{ "cells": [ { "cell_type": "markdown", "id": "d3fcd466", "metadata": {}, "source": [ "# Time of flight measurement\n", "Here show how to measure time of flight for your system.\n", "This is useful to calibrate the acquisition delay for subsequent experiments." ] }, { "cell_type": "code", "execution_count": 1, "id": "6ea2f6fc", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:22.639388Z", "iopub.status.busy": "2024-11-13T02:35:22.639086Z", "iopub.status.idle": "2024-11-13T02:35:24.275507Z", "shell.execute_reply": "2024-11-13T02:35:24.274675Z" }, "tags": [ "imports" ] }, "outputs": [], "source": [ "import json\n", "\n", "import numpy as np\n", "import rich # noqa:F401\n", "from qcodes.parameters import ManualParameter\n", "\n", "import quantify_core.data.handling as dh\n", "from quantify_core.analysis.time_of_flight_analysis import TimeOfFlightAnalysis\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.math import closest_number_ceil\n", "from quantify_scheduler.operations.gate_library import Measure\n", "\n", "from utils import initialize_hardware, run # noqa:F401" ] }, { "cell_type": "code", "execution_count": 2, "id": "c402b131", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.278533Z", "iopub.status.busy": "2024-11-13T02:35:24.277809Z", "iopub.status.idle": "2024-11-13T02:35:24.281695Z", "shell.execute_reply": "2024-11-13T02:35:24.281052Z" }, "tags": [ "config", "header_1" ] }, "outputs": [], "source": [ "hw_config_path = \"configs/tuning_spin_coupled_pair_hardware_config.json\"\n", "device_path = \"devices/spin_device_2q.json\"" ] }, { "cell_type": "code", "execution_count": 3, "id": "a08a8921", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.283540Z", "iopub.status.busy": "2024-11-13T02:35:24.283377Z", "iopub.status.idle": "2024-11-13T02:35:24.287630Z", "shell.execute_reply": "2024-11-13T02:35:24.286991Z" }, "tags": [ "header_2" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Data will be saved in:\n", "/root/quantify-data\n" ] } ], "source": [ "with open(hw_config_path) 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": "code", "execution_count": 4, "id": "1c9c006f", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.289429Z", "iopub.status.busy": "2024-11-13T02:35:24.289264Z", "iopub.status.idle": "2024-11-13T02:35:24.873342Z", "shell.execute_reply": "2024-11-13T02:35:24.872512Z" }, "tags": [ "header_3" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/builds/qblox/packages/software/qblox_instruments_docs/.venv/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1220: ValidationWarning: Setting `auto_lo_cal=on_lo_interm_freq_change` will overwrite settings `dc_offset_i=0.0` and `dc_offset_q=0.0`. To suppress this warning, do not set either `dc_offset_i` or `dc_offset_q` for this port-clock.\n", " warnings.warn(\n", "/builds/qblox/packages/software/qblox_instruments_docs/.venv/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1235: ValidationWarning: Setting `auto_sideband_cal=on_interm_freq_change` will overwrite settings `amp_ratio=1.0` and `phase_error=0.0`. To suppress this warning, do not set either `amp_ratio` or `phase_error` for this port-clock.\n", " warnings.warn(\n" ] } ], "source": [ "quantum_device = QuantumDevice.from_json_file(device_path)\n", "qubit = quantum_device.get_element(\"q0\")\n", "quantum_device.hardware_config(hardware_cfg)\n", "meas_ctrl, _, cluster = initialize_hardware(quantum_device, ip=None)" ] }, { "cell_type": "markdown", "id": "ed5476fc", "metadata": { "tags": [ "no_demo" ] }, "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 connectivity is as follows, by cluster slot:\n", "\n", "- **QCM** (Slot 2)\n", " - $\\text{O}^{1}$: Flux line for `q0`.\n", " - $\\text{O}^{2}$: Flux line for `q1`.\n", "\n", "- **QCM-RF** (Slot 6)\n", " - $\\text{O}^{1}$: Drive line for `q0` using fixed 80 MHz IF.\n", " - $\\text{O}^{2}$: Drive line for `q1` using fixed 80 MHz IF.\n", "\n", "- **QRM-RF** (Slot 8)\n", " - $\\text{O}^{1}$ and $\\text{I}^{1}$: Shared readout line for `q0`/`q1` 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." ] }, { "cell_type": "markdown", "id": "83c394bd", "metadata": { "tags": [ "no_demo" ] }, "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": "markdown", "id": "420c1ceb", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Schedule definition" ] }, { "cell_type": "code", "execution_count": 5, "id": "e917f0da", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.876383Z", "iopub.status.busy": "2024-11-13T02:35:24.876100Z", "iopub.status.idle": "2024-11-13T02:35:24.880502Z", "shell.execute_reply": "2024-11-13T02:35:24.879696Z" } }, "outputs": [], "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": "4521aead", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Measuring time of flight with trace acquisition" ] }, { "cell_type": "code", "execution_count": 6, "id": "e6eada52", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.883032Z", "iopub.status.busy": "2024-11-13T02:35:24.882748Z", "iopub.status.idle": "2024-11-13T02:35:24.887855Z", "shell.execute_reply": "2024-11-13T02:35:24.887089Z" }, "lines_to_next_cell": 0 }, "outputs": [], "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": 7, "id": "8e2103a4", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.890333Z", "iopub.status.busy": "2024-11-13T02:35:24.890040Z", "iopub.status.idle": "2024-11-13T02:35:24.895550Z", "shell.execute_reply": "2024-11-13T02:35:24.894739Z" }, "lines_to_next_cell": 0 }, "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": 8, "id": "8dd87d5a", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:24.898177Z", "iopub.status.busy": "2024-11-13T02:35:24.897847Z", "iopub.status.idle": "2024-11-13T02:35:25.070702Z", "shell.execute_reply": "2024-11-13T02:35:25.070027Z" } }, "outputs": [ { "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" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ca44221fc0004ca1960a35b6ac24f7e6", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Completed: 0%| [ elapsed time: 00:00 | time left: ? ] it" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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       "Dimensions:  (x0: 1000)\n",
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       "    name:                             Time of flight measurement q0\n",
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" ], "text/plain": [ " 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 0.001239 -0.00163 ... 0.0002749 -0.0004191\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: 20241113-023524-902-de490d\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": 8, "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": "166c415b", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Analysis" ] }, { "cell_type": "code", "execution_count": 9, "id": "4b7cac04", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:25.072765Z", "iopub.status.busy": "2024-11-13T02:35:25.072464Z", "iopub.status.idle": "2024-11-13T02:35:25.905239Z", "shell.execute_reply": "2024-11-13T02:35:25.904615Z" } }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "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": 10, "id": "3fbf36f6", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:25.907170Z", "iopub.status.busy": "2024-11-13T02:35:25.906993Z", "iopub.status.idle": "2024-11-13T02:35:25.910545Z", "shell.execute_reply": "2024-11-13T02:35:25.909996Z" } }, "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": 11, "id": "7b568b92", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:25.912268Z", "iopub.status.busy": "2024-11-13T02:35:25.912104Z", "iopub.status.idle": "2024-11-13T02:35:25.944139Z", "shell.execute_reply": "2024-11-13T02:35:25.943467Z" }, "tags": [ "no_demo" ] }, "outputs": [ { "data": { "text/html": [ "
{\n",
       "    'config_type': 'quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig',\n",
       "    'hardware_description': {\n",
       "        'cluster0': {\n",
       "            'instrument_type': 'Cluster',\n",
       "            'modules': {\n",
       "                '2': {'instrument_type': 'QCM'},\n",
       "                '4': {'instrument_type': 'QRM'},\n",
       "                '6': {'instrument_type': 'QCM_RF'}\n",
       "            },\n",
       "            'sequence_to_file': False,\n",
       "            'ref': 'internal'\n",
       "        }\n",
       "    },\n",
       "    'hardware_options': {\n",
       "        'output_att': {'q0:mw-q0.f_larmor': 0, 'q1:mw-q1.f_larmor': 0, 'q0:res-q0.ro': 0},\n",
       "        'mixer_corrections': {\n",
       "            'q0:mw-q0.f_larmor': {\n",
       "                'auto_lo_cal': 'on_lo_interm_freq_change',\n",
       "                'auto_sideband_cal': 'on_interm_freq_change',\n",
       "                'dc_offset_i': None,\n",
       "                'dc_offset_q': None,\n",
       "                'amp_ratio': 1.0,\n",
       "                'phase_error': 0.0\n",
       "            },\n",
       "            'q1:mw-q1.f_larmor': {\n",
       "                'auto_lo_cal': 'on_lo_interm_freq_change',\n",
       "                'auto_sideband_cal': 'on_interm_freq_change',\n",
       "                'dc_offset_i': None,\n",
       "                'dc_offset_q': None,\n",
       "                'amp_ratio': 1.0,\n",
       "                'phase_error': 0.0\n",
       "            }\n",
       "        },\n",
       "        'modulation_frequencies': {\n",
       "            'q0:mw-q0.f_larmor': {'interm_freq': 80000000.0},\n",
       "            'q1:mw-q1.f_larmor': {'interm_freq': 70000000.0}\n",
       "        }\n",
       "    },\n",
       "    'connectivity': {\n",
       "        'graph': [\n",
       "            ['cluster0.module2.real_output_0', 'q0:gt'],\n",
       "            ['cluster0.module2.real_output_1', 'q1:gt'],\n",
       "            ['cluster0.module4.real_output_0', 'q0:res'],\n",
       "            ['cluster0.module4.real_output_0', 'q1:res'],\n",
       "            ['cluster0.module6.complex_output_0', 'q0:mw'],\n",
       "            ['cluster0.module6.complex_output_1', 'q1:mw']\n",
       "        ]\n",
       "    }\n",
       "}\n",
       "
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