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  {
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   "id": "f903ab3a",
   "metadata": {},
   "source": [
    "# Time of flight measurement\n",
    "The notebook will show how to measure time of flight for your system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f95bfb6b",
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   "source": [
    "from __future__ import annotations\n",
    "\n",
    "import json\n",
    "\n",
    "import numpy as np\n",
    "import rich  # noqa:F401\n",
    "from qcodes.instrument import find_or_create_instrument\n",
    "from qcodes.parameters import ManualParameter\n",
    "\n",
    "import quantify_core.data.handling as dh\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "from quantify_core.analysis.time_of_flight_analysis import TimeOfFlightAnalysis\n",
    "from quantify_core.measurement.control import MeasurementControl\n",
    "from quantify_core.visualization.pyqt_plotmon import PlotMonitor_pyqt as PlotMonitor\n",
    "from quantify_scheduler import Schedule\n",
    "from quantify_scheduler.backends.qblox import constants\n",
    "from quantify_scheduler.device_under_test.quantum_device import QuantumDevice\n",
    "from quantify_scheduler.gettables import ScheduleGettable\n",
    "from quantify_scheduler.instrument_coordinator import InstrumentCoordinator\n",
    "from quantify_scheduler.instrument_coordinator.components.qblox import (\n",
    "    ClusterComponent,\n",
    ")\n",
    "from quantify_scheduler.math import closest_number_ceil\n",
    "from quantify_scheduler.operations.gate_library import Measure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b4a17a0",
   "metadata": {},
   "source": [
    "## Setup\n",
    "In this section we configure the hardware configuration which specifies the connectivity of our system.\n",
    "\n",
    "The experiments of this tutorial are meant to be executed with a Qblox Cluster controlling a transmon system.\n",
    "The experiments can also be executed using a dummy Qblox device that is created via an instance of the `Cluster` class, and is initialized with a dummy configuration.\n",
    "When using a dummy device, the analysis will not work because the experiments will return `np.nan` values.\n",
    "\n",
    "### Configuration file\n",
    "\n",
    "This is a template hardware configuration file for a 2-qubit system with a flux-control line which can be used to tune the qubit frequency. We will only work with qubit 0.\n",
    "\n",
    "The hardware setup is as follows, by cluster slot:\n",
    "- **QCM** (Slot 2)\n",
    "  - Flux line for `q0`.\n",
    "- **QCM-RF** (Slot 6)\n",
    "  - Drive line for `q0` using fixed 80 MHz IF.\n",
    "- **QRM-RF** (Slot 8)\n",
    "  - Readout line for `q0` using a fixed LO set at 7.5 GHz.\n",
    "\n",
    "Note that in the hardware configuration below the mixers are uncorrected, but for high fidelity experiments this should also be done for all the modules."
   ]
  },
  {
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   "execution_count": 2,
   "id": "5dee92e8",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data will be saved in:\n",
      "/root/quantify-data\n"
     ]
    }
   ],
   "source": [
    "with open(\"configs/tuning_transmon_coupled_pair_hardware_config.json\") as hw_cfg_json_file:\n",
    "    hardware_cfg = json.load(hw_cfg_json_file)\n",
    "\n",
    "# Enter your own dataset directory here!\n",
    "dh.set_datadir(dh.default_datadir())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b2a9aa5",
   "metadata": {},
   "source": [
    "### Scan For Clusters\n",
    "\n",
    "We scan for the available devices connected via ethernet using the Plug & Play functionality of the Qblox Instruments package (see [Plug & Play](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/api_reference/tools.html#api-pnp) for more info)."
   ]
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   "id": "649397d5",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No devices found\r\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "851f7469",
   "metadata": {
    "execution": {
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   "source": [
    "cluster_ip = None  # To run this tutorial on hardware, fill in the IP address of the cluster here\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f64ae81a",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "03aee47c",
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   "source": [
    "cluster = find_or_create_instrument(\n",
    "    Cluster,\n",
    "    recreate=True,\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg=(\n",
    "        {\n",
    "            2: ClusterType.CLUSTER_QCM,\n",
    "            4: ClusterType.CLUSTER_QRM,\n",
    "            6: ClusterType.CLUSTER_QCM_RF,\n",
    "            8: ClusterType.CLUSTER_QRM_RF,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6524430c",
   "metadata": {},
   "source": [
    "### Quantum device settings\n",
    "Here we initialize our `QuantumDevice` and our qubit parameters,  checkout this [tutorial](https://quantify-os.org/docs/quantify-scheduler/tutorials/Operations%20and%20Qubits.html) for further details.\n",
    "\n",
    "In short, a `QuantumDevice` contains device elements where we save our found parameters. Here we are loading a template for 2 qubits, but we will only use qubit 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1083fcf6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:49.149732Z",
     "iopub.status.busy": "2024-09-02T01:45:49.149510Z",
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     "shell.execute_reply": "2024-09-02T01:45:49.160434Z"
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   },
   "outputs": [],
   "source": [
    "quantum_device = QuantumDevice.from_json_file(\"devices/transmon_device_2q.json\")\n",
    "qubit = quantum_device.get_element(\"q0\")\n",
    "quantum_device.hardware_config(hardware_cfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05183721",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "### Configure measurement control loop\n",
    "We will use a `MeasurementControl` object for data acquisition as well as an `InstrumentCoordinator` for controlling the instruments in our setup.\n",
    "\n",
    "The `PlotMonitor` is used for live plotting.\n",
    "\n",
    "All of these are then associated with the `QuantumDevice`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fd2ea276",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:49.163571Z",
     "iopub.status.busy": "2024-09-02T01:45:49.163296Z",
     "iopub.status.idle": "2024-09-02T01:45:49.170514Z",
     "shell.execute_reply": "2024-09-02T01:45:49.169870Z"
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   "outputs": [],
   "source": [
    "def configure_measurement_control_loop(\n",
    "    device: QuantumDevice, cluster: Cluster, live_plotting: bool = False\n",
    ") -> tuple[MeasurementControl, InstrumentCoordinator]:\n",
    "    meas_ctrl = find_or_create_instrument(MeasurementControl, recreate=True, name=\"meas_ctrl\")\n",
    "    ic = find_or_create_instrument(InstrumentCoordinator, recreate=True, name=\"ic\")\n",
    "\n",
    "    # Add cluster to instrument coordinator\n",
    "    ic_cluster = ClusterComponent(cluster)\n",
    "    ic.add_component(ic_cluster)\n",
    "\n",
    "    if live_plotting:\n",
    "        # Associate plot monitor with measurement controller\n",
    "        plotmon = find_or_create_instrument(PlotMonitor, recreate=False, name=\"PlotMonitor\")\n",
    "        meas_ctrl.instr_plotmon(plotmon.name)\n",
    "\n",
    "    # Associate measurement controller and instrument coordinator with the quantum device\n",
    "    device.instr_measurement_control(meas_ctrl.name)\n",
    "    device.instr_instrument_coordinator(ic.name)\n",
    "\n",
    "    return (meas_ctrl, ic)\n",
    "\n",
    "\n",
    "meas_ctrl, instrument_coordinator = configure_measurement_control_loop(quantum_device, cluster)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c651eb20",
   "metadata": {
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   },
   "source": [
    "## Schedule definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1c157695",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:49.172840Z",
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     "shell.execute_reply": "2024-09-02T01:45:49.175443Z"
    }
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   "source": [
    "def tof_trace_schedule(\n",
    "    qubit_name: str,\n",
    "    repetitions: int = 1,\n",
    ") -> Schedule:\n",
    "    schedule = Schedule(\"Trace measurement schedule\", repetitions=repetitions)\n",
    "    schedule.add(Measure(qubit_name, acq_protocol=\"Trace\"))\n",
    "    return schedule"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c391237e",
   "metadata": {
    "lines_to_next_cell": 0
   },
   "source": [
    "## Measuring time of flight with trace acquisition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "29bcb8ab",
   "metadata": {
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   "source": [
    "def set_readout_attenuation_hardware_config(attenuation_dB: int):\n",
    "    hwcfg = quantum_device.hardware_config()\n",
    "    output_att = hwcfg[\"hardware_options\"][\"output_att\"]\n",
    "    output_att[f\"{qubit.ports.readout()}-{qubit.name}.ro\"] = attenuation_dB\n",
    "    quantum_device.hardware_config(hwcfg)\n",
    "\n",
    "\n",
    "set_readout_attenuation_hardware_config(0)\n",
    "qubit.measure.pulse_duration(300e-9)\n",
    "qubit.measure.integration_time(1e-6)\n",
    "qubit.measure.pulse_amp(0.1)\n",
    "qubit.measure.acq_delay(4e-9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "905493e0",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-09-02T01:45:49.187888Z"
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   "outputs": [],
   "source": [
    "tof_t = ManualParameter(name=\"tof_t\", unit=\"ns\", label=\"Trace acquisition sample\")\n",
    "tof_t.batched = True\n",
    "tof_t.batch_size = round(qubit.measure.integration_time() * constants.SAMPLING_RATE)\n",
    "\n",
    "tof_sched_kwargs = dict(\n",
    "    qubit_name=qubit.name,\n",
    ")\n",
    "\n",
    "# set gettable\n",
    "gettable = ScheduleGettable(\n",
    "    quantum_device,\n",
    "    schedule_function=tof_trace_schedule,\n",
    "    schedule_kwargs=tof_sched_kwargs,\n",
    "    real_imag=False,\n",
    "    batched=True,\n",
    ")\n",
    "\n",
    "# set measurement control\n",
    "meas_ctrl.gettables(gettable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "12ca8055",
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    "execution": {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting batched measurement...\n",
      "Iterative settable(s) [outer loop(s)]:\n",
      "\t --- (None) --- \n",
      "Batched settable(s):\n",
      "\t tof_t \n",
      "Batch size limit: 1000\n",
      "\n"
     ]
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       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 24kB\n",
       "Dimensions:  (x0: 1000)\n",
       "Coordinates:\n",
       "  * x0       (x0) int64 8kB 0 1 2 3 4 5 6 7 ... 992 993 994 995 996 997 998 999\n",
       "Data variables:\n",
       "    y0       (x0) float64 8kB 0.0004166 -0.002275 ... -0.0004985 -0.0005552\n",
       "    y1       (x0) float64 8kB 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    tuid:                             20240902-014549-194-f0e128\n",
       "    name:                             Time of flight measurement q0\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  False</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b5fd1070-e5e1-4526-b104-ca0cea7ec10f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b5fd1070-e5e1-4526-b104-ca0cea7ec10f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x0</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-687d9d89-0a3f-464e-a885-9d3def1853fb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-687d9d89-0a3f-464e-a885-9d3def1853fb' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x0</span></div><div class='xr-var-dims'>(x0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-fc0e7a2b-e66a-4c00-9417-44188010ca05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc0e7a2b-e66a-4c00-9417-44188010ca05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4becf20c-9806-406c-90b5-83277d6f4c1a' class='xr-var-data-in' type='checkbox'><label for='data-4becf20c-9806-406c-90b5-83277d6f4c1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>tof_t</dd><dt><span>long_name :</span></dt><dd>Trace acquisition sample</dd><dt><span>units :</span></dt><dd>ns</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1000</dd></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-adc33a06-2901-4e4e-bf8d-155c332faaf8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-adc33a06-2901-4e4e-bf8d-155c332faaf8' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(x0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0004166 -0.002275 ... -0.0005552</div><input id='attrs-ff3b7126-c903-48c5-9627-54b185a4d178' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff3b7126-c903-48c5-9627-54b185a4d178' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88a41317-aa38-4603-84a6-e23b3ab874e5' class='xr-var-data-in' type='checkbox'><label for='data-88a41317-aa38-4603-84a6-e23b3ab874e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>magn</dd><dt><span>long_name :</span></dt><dd>Magnitude0</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([ 4.16623685e-04, -2.27487186e-03,  9.98954628e-04, -2.16237977e-04,\n",
       "       -7.19596738e-04, -4.26260542e-04, -1.76973986e-04,  9.50041586e-04,\n",
       "        9.27261833e-04, -1.23039520e-03,  9.56268157e-04,  9.46196188e-04,\n",
       "        1.04665507e-03, -1.83766816e-03,  4.02330024e-04, -7.87575806e-04,\n",
       "        1.97448477e-04,  7.89257783e-04, -8.33453595e-05, -1.67551615e-03,\n",
       "        2.90312389e-04,  7.25238297e-05,  4.54709782e-04,  3.78040099e-04,\n",
       "        1.54624368e-03,  6.86596024e-04,  4.89552391e-04, -7.58584366e-04,\n",
       "        1.49422397e-04, -6.79711254e-04,  1.10570078e-03,  9.56121161e-04,\n",
       "       -3.79462487e-04,  1.78508291e-03, -3.78555580e-05, -7.94351733e-05,\n",
       "       -5.27918870e-04,  9.04405602e-05,  1.84706075e-04, -2.50021539e-04,\n",
       "       -1.27775084e-03,  2.90231085e-04, -1.13316755e-03, -7.88050765e-04,\n",
       "       -1.58231059e-05,  1.57663804e-03, -4.51593336e-06,  4.42574300e-04,\n",
       "        3.11139939e-04, -1.34014860e-03, -7.81620255e-04, -3.00657685e-04,\n",
       "        1.69994715e-03,  4.29423984e-04, -1.88240125e-03, -4.33973284e-04,\n",
       "       -1.21720019e-05,  6.28979506e-04, -6.35896735e-04,  3.35593148e-04,\n",
       "        1.25728762e-03,  8.87943126e-04,  1.39941698e-03,  4.34766024e-04,\n",
       "        7.42466344e-04,  4.96936425e-04,  1.90320019e-03,  8.68722199e-04,\n",
       "        5.11117988e-04, -7.65309027e-04, -1.39815408e-03,  4.63210021e-04,\n",
       "        3.15249196e-05, -2.05857264e-03,  1.57694331e-03, -6.34677698e-04,\n",
       "        7.10493922e-04,  8.83613918e-06, -2.28209320e-03,  8.23369711e-04,\n",
       "...\n",
       "       -6.78742370e-04,  4.63228148e-04, -8.91718482e-04, -2.98875861e-04,\n",
       "       -1.44409882e-03, -9.29660372e-04, -2.39486154e-05, -1.73015377e-03,\n",
       "       -6.69930558e-04, -8.62411988e-04,  6.51931765e-04,  1.26194793e-03,\n",
       "        1.34499463e-04, -6.92608888e-04,  4.21483679e-04,  9.50848530e-05,\n",
       "       -1.22417535e-03,  1.63540385e-03,  1.49678918e-03,  6.66841203e-04,\n",
       "       -1.57708375e-03, -8.39350742e-05,  7.22422553e-04, -8.45480615e-04,\n",
       "        5.07204279e-04, -1.24832882e-03,  6.15588166e-05, -5.19892217e-04,\n",
       "        2.84672783e-04,  3.69024528e-06, -4.52235765e-04,  1.36173770e-04,\n",
       "        6.19085874e-04,  2.21247464e-03, -2.36303675e-04,  1.92034989e-03,\n",
       "       -3.92452114e-04,  1.97531623e-04, -4.93699812e-04, -2.11216380e-04,\n",
       "       -7.88235170e-04, -3.94259322e-04, -2.88833726e-05, -6.72421352e-04,\n",
       "        7.21932701e-04,  1.07531881e-03,  9.76212421e-04, -7.75557691e-04,\n",
       "       -4.18054375e-04, -1.37812425e-03,  3.36801549e-04,  1.13111380e-03,\n",
       "       -7.19061255e-04, -6.83776103e-04, -1.36682621e-03,  1.85897157e-03,\n",
       "       -1.01510572e-03, -2.67383290e-04,  1.02306791e-03,  3.49023948e-04,\n",
       "       -1.66527681e-03, -4.63554909e-04, -1.25504847e-03, -7.10580864e-04,\n",
       "       -2.08910779e-03,  3.76647608e-04, -2.43755278e-04,  5.33896494e-04,\n",
       "        8.54434487e-04,  2.98085985e-04,  1.33570775e-03,  2.06702967e-03,\n",
       "        1.08048380e-03,  2.40607494e-03, -8.80581542e-04, -1.18062399e-03,\n",
       "       -3.26505020e-04,  4.27640859e-04, -4.98493111e-04, -5.55160931e-04])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y1</span></div><div class='xr-var-dims'>(x0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ea46105e-15e4-4626-9d80-1f5f04732013' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea46105e-15e4-4626-9d80-1f5f04732013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecdc79c8-6b8b-4732-ace8-196f6cf9c59f' class='xr-var-data-in' type='checkbox'><label for='data-ecdc79c8-6b8b-4732-ace8-196f6cf9c59f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>phase</dd><dt><span>long_name :</span></dt><dd>Phase0</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "...\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa77d927-0297-438e-bd27-2e509387a186' class='xr-section-summary-in' type='checkbox'  ><label for='section-fa77d927-0297-438e-bd27-2e509387a186' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c5741cca-2ce5-430f-9969-2f70e21fd14f' class='xr-index-data-in' type='checkbox'/><label for='index-c5741cca-2ce5-430f-9969-2f70e21fd14f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "       ...\n",
       "       990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;x0&#x27;, length=1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-53996928-3f32-4346-ae39-86aaaac8dc34' class='xr-section-summary-in' type='checkbox'  checked><label for='section-53996928-3f32-4346-ae39-86aaaac8dc34' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>tuid :</span></dt><dd>20240902-014549-194-f0e128</dd><dt><span>name :</span></dt><dd>Time of flight measurement q0</dd><dt><span>grid_2d :</span></dt><dd>False</dd><dt><span>grid_2d_uniformly_spaced :</span></dt><dd>False</dd><dt><span>1d_2_settables_uniformly_spaced :</span></dt><dd>False</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 24kB\n",
       "Dimensions:  (x0: 1000)\n",
       "Coordinates:\n",
       "  * x0       (x0) int64 8kB 0 1 2 3 4 5 6 7 ... 992 993 994 995 996 997 998 999\n",
       "Data variables:\n",
       "    y0       (x0) float64 8kB 0.0004166 -0.002275 ... -0.0004985 -0.0005552\n",
       "    y1       (x0) float64 8kB 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    tuid:                             20240902-014549-194-f0e128\n",
       "    name:                             Time of flight measurement q0\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  False"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tof_t_setpoints = np.arange(tof_t.batch_size)\n",
    "\n",
    "meas_ctrl.settables(tof_t)\n",
    "meas_ctrl.setpoints(tof_t_setpoints)\n",
    "\n",
    "# replace the get method for the gettable in case the cluster is a dummy\n",
    "if \"dummy\" in str(cluster._transport):\n",
    "\n",
    "    def get_fake_tof_data():\n",
    "        \"\"\"Generate mock data for a time of flight measurement.\"\"\"\n",
    "        y = (\n",
    "            np.heaviside(tof_t_setpoints - 200, 0.5)\n",
    "            - np.heaviside(tof_t_setpoints - tof_t_setpoints.size * 0.7, 0.5)\n",
    "        ) * 30e-3\n",
    "        y += np.random.normal(loc=0.0, scale=1e-3, size=y.size)\n",
    "        return [y, np.zeros_like(y)]\n",
    "\n",
    "    gettable.get = get_fake_tof_data\n",
    "\n",
    "tof_ds = dh.to_gridded_dataset(meas_ctrl.run(\"Time of flight measurement \" + qubit.name))\n",
    "tof_ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51f5dec8",
   "metadata": {
    "lines_to_next_cell": 0
   },
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1427b344",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:49.360665Z",
     "iopub.status.busy": "2024-09-02T01:45:49.360347Z",
     "iopub.status.idle": "2024-09-02T01:45:50.164661Z",
     "shell.execute_reply": "2024-09-02T01:45:50.163962Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tof_analysis = TimeOfFlightAnalysis(tuid=dh.get_latest_tuid())\n",
    "tof_analysis.run(playback_delay=149e-9).display_figs_mpl()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "380b8534",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:50.167058Z",
     "iopub.status.busy": "2024-09-02T01:45:50.166854Z",
     "iopub.status.idle": "2024-09-02T01:45:50.170626Z",
     "shell.execute_reply": "2024-09-02T01:45:50.169960Z"
    }
   },
   "outputs": [],
   "source": [
    "fit_results = tof_analysis.quantities_of_interest\n",
    "nco_prop_delay = fit_results[\"nco_prop_delay\"]\n",
    "measured_tof = fit_results[\"tof\"]\n",
    "\n",
    "qubit.measure.acq_delay(\n",
    "    closest_number_ceil(\n",
    "        measured_tof * constants.SAMPLING_RATE, constants.MIN_TIME_BETWEEN_OPERATIONS\n",
    "    )\n",
    "    / constants.SAMPLING_RATE\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ea5e4596",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:50.172805Z",
     "iopub.status.busy": "2024-09-02T01:45:50.172618Z",
     "iopub.status.idle": "2024-09-02T01:45:50.291919Z",
     "shell.execute_reply": "2024-09-02T01:45:50.291232Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'config_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig'</span>,\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'hardware_description'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "        <span style=\"color: #008000; text-decoration-color: #008000\">'cluster0'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'instrument_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Cluster'</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'modules'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'6'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'instrument_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'QCM_RF'</span><span style=\"font-weight: bold\">}</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'instrument_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'QCM'</span><span style=\"font-weight: bold\">}</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'8'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'instrument_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'QRM_RF'</span><span style=\"font-weight: bold\">}</span>\n",
       "            <span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'sequence_to_file'</span>: <span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'ref'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'internal'</span>\n",
       "        <span style=\"font-weight: bold\">}</span>\n",
       "    <span style=\"font-weight: bold\">}</span>,\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'hardware_options'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "        <span style=\"color: #008000; text-decoration-color: #008000\">'output_att'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'q0:mw-q0.01'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q1:mw-q1.01'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q0:res-q0.ro'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q1:res-q1.ro'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">60</span><span style=\"font-weight: bold\">}</span>,\n",
       "        <span style=\"color: #008000; text-decoration-color: #008000\">'mixer_corrections'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q0:mw-q0.01'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_lo_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_lo_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_sideband_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_i'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_q'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'amp_ratio'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'phase_error'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>\n",
       "            <span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q1:mw-q1.01'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_lo_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_lo_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_sideband_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_i'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_q'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'amp_ratio'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'phase_error'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>\n",
       "            <span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q0:res-q0.ro'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_lo_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_lo_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_sideband_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_i'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_q'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'amp_ratio'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'phase_error'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>\n",
       "            <span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q1:res-q1.ro'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_lo_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_lo_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'auto_sideband_cal'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'on_interm_freq_change'</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_i'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'dc_offset_q'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'amp_ratio'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>,\n",
       "                <span style=\"color: #008000; text-decoration-color: #008000\">'phase_error'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>\n",
       "            <span style=\"font-weight: bold\">}</span>\n",
       "        <span style=\"font-weight: bold\">}</span>,\n",
       "        <span style=\"color: #008000; text-decoration-color: #008000\">'modulation_frequencies'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q0:mw-q0.01'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'interm_freq'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80000000.0</span><span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q1:mw-q1.01'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'interm_freq'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">80000000.0</span><span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q0:res-q0.ro'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'lo_freq'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7500000000.0</span><span style=\"font-weight: bold\">}</span>,\n",
       "            <span style=\"color: #008000; text-decoration-color: #008000\">'q1:res-q1.ro'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'lo_freq'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7500000000.0</span><span style=\"font-weight: bold\">}</span>\n",
       "        <span style=\"font-weight: bold\">}</span>\n",
       "    <span style=\"font-weight: bold\">}</span>,\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'connectivity'</span>: <span style=\"font-weight: bold\">{</span>\n",
       "        <span style=\"color: #008000; text-decoration-color: #008000\">'graph'</span>: <span style=\"font-weight: bold\">[</span>\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module6.complex_output_0'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q0:mw'</span><span style=\"font-weight: bold\">]</span>,\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module6.complex_output_1'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q1:mw'</span><span style=\"font-weight: bold\">]</span>,\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module2.real_output_0'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q0:fl'</span><span style=\"font-weight: bold\">]</span>,\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module2.real_output_1'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q1:fl'</span><span style=\"font-weight: bold\">]</span>,\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module8.complex_output_0'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q0:res'</span><span style=\"font-weight: bold\">]</span>,\n",
       "            <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'cluster0.module8.complex_output_0'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'q1:res'</span><span style=\"font-weight: bold\">]</span>\n",
       "        <span style=\"font-weight: bold\">]</span>\n",
       "    <span style=\"font-weight: bold\">}</span>\n",
       "<span style=\"font-weight: bold\">}</span>\n",
       "</pre>\n"
      ],
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       "\u001b[1m{\u001b[0m\n",
       "    \u001b[32m'config_type'\u001b[0m: \u001b[32m'quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig'\u001b[0m,\n",
       "    \u001b[32m'hardware_description'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "        \u001b[32m'cluster0'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "            \u001b[32m'instrument_type'\u001b[0m: \u001b[32m'Cluster'\u001b[0m,\n",
       "            \u001b[32m'modules'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "                \u001b[32m'6'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'instrument_type'\u001b[0m: \u001b[32m'QCM_RF'\u001b[0m\u001b[1m}\u001b[0m,\n",
       "                \u001b[32m'2'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'instrument_type'\u001b[0m: \u001b[32m'QCM'\u001b[0m\u001b[1m}\u001b[0m,\n",
       "                \u001b[32m'8'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'instrument_type'\u001b[0m: \u001b[32m'QRM_RF'\u001b[0m\u001b[1m}\u001b[0m\n",
       "            \u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'sequence_to_file'\u001b[0m: \u001b[3;91mFalse\u001b[0m,\n",
       "            \u001b[32m'ref'\u001b[0m: \u001b[32m'internal'\u001b[0m\n",
       "        \u001b[1m}\u001b[0m\n",
       "    \u001b[1m}\u001b[0m,\n",
       "    \u001b[32m'hardware_options'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "        \u001b[32m'output_att'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'q0:mw-q0.01'\u001b[0m: \u001b[1;36m10\u001b[0m, \u001b[32m'q1:mw-q1.01'\u001b[0m: \u001b[1;36m10\u001b[0m, \u001b[32m'q0:res-q0.ro'\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[32m'q1:res-q1.ro'\u001b[0m: \u001b[1;36m60\u001b[0m\u001b[1m}\u001b[0m,\n",
       "        \u001b[32m'mixer_corrections'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "            \u001b[32m'q0:mw-q0.01'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "                \u001b[32m'auto_lo_cal'\u001b[0m: \u001b[32m'on_lo_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'auto_sideband_cal'\u001b[0m: \u001b[32m'on_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'dc_offset_i'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'dc_offset_q'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'amp_ratio'\u001b[0m: \u001b[1;36m1.0\u001b[0m,\n",
       "                \u001b[32m'phase_error'\u001b[0m: \u001b[1;36m0.0\u001b[0m\n",
       "            \u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q1:mw-q1.01'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "                \u001b[32m'auto_lo_cal'\u001b[0m: \u001b[32m'on_lo_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'auto_sideband_cal'\u001b[0m: \u001b[32m'on_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'dc_offset_i'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'dc_offset_q'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'amp_ratio'\u001b[0m: \u001b[1;36m1.0\u001b[0m,\n",
       "                \u001b[32m'phase_error'\u001b[0m: \u001b[1;36m0.0\u001b[0m\n",
       "            \u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q0:res-q0.ro'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "                \u001b[32m'auto_lo_cal'\u001b[0m: \u001b[32m'on_lo_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'auto_sideband_cal'\u001b[0m: \u001b[32m'on_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'dc_offset_i'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'dc_offset_q'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'amp_ratio'\u001b[0m: \u001b[1;36m1.0\u001b[0m,\n",
       "                \u001b[32m'phase_error'\u001b[0m: \u001b[1;36m0.0\u001b[0m\n",
       "            \u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q1:res-q1.ro'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "                \u001b[32m'auto_lo_cal'\u001b[0m: \u001b[32m'on_lo_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'auto_sideband_cal'\u001b[0m: \u001b[32m'on_interm_freq_change'\u001b[0m,\n",
       "                \u001b[32m'dc_offset_i'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'dc_offset_q'\u001b[0m: \u001b[1;36m0.0\u001b[0m,\n",
       "                \u001b[32m'amp_ratio'\u001b[0m: \u001b[1;36m1.0\u001b[0m,\n",
       "                \u001b[32m'phase_error'\u001b[0m: \u001b[1;36m0.0\u001b[0m\n",
       "            \u001b[1m}\u001b[0m\n",
       "        \u001b[1m}\u001b[0m,\n",
       "        \u001b[32m'modulation_frequencies'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "            \u001b[32m'q0:mw-q0.01'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'interm_freq'\u001b[0m: \u001b[1;36m80000000.0\u001b[0m\u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q1:mw-q1.01'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'interm_freq'\u001b[0m: \u001b[1;36m80000000.0\u001b[0m\u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q0:res-q0.ro'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'lo_freq'\u001b[0m: \u001b[1;36m7500000000.0\u001b[0m\u001b[1m}\u001b[0m,\n",
       "            \u001b[32m'q1:res-q1.ro'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'lo_freq'\u001b[0m: \u001b[1;36m7500000000.0\u001b[0m\u001b[1m}\u001b[0m\n",
       "        \u001b[1m}\u001b[0m\n",
       "    \u001b[1m}\u001b[0m,\n",
       "    \u001b[32m'connectivity'\u001b[0m: \u001b[1m{\u001b[0m\n",
       "        \u001b[32m'graph'\u001b[0m: \u001b[1m[\u001b[0m\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module6.complex_output_0'\u001b[0m, \u001b[32m'q0:mw'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module6.complex_output_1'\u001b[0m, \u001b[32m'q1:mw'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module2.real_output_0'\u001b[0m, \u001b[32m'q0:fl'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module2.real_output_1'\u001b[0m, \u001b[32m'q1:fl'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module8.complex_output_0'\u001b[0m, \u001b[32m'q0:res'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "            \u001b[1m[\u001b[0m\u001b[32m'cluster0.module8.complex_output_0'\u001b[0m, \u001b[32m'q1:res'\u001b[0m\u001b[1m]\u001b[0m\n",
       "        \u001b[1m]\u001b[0m\n",
       "    \u001b[1m}\u001b[0m\n",
       "\u001b[1m}\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "rich.print(quantum_device.hardware_config())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5c43164d",
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    "execution": {
     "iopub.execute_input": "2024-09-02T01:45:50.294381Z",
     "iopub.status.busy": "2024-09-02T01:45:50.294189Z",
     "iopub.status.idle": "2024-09-02T01:45:50.299976Z",
     "shell.execute_reply": "2024-09-02T01:45:50.299380Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'devices/device_2q_2024-09-02_01-45-50_UTC.json'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quantum_device.to_json_file(\"devices/\")"
   ]
  }
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