From e8a906cf8d16e05c4f6c44bf7334e2ce4f35acc9 Mon Sep 17 00:00:00 2001
From: Liberto Beltran <liberto.beltran@phys.ethz.ch>
Date: Sat, 2 Dec 2023 13:41:06 +0100
Subject: [PATCH] updated s17 plottin file

---
 s17_plotting.ipynb | 655 +--------------------------------------------
 1 file changed, 1 insertion(+), 654 deletions(-)

diff --git a/s17_plotting.ipynb b/s17_plotting.ipynb
index ff39f9f..af15291 100644
--- a/s17_plotting.ipynb
+++ b/s17_plotting.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -522,659 +522,6 @@
     "# Show the plot\n",
     "plt.show()\n"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Bell-state analysis"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(0.0, 0.0, 0.0)"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import random\n",
-    "import stim\n",
-    "def simulate_circuit_bell(circuit_in, \n",
-    "                        p_amp_ge = 0.01, \n",
-    "                        p_amp_eg = 0, \n",
-    "                        parity = 0, \\\n",
-    "                        phase = 0, \n",
-    "                        cycles = 0,\n",
-    "                        after_clifford_depolarization =0.0, \n",
-    "                        correct_ancilla = True, \n",
-    "                        correct_data = True): \n",
-    "\n",
-    "    # qubit indices\n",
-    "    data_0_idx = 0\n",
-    "    ancilla_idx = 1\n",
-    "    data_1_idx = 2\n",
-    "\n",
-    "    # init simulator \n",
-    "    simulator = stim.TableauSimulator()\n",
-    "    circuit = circuit_in.flattened() #circuit.flattened()  \n",
-    "    \n",
-    "    # Describes whether we apply an ancilla flip to the msmt. \n",
-    "    \n",
-    "    if cycles ==1: \n",
-    "        parity_readout_flip = parity\n",
-    "        phase_readout_flip = phase \n",
-    "    else: \n",
-    "        parity_readout_flip = parity\n",
-    "        phase_readout_flip = phase \n",
-    "    \n",
-    "    # if the (revert flipped) readout results match this, we correct. \n",
-    "    parity_correct_array = [not parity for i in range(cycles)]\n",
-    "    phase_correct_array  = [not phase for i in range(cycles)]\n",
-    "\n",
-    "    # Contains the reverted ancilla readouts (e.g. flipped back.)\n",
-    "    parity_readout_array = []\n",
-    "    phase_readout_array  = []\n",
-    "    \n",
-    "    # Execute circuit\n",
-    "    for k in range(len(circuit)) :\n",
-    "        instruction = circuit[k]\n",
-    "        sub_circuit = circuit[k:k+1]\n",
-    "        # Insert asymmetric error at Measure Reset instruction\n",
-    "        if  instruction.name == 'MR' :\n",
-    "            ts = instruction.targets_copy()\n",
-    "            measurements = simulator.current_measurement_record()\n",
-    "            \n",
-    "            # Flip Ancilla \n",
-    "            if correct_ancilla: \n",
-    "                # correction before ZZ ancilla\n",
-    "                if len(measurements)%2 == 0 and parity_readout_flip == 1:\n",
-    "                        simulator.x(ancilla_idx)\n",
-    "                # correction before XX ancilla \n",
-    "                elif len(measurements)%2 ==1 and phase_readout_flip == 1:     \n",
-    "                        simulator.x(ancilla_idx)\n",
-    "            \n",
-    "\n",
-    "            \n",
-    "            # Amplitude noise \n",
-    "            for i in range(len(ts)):\n",
-    "                    qubit = ts[i].value\n",
-    "                    assert qubit == ancilla_idx\n",
-    "                    # check whether we are in |1>\n",
-    "                    if simulator.peek_bloch(qubit) == stim.PauliString(\"-Z\"): \n",
-    "                        if random.random() < p_amp_ge: \n",
-    "                            simulator.x(qubit)  \n",
-    "                    # check whether we are in |0> \n",
-    "                    elif simulator.peek_bloch(qubit) == stim.PauliString(\"+Z\"): \n",
-    "                        if random.random() < p_amp_eg: \n",
-    "                            simulator.x(qubit)    \n",
-    "\n",
-    "            # execute MR instruction\n",
-    "            simulator.do_circuit(sub_circuit)\n",
-    "            \n",
-    "            # Correct with feedback pulse, after executing MR instruction  \n",
-    "            if correct_data: \n",
-    "                measurements = simulator.current_measurement_record()\n",
-    "                last_msmt = measurements[-1]\n",
-    "                \n",
-    "                ## ZZ stabilizer correction \n",
-    "                if len(measurements)%2 == 1: \n",
-    "                    # XOR current readout with ancilla parity flip  \n",
-    "                    if correct_ancilla: \n",
-    "                        if parity_readout_flip == 1 : \n",
-    "                            parity_readout_array.append(not(last_msmt) ) \n",
-    "                        else: \n",
-    "                            parity_readout_array.append(last_msmt )\n",
-    "                        if last_msmt == 1:\n",
-    "                            parity_readout_flip = not(parity_readout_flip)\n",
-    "                    else: \n",
-    "                        parity_readout_array.append(last_msmt)\n",
-    "                      \n",
-    "                    if len(parity_readout_array) > cycles: \n",
-    "                        parity_readout_array = parity_readout_array[-cycles:]\n",
-    "   \n",
-    "                    if len(parity_readout_array) == cycles  and \\\n",
-    "                        parity_readout_array  == parity_correct_array: \n",
-    "                        # parity_readout_array[-1]  == parity_correct_array[-1]: \n",
-    "                        # print(\"ZZ\",parity_readout_array,last_msmt )\n",
-    "                        # apply correction\n",
-    "                        simulator.x(data_1_idx) \n",
-    "                        # clifford noise after gate. \n",
-    "                        simulator.depolarize1(data_1_idx,p=after_clifford_depolarization)   \n",
-    "                        # reset readout flip to corrected, expected value\n",
-    "                        parity_readout_flip = parity\n",
-    "                        # reset readout parity array. \n",
-    "                        parity_readout_array = []                       \n",
-    "                        \n",
-    "                        \n",
-    "                #  XX stabilizer correction  \n",
-    "                elif len(measurements)%2 == 0:\n",
-    "                    # XOR current readout with ancilla phase flip\n",
-    "                    if correct_ancilla:\n",
-    "                        if phase_readout_flip == 1:\n",
-    "                            phase_readout_array.append(not(last_msmt))\n",
-    "                        else: \n",
-    "                            phase_readout_array.append(last_msmt )\n",
-    "                        if last_msmt == 1:\n",
-    "                            phase_readout_flip = not(phase_readout_flip)\n",
-    "                    else: \n",
-    "                        phase_readout_array.append(last_msmt)\n",
-    "                    if len(phase_readout_array) > cycles: \n",
-    "                        phase_readout_array = phase_readout_array[-cycles:]\n",
-    "                                       \n",
-    "                    if len(phase_readout_array)== cycles  and \\\n",
-    "                        phase_readout_array == phase_correct_array: \n",
-    "                        # phase_readout_array[-1] == phase_correct_array[-1] : \n",
-    "                        # print(\"XX\",phase_readout_array,last_msmt )    \n",
-    "                        # apply correction\n",
-    "                        simulator.x(data_1_idx) \n",
-    "                        # clifford noise after gate. \n",
-    "                        simulator.depolarize1(data_1_idx,p=after_clifford_depolarization)  \n",
-    "                        # reset readout phase to corrected, expected value \n",
-    "                        phase_readout_flip = phase \n",
-    "                        # reset readout phase array\n",
-    "                        phase_readout_array = []\n",
-    "                              \n",
-    "        else: \n",
-    "            simulator.do_circuit(sub_circuit)\n",
-    "\n",
-    "    return simulator   \n",
-    "\n",
-    "\n",
-    "def count_logical_errors_bell(circuit: stim.Circuit,   num_shots: int, \\\n",
-    "                        p_amp_ge = 0.01,p_amp_eg= 0, parity = 0, phase = 0, cycles = 0,\\\n",
-    "                        after_clifford_depolarization =0,correct_ancilla = True, correct_data = True) -> int:\n",
-    "    # Sample the circuit.\n",
-    "    num_errors = 0\n",
-    "    num_errors_z = 0\n",
-    "    num_errors_x = 0\n",
-    "    for i in range(num_shots):\n",
-    "        simulator = simulate_circuit_bell(circuit,p_amp_ge = p_amp_ge, p_amp_eg = p_amp_eg, \\\n",
-    "                                          parity = parity, phase = phase,\\\n",
-    "            cycles = cycles,after_clifford_depolarization =after_clifford_depolarization, \\\n",
-    "                correct_ancilla = correct_ancilla, correct_data=correct_data)\n",
-    "        # measurements.append(simulator.current_measurement_record())\n",
-    "        if simulator.measure_observable(stim.PauliString(\"Z_Z\")) != parity or \\\n",
-    "            simulator.measure_observable(stim.PauliString(\"X_X\")) != phase: \n",
-    "                num_errors +=1\n",
-    "        if simulator.measure_observable(stim.PauliString(\"Z_Z\"))  != parity:\n",
-    "            num_errors_z += 1\n",
-    "        if simulator.measure_observable(stim.PauliString(\"X_X\")) != phase :  \n",
-    "            num_errors_x += 1\n",
-    "    return num_errors, num_errors_z, num_errors_x\n",
-    "    \n",
-    "\n",
-    "def generate_bell_circuit(\n",
-    "    parity = 0,  # parity of stabilized bell state\n",
-    "    phase = 1,   # phase of stabilized bell state\n",
-    "    fidelity_parity = 1,\n",
-    "    fidelity_phase = 1,\n",
-    "    rounds = 3, \n",
-    "    after_clifford_depolarization= 0.001,\n",
-    "    after_reset_flip_probability=0.001,\n",
-    "    before_measure_flip_probability= 0.001,\n",
-    "    before_round_data_depolarization=0.001,\n",
-    "    ):\n",
-    "\n",
-    "    # qubit indices    \n",
-    "    data0 = 0\n",
-    "    data1 = 2\n",
-    "    ancilla = 1\n",
-    "\n",
-    "    parity_string = ''\n",
-    "    if parity == 0:\n",
-    "        parity_string = 'I'\n",
-    "    else: \n",
-    "        parity_string = 'X'\n",
-    "\n",
-    "    phase_string = ''\n",
-    "    if phase == 0:\n",
-    "        phase_string = 'I'\n",
-    "    else:\n",
-    "        phase_string = 'X'\n",
-    "        \n",
-    "        \n",
-    "    # CX 0 1 2 1\n",
-    "    #                         DEPOLARIZE2({after_clifford_depolarization}) 0 1 2 1\n",
-    "                            \n",
-    "    #                         X_ERROR({before_measure_flip_probability}) 1\n",
-    "    #                         MR 1\n",
-    "    #                         X_ERROR({after_reset_flip_probability}) 1\n",
-    "                            \n",
-    "    #                         H 0 2\n",
-    "    #                         DEPOLARIZE1({after_clifford_depolarization}) 0 2\n",
-    "    #                         CX 0 1 2 1\n",
-    "    #                         DEPOLARIZE2({after_clifford_depolarization}) 0 1 2 1\n",
-    "    #                         H 0 2 \n",
-    "    #                         DEPOLARIZE1({after_clifford_depolarization}) 0 2\n",
-    "                            \n",
-    "    #                         X_ERROR({before_measure_flip_probability}) 1\n",
-    "    #                         MR 1\n",
-    "    #                         X_ERROR({after_reset_flip_probability}) 1\n",
-    "                            \n",
-    "    #                         DETECTOR rec[-2] \n",
-    "    #                         DETECTOR rec[-1]                       \n",
-    "        \n",
-    "                            #     DETECTOR rec[-2] rec[-4]\n",
-    "                            # DETECTOR rec[-1] rec[-3]\n",
-    "                            \n",
-    "    \n",
-    "                            # MPP X0*X2\n",
-    "                            # MPP Z0*Z2                         \n",
-    "                            # OBSERVABLE_INCLUDE(0)  rec[-1] \n",
-    "                            # OBSERVABLE_INCLUDE(1)  rec[-2]\n",
-    "               #DEPOLARIZE1({before_round_data_depolarization}) 0 2\n",
-    "    \n",
-    "    circuit_bell = stim.Circuit(f''' \n",
-    "\n",
-    "                            R 0 1 2\n",
-    "                            X_ERROR({after_reset_flip_probability}) 0 1 2\n",
-    "                            \n",
-    "                            {parity_string} 2\n",
-    "                            DEPOLARIZE1({after_clifford_depolarization}) 2\n",
-    "                            \n",
-    "                            {phase_string}  0\n",
-    "                            DEPOLARIZE1({after_clifford_depolarization}) 0\n",
-    "                            \n",
-    "                            H 0\n",
-    "                            DEPOLARIZE1({after_clifford_depolarization}) 0\n",
-    "                            CX 0 2\n",
-    "                            DEPOLARIZE2({after_clifford_depolarization}) 0 2 \n",
-    "                            \n",
-    "                            X_ERROR({1-fidelity_parity}) 2\n",
-    "                            Z_ERROR({1-fidelity_phase}) 2\n",
-    "             \n",
-    "                    \n",
-    "                            REPEAT {rounds} {{\n",
-    "                                \n",
-    "                            CX 0 1 2 1\n",
-    "                            DEPOLARIZE2({after_clifford_depolarization}) 0 1 2 1\n",
-    "                            \n",
-    "                            X_ERROR({before_measure_flip_probability}) 1\n",
-    "                            MR 1\n",
-    "                            X_ERROR({after_reset_flip_probability}) 1\n",
-    "                            \n",
-    "                            H 0 2\n",
-    "                            DEPOLARIZE1({after_clifford_depolarization}) 0 2\n",
-    "                            CX 0 1 2 1\n",
-    "                            DEPOLARIZE2({after_clifford_depolarization}) 0 1 2 1\n",
-    "\n",
-    "                            X_ERROR({before_measure_flip_probability}) 1\n",
-    "                            MR 1\n",
-    "                            X_ERROR({after_reset_flip_probability}) 1\n",
-    "                            \n",
-    "                            H 0 2 \n",
-    "                            DEPOLARIZE1({after_clifford_depolarization}) 0 2\n",
-    "                            \n",
-    "                                }}\n",
-    "                                \n",
-    "                            ''')\n",
-    "    return circuit_bell\n",
-    "\n",
-    "\n",
-    "def get_logical_error_bell( parity = 0, \n",
-    "                            phase = 1, \n",
-    "                            cycles = 1,  # cycles of memory in logic. \n",
-    "                            after_clifford_depolarization= 0.01, \n",
-    "                            after_reset_flip_probability= 0,  \n",
-    "                            before_measure_flip_probability = 0, \n",
-    "                            before_round_data_depolarization=0.01,  \n",
-    "                            p_amp_ge = 0.01,\n",
-    "                            p_amp_eg= 0, \n",
-    "                            rounds = 1,  # rounds in run\n",
-    "                            runs = 1, \n",
-    "                            correct_ancilla = True, \n",
-    "                            correct_data = True):\n",
-    "    \n",
-    "    circuit_bell = generate_bell_circuit(\n",
-    "        parity=parity,\n",
-    "        phase=phase,       \n",
-    "        rounds=rounds,    # maybe change this, \n",
-    "        fidelity_parity= 1,\n",
-    "        fidelity_phase= 1,\n",
-    "        after_clifford_depolarization=after_clifford_depolarization, \n",
-    "        after_reset_flip_probability=after_reset_flip_probability,\n",
-    "        before_measure_flip_probability= before_measure_flip_probability,\n",
-    "        before_round_data_depolarization=before_round_data_depolarization,\n",
-    "  \n",
-    "    )\n",
-    "\n",
-    "\n",
-    "    n_errors, num_errors_z, num_errors_x = count_logical_errors_bell(circuit_bell,  \n",
-    "                                                runs, \n",
-    "                                                cycles = cycles, \n",
-    "                                                parity = parity, \n",
-    "                                                phase = phase, \n",
-    "                                                p_amp_ge = p_amp_ge,\n",
-    "                                                p_amp_eg= p_amp_eg,\n",
-    "                                                after_clifford_depolarization =after_clifford_depolarization, \n",
-    "                                                correct_ancilla = correct_ancilla, \n",
-    "                                                correct_data=correct_data)\n",
-    "    return n_errors/runs, num_errors_z/runs, num_errors_x/runs\n",
-    "        # logical_err_array.append(logical_err)\n",
-    "\n",
-    "        \n",
-    "get_logical_error_bell( parity = 1, \n",
-    "                        phase = 1, \n",
-    "                        cycles = 2, \n",
-    "                        after_clifford_depolarization= 0.01, \n",
-    "                        after_reset_flip_probability= 0.0,  \n",
-    "                        before_measure_flip_probability = 0.0, \n",
-    "                        before_round_data_depolarization=0.0,  \n",
-    "                        p_amp_ge = 0.1,\n",
-    "                        p_amp_eg= 0.0, \n",
-    "                        rounds = 5,  \n",
-    "                        runs = 3, \n",
-    "                        correct_ancilla = False, \n",
-    "                        correct_data= True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "def compare_msmt_times(runs = 100,\n",
-    "                    parity = 1,\n",
-    "                    phase = 1,\n",
-    "                    rounds = 4,\n",
-    "                    after_clifford_depolarization = 0.01,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.01,\n",
-    "                    correct_ancilla = True,\n",
-    "                    p_ge = 0.1, \n",
-    "                    correct_data = True\n",
-    "):\n",
-    "    plot_array = np.linspace(0.00, p_ge, 20 )\n",
-    "    #plot_array = np.linspace(0.00, after_clifford_depolarization,20)\n",
-    "    rounds_array =  np.arange(3,rounds+1,1) #   \n",
-    "\n",
-    "    cycles_1 = []\n",
-    "    cycles_2 = []\n",
-    "    cycles_3 = []\n",
-    "\n",
-    "    for p in plot_array:  \n",
-    "       \n",
-    "        cycles_1_sum = 0\n",
-    "        cycles_2_sum = 0\n",
-    "        cycles_3_sum = 0\n",
-    "        for r in rounds_array:\n",
-    "            \n",
-    "            after_clifford_depol = after_clifford_depolarization # p\n",
-    "            prob_ge = p#p_ge\n",
-    "            cycles_1_sum += get_logical_error_bell(parity = parity, phase = phase, cycles = 1, \\\n",
-    "                after_clifford_depolarization= after_clifford_depol, after_reset_flip_probability= after_reset_flip_probability,  \\\n",
-    "                before_measure_flip_probability = before_measure_flip_probability, \\\n",
-    "                    before_round_data_depolarization=before_round_data_depolarization,  p_amp_ge = prob_ge,p_amp_eg= 0, \\\n",
-    "                    runs = runs, rounds=r, correct_ancilla = correct_ancilla,  correct_data= correct_data)[0] /len(rounds_array)\n",
-    "                                \n",
-    "                            \n",
-    "            cycles_2_sum += get_logical_error_bell(parity = parity, phase = phase, cycles = 2, \\\n",
-    "                after_clifford_depolarization= after_clifford_depol, after_reset_flip_probability= after_reset_flip_probability,  \\\n",
-    "                before_measure_flip_probability = before_measure_flip_probability, \\\n",
-    "                    before_round_data_depolarization=before_round_data_depolarization,  p_amp_ge = prob_ge,p_amp_eg= 0, \\\n",
-    "                    runs = runs, rounds=r, correct_ancilla = correct_ancilla,  correct_data= correct_data)[0] /len(rounds_array)\n",
-    "                                \n",
-    "            # cycles_3_sum += get_logical_error_bell(parity = parity, phase = phase, cycles = 3, \\\n",
-    "            #     after_clifford_depolarization= after_clifford_depol, after_reset_flip_probability= after_reset_flip_probability,  \\\n",
-    "            #     before_measure_flip_probability = before_measure_flip_probability, \\\n",
-    "            #         before_round_data_depolarization=before_round_data_depolarization,  p_amp_ge = prob_ge,p_amp_eg= 0, \\\n",
-    "            #         runs = runs, rounds=r, correct_ancilla = correct_ancilla,  correct_data= correct_data)[0] /len(rounds_array)\n",
-    "        \n",
-    "        cycles_1.append(cycles_1_sum / len(rounds_array))\n",
-    "        cycles_2.append(cycles_2_sum / len(rounds_array))\n",
-    "        # cycles_3.append(cycles_3_sum / len(rounds_array))                     \n",
-    "                  \n",
-    "    \n",
-    "    import matplotlib.pyplot as plt\n",
-    "    if correct_ancilla:\n",
-    "        plt.plot(plot_array,cycles_1, label='1 with flip', color='r', marker='o')\n",
-    "        plt.plot(plot_array,cycles_2, label='2 with flip', color='b', marker='o')\n",
-    "        # plt.plot(plot_array,cycles_3, label='3', color='g', marker='o')\n",
-    "    else: \n",
-    "        plt.plot(plot_array,cycles_1, label='1 without flip', color='r', marker='.')\n",
-    "        plt.plot(plot_array,cycles_2, label='2 without flip ', color='b', marker='.')\n",
-    "        # plt.plot(plot_array,cycles_3, label='3', color='g', marker='.')\n",
-    "    plt.legend()\n",
-    "    # plt.title(f' Logical Bell-state error.vs. T1 ancilla decay during msmt. ($\\Phi{phase, parity, }$ clifford_err: {after_clifford_depolarization}, data_err before rnd: {before_round_data_depolarization}, runs: {runs})')\n",
-    "    # plt.title(f\"phase:{phase}, parity: {parity}, ancilla correct: {correct_ancilla}\") \n",
-    "    plt.title(f\"phase:{phase}, parity: {parity}\") \n",
-    "    plt.xlabel('p_X conditioned on ancilla in |1>')\n",
-    "    plt.ylabel('p_error, Logical Z')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "runs = 100\n",
-    "rounds = 5\n",
-    "parity = 1\n",
-    "phase = 1\n",
-    "\n",
-    "compare_msmt_times(runs = runs,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.0,\n",
-    "                    before_measure_flip_probability = 0.0,\n",
-    "                    before_round_data_depolarization = 0.0,\n",
-    "                    correct_ancilla = True,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) \n",
-    "\n",
-    "\n",
-    "compare_msmt_times(runs = runs,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.0,\n",
-    "                    before_measure_flip_probability = 0.0,\n",
-    "                    before_round_data_depolarization = 0.0,\n",
-    "                    correct_ancilla = False,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "runs = 100\n",
-    "rounds = 5\n",
-    "parity = 1\n",
-    "phase = 1\n",
-    "\n",
-    "compare_msmt_times(runs = runs,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.01,\n",
-    "                    correct_ancilla = True,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) \n",
-    "\n",
-    "\n",
-    "compare_msmt_times(runs = runs,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.01,\n",
-    "                    correct_ancilla = False,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# only last one helps or decision\n",
-    "runs = 100\n",
-    "rounds = 5\n",
-    "parity = 1\n",
-    "phase = 1\n",
-    "\n",
-    "compare_msmt_times(runs = runs,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.01,\n",
-    "                    correct_ancilla = True,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) \n",
-    "\n",
-    "\n",
-    "compare_msmt_times(runs = 100,\n",
-    "                    parity = parity,\n",
-    "                    phase = phase,\n",
-    "                    rounds = rounds,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.01,\n",
-    "                    correct_ancilla = False,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 102,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "compare_msmt_times(runs = 1000,\n",
-    "                    parity = 0,\n",
-    "                    phase = 0,\n",
-    "                    rounds = 2,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.00,\n",
-    "                    correct_ancilla = True,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) \n",
-    "\n",
-    "\n",
-    "compare_msmt_times(runs = 1000,\n",
-    "                    parity = 0,\n",
-    "                    phase = 0,\n",
-    "                    rounds = 2,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.00,\n",
-    "                    correct_ancilla = False,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "compare_msmt_times(runs = 1000,\n",
-    "                    parity = 1,\n",
-    "                    phase = 1,\n",
-    "                    rounds = 1,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.0,\n",
-    "                    before_measure_flip_probability = 0.00,\n",
-    "                    before_round_data_depolarization = 0.00,\n",
-    "                    correct_ancilla = True,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) \n",
-    "\n",
-    "\n",
-    "compare_msmt_times(runs = 1000,\n",
-    "                    parity = 1,\n",
-    "                    phase = 1,\n",
-    "                    rounds = 1,\n",
-    "                    after_clifford_depolarization = 0.001,\n",
-    "                    after_reset_flip_probability = 0.01,\n",
-    "                    before_measure_flip_probability = 0.01,\n",
-    "                    before_round_data_depolarization = 0.00,\n",
-    "                    correct_ancilla = False,\n",
-    "                    correct_data=True,\n",
-    "                    p_ge = 0.02) "
-   ]
   }
  ],
  "metadata": {
-- 
GitLab