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  {
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   "metadata": {},
   "source": [
    "# Time of flight measurement\n",
    "The notebook will show how to measure time of flight for your system."
   ]
  },
  {
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   "execution_count": 1,
   "id": "60195c03",
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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": "05f96e35",
   "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": "e105d514",
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    "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": "814050b8",
   "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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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No devices found\r\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9aad5056",
   "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": "406dcd59",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
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   "execution_count": 5,
   "id": "0fc4700d",
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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": "0078aa35",
   "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": "802994ec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:10.416415Z",
     "iopub.status.busy": "2024-09-18T14:59:10.416211Z",
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     "shell.execute_reply": "2024-09-18T14:59:10.427203Z"
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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": "909ae524",
   "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": "02016f12",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:10.429860Z",
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   "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": "4fae8db4",
   "metadata": {
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   },
   "source": [
    "## Schedule definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "20a9e71c",
   "metadata": {
    "execution": {
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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": "b335aebf",
   "metadata": {
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   },
   "source": [
    "## Measuring time of flight with trace acquisition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ed9d9e1",
   "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": "8957b861",
   "metadata": {
    "execution": {
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   "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)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 11,
   "id": "4b873568",
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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 9.913e-07 0.0007135 ... 0.0001498 -0.0003165\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:                             20240918-145910-459-4d893a\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-424626b9-8136-485d-be20-6b8a6636931e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-424626b9-8136-485d-be20-6b8a6636931e' 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-2bd7d446-092e-4787-b746-d8e7d0079590' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2bd7d446-092e-4787-b746-d8e7d0079590' 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-68a8c187-3cf7-4f18-9911-a2f9bbeabf0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68a8c187-3cf7-4f18-9911-a2f9bbeabf0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bad2eef-88e4-4fb7-80e4-eb652d30967f' class='xr-var-data-in' type='checkbox'><label for='data-4bad2eef-88e4-4fb7-80e4-eb652d30967f' 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-c6598197-53fd-4a2b-bb0c-a7f2b3d93ba4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c6598197-53fd-4a2b-bb0c-a7f2b3d93ba4' 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'>9.913e-07 0.0007135 ... -0.0003165</div><input id='attrs-0f38f77a-5a44-4cdf-8b4e-8fcf37bb6276' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f38f77a-5a44-4cdf-8b4e-8fcf37bb6276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddcb028b-491e-4040-a9cc-13c64e92999f' class='xr-var-data-in' type='checkbox'><label for='data-ddcb028b-491e-4040-a9cc-13c64e92999f' 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([ 9.91295590e-07,  7.13548960e-04, -4.20967113e-04, -2.60688098e-03,\n",
       "        4.76518199e-04, -2.38535698e-04, -7.98802267e-04, -2.03240482e-03,\n",
       "        5.25509519e-04, -1.19774739e-04, -8.66893953e-04,  5.29692060e-04,\n",
       "        1.66051664e-03, -1.85339000e-03, -5.79047403e-05,  1.15107257e-03,\n",
       "        5.21535589e-04, -8.73838214e-04, -1.43798586e-03, -8.70610213e-05,\n",
       "       -4.40981384e-05,  2.18692023e-04,  7.70455470e-04,  1.16594135e-03,\n",
       "        1.48453435e-03,  5.89139830e-04,  1.24603526e-04,  1.28075835e-04,\n",
       "       -1.29312675e-03, -2.13838749e-04,  9.71683846e-04,  7.55565285e-04,\n",
       "       -2.27148859e-04, -2.14634564e-04,  7.67458235e-05, -5.33957633e-04,\n",
       "       -8.47470784e-04,  5.04279130e-05,  1.17250736e-03,  5.57241697e-05,\n",
       "        1.48216203e-04, -1.06450649e-03,  7.57126133e-04,  1.28340486e-04,\n",
       "        6.39169870e-04, -3.72696079e-04,  2.19906733e-03,  7.87510423e-04,\n",
       "        5.57338325e-04, -1.26448895e-03,  1.90106368e-04,  1.45365349e-04,\n",
       "       -8.98252166e-04, -1.68194314e-04,  1.96726844e-04, -1.20371000e-03,\n",
       "        2.15703411e-04, -9.27740451e-04, -1.29070621e-03,  4.27253499e-04,\n",
       "        1.16205136e-04,  9.22116527e-04, -9.13731406e-04, -6.70358117e-04,\n",
       "        9.23450716e-04,  7.84204527e-04,  1.29227262e-03,  3.87782529e-04,\n",
       "       -1.13647023e-03,  1.35768422e-03,  2.67464554e-04, -1.27600931e-03,\n",
       "       -4.15287124e-04, -2.69156600e-04,  1.01540711e-03, -7.48905731e-04,\n",
       "       -8.98306410e-04,  8.90535048e-04,  7.17748209e-04,  1.43899576e-03,\n",
       "...\n",
       "        1.32273988e-04,  7.88462584e-04, -1.65593338e-03,  7.76066172e-04,\n",
       "       -1.10080307e-03,  5.08001171e-05, -7.40248385e-04,  9.62980967e-04,\n",
       "        4.24379022e-04, -1.02480340e-03,  1.21012650e-04,  1.96810329e-04,\n",
       "       -7.69442024e-05,  7.00089425e-04, -2.63297705e-04,  1.83409762e-03,\n",
       "        1.00940393e-03,  4.29581129e-04, -8.78328000e-05, -1.52199541e-03,\n",
       "       -1.23388230e-03,  3.14625494e-04,  1.07779921e-03,  6.60670074e-04,\n",
       "        4.34271510e-04, -3.01930971e-04, -1.53218659e-03, -8.35238517e-04,\n",
       "       -3.32692477e-04, -4.40032606e-04,  1.69578334e-03, -5.18112211e-05,\n",
       "        5.16554260e-04, -2.76576842e-04, -7.00954999e-04,  8.88761895e-04,\n",
       "        1.35579817e-03,  2.06242229e-03,  2.68046736e-04, -2.00339049e-03,\n",
       "       -6.09362623e-04, -2.74478425e-04, -1.83462520e-04,  2.42727351e-03,\n",
       "       -7.60319756e-04, -1.40388911e-03,  4.46989386e-04,  1.27934101e-03,\n",
       "       -3.92834176e-04, -1.21116415e-03, -4.22229992e-04, -9.07942753e-04,\n",
       "        1.65753329e-03, -5.14716038e-04, -1.37333871e-03, -1.09558604e-04,\n",
       "       -1.19113752e-03,  4.41856590e-04, -4.27024436e-05, -1.22956021e-03,\n",
       "        2.17496628e-04,  5.69270301e-04, -1.46471886e-03, -2.32811889e-04,\n",
       "       -9.05366652e-04, -1.85184964e-03,  2.70210812e-05, -1.65914537e-05,\n",
       "        2.09097210e-03, -5.25105793e-04,  1.30049618e-03,  7.04043854e-05,\n",
       "       -3.07797346e-04, -8.57924399e-04,  8.81510962e-04,  2.67035463e-04,\n",
       "       -5.70897268e-04,  5.29421991e-04,  1.49767185e-04, -3.16462108e-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-54ccf15b-0644-4ea6-a22d-0e390965615c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54ccf15b-0644-4ea6-a22d-0e390965615c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0bfacef-55de-4136-b719-44de596c0baf' class='xr-var-data-in' type='checkbox'><label for='data-b0bfacef-55de-4136-b719-44de596c0baf' 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-2c372b89-f69d-487c-b3d0-0358a0e0da84' class='xr-section-summary-in' type='checkbox'  ><label for='section-2c372b89-f69d-487c-b3d0-0358a0e0da84' 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-d8a5a57a-7889-4075-8f9d-06ccf24530de' class='xr-index-data-in' type='checkbox'/><label for='index-d8a5a57a-7889-4075-8f9d-06ccf24530de' 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-97d2c9d1-501f-424f-ae5c-86356732d02e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-97d2c9d1-501f-424f-ae5c-86356732d02e' 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>20240918-145910-459-4d893a</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 9.913e-07 0.0007135 ... 0.0001498 -0.0003165\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:                             20240918-145910-459-4d893a\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": "e67be781",
   "metadata": {
    "lines_to_next_cell": 0
   },
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "db31909d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:10.626522Z",
     "iopub.status.busy": "2024-09-18T14:59:10.626207Z",
     "iopub.status.idle": "2024-09-18T14:59:11.411022Z",
     "shell.execute_reply": "2024-09-18T14:59:11.410288Z"
    }
   },
   "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": "5c8d4af4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:11.413052Z",
     "iopub.status.busy": "2024-09-18T14:59:11.412848Z",
     "iopub.status.idle": "2024-09-18T14:59:11.416741Z",
     "shell.execute_reply": "2024-09-18T14:59:11.416029Z"
    }
   },
   "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": "a79feaae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:11.418444Z",
     "iopub.status.busy": "2024-09-18T14:59:11.418255Z",
     "iopub.status.idle": "2024-09-18T14:59:11.535987Z",
     "shell.execute_reply": "2024-09-18T14:59:11.535364Z"
    }
   },
   "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"
      ],
      "text/plain": [
       "\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": "beddf08a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-18T14:59:11.537779Z",
     "iopub.status.busy": "2024-09-18T14:59:11.537607Z",
     "iopub.status.idle": "2024-09-18T14:59:11.543209Z",
     "shell.execute_reply": "2024-09-18T14:59:11.542584Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'devices/device_2q_2024-09-18_14-59-11_UTC.json'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quantum_device.to_json_file(\"devices/\")"
   ]
  }
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