the_qubit_questers/MISQuantum.ipynb

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      "application/vnd.bokehjs_load.v0+json": ""
     },
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    }
   ],
   "source": [
    "from bloqade import rydberg_h, piecewise_linear, piecewise_constant, waveform, cast, save\n",
    "from bloqade.atom_arrangement import ListOfLocations, Lieb, Square, Chain, Honeycomb, Kagome, Triangular, Rectangular\n",
    "from bloqade.emulate.ir.state_vector import StateVector, RydbergHamiltonian\n",
    "from bokeh.io import output_notebook # to plot \"show()\" on the notebook, without opening a browser\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.optimize import minimize\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Rb = np.sqrt(3*np.sqrt(10))*4\n",
    "C6 = 862690*2*np.pi\n",
    "Ω_max = 2.5*2*np.pi\n",
    "Δ_end = C6 / (Rb**6)\n",
    "Δ_start = -10*2*np.pi\n",
    "Δ0 = Δ_end\n",
    "T_max = 0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "tags": []
   },
   "outputs": [
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  if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1785"
      }
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     "output_type": "display_data"
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   ],
   "source": [
    "#geometry\n",
    "rng = np.random.default_rng(18)\n",
    "atom_pos=Square(4, lattice_spacing=4).apply_defect_density(0.2, rng=rng).remove_vacant_sites()\n",
    "atom_pos.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "x = [-34.357805747236654, 1.4329770373209492, 7.5693393460213, 9.973535516555557, 19.50077146687081]\n",
    "\n",
    "#dynamics\n",
    "durations_delta = [0.05, 0.15, 0.1, 0.1, 0.1, 0.1, 0.15, 0.05]\n",
    "durations_delta = [5*i for i in durations_delta]\n",
    "deltas = [Δ_start, Δ_start, Δ0*x[0], Δ0*x[1], Δ0*x[2], Δ0*x[3], Δ0*x[4], Δ_end, Δ_end]\n",
    "durations_omega = [0.1, 0.1, 3.6, 0.1, 0.1]\n",
    "omegas = [0.0, 0.0, Ω_max, Ω_max, 0.0, 0.0]\n",
    "\n",
    "Delta = piecewise_linear(durations_delta,deltas)\n",
    "Omega = piecewise_linear(durations_omega,omegas)\n",
    "\n",
    "#create Hamiltonian\n",
    "program = rydberg_h(atom_pos, detuning=Delta, amplitude=Omega, phase=None)\n",
    "#output = program.bloqade.python().run(shots=100, interaction_picture=True)\n",
    "output_Q = program.braket.aquila().run_async(shots=100)\n",
    "#output.report().counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                             task ID     status  shots\n",
       "0  arn:aws:braket:us-east-1:592242689881:quantum-...  Completed    100"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#output.report().counts()\n",
    "output_Q.fetch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[OrderedDict([('1111111111110', 6),\n",
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       "              ('0111111111011', 4),\n",
       "              ('1110111111111', 4),\n",
       "              ('1111111111010', 4),\n",
       "              ('1111111111011', 4),\n",
       "              ('1110111111110', 3),\n",
       "              ('1111110111011', 3),\n",
       "              ('1111111011111', 3),\n",
       "              ('1111111110011', 3),\n",
       "              ('0111111110011', 2),\n",
       "              ('0111111111101', 2),\n",
       "              ('1011111011111', 2),\n",
       "              ('1011111111011', 2),\n",
       "              ('1011111111111', 2),\n",
       "              ('1110110111111', 2),\n",
       "              ('1110111110111', 2),\n",
       "              ('1111010111110', 2),\n",
       "              ('1111011111111', 2),\n",
       "              ('1111111111101', 2),\n",
       "              ('0010000011010', 1),\n",
       "              ('0110010010010', 1),\n",
       "              ('0111010111110', 1),\n",
       "              ('0111101111011', 1),\n",
       "              ('0111110011100', 1),\n",
       "              ('0111110101111', 1),\n",
       "              ('0111110111101', 1),\n",
       "              ('0111111101111', 1),\n",
       "              ('0111111111111', 1),\n",
       "              ('1011110110011', 1),\n",
       "              ('1011111011011', 1),\n",
       "              ('1011111110011', 1),\n",
       "              ('1011111111101', 1),\n",
       "              ('1011111111110', 1),\n",
       "              ('1100111111011', 1),\n",
       "              ('1101111110101', 1),\n",
       "              ('1110110111101', 1),\n",
       "              ('1110111111100', 1),\n",
       "              ('1111011110111', 1),\n",
       "              ('1111011111011', 1),\n",
       "              ('1111101111101', 1),\n",
       "              ('1111110111010', 1),\n",
       "              ('1111110111101', 1),\n",
       "              ('1111110111110', 1),\n",
       "              ('1111111011110', 1),\n",
       "              ('1111111110111', 1)])]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_Q.report().counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "save(output_Q, \"outputQ_5x5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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