{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating a Bell state with pulses on Rigetti's Aspen M-3\n",
    "\n",
    "Let's create a Bell state program, the `Hello world!` example in quantum computing, with pulses on a Rigetti's device. \n",
    "\n",
    "The canonical circuit to generate a Bell pair is constitued of an Hadamard gate on a first qubit followed by a CNOT gate between this qubit and a second qubit. In this notebook, we will realize that creating entangled states requires specific mechanisms that are tightly connected to the hardware type and device architecture. Specifically here, we will focus on the native gate set of the Rigetti's device and choose to use specific waveforms and frames that enable native CZ gates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use Braket SDK Cost Tracking to estimate the cost to run this example\n",
    "from braket.tracking import Tracker\n",
    "t = Tracker().start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first import few packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from braket.aws import AwsDevice\n",
    "from braket.pulse import PulseSequence, ArbitraryWaveform\n",
    "\n",
    "from braket.circuits import Circuit\n",
    "import braket.circuits.circuit as circuit\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use two qubits, #10 amd #113, that are physically connected to each other. We also instantiate a Rigetti device to extract frames and submit circuits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=10\n",
    "b=113\n",
    "\n",
    "device = AwsDevice(\"arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bell pair with the H and Ctrl-Z gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we show how to transform our common Bell state circuit into one that contains a CZ gate instead of a CNOT gate.\n",
    "\n",
    "As, CNOT and CZ only differ by a basis transform, we will add Hadamard gates before and after the CZ gate. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T    : |0|1|2|\n",
      "              \n",
      "q10  : -H-C---\n",
      "          |   \n",
      "q113 : -H-Z-H-\n",
      "\n",
      "T    : |0|1|2|\n"
     ]
    }
   ],
   "source": [
    "bell_pair_with_gates = Circuit().h(a).h(b).cz(a, b).h(b)\n",
    "print(bell_pair_with_gates)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The circuit is then executed on the Aspen-M-3 device and we plot the measurement histogram which hints that we created $$\\frac{|00\\rangle+|11\\rangle}{\\sqrt{2}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use `disable_qubit_rewiring = True` to be sure that the Bell pair will be created on the specified qubit and not on remapped qubits so we have a fair comparison with the rest of the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Population')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_shots = 100\n",
    "task = device.run(bell_pair_with_gates, shots = nb_shots, disable_qubit_rewiring=True)\n",
    "counts = task.result().measurement_counts\n",
    "plt.bar(sorted(counts), [counts[k]/nb_shots for k in sorted(counts)])\n",
    "plt.xlabel(\"State\")\n",
    "plt.ylabel(\"Population\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bell pair with the pulse implementation of CZ"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since Hadamard gates are not native gates on Aspen, we cannot add them to circuits containing pulse sequences. We need to first decompose them into a sequence of native gates. We will use the RX and RZ gates here.\n",
    "\n",
    "We will annotate this decomposition with `circuit.subroutine` to register this as a custom gate in the circuit allowing easy reuse."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T   : |   0    |   1    |   2    |    3    |\n",
      "                                            \n",
      "q10 : -Rz(3.14)-Rx(1.57)-Rz(1.57)-Rx(-1.57)-\n",
      "\n",
      "T   : |   0    |   1    |   2    |    3    |\n"
     ]
    }
   ],
   "source": [
    "@circuit.subroutine(register=True)\n",
    "def rigetti_native_h(q0):\n",
    "    return (\n",
    "        Circuit()\n",
    "        .rz(q0, np.pi)\n",
    "        .rx(q0, np.pi/2)\n",
    "        .rz(q0, np.pi/2)\n",
    "        .rx(q0, -np.pi/2)\n",
    "    )\n",
    "    \n",
    "print(Circuit().rigetti_native_h(a))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the CZ gate, we will use an arbitrary waveform with parameters (amplitude, rise/fall time, duration) that have been predetermined beforehand. This waveform will be applied on the `q10_q113_cz_frame frame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_b_cz_wfm = ArbitraryWaveform([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.00017888439538396808, 0.00046751103636033026, 0.0011372942989106456, 0.002577059611929697, 0.005443941944632366, 0.010731922770068104, 0.01976701723583167, 0.03406712171899736, 0.05503285980691202, 0.08350670755829034, 0.11932853352131022, 0.16107456696238298, 0.20614055551722368, 0.2512065440720643, 0.292952577513137, 0.328774403476157, 0.3572482512275353, 0.3782139893154499, 0.3925140937986156, 0.40154918826437913, 0.4068371690898149, 0.4097040514225177, 0.41114381673553674, 0.411813599998087, 0.4121022266390633, 0.4122174383870584, 0.41226003881132406, 0.4122746298554775, 0.4122792591252675, 0.4122806196003006, 0.41228098995582513, 0.41228108334474756, 0.4122811051578895, 0.4122811098772742, 0.4122811108230642, 0.4122811109986316, 0.41228111102881937, 0.41228111103362725, 0.4122811110343365, 0.41228111103443343, 0.4122811110344457, 0.4122811110344471, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.41228111103444737, 0.4122811110344471, 0.4122811110344457, 0.41228111103443343, 0.4122811110343365, 0.41228111103362725, 0.41228111102881937, 0.4122811109986316, 0.4122811108230642, 0.4122811098772742, 0.4122811051578895, 0.41228108334474756, 0.41228098995582513, 0.4122806196003006, 0.4122792591252675, 0.4122746298554775, 0.41226003881132406, 0.4122174383870584, 0.4121022266390633, 0.411813599998087, 0.41114381673553674, 0.4097040514225176, 0.4068371690898149, 0.40154918826437913, 0.3925140937986155, 0.37821398931544986, 0.3572482512275351, 0.32877440347615655, 0.2929525775131368, 0.2512065440720641, 0.20614055551722307, 0.16107456696238268, 0.11932853352131002, 0.08350670755829034, 0.05503285980691184, 0.03406712171899729, 0.01976701723583167, 0.010731922770068058, 0.005443941944632366, 0.002577059611929697, 0.0011372942989106229, 0.00046751103636033026, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To draw this waveform as it will be played on the device, we need to know the frame and the corresponding time separation between each sample. This information is stored in the device capabilities. \n",
    "\n",
    "First we retrieve the frame that we will use to create a CZ gate between qubit 10 and 113. The minimum time increment can then be extracted through the corresponding port.\n",
    "\n",
    "The pulse length will be the product of the number of samples and the minimum time increment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CZ pulse duration: 124.0 ns\n"
     ]
    }
   ],
   "source": [
    "a_b_cz_frame = device.frames[f'q{a}_q{b}_cz_frame']\n",
    "dt=a_b_cz_frame.port.dt\n",
    "\n",
    "a_b_cz_wfm_duration = len(a_b_cz_wfm.amplitudes)*dt\n",
    "print('CZ pulse duration:', round(a_b_cz_wfm_duration * 1e9,0), 'ns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With all these data, we call also plot the waveform and see that it is rounded square pulse. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.arange(0, len(a_b_cz_wfm.amplitudes))*dt*1e9, a_b_cz_wfm.amplitudes)\n",
    "plt.xlabel('Time (ns)')\n",
    "plt.ylabel('Amplitude (a. u.)')\n",
    "plt.title(f'Pulse on CZ frame between qubit {a} and {b}');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Playing the CZ waveform on a frame that is related to a fast-flux port enable a CZ interaction that causes the systems to oscillate between $|11\\rangle$ and $|20\\rangle$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_rf_frame = device.frames[f'q{a}_rf_frame']\n",
    "b_rf_frame = device.frames[f'q{b}_rf_frame']\n",
    "frames = [a_rf_frame, b_rf_frame, a_b_cz_frame]\n",
    "\n",
    "cz_pulse_sequence = (\n",
    "    PulseSequence()\n",
    "    .barrier(frames)\n",
    "    .play(a_b_cz_frame, a_b_cz_wfm)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One side-effect of this pulse that that the mean qubit frequencies will be shifted during the process.\n",
    "The qubit frames rotate at the different rates and a relative phase is acquired with respect to the all frames connected to these qubits. \n",
    "\n",
    "These phase shifts was measured via Ramsey sequences beforehand (and given here as hardcoded information via `phase_shift_a` and `phase_shift_b`). We apply corrections by using shift_phase instructions on RF and XY frames after the CZ pulse. (see Caldwell et all, https://arxiv.org/abs/1706.06562 for more information). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "phase_shift_a=1.1733407221086924\n",
    "phase_shift_b=6.269846678712192\n",
    "\n",
    "cz_pulse_sequence = (\n",
    "    cz_pulse_sequence\n",
    "    .delay(a_rf_frame, a_b_cz_wfm_duration)\n",
    "    .shift_phase(a_rf_frame, phase_shift_a)\n",
    "    .delay(b_rf_frame, a_b_cz_wfm_duration)\n",
    "    .shift_phase(b_rf_frame, phase_shift_b)\n",
    "    .barrier(frames)\n",
    ")\n",
    "for phase, q in [(phase_shift_a/2, a), (-phase_shift_b/2, b)]:\n",
    "    for neighbor in device.properties.paradigm.connectivity.connectivityGraph[str(q)]:\n",
    "        xy_frame_name = f\"q{min(q, int(neighbor))}_q{max(q, int(neighbor))}_xy_frame\"\n",
    "        if xy_frame_name in device.frames:\n",
    "            xy_frame = device.frames[xy_frame_name]\n",
    "            cz_pulse_sequence.shift_phase(xy_frame, phase)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pulse sequences can be exported as time series via the function `to_time_trace` for visualization. This method returns an object that contains all the numerical values of our pulse sequences, and can be used to plot the traces for each frames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = cz_pulse_sequence.to_time_trace()\n",
    "for frame_id in data.amplitudes:\n",
    "    f=plt.figure(figsize=(12,4))\n",
    "    plt.subplot(1,3,1)\n",
    "    plt.plot(data.amplitudes[frame_id].times(), np.real(data.amplitudes[frame_id].values()), label=\"Real\")\n",
    "    plt.plot(data.amplitudes[frame_id].times(), np.imag(data.amplitudes[frame_id].values()), label=\"Imag\")\n",
    "    plt.xlabel(\"Time (s)\")\n",
    "    plt.ylabel(\"Amplitude (norm.)\")\n",
    "    plt.legend(loc=\"upper right\")\n",
    "\n",
    "    plt.subplot(1,3,2)\n",
    "    plt.title(frame_id)\n",
    "    plt.plot(data.frequencies[frame_id].times(), data.frequencies[frame_id].values())\n",
    "    plt.xlabel(\"Time (s)\")\n",
    "    plt.ylabel(\"Frequency (Hz)\")\n",
    "\n",
    "    plt.subplot(1,3,3)\n",
    "    plt.plot(data.phases[frame_id].times(), data.phases[frame_id].values())\n",
    "    plt.xlabel(\"Time (s)\")\n",
    "    plt.ylabel(\"Phase (rad)\")\n",
    "    f.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can build our own implementation of the Bell circuit using a `pulse_gate` instruction that encapsulates the pulse sequence into a gate instructions. \n",
    "\n",
    "Pulse gates are strictly defined by the pulse sequence and the associated frames. The qubit or a list of qubits provided to `pulse_gate` are for representational purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T    : |   0    |   1    |   2    |    3    |4 |   5    |   6    |   7    |    8    |\n",
      "                                                                                     \n",
      "q10  : -Rz(3.14)-Rx(1.57)-Rz(1.57)-Rx(-1.57)-PG--------------------------------------\n",
      "                                             |                                       \n",
      "q113 : -Rz(3.14)-Rx(1.57)-Rz(1.57)-Rx(-1.57)-PG-Rz(3.14)-Rx(1.57)-Rz(1.57)-Rx(-1.57)-\n",
      "\n",
      "T    : |   0    |   1    |   2    |    3    |4 |   5    |   6    |   7    |    8    |\n"
     ]
    }
   ],
   "source": [
    "bell_pair_with_pulse = (\n",
    "    Circuit()\n",
    "    .rigetti_native_h(a)\n",
    "    .rigetti_native_h(b)\n",
    "    .pulse_gate([a, b], cz_pulse_sequence)\n",
    "    .rigetti_native_h(b)\n",
    ")\n",
    "print(bell_pair_with_pulse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Circuits with embedded pulse sequences can be executed normally.\n",
    "\n",
    "As pulse sequences are inherently hardware dependent since the timings and strength of the waveforms are tuned to be optimal for the frame they are played on, you can only use pulse gates with the flag `disable_qubit_rewiring=True` that prevents any compiler to remap qubits. Amazon Braket SDK toggles automatically the flag when it detects that pulse sequences are embedded in a circuit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Population')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAiJElEQVR4nO3df1RUdf7H8deAMiMi+IMNwlAUXH9kQsLCYl/TWgyPpqvZOdZuiZiWW6TunPaU7Qppu2dMjeiHm/1YtZ+rx5NZe3LdU5PaWqirSD82dasjQSqImSJoYMx8/+g0LQsqDAMXPzwf58w5cu+dO+/pnuzZvXcGm9fr9QoAAMAQQVYPAAAAEEjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACM0sXqAdqbx+PRkSNH1KNHD9lsNqvHAQAAzeD1enX69GnFxMQoKOjC52Y6XdwcOXJEsbGxVo8BAAD8UFZWpiuuuOKC23S6uOnRo4ek7//hhIeHWzwNAABojqqqKsXGxvr+O34hnS5ufrgUFR4eTtwAAHCJac4tJdxQDAAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKF2sHgAAgLYQ98BbVo/QaZUsnWjp63PmBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFG6WD2AaeIeeMvqETqtkqUTrR4BANABcOYGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGCUDhE3K1euVFxcnBwOh9LS0rR79+5mPW/dunWy2WyaMmVK2w4IAAAuGZbHzfr16+V0OpWXl6eioiIlJiYqMzNTx44du+DzSkpKdN9992n06NHtNCkAALgUWB43+fn5mjNnjrKzszVs2DCtWrVKoaGhWr169XmfU19fr1//+tdavHixBg4ceMH919bWqqqqqsEDAACYy9K4qaur0969e5WRkeFbFhQUpIyMDBUWFp73eUuWLNFll12mO+6446Kv4XK5FBER4XvExsYGZHYAANAxWRo3x48fV319vaKiohosj4qKUnl5eZPP2bFjh/7yl7/oueeea9ZrLFy4UKdOnfI9ysrKWj03AADouLpYPUBLnD59Wrfffruee+45RUZGNus5drtddru9jScDAAAdhaVxExkZqeDgYFVUVDRYXlFRoejo6Ebbf/HFFyopKdGkSZN8yzwejySpS5cuOnjwoOLj49t2aAAA0KFZelkqJCREycnJcrvdvmUej0dut1vp6emNth8yZIg+/vhjFRcX+x6TJ0/Wddddp+LiYu6nAQAA1l+WcjqdysrKUkpKilJTU1VQUKCamhplZ2dLkmbMmKG+ffvK5XLJ4XBo+PDhDZ7fs2dPSWq0HAAAdE6Wx8306dNVWVmp3NxclZeXKykpSVu2bPHdZFxaWqqgIMs/sQ4AAC4RlseNJOXk5CgnJ6fJddu2bbvgc9euXRv4gQAAwCWLUyIAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACjEDcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMEqHiJuVK1cqLi5ODodDaWlp2r1793m33bhxo1JSUtSzZ091795dSUlJeumll9pxWgAA0JFZHjfr16+X0+lUXl6eioqKlJiYqMzMTB07dqzJ7Xv37q3f//73Kiws1EcffaTs7GxlZ2frH//4RztPDgAAOiLL4yY/P19z5sxRdna2hg0bplWrVik0NFSrV69ucvuxY8dq6tSpGjp0qOLj4zV//nyNGDFCO3bsaHL72tpaVVVVNXgAAABzWRo3dXV12rt3rzIyMnzLgoKClJGRocLCwos+3+v1yu126+DBg7r22mub3MblcikiIsL3iI2NDdj8AACg47E0bo4fP676+npFRUU1WB4VFaXy8vLzPu/UqVMKCwtTSEiIJk6cqCeffFLjxo1rctuFCxfq1KlTvkdZWVlA3wMAAOhYulg9gD969Oih4uJiVVdXy+12y+l0auDAgRo7dmyjbe12u+x2e/sPCQAALGFp3ERGRio4OFgVFRUNlldUVCg6Ovq8zwsKClJCQoIkKSkpSfv375fL5WoybgAAQOdi6WWpkJAQJScny+12+5Z5PB653W6lp6c3ez8ej0e1tbVtMSIAALjEWH5Zyul0KisrSykpKUpNTVVBQYFqamqUnZ0tSZoxY4b69u0rl8sl6fsbhFNSUhQfH6/a2lpt3rxZL730kp5++mkr3wYAAOggLI+b6dOnq7KyUrm5uSovL1dSUpK2bNniu8m4tLRUQUE/nmCqqanR3Xffra+++krdunXTkCFD9PLLL2v69OlWvQUAANCB2Lxer9fqIdpTVVWVIiIidOrUKYWHhwd8/3EPvBXwfaJ5SpZOtHoEAB0Ifx9bpy3+Pm7Jf78t/xI/AACAQCJuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBR/IqbiooK3X777YqJiVGXLl0UHBzc4AEAAGAVv77Eb+bMmSotLdWiRYt0+eWXy2azBXouAAAAv/gVNzt27NA///lPJSUlBXgcAACA1vHrslRsbKw62RcbAwCAS4RfcVNQUKAHHnhAJSUlAR4HAACgdfy6LDV9+nSdOXNG8fHxCg0NVdeuXRusP3HiRECGAwAAaCm/4qagoCDAYwAAAASGX3GTlZUV6DkAAAACwq+4kaT6+npt2rRJ+/fvlyRdeeWVmjx5Mt9zAwAALOVX3Hz++eeaMGGCDh8+rMGDB0uSXC6XYmNj9dZbbyk+Pj6gQwIAADSXX5+WmjdvnuLj41VWVqaioiIVFRWptLRUAwYM0Lx58wI9IwAAQLP5deZm+/bt2rlzp3r37u1b1qdPHy1dulTXXHNNwIYDAABoKb/O3Njtdp0+fbrR8urqaoWEhLR6KAAAAH/5FTc33nij7rzzTu3atUter1der1c7d+7U3LlzNXny5EDPCAAA0Gx+xc0TTzyh+Ph4paeny+FwyOFw6JprrlFCQoIef/zxQM8IAADQbH7dc9OzZ0+98cYb+uyzz3TgwAFJ0tChQ5WQkBDQ4QAAAFrK7++5kaRBgwZp0KBBgZoFAACg1ZodN06nUw8//LC6d+8up9N5wW3z8/NbPRgAAIA/mh03+/bt07lz53x/BgAA6IiaHTdbt25t8s8AAAAdiV+flpo1a1aT33NTU1OjWbNmtXooAAAAf/kVNy+88ILOnj3baPnZs2f14osvtnooAAAAf7Xo01JVVVW+L+07ffq0HA6Hb119fb02b96syy67LOBDAgAANFeL4qZnz56y2Wyy2Wz66U9/2mi9zWbT4sWLAzYcAABAS7UobrZu3Sqv16vrr79er732WoNfnBkSEqL+/fsrJiYm4EMCAAA0V4viZsyYMZKkQ4cOKTY2VkFBft2yAwAA0Gb8+obi/v37S5LOnDmj0tJS1dXVNVg/YsSI1k8GAADgB7/iprKyUtnZ2fr73//e5Pr6+vpWDQUAAOAvv64rLViwQCdPntSuXbvUrVs3bdmyRS+88IIGDRqkN998M9AzAgAANJtfZ27effddvfHGG0pJSVFQUJD69++vcePGKTw8XC6XSxMnTgz0nAAAAM3i15mbmpoa3/fZ9OrVS5WVlZKkq666SkVFRYGbDgAAoIX8ipvBgwfr4MGDkqTExEQ988wzOnz4sFatWqXLL788oAMCAAC0hF+XpebPn6+jR49KkvLy8jR+/Hi98sorCgkJ0dq1awM5HwAAQIv4FTe33Xab78/Jycn68ssvdeDAAfXr10+RkZEBGw4AAKCl/Iqb/xUaGqqRI0cGYlcAAACt0uy4cTqdzd5pfn6+X8MAAAC0VrPjZt++fc3azmaz+T0MAABAazU7brZu3dqWcwAAAAQEv/kSAAAYxa8biq+77roLXn569913/R4IAACgNfyKm6SkpAY/nzt3TsXFxfrkk0+UlZUViLkAAAD84lfcPPbYY00uf+ihh1RdXd2qgQAAAFojoPfc3HbbbVq9enUgdwkAANAiAY2bwsJCORyOQO4SAACgRfy6LHXTTTc1+Nnr9ero0aPas2ePFi1aFJDBAAAA/OFX3ERERDT4OSgoSIMHD9aSJUt0ww03BGQwAAAAf/gVN2vWrAn0HAAAAAHRql+cuWfPHu3fv1+SNGzYMCUnJwdkKAAAAH/5FTdfffWVbr31Vr3//vvq2bOnJOnkyZMaNWqU1q1bpyuuuCKQMwIAADSbX5+Wmj17ts6dO6f9+/frxIkTOnHihPbv3y+Px6PZs2cHekYAAIBm8+vMzfbt2/XBBx9o8ODBvmWDBw/Wk08+qdGjRwdsOAAAgJby68xNbGyszp0712h5fX29YmJiWj0UAACAv/yKm+XLl+vee+/Vnj17fMv27Nmj+fPna8WKFQEbDgAAoKX8uiw1c+ZMnTlzRmlpaerS5ftdfPfdd+rSpYtmzZqlWbNm+bY9ceJEYCYFAABoBr/ipqCgIMBjAAAABIZfcZOVlRXoOQAAAALC7y/xq6+v16ZNm3xf4nfllVdq8uTJCg4ODthwAAAALeVX3Hz++eeaMGGCDh8+7Ps4uMvlUmxsrN566y3Fx8cHdEgAAIDm8uvTUvPmzVN8fLzKyspUVFSkoqIilZaWasCAAZo3b16gZwQAAGg2v+Jm+/btWrZsmXr37u1b1qdPHy1dulTbt29v8f5WrlypuLg4ORwOpaWlaffu3efd9rnnntPo0aPVq1cv9erVSxkZGRfcHgAAdC5+xY3dbtfp06cbLa+urlZISEiL9rV+/Xo5nU7l5eWpqKhIiYmJyszM1LFjx5rcftu2bbr11lu1detWFRYWKjY2VjfccIMOHz7sz1sBAACG8StubrzxRt15553atWuXvF6vvF6vdu7cqblz52ry5Mkt2ld+fr7mzJmj7OxsDRs2TKtWrVJoaKhWr17d5PavvPKK7r77biUlJWnIkCF6/vnn5fF45Ha7/XkrAADAMH7FzRNPPKGEhASNGjVKDodDDodD11xzjRISEvT44483ez91dXXau3evMjIyfhwoKEgZGRkqLCxs1j7OnDmjc+fONbhE9t9qa2tVVVXV4AEAAMzVok9LeTweLV++XG+++abq6uo0ZcoUZWVlyWazaejQoUpISGjRix8/flz19fWKiopqsDwqKkoHDhxo1j7uv/9+xcTENAik/+ZyubR48eIWzQUAAC5dLTpz86c//UkPPvigwsLC1LdvX23evFmbNm3SpEmTWhw2gbB06VKtW7dOr7/+uhwOR5PbLFy4UKdOnfI9ysrK2nlKAADQnlp05ubFF1/Un//8Z911112SpHfeeUcTJ07U888/r6Cgll/hioyMVHBwsCoqKhosr6ioUHR09AWfu2LFCi1dulTvvPOORowYcd7t7Ha77HZ7i2cDAACXphYVSWlpqSZMmOD7OSMjQzabTUeOHPHrxUNCQpScnNzgZuAfbg5OT08/7/OWLVumhx9+WFu2bFFKSopfrw0AAMzUojM33333XaPLP127dtW5c+f8HsDpdCorK0spKSlKTU1VQUGBampqlJ2dLUmaMWOG+vbtK5fLJUl65JFHlJubq1dffVVxcXEqLy+XJIWFhSksLMzvOQAAgBlaFDder1czZ85scJnn22+/1dy5c9W9e3ffso0bNzZ7n9OnT1dlZaVyc3NVXl6upKQkbdmyxXeTcWlpaYNLXk8//bTq6up08803N9hPXl6eHnrooZa8HQAAYKAWxU1Tvw38tttua/UQOTk5ysnJaXLdtm3bGvxcUlLS6tcDAADmalHcrFmzpq3mAAAACAi/vsQPAACgoyJuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGsTxuVq5cqbi4ODkcDqWlpWn37t3n3fbf//63pk2bpri4ONlsNhUUFLTfoAAA4JJgadysX79eTqdTeXl5KioqUmJiojIzM3Xs2LEmtz9z5owGDhyopUuXKjo6up2nBQAAlwJL4yY/P19z5sxRdna2hg0bplWrVik0NFSrV69ucvuf/exnWr58uW655RbZ7fZ2nhYAAFwKLIuburo67d27VxkZGT8OExSkjIwMFRYWBux1amtrVVVV1eABAADMZVncHD9+XPX19YqKimqwPCoqSuXl5QF7HZfLpYiICN8jNjY2YPsGAAAdj+U3FLe1hQsX6tSpU75HWVmZ1SMBAIA21MWqF46MjFRwcLAqKioaLK+oqAjozcJ2u537cwAA6EQsO3MTEhKi5ORkud1u3zKPxyO326309HSrxgIAAJc4y87cSJLT6VRWVpZSUlKUmpqqgoIC1dTUKDs7W5I0Y8YM9e3bVy6XS9L3NyF/+umnvj8fPnxYxcXFCgsLU0JCgmXvAwAAdByWxs306dNVWVmp3NxclZeXKykpSVu2bPHdZFxaWqqgoB9PLh05ckRXX3217+cVK1ZoxYoVGjNmjLZt29be4wMAgA7I0riRpJycHOXk5DS57n+DJS4uTl6vtx2mAgAAlyrjPy0FAAA6F+IGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYJQuVg8AAFaKe+Atq0fotEqWTrR6BBiKMzcAAMAoxA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAo/AlfkAz8EVv1uGL3gC0FGduAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAEAAEYhbgAAgFGIGwAAYBTiBgAAGKVDxM3KlSsVFxcnh8OhtLQ07d69+4Lbb9iwQUOGDJHD4dBVV12lzZs3t9OkAACgo7M8btavXy+n06m8vDwVFRUpMTFRmZmZOnbsWJPbf/DBB7r11lt1xx13aN++fZoyZYqmTJmiTz75pJ0nBwAAHZHlcZOfn685c+YoOztbw4YN06pVqxQaGqrVq1c3uf3jjz+u8ePH63e/+52GDh2qhx9+WCNHjtRTTz3VzpMDAICOqIuVL15XV6e9e/dq4cKFvmVBQUHKyMhQYWFhk88pLCyU0+lssCwzM1ObNm1qcvva2lrV1tb6fj516pQkqaqqqpXTN81Te6ZN9ouLa6tjKnFcrdSWx1Xi2FqJY2uutji2P+zT6/VedFtL4+b48eOqr69XVFRUg+VRUVE6cOBAk88pLy9vcvvy8vImt3e5XFq8eHGj5bGxsX5OjY4qosDqCdAWOK7m4tiaqy2P7enTpxUREXHBbSyNm/awcOHCBmd6PB6PTpw4oT59+shms1k4WcdSVVWl2NhYlZWVKTw83OpxEEAcW3NxbM3EcW2a1+vV6dOnFRMTc9FtLY2byMhIBQcHq6KiosHyiooKRUdHN/mc6OjoFm1vt9tlt9sbLOvZs6f/QxsuPDycf5kMxbE1F8fWTBzXxi52xuYHlt5QHBISouTkZLndbt8yj8cjt9ut9PT0Jp+Tnp7eYHtJevvtt8+7PQAA6FwsvyzldDqVlZWllJQUpaamqqCgQDU1NcrOzpYkzZgxQ3379pXL5ZIkzZ8/X2PGjNGjjz6qiRMnat26ddqzZ4+effZZK98GAADoICyPm+nTp6uyslK5ubkqLy9XUlKStmzZ4rtpuLS0VEFBP55gGjVqlF599VX94Q9/0IMPPqhBgwZp06ZNGj58uFVvwQh2u115eXmNLuHh0sexNRfH1kwc19azeZvzmSoAAIBLhOVf4gcAABBIxA0AADAKcQMAAIxC3AAAAKMQN53QypUrFRcXJ4fDobS0NO3evdu37ttvv9U999yjPn36KCwsTNOmTWv0pYnouC50bJ999lmNHTtW4eHhstlsOnnypHWDotnee+89TZo0STExMbLZbI1+j57X61Vubq4uv/xydevWTRkZGfrss8+sGRYtcrFju3HjRt1www2+b9QvLi62ZM5LEXHTyaxfv15Op1N5eXkqKipSYmKiMjMzdezYMUnSb3/7W/3tb3/Thg0btH37dh05ckQ33XSTxVOjOS52bM+cOaPx48frwQcftHhStERNTY0SExO1cuXKJtcvW7ZMTzzxhFatWqVdu3ape/fuyszM1LffftvOk6KlLnZsa2pq9H//93965JFH2nkyA3jRqaSmpnrvuece38/19fXemJgYr8vl8p48edLbtWtX74YNG3zr9+/f75XkLSwstGJctMCFju1/27p1q1eS95tvvmnnCdFakryvv/6672ePx+ONjo72Ll++3Lfs5MmTXrvd7v3rX/9qwYTw1/8e2/926NAhryTvvn372nWmSxlnbjqRuro67d27VxkZGb5lQUFBysjIUGFhofbu3atz5841WD9kyBD169dPhYWFVoyMZrrYsYWZDh06pPLy8gbHPSIiQmlpaRx3dGrETSdy/Phx1dfX+779+QdRUVEqLy9XeXm5QkJCGv1i0R/Wo+O62LGFmX44thx3oCHiBgAAGIW46UQiIyMVHBzc6NNPFRUVio6OVnR0tOrq6hp9iuaH9ei4LnZsYaYfji3HHWiIuOlEQkJClJycLLfb7Vvm8XjkdruVnp6u5ORkde3atcH6gwcPqrS0VOnp6VaMjGa62LGFmQYMGKDo6OgGx72qqkq7du3iuKNTs/y3gqN9OZ1OZWVlKSUlRampqSooKFBNTY2ys7MVERGhO+64Q06nU71791Z4eLjuvfdepaen6+c//7nVo+MiLnRsJfnuq/r8888lSR9//LF69Oihfv36qXfv3laOjguorq72HTPp+5uIi4uL1bt3b/Xr108LFizQH//4Rw0aNEgDBgzQokWLFBMToylTplg3NJrlYsf2xIkTKi0t1ZEjRyR9/z+bknxn2nEBVn9cC+3vySef9Pbr188bEhLiTU1N9e7cudO37uzZs967777b26tXL29oaKh36tSp3qNHj1o4LVriQsc2Ly/PK6nRY82aNdYNjIv64aP7//vIysryer3ffxx80aJF3qioKK/dbvf+4he/8B48eNDaodEsFzu2a9asaXJ9Xl6epXNfCmxer9fbvjkFAADQdrjnBgAAGIW4AQAARiFuAACAUYgbAABgFOIGAAAYhbgBAABGIW4AAIBRiBsAAGAU4gYAABiFuAHQoVRWVuo3v/mN+vXrJ7vdrujoaGVmZur999+XJNlsNm3atKnF+42Li1NBQUFghwXQIfGLMwF0KNOmTVNdXZ1eeOEFDRw4UBUVFXK73fr666+tHg3AJYLfLQWgwzh58qR69eqlbdu2acyYMY3Wx8XF6csvv/T93L9/f5WUlOiLL76Q0+nUzp07VVNTo6FDh8rlcikjI0OSNHbsWG3fvr3Bvn74q2/Hjh1auHCh9uzZo8jISE2dOlUul0vdu3dvw3cKoC1xWQpAhxEWFqawsDBt2rRJtbW1jdb/61//kiStWbNGR48e9f1cXV2tCRMmyO12a9++fRo/frwmTZqk0tJSSdLGjRt1xRVXaMmSJTp69KiOHj0qSfriiy80fvx4TZs2TR999JHWr1+vHTt2KCcnp53eMYC2wJkbAB3Ka6+9pjlz5ujs2bMaOXKkxowZo1tuuUUjRoyQ9P09N6+//rqmTJlywf0MHz5cc+fO9YVKXFycFixYoAULFvi2mT17toKDg/XMM8/4lu3YsUNjxoxRTU2NHA5HwN8fgLbHmRsAHcq0adN05MgRvfnmmxo/fry2bdumkSNHau3ated9TnV1te677z4NHTpUPXv2VFhYmPbv3+87c3M+H374odauXes7YxQWFqbMzEx5PB4dOnQowO8MQHvhhmIAHY7D4dC4ceM0btw4LVq0SLNnz1ZeXp5mzpzZ5Pb33Xef3n77ba1YsUIJCQnq1q2bbr75ZtXV1V3wdaqrq3XXXXdp3rx5jdb169cvEG8FgAWIGwAd3rBhw3wf/+7atavq6+sbrH///fc1c+ZMTZ06VdL30VJSUtJgm5CQkEbPGzlypD799FMlJCS02ewA2h+XpQB0GF9//bWuv/56vfzyy/roo4906NAhbdiwQcuWLdMvf/lLSd/fO+N2u1VeXq5vvvlGkjRo0CBt3LhRxcXF+vDDD/WrX/1KHo+nwb7j4uL03nvv6fDhwzp+/Lgk6f7779cHH3ygnJwcFRcX67PPPtMbb7zBDcXAJY64AdBhhIWFKS0tTY899piuvfZaDR8+XIsWLdKcOXP01FNPSZIeffRRvf3224qNjdXVV18tScrPz1evXr00atQoTZo0SZmZmRo5cmSDfS9ZskQlJSWKj4/XT37yE0nSiBEjtH37dv3nP//R6NGjdfXVVys3N1cxMTHt+8YBBBSflgIAAEbhzA0AADAKcQMAAIxC3AAAAKMQNwAAwCjEDQAAMApxAwAAjELcAAAAoxA3AADAKMQNAAAwCnEDAACMQtwAAACj/D/jTJmds6AcQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_shots = 500\n",
    "task = device.run(bell_pair_with_pulse, shots=nb_shots, disable_qubit_rewiring=True)\n",
    "counts = task.result().measurement_counts\n",
    "plt.bar(sorted(counts), [counts[k]/nb_shots for k in sorted(counts)])\n",
    "plt.xlabel(\"State\")\n",
    "plt.ylabel(\"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Task Summary\n",
      "{'arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3': {'shots': 600, 'tasks': {'COMPLETED': 2}}}\n",
      "Note: Charges shown are estimates based on your Amazon Braket simulator and quantum processing unit (QPU) task usage. Estimated charges shown may differ from your actual charges. Estimated charges do not factor in any discounts or credits, and you may experience additional charges based on your use of other services such as Amazon Elastic Compute Cloud (Amazon EC2).\n",
      "Estimated cost to run this example: 0.810 USD\n"
     ]
    }
   ],
   "source": [
    "print(\"Task Summary\")\n",
    "print(t.quantum_tasks_statistics())\n",
    "print('Note: Charges shown are estimates based on your Amazon Braket simulator and quantum processing unit (QPU) task usage. Estimated charges shown may differ from your actual charges. Estimated charges do not factor in any discounts or credits, and you may experience additional charges based on your use of other services such as Amazon Elastic Compute Cloud (Amazon EC2).')\n",
    "print(f\"Estimated cost to run this example: {t.qpu_tasks_cost() + t.simulator_tasks_cost():.3f} USD\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.15"
  },
  "vscode": {
   "interpreter": {
    "hash": "e8fe7b1d737818ec041fd05b4c8bbd1804e351a931e38c7cd860a34c69554183"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}