-4283-abe4-f18b92804274",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.55126953, -0.84130859, -0.84130859])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_Simulation=GS_energy_Simulation.result()\n",
    "gs_energy_Simulation=result_Simulation[0].data.evs\n",
    "\n",
    "gs_energy_Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b25b6754-4b64-42f4-bce8-88157389eafd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.1025390625"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2*k*gs_energy_Simulation[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5a062ae1-0bca-4ee6-a490-053ebdc01394",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2.364501953125"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Initial_Energy_Consumer=2*k*gs_energy_Simulation[0]+h*gs_energy_Simulation[1]\n",
    "Initial_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8e16754f-e140-4852-a878-505a89e4894a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.261962890625"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Initial_Energy_Supplier=h*gs_energy_Simulation[2]\n",
    "Initial_Energy_Supplier"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b8d2c71-a0eb-4678-b5aa-2f8c4c067e7c",
   "metadata": {},
   "source": [
    "# Quantum Energy Teleportation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0a57a9fb-88da-4740-99e3-26926540f977",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1058.23x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QET_Simulation = pm.run(QET_Estimator(k,h))\n",
    "QET_Simulation.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ccb1ef51-ea8a-41da-8f28-058dae64579f",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XZ','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(QET_Simulation.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "90a47f8f-fd5b-41d6-b176-049d4ee81691",
   "metadata": {},
   "outputs": [],
   "source": [
    "QET_energy_Simulation= estimator.run([(QET_Simulation,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9964aac2-55e4-4f66-84cf-11b08989aa57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.78808594, -0.60302734, -0.00244141])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=QET_energy_Simulation.result()\n",
    "QET_energy=result[0].data.evs\n",
    "\n",
    "QET_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "605c899b-a416-4bef-9f71-b55826dbf1dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2.480712890625"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Consumer=2*k*QET_energy[0]+h*QET_energy[1]\n",
    "Post_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "95ab119e-1f7e-481c-8e73-5d7b136ff5dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.1162109375"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Teleported_Energy=Post_Energy_Consumer-Initial_Energy_Consumer\n",
    "Teleported_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ba56a2eb-96b9-4bdc-be29-6b3aaa69d6c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.25830078125"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Supplier=h*QET_energy[2]\n",
    "Injected_Energy=Post_Energy_Supplier-Initial_Energy_Supplier\n",
    "Injected_Energy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adfdc387-5f42-48f4-bbe6-d20b3969879c",
   "metadata": {},
   "source": [
    "# Combine QET with QST to confirm energy consumption"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abe4052b-e8ce-4074-8936-8d438ae2c94a",
   "metadata": {},
   "source": [
    "## Confirm energy consumption "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b248e067-d943-4402-a743-a46fafe24bdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1225.45x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirm_QET_Simulation = pm.run(QET_QST_Estimator(k,h))\n",
    "Confirm_QET_Simulation.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "52e21a71-3913-427e-a0bc-449ac2bf6cf2",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XIIZ','ZIII']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(Confirm_QET_Simulation.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "51bf61ca-d7d8-40b1-9f78-b60e9be88829",
   "metadata": {},
   "outputs": [],
   "source": [
    "Confirmed_energy_Simulation = estimator.run([(Confirm_QET_Simulation,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "84b47897-3c82-48b5-853f-a25c04c83496",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.80517578, -0.59912109])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=Confirmed_energy_Simulation.result()\n",
    "Confirmed_energy=result[0].data.evs\n",
    "\n",
    "Confirmed_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4c0df5d3-9c03-490d-9cbe-66a3f6af9708",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.14453125"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirmed_Energy_Consumer=2*k*Confirmed_energy[0]+h*Confirmed_energy[1]\n",
    "Consumed_Energy=Confirmed_Energy_Consumer-Initial_Energy_Consumer\n",
    "Consumed_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8563859f-f29e-4ff7-aabb-97cb92718d74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2436974789915967"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio=Consumed_Energy/Teleported_Energy\n",
    "ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b25fe8f2-a390-4b5b-8745-e53cfda83e39",
   "metadata": {},
   "source": [
    "## Confirmation of No Energy Consumption"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "77f261cb-1e7c-47b6-8f54-e30e772dd3e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 574.791x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirm_NO_QET_Simulation = pm.run(Confirm_NO_QET_Estimator(k,h))\n",
    "Confirm_NO_QET_Estimator(k,h).draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "72d5d939-6601-4bce-946d-ec2bcd4e9c9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Confirmed_energy_Simulation = estimator.run([(Confirm_NO_QET_Simulation,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d6987fc8-42e8-4747-b5bd-557db5290560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.55175781, -0.83056641])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=Confirmed_energy_Simulation.result()\n",
    "Confirmed_energy=result[0].data.evs\n",
    "\n",
    "Confirmed_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "10616687-8580-4740-b879-c33aa36862da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.01513671875"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirmed_Energy_Consumer=2*k*Confirmed_energy[0]+h*Confirmed_energy[1]\n",
    "Consumed_Energy=Confirmed_Energy_Consumer-Initial_Energy_Consumer\n",
    "Consumed_Energy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "276f54ff-4383-4b06-87d8-fb8f4f18fc68",
   "metadata": {},
   "source": [
    "# Experiment by Quantum Computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "058aa557-f18f-4fb5-b83a-d0d80a3ef043",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Enable your account on Qiskit, replace 'My_API_Token' with your newly generated token\n",
    "from qiskit_ibm_experiment import IBMExperimentService\n",
    "My_API_Token='Your token'\n",
    "IBMExperimentService.save_account(token=My_API_Token,overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bddb6d2-0a50-4909-b8ba-de1e5cd0dc11",
   "metadata": {},
   "source": [
    "## Quantum Hardware"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "98ecf2ad-7591-499a-ae5d-56bf5c8619d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The history saving thread hit an unexpected error (OperationalError('attempt to write a readonly database')).History will not be written to the database.\n",
      "Available backends: [<IBMBackend('ibm_brisbane')>, <IBMBackend('ibm_brussels')>, <IBMBackend('ibm_fez')>, <IBMBackend('ibm_kyiv')>, <IBMBackend('ibm_marrakesh')>, <IBMBackend('ibm_sherbrooke')>, <IBMBackend('ibm_strasbourg')>, <IBMBackend('ibm_torino')>]\n",
      "Name: ibm_sherbrooke\n"
     ]
    }
   ],
   "source": [
    "# Initialize the Qiskit runtime service\n",
    "service = QiskitRuntimeService()\n",
    "available_backends=service.backends()\n",
    "backend = service.least_busy()\n",
    "session = Session(backend=backend)\n",
    "estimator = Estimator(mode=session)\n",
    "sampler = Sampler(mode=session)\n",
    "\n",
    "# Backend details\n",
    "print(\"Available backends:\",available_backends)\n",
    "print(\"Name:\", backend.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ca9858f2-af0b-4408-ba14-6388f2e11824",
   "metadata": {},
   "outputs": [],
   "source": [
    "service = QiskitRuntimeService()\n",
    "#backend = service.backend(\"ibm_marrakesh\")\n",
    "backend = service.backend('ibm_strasbourg')\n",
    "session = Session(backend=backend)\n",
    "estimator = Estimator(mode=session)\n",
    "sampler = Sampler(mode=session)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59d63afc-1af1-427c-bc0b-3010c2ab7fab",
   "metadata": {},
   "source": [
    "## Fake Hardware"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7884280d-ff71-4470-ab41-e470832317cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_ibm_runtime.fake_provider import FakeAlmadenV2\n",
    "#backend = FakeAlmadenV2()\n",
    "#backend = Aer.get_backend('qasm_simulator')\n",
    "backend = FakeSherbrooke()\n",
    "shots = int(1e4)\n",
    "estimator = Estimator(backend)\n",
    "estimator.options.resilience_level = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "252400af-e596-4fbc-bed5-a3ed30fa8690",
   "metadata": {},
   "source": [
    "## Pass Managers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "7b024d68-71ef-4422-ad89-d5dd432aaebf",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm1 = generate_preset_pass_manager(backend=backend, optimization_level=3, initial_layout=[119,120])\n",
    "pm2 = generate_preset_pass_manager(backend=backend, optimization_level=3, initial_layout=[119,120,121,122])\n",
    "                                                                            "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ec0325a-b764-4526-ac33-3c7709a90e0c",
   "metadata": {},
   "source": [
    "## Ground State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "89760236-b186-4eca-b9a6-504d7e5e54c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 896.739x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GS_QC = pm1.run(minimal_model_ground_state_circuit(k,h))\n",
    "GS_QC.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c9ef4df1-66af-4451-a603-0db7ab460376",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XZ','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(GS_QC.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f87277bc-ba26-4d54-9a9a-7ecec47e76a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/kazukiikeda/.pyenv/versions/3.12.1/lib/python3.12/site-packages/qiskit_ibm_runtime/fake_provider/local_service.py:186: UserWarning: The resilience_level option has no effect in local testing mode.\n",
      "  warnings.warn(\"The resilience_level option has no effect in local testing mode.\")\n"
     ]
    }
   ],
   "source": [
    "GS_energy_QC = estimator.run([(GS_QC,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "15c24083-121a-4c5c-bec4-10b5619f927d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.00732422, -0.75341797, -0.76269531])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=GS_energy_QC.result()\n",
    "gs_energy=result[0].data.evs\n",
    "\n",
    "gs_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "bcdc6ba1-2ea1-4cce-95b7-c15a5335c635",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.144775390625"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Initial_Energy_Consumer=2*k*gs_energy[0]+h*gs_energy[1]\n",
    "Initial_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "75aa1ea2-14d0-4936-b021-4ea9a0448571",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.14404296875"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Initial_Energy_Supplier=h*gs_energy[2]\n",
    "Initial_Energy_Supplier"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f9fbda7-5ece-44e9-bc89-5ea4487d8a89",
   "metadata": {},
   "source": [
    "## QET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a0899ca4-568d-465c-9fc1-a85139e2a66b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1314.79x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QET_QC = pm1.run(QET_Estimator(k,h))\n",
    "QET_QC.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0187e995-daee-44f5-8205-e7b63ff06806",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XZ','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(QET_QC.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c401446b-1722-4cbf-bb1b-9ecee67d66e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/kazukiikeda/.pyenv/versions/3.12.1/lib/python3.12/site-packages/qiskit_ibm_runtime/fake_provider/local_service.py:186: UserWarning: The resilience_level option has no effect in local testing mode.\n",
      "  warnings.warn(\"The resilience_level option has no effect in local testing mode.\")\n"
     ]
    }
   ],
   "source": [
    "QET_energy_QC = estimator.run([(QET_QC,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "12dcb140-74de-4084-b8c8-f6065a71800c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.68359375, -0.52490234,  0.00683594])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=QET_energy_QC.result()\n",
    "QET_energy=result[0].data.evs\n",
    "\n",
    "QET_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d5d5d550-544e-490b-a474-8f9cf979542d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2.154541015625"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Consumer=2*k*QET_energy[0]+h*QET_energy[1]\n",
    "Post_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5190523c-58c6-42b0-8517-390e596fcf40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.009765625"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Teleported_Energy=Post_Energy_Consumer-Initial_Energy_Consumer\n",
    "Teleported_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "973c9218-5b2a-4275-8dbd-b0d009fde093",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.154296875"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Supplier=h*QET_energy[2]\n",
    "Injected_Energy=Post_Energy_Supplier-Initial_Energy_Supplier\n",
    "Injected_Energy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e58ac76a-506b-47d1-a734-09ac00059a7c",
   "metadata": {},
   "source": [
    "## Confirm Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e7ef8ad7-14d1-4eba-8fa1-cdc6428d305a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2318.53x785.944 with 1 Axes>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirm_QET_QC = pm2.run(QET_QST_Estimator(k,h))\n",
    "Confirm_QET_QC.draw(\"mpl\", idle_wires=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "896a37ca-3452-407c-b855-8dac329589fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list=['XIIZ','ZIII']\n",
    "observables=[SparsePauliOp(label) for label in observables_list]\n",
    "mapped_observable = [observable.apply_layout(Confirm_QET_QC.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4232df4c-4491-4853-a3d1-0dfe12a9e59f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/kazukiikeda/.pyenv/versions/3.12.1/lib/python3.12/site-packages/qiskit_ibm_runtime/fake_provider/local_service.py:186: UserWarning: The resilience_level option has no effect in local testing mode.\n",
      "  warnings.warn(\"The resilience_level option has no effect in local testing mode.\")\n"
     ]
    }
   ],
   "source": [
    "Confirmed_energy_QC = estimator.run([(Confirm_QET_QC,mapped_observable)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9d0975b5-3c7a-4954-8d76-062a75c62019",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.64257812, -0.48876953])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=Confirmed_energy_QC.result()\n",
    "Confirmed_energy=result[0].data.evs\n",
    "\n",
    "Confirmed_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c3504ca1-0c34-4a87-9f92-7fe749a70ac7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.87353515625"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirmed_Energy_Consumer=2*k*Confirmed_energy[0]+h*Confirmed_energy[1]\n",
    "Consumed_Energy=Confirmed_Energy_Consumer-Initial_Energy_Consumer\n",
    "Consumed_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "b212d0af-2cbc-4681-b8a9-83a07b3d9e80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8650870406189555"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio=Consumed_Energy/Teleported_Energy\n",
    "ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c528641-a9fc-4b63-89aa-134aaf3d51a2",
   "metadata": {},
   "source": [
    "## Run QC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1163af99-348c-4064-be86-8b1465342a5c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61d4b459-9340-4bf8-9492-f960ddad953b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6effa4b4-ffc3-4f38-b87b-7a2346bfef89",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the Qiskit runtime service\n",
    "service = QiskitRuntimeService()\n",
    "available_backends=service.backends()\n",
    "backend = service.least_busy()\n",
    "session = Session(backend=backend)\n",
    "estimator = Estimator(mode=session)\n",
    "sampler = Sampler(mode=session)\n",
    "\n",
    "# Backend details\n",
    "print(\"Available backends:\",available_backends)\n",
    "print(\"Name:\", backend.name)\n",
    "\n",
    "estimator.options.resilience_level = 2\n",
    "estimator.options.default_shots = 100,000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f008461e-b764-45ca-abcc-b512e340da92",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_ibm_runtime.fake_provider import FakeAlmadenV2\n",
    "#backend = FakeAlmadenV2()\n",
    "#backend = Aer.get_backend('qasm_simulator')\n",
    "backend = FakeSherbrooke()\n",
    "shots = int(1e5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0dc4cce0-f3cf-4da2-b6de-9be727a45f19",
   "metadata": {},
   "outputs": [],
   "source": [
    "backend = FakeSherbrooke()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e46a636d-4c31-4f43-b1b4-c9d6b0d0a56a",
   "metadata": {},
   "outputs": [],
   "source": [
    "estimator.options.default_shots = 100000\n",
    "estimator = Estimator(backend)\n",
    "estimator.options.resilience_level = 2\n",
    "estimator.options.dynamical_decoupling.enable = True\n",
    "estimator.options.dynamical_decoupling.sequence_type = \"XpXm\"\n",
    "\n",
    "estimator.options.twirling.enable_gates = True\n",
    "estimator.options.twirling.num_randomizations = 32\n",
    "#estimator.options.twirling.shots_per_randomization = 100\n",
    "\n",
    "estimator.options.resilience.measure_mitigation = True\n",
    "estimator.options.resilience.measure_noise_learning.num_randomizations = 32\n",
    "estimator.options.resilience.measure_noise_learning.shots_per_randomization = 100\n",
    "\n",
    "estimator.options.resilience.zne_mitigation = True\n",
    "estimator.options.resilience.zne.noise_factors = (1, 2, 3)\n",
    "estimator.options.resilience.zne.extrapolator = \"linear\"\n",
    "\n",
    "estimator.options.resilience.zne_mitigation = True\n",
    "estimator.options.resilience.zne.amplifier = \"pea\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30b5a52f-f464-4220-98e1-366a7a83f97c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "fd8fa61f-070b-4090-9c88-f74897d2189f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pm1 = generate_preset_pass_manager(backend=backend, optimization_level=3, initial_layout=[119,120])\n",
    "pm2 = generate_preset_pass_manager(backend=backend, optimization_level=3, initial_layout=[119,120,121,122])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "2e5ecfc2-48a0-49b6-a3aa-47b9b5eccdb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "k=1\n",
    "h=1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "b474fc17-e32b-4985-a719-ba6dc95d51f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "GS_QC = pm1.run(minimal_model_ground_state_circuit(k,h))\n",
    "QET_QC = pm1.run(QET_Estimator(k,h))\n",
    "Confirm_QET_QC = pm2.run(QET_QST_Estimator(k,h))\n",
    "Confirm_NO_QET_QC = pm2.run(Confirm_NO_QET_Estimator(k,h))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "7a784f9a-c62f-42a1-a983-0dd9029e64bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "observables_list0=['XX','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list0]\n",
    "mapped_observable0 = [observable.apply_layout(GS_QC.layout) for observable in observables]\n",
    "\n",
    "observables_list1=['XZ','ZI','IZ']\n",
    "observables=[SparsePauliOp(label) for label in observables_list1]\n",
    "mapped_observable1 = [observable.apply_layout(QET_QC.layout) for observable in observables]\n",
    "\n",
    "observables_list2=['XIIZ','ZIII']\n",
    "observables=[SparsePauliOp(label) for label in observables_list2]\n",
    "mapped_observable2 = [observable.apply_layout(Confirm_QET_QC.layout) for observable in observables]\n",
    "\n",
    "observables_list2=['XIIZ','ZIII']\n",
    "observables=[SparsePauliOp(label) for label in observables_list2]\n",
    "mapped_observable3 = [observable.apply_layout(Confirm_NO_QET_QC.layout) for observable in observables]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "1f47a15d-f8f1-4303-8c13-37a97d639a33",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Job ID: cyfjwk29b62g0081ws2g\n"
     ]
    }
   ],
   "source": [
    "# (GS_QC,mapped_observable0) Ground \n",
    "# (QET_QC,mapped_observable1) QET\n",
    "# (Confirm_QET_QC,mapped_observable2) Confirm QET\n",
    "# (Confirm_NO_QET_QC,mapped_observable3) Confirm no QET\n",
    "\n",
    "TEST_QC = estimator.run([(GS_QC,mapped_observable0),(QET_QC,mapped_observable1),(Confirm_QET_QC,mapped_observable2),(Confirm_NO_QET_QC,mapped_observable3)])\n",
    "print(f\">>> Job ID: {TEST_QC.job_id()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "963035fc-5b9b-43e7-9324-76014e847945",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e46f1529-9341-4105-a3e3-27caee3dd77f",
   "metadata": {},
   "outputs": [],
   "source": [
    "result=TEST_QC.result()\n",
    "#result[0].data.evs, result[0].data.stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "08fac9bc-f7b4-4831-8e56-673c5566bc24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3.8481137457137806"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ground State Energy\n",
    "Initial_Energy_Consumer=2*k*result[0].data.evs[0]+h*result[0].data.evs[1]\n",
    "Initial_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "220d00bb-9220-46e7-b218-487eef35a5cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2.0156996791944635"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Initial_Energy_Supplier=h*result[0].data.evs[2]\n",
    "Initial_Energy_Supplier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "b74f30ff-2e68-4ae2-8658-299a29d3980c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-1.30329403, -0.92686662,  0.02737266]),\n",
       " array([0.15791377, 0.33555245, 0.02711239]))"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Post Energy\n",
    "result[1].data.evs, result[1].data.stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "86fcd519-7002-41fa-92e6-8dee50266ef2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3.996887994979174"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Consumer=2*k*result[1].data.evs[0]+h*result[1].data.evs[1]\n",
    "Post_Energy_Consumer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "caaa00a0-1492-41a3-93e7-2a032d395f53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.14877424926539318"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Teleported_Energy=Post_Energy_Consumer-Initial_Energy_Consumer\n",
    "Teleported_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "1756dd82-85b3-4192-a216-1efe05a37ac8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0772881748585803"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Post_Energy_Supplier=h*h*result[1].data.evs[2]\n",
    "Injected_Energy=Post_Energy_Supplier-Initial_Energy_Supplier\n",
    "Injected_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "6eb20460-60dd-4bbe-9e95-3155b32b105a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-0.9570403 , -0.70798499]), array([0.37250321, 0.35073205]))"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result[2].data.evs, result[2].data.stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "bfd00225-d737-4825-995a-de71a0e4c4ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8720556578159226, -5.86160348394898)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Confirmed_Energy_Consumer=2*k*result[2].data.evs[0]+h*result[2].data.evs[1]\n",
    "Consumed_Energy=Confirmed_Energy_Consumer-Initial_Energy_Consumer\n",
    "Consumed_Energy, Consumed_Energy/Teleported_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ed260de-1ef0-445c-934f-a4ee0a1bb3a4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1f574f69-45a3-453f-8278-2dd94370652a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-0.6361117, -1.1242221]), array([0.24826187, 0.43729686]))"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result[3].data.evs, result[3].data.stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "156ce4a4-e4aa-4f9c-9af6-25fae8a19cb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8895572058201755"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NO_Energy_Consumer=2*k*result[3].data.evs[0]+h*result[3].data.evs[1]\n",
    "NO_Consumed_Energy=NO_Energy_Consumer-Initial_Energy_Consumer\n",
    "NO_Consumed_Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e27777b-4c44-4374-a0bb-4503d2331140",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d800937e-b184-411d-9100-08431325a54e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a6fa4322-ff52-4518-8a1f-3699e91a74a8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a898a4c-c05d-462d-bbcc-4c6c2bad000b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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