{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1287c4fe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:14.562778Z",
     "iopub.status.busy": "2024-04-26T18:19:14.562487Z",
     "iopub.status.idle": "2024-04-26T18:19:14.566208Z",
     "shell.execute_reply": "2024-04-26T18:19:14.565766Z"
    },
    "nbsphinx": "hidden"
   },
   "outputs": [],
   "source": [
    "# Copyright 2024 Keysight Technologies Inc."
   ]
  },
  {
   "cell_type": "raw",
   "id": "f9f22253",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Example: Running XRB\n",
    "====================\n",
    "\n",
    "This example illustrates how to generate extended randomized benchmarking\n",
    "(:tqdoc:`XRB`\\) circuits and use them to estimate the probability of a stochastic\n",
    "error acting on the specified system(s) during a random gate. While this example uses\n",
    "the built-in :py:class:`~trueq.Simulator` to execute the circuits, the same\n",
    "procedure can be followed for hardware applications.\n",
    "\n",
    "Isolated XRB\n",
    "------------\n",
    "\n",
    "This section illustrates how to generate :tqdoc:`XRB` circuits to characterize a pair\n",
    "of qubits in isolation. Here, we are performing two-qubit :tqdoc:`XRB` which learns\n",
    "the stochastic infidelity over the two-qubit Clifford gateset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "da55600d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:14.568166Z",
     "iopub.status.busy": "2024-04-26T18:19:14.567884Z",
     "iopub.status.idle": "2024-04-26T18:19:17.720640Z",
     "shell.execute_reply": "2024-04-26T18:19:17.720166Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import trueq as tq\n",
    "\n",
    "# generate XRB circuits to characterize a pair of qubits [0, 1]\n",
    "# with 9 * 30 random circuits for each circuit depth [2, 4, 16]\n",
    "circuits = tq.make_xrb([[0, 1]], [2, 4, 16], 30)\n",
    "\n",
    "# initialize a noisy simulator with stochastic Pauli and overrotation\n",
    "sim = tq.Simulator().add_stochastic_pauli(px=0.02).add_overrotation(0.04)\n",
    "\n",
    "# run the circuits on the simulator to populate their results\n",
    "sim.run(circuits, n_shots=1000)\n",
    "\n",
    "# plot the exponential decay of the purities\n",
    "circuits.plot.raw()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "da1c7511",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Print the fit summary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7d24268",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:17.723079Z",
     "iopub.status.busy": "2024-04-26T18:19:17.722560Z",
     "iopub.status.idle": "2024-04-26T18:19:17.779848Z",
     "shell.execute_reply": "2024-04-26T18:19:17.779400Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "<script>\n",
       "    if (trueq !== \"2.14.5\") {\n",
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       "        document.head.appendChild(css);\n",
       "        var polyfill = document.createElement(\"script\");\n",
       "        polyfill.src = \"https://polyfill.io/v3/polyfill.min.js?features=es6\";\n",
       "        document.body.appendChild(polyfill);\n",
       "        var mathjax = document.createElement(\"script\");\n",
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       "        document.body.appendChild(mathjax);\n",
       "        var trueq = \"2.14.5\";\n",
       "      }\n",
       "</script>\n",
       "<div class=\"tq-trusted\">True-Q formatting will not be loaded without trusting this\n",
       "notebook or rerunning the affected cells. Notebooks can be marked as trusted by clicking\n",
       "\"File -> Trust Notebook\".</div>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "<table class=\"tq-table tq-right-border \" id=\"id168280423706354155475426990570614026993\">\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "        \n",
       "    <tr class=\"tq-highlight\">\n",
       "        <td class=\"protocol\" style=\"vertical-align: bottom;\">\n",
       "            <div style=\"font-weight: bold;\">XRB</div>\n",
       "            <div class=\"tq-tooltip\">Extended Randomized Benchmarking</div>\n",
       "        </td>\n",
       "            \n",
       "            <td>\n",
       "                Cliffords\n",
       "\n",
       "                    <div>(0, 1)</div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    <dl>\n",
       "                        <dt>Key:</dt>\n",
       "                        <dd>\n",
       "                            <ul>\n",
       "                                    <li>labels: (0, 1)</li>\n",
       "                                    <li>protocol: XRB</li>\n",
       "                                    <li>twirl: Cliffords on [(0, 1)]</li>\n",
       "                            </ul>\n",
       "                        </dd>\n",
       "                    </dl>\n",
       "                </div>\n",
       "            </td>\n",
       "    </tr>\n",
       "    \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${e}_{S}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The probability of a stochastic error acting on the specified systems during a random gate.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        4.0e-02 (7.7e-04)\n",
       "                        <div class=\"tq-tooltip\">0.03964839003461862, 0.0007715144117231922</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${u}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The unitarity of the noise, that is, the average decrease in the purity of an initial state.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.2e-01 (1.6e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9170935624139733, 0.0015806402291410383</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${A}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    SPAM parameter of the exponential decay $Au^m$.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.9e-01 (9.0e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9901245371245811, 0.009009681915540932</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "                    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "</table>\n",
       "\n",
       "\n",
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      ],
      "text/plain": [
       "EstimateCollection(1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuits.fit()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "03d48f24",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Simultaneous XRB\n",
    "----------------\n",
    "\n",
    "This section demonstrates how to generate :tqdoc:`XRB` circuits that characterize the\n",
    "amount of stochastic noise while gates are applied simultaneously on a device.\n",
    "\n",
    "For example, to generate XRB circuits to simultaneously characterize a single qubit\n",
    "``[0]``, a pair of qubits ``[1, 2]``, and another single qubit ``[3]`` with\n",
    ":math:`9 \\times 30` random circuits for each circuit depth ``[2, 4, 16]``, we can\n",
    "write:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f993efdd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:17.781911Z",
     "iopub.status.busy": "2024-04-26T18:19:17.781547Z",
     "iopub.status.idle": "2024-04-26T18:19:19.878364Z",
     "shell.execute_reply": "2024-04-26T18:19:19.877883Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1350x350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "circuits = tq.make_xrb([[0], [1, 2], [3]], [2, 4, 16], 30)\n",
    "\n",
    "# initialize a noisy simulator with stochastic Pauli and overrotation\n",
    "sim = tq.Simulator().add_stochastic_pauli(px=0.02).add_overrotation(0.04)\n",
    "\n",
    "# run the circuits on the simulator to populate their results\n",
    "sim.run(circuits, n_shots=1000)\n",
    "\n",
    "# plot the exponential decay of the purities\n",
    "circuits.plot.raw()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "eff9aafb",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Print the fit summary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3eaa953c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:19.880723Z",
     "iopub.status.busy": "2024-04-26T18:19:19.880321Z",
     "iopub.status.idle": "2024-04-26T18:19:19.933343Z",
     "shell.execute_reply": "2024-04-26T18:19:19.932919Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "notebook or rerunning the affected cells. Notebooks can be marked as trusted by clicking\n",
       "\"File -> Trust Notebook\".</div>\n",
       "\n",
       "\n",
       "\n",
       "\n",
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       "        <td class=\"protocol\" style=\"vertical-align: bottom;\">\n",
       "            <div style=\"font-weight: bold;\">XRB</div>\n",
       "            <div class=\"tq-tooltip\">Extended Randomized Benchmarking</div>\n",
       "        </td>\n",
       "            \n",
       "            <td>\n",
       "                Cliffords\n",
       "\n",
       "                    <div>(0,)</div>\n",
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       "                    <dl>\n",
       "                        <dt>Key:</dt>\n",
       "                        <dd>\n",
       "                            <ul>\n",
       "                                    <li>labels: (0,)</li>\n",
       "                                    <li>protocol: XRB</li>\n",
       "                                    <li>twirl: Cliffords on [0, (1, 2), 3]</li>\n",
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       "            </td>\n",
       "            \n",
       "            <td>\n",
       "                Cliffords\n",
       "\n",
       "                    <div>(1, 2)</div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    <dl>\n",
       "                        <dt>Key:</dt>\n",
       "                        <dd>\n",
       "                            <ul>\n",
       "                                    <li>labels: (1, 2)</li>\n",
       "                                    <li>protocol: XRB</li>\n",
       "                                    <li>twirl: Cliffords on [0, (1, 2), 3]</li>\n",
       "                            </ul>\n",
       "                        </dd>\n",
       "                    </dl>\n",
       "                </div>\n",
       "            </td>\n",
       "            \n",
       "            <td>\n",
       "                Cliffords\n",
       "\n",
       "                    <div>(3,)</div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    <dl>\n",
       "                        <dt>Key:</dt>\n",
       "                        <dd>\n",
       "                            <ul>\n",
       "                                    <li>labels: (3,)</li>\n",
       "                                    <li>protocol: XRB</li>\n",
       "                                    <li>twirl: Cliffords on [0, (1, 2), 3]</li>\n",
       "                            </ul>\n",
       "                        </dd>\n",
       "                    </dl>\n",
       "                </div>\n",
       "            </td>\n",
       "    </tr>\n",
       "    \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${e}_{S}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The probability of a stochastic error acting on the specified systems during a random gate.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        1.9e-02 (7.8e-04)\n",
       "                        <div class=\"tq-tooltip\">0.019252635636475723, 0.0007790272643924942</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        3.8e-02 (1.0e-03)\n",
       "                        <div class=\"tq-tooltip\">0.038128274294094266, 0.0010368039759344782</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        2.0e-02 (7.2e-04)\n",
       "                        <div class=\"tq-tooltip\">0.019701537381388357, 0.0007232024276490294</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${u}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The unitarity of the noise, that is, the average decrease in the purity of an initial state.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.5e-01 (2.0e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9491538569413327, 0.0020374104968540405</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.2e-01 (2.1e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9202103644932877, 0.002127514516375127</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.5e-01 (1.9e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9479801010832181, 0.00189054460796371</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${A}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    SPAM parameter of the exponential decay $Au^m$.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.7e-01 (1.1e-02)\n",
       "                        <div class=\"tq-tooltip\">0.9730845881357387, 0.011412005184361088</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.7e-01 (9.5e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9706836022041112, 0.009483239490881932</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.7e-01 (1.0e-02)\n",
       "                        <div class=\"tq-tooltip\">0.9658482484676595, 0.01012431702498326</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "                    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "</table>\n",
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      ],
      "text/plain": [
       "EstimateCollection(3)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuits.fit()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "77d98bb7",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Simultaneous XRB on Qudits\n",
    "--------------------------\n",
    "\n",
    "The :py:meth:`~trueq.make_xrb` function can be used for qudits of higher dimension in\n",
    "exactly the same way as for qubits. For example, consider the same simultaneous\n",
    "characterization configuration as in the example above but with qutrits instead of\n",
    "qubits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7f1195f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:19.935468Z",
     "iopub.status.busy": "2024-04-26T18:19:19.935159Z",
     "iopub.status.idle": "2024-04-26T18:19:20.124270Z",
     "shell.execute_reply": "2024-04-26T18:19:20.123810Z"
    }
   },
   "outputs": [
    {
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       "DisplayWrapper(<svg xmlns=\"http://w...)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set the global dimension to 3 for qutrits\n",
    "tq.settings.set_dim(3)\n",
    "\n",
    "# create circuits for the simultaneous characterization of\n",
    "# qutrit 1, the qutrit pair (1, 2) and qutrit 3:\n",
    "circuits = tq.make_xrb([[0], [1, 2], [3]], [2, 4, 16], 30)\n",
    "\n",
    "# display a sample circuit\n",
    "circuits[0].draw()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "b3e5de56",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "We again initialize a noisy simulator with overrotation errors and stochastic Pauli\n",
    "noise. The :py:meth:`~trueq.Simulator.add_overrotation` method works natively for\n",
    "qudits of higher dimension. To implement the stochastic noise, we use a probabilistic\n",
    "sum of Weyl operators, analogous to the stochastic Pauli channel used for qubits. We\n",
    "add this noise to our simulator using the\n",
    ":py:meth:`~trueq.Simulator.add_stochastic_weyl` method. For this example, we add a\n",
    "small qutrit :math:`X` and :math:`X^2` error:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d7910e06",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:20.127706Z",
     "iopub.status.busy": "2024-04-26T18:19:20.127226Z",
     "iopub.status.idle": "2024-04-26T18:19:26.773770Z",
     "shell.execute_reply": "2024-04-26T18:19:26.773299Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1350x350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim = tq.Simulator().add_stochastic_pauli(W10=0.02, W20=0.01).add_overrotation(0.04)\n",
    "\n",
    "# run the circuits on the simulator to populate their results\n",
    "sim.run(circuits, n_shots=1000)\n",
    "\n",
    "# plot the exponential decay of the purities\n",
    "circuits.plot.raw()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "0e636acd",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    "Display the fit parameter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "938b542b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-26T18:19:26.776102Z",
     "iopub.status.busy": "2024-04-26T18:19:26.775675Z",
     "iopub.status.idle": "2024-04-26T18:19:26.914499Z",
     "shell.execute_reply": "2024-04-26T18:19:26.914006Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "            <div class=\"tq-tooltip\">Extended Randomized Benchmarking</div>\n",
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       "            \n",
       "            <td>\n",
       "                Cliffords\n",
       "\n",
       "                    <div>(0,)</div>\n",
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       "                        <dt>Key:</dt>\n",
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       "                                    <li>protocol: XRB</li>\n",
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       "                        <dt>Key:</dt>\n",
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       "                                    <li>protocol: XRB</li>\n",
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       "                <div class=\"tq-tooltip\">\n",
       "                    <dl>\n",
       "                        <dt>Key:</dt>\n",
       "                        <dd>\n",
       "                            <ul>\n",
       "                                    <li>labels: (3,)</li>\n",
       "                                    <li>protocol: XRB</li>\n",
       "                                    <li>twirl: Cliffords on [0, (1, 2), 3]</li>\n",
       "                            </ul>\n",
       "                        </dd>\n",
       "                    </dl>\n",
       "                </div>\n",
       "            </td>\n",
       "    </tr>\n",
       "    \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${e}_{S}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The probability of a stochastic error acting on the specified systems during a random gate.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        3.2e-02 (9.6e-04)\n",
       "                        <div class=\"tq-tooltip\">0.03208522872567443, 0.0009587915032335817</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        5.7e-02 (9.0e-04)\n",
       "                        <div class=\"tq-tooltip\">0.05730118855628075, 0.0009025833049068695</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        3.1e-02 (7.6e-04)\n",
       "                        <div class=\"tq-tooltip\">0.030563616891930545, 0.000762786516217963</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${u}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    The unitarity of the noise, that is, the average decrease in the purity of an initial state.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.3e-01 (2.1e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9289663800074087, 0.002088064031742223</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        8.9e-01 (1.7e-03)\n",
       "                        <div class=\"tq-tooltip\">0.8872895622111183, 0.0017230000227484161</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.3e-01 (1.7e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9322827635053625, 0.0016638142530733804</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>\n",
       "                <div style=\"display: inline-block; padding-left: 5px; text-align: right;\">\n",
       "                    ${A}$\n",
       "                </div>\n",
       "                <div class=\"tq-tooltip\">\n",
       "                    SPAM parameter of the exponential decay $Au^m$.\n",
       "                </div>\n",
       "            </td>\n",
       "                \n",
       "                <td>\n",
       "                        1.0e+00 (1.1e-02)\n",
       "                        <div class=\"tq-tooltip\">0.9957762645484559, 0.011187114159611102</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.9e-01 (8.7e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9899700211346119, 0.008712167211532047</div>\n",
       "                </td>\n",
       "                \n",
       "                <td>\n",
       "                        9.8e-01 (9.6e-03)\n",
       "                        <div class=\"tq-tooltip\">0.9762061135717386, 0.009575470438259721</div>\n",
       "                </td>\n",
       "        </tr>\n",
       "                    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n",
       "</table>\n",
       "\n",
       "\n",
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      ],
      "text/plain": [
       "EstimateCollection(3)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuits.fit()"
   ]
  }
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