{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "f5b2beb9", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:42.013344Z", "iopub.status.busy": "2025-10-02T01:24:42.013163Z", "iopub.status.idle": "2025-10-02T01:24:42.016364Z", "shell.execute_reply": "2025-10-02T01:24:42.015849Z" }, "nbsphinx": "hidden" }, "outputs": [], "source": [ "# Copyright 2025 Keysight Technologies Inc." ] }, { "cell_type": "raw", "id": "ab478469", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Sweeping program variables\n", "==========================\n", "\n", "The :doc:`hello_hardware` tutorial covers the basic workflow for running experiments\n", "on hardware and extracting trace data and I/Q data. Here we expand on that and add\n", "sweeps to the programs.\n", "\n", "Setting up\n", "----------\n", "\n", "As before, we use two AWG channels and two digitizers." ] }, { "cell_type": "code", "execution_count": 2, "id": "c9471562", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:42.018178Z", "iopub.status.busy": "2025-10-02T01:24:42.018013Z", "iopub.status.idle": "2025-10-02T01:24:45.128322Z", "shell.execute_reply": "2025-10-02T01:24:45.127700Z" }, "lines_to_next_cell": 2 }, "outputs": [], "source": [ "import keysight.qcs as qcs\n", "import numpy as np\n", "\n", "# set the following to True when connected to hardware:\n", "run_on_hw = False\n", "\n", "# instantiate channels representing two AWGs and two digitizers\n", "awgs = qcs.Channels(range(2), \"readoutawg\")\n", "digs = qcs.Channels(range(2), \"readoutreceiver\")\n", "\n", "# load our channel mapper to connect the virtual channels above to physical ones\n", "mapper = qcs.load(\"../../assets/channel_mapper.qcs\")" ] }, { "cell_type": "raw", "id": "83290248", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Single variable sweeps\n", "----------------------\n", "\n", "We define a program that plays a single RF waveform on our AWG channels and performs\n", "an acquisition on the digitizer channels with an\n", ":py:class:`~keysight.qcs.channels.acquisitions.IntegrationFilter`\\ to perform I/Q\n", "demodulation of the trace data.\n", "\n", "We are sweeping the frequency of the RF pulse but keep the frequency of the\n", "integration filter constant." ] }, { "cell_type": "code", "execution_count": 3, "id": "30843312", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:45.130920Z", "iopub.status.busy": "2025-10-02T01:24:45.130554Z", "iopub.status.idle": "2025-10-02T01:24:45.271627Z", "shell.execute_reply": "2025-10-02T01:24:45.271065Z" }, "lines_to_next_cell": 2 }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", "
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Alternatively, we can retrieve them through the ``repetitions``\n", "attribute:" ] }, { "cell_type": "code", "execution_count": 4, "id": "98abee22", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:45.273445Z", "iopub.status.busy": "2025-10-02T01:24:45.273262Z", "iopub.status.idle": "2025-10-02T01:24:45.276982Z", "shell.execute_reply": "2025-10-02T01:24:45.276492Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[Sweep(rf=Array(name=frequencies, shape=(5,), dtype=float, unit=none)), Repeat(10)]\n" ] } ], "source": [ "print(program.repetitions.items)" ] }, { "cell_type": "raw", "id": "d427645b", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Next, we execute the program on hardware." ] }, { "cell_type": "code", "execution_count": 5, "id": "67da2e96", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:45.278596Z", "iopub.status.busy": "2025-10-02T01:24:45.278437Z", "iopub.status.idle": "2025-10-02T01:24:45.415012Z", "shell.execute_reply": "2025-10-02T01:24:45.414423Z" } }, "outputs": [], "source": [ "if run_on_hw:\n", " # initialize the backend pass\n", " backend = qcs.HclBackend(channel_mapper=mapper)\n", " # the executor returns the program populated with results\n", " program = qcs.Executor(backend).execute(program)\n", " # (optional) export the data to an HDF5 file\n", " program.to_hdf5(\"program2.hdf5\")\n", "\n", "# we are loading a previously run program here for this example\n", "program = qcs.load(\"program2.hdf5\")" ] }, { "cell_type": "raw", "id": "42c5d239", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "The results will now consist of five traces for each sweep point and for each channel." ] }, { "cell_type": "code", "execution_count": 6, "id": "b02ea859", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:45.417366Z", "iopub.status.busy": "2025-10-02T01:24:45.417187Z", "iopub.status.idle": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "program.plot_trace()" ] }, { "cell_type": "raw", "id": "f7ec0f43", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "We can retrieve the I/Q data by calling the\n", ":py:meth:`~keysight.qcs.programs.Program.get_iq_pandas` method, which\n", "returns a dataframe that has the sweep values in its column header." ] }, { "cell_type": "code", "execution_count": 7, "id": "2edbcbaa", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:47.423971Z", "iopub.status.busy": "2025-10-02T01:24:47.423610Z", "iopub.status.idle": "2025-10-02T01:24:47.762169Z", "shell.execute_reply": "2025-10-02T01:24:47.761193Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " (rf, 4.05 GHz) \\\n", " 0 1 \n", "(((readoutreceiver_0))) 0.002351-0.002617j 0.001562-0.003162j \n", "(((readoutreceiver_1))) -0.003926-0.002629j -0.002427-0.001740j \n", "(((readoutreceiver_2))) 0.004186-0.001393j 0.004653-0.001658j \n", "(((readoutreceiver_3))) 0.003129+0.001425j 0.003441+0.001442j \n", "\n", " \\\n", " 2 3 \n", "(((readoutreceiver_0))) 0.001999-0.003444j 0.002334-0.002812j \n", "(((readoutreceiver_1))) -0.002129-0.000508j -0.003600-0.001572j \n", "(((readoutreceiver_2))) 0.004354-0.000896j 0.004046-0.001135j \n", "(((readoutreceiver_3))) 0.002865+0.002030j 0.003196+0.001574j \n", "\n", " \\\n", " 4 5 \n", "(((readoutreceiver_0))) 0.001619-0.003178j 0.001974-0.003325j \n", "(((readoutreceiver_1))) -0.002188-0.001321j -0.001880-0.000612j \n", "(((readoutreceiver_2))) 0.004784-0.001412j 0.004066-0.000832j \n", "(((readoutreceiver_3))) 0.003758+0.001457j 0.003232+0.002031j \n", "\n", " \\\n", " 6 7 \n", "(((readoutreceiver_0))) 0.002244-0.002614j 0.001584-0.003135j \n", "(((readoutreceiver_1))) -0.004357-0.002121j -0.002159-0.002206j \n", "(((readoutreceiver_2))) 0.003935-0.001297j 0.004887-0.001311j \n", "(((readoutreceiver_3))) 0.002919+0.001560j 0.003477+0.001332j \n", "\n", " ... \\\n", " 8 9 ... \n", "(((readoutreceiver_0))) 0.001894-0.003386j 0.002325-0.002754j ... \n", "(((readoutreceiver_1))) -0.002250-0.000615j -0.004123-0.002111j ... \n", "(((readoutreceiver_2))) 0.004025-0.000916j 0.004254-0.001515j ... \n", "(((readoutreceiver_3))) 0.002991+0.002071j 0.003148+0.001320j ... \n", "\n", " (rf, 4.25 GHz) \\\n", " 0 1 \n", "(((readoutreceiver_0))) -0.000353-0.000242j -0.000056+0.000357j \n", "(((readoutreceiver_1))) 0.000047-0.000634j -0.000227+0.000729j \n", "(((readoutreceiver_2))) 0.000401-0.000258j -0.000200-0.000369j \n", "(((readoutreceiver_3))) -0.000067+0.000023j -0.000269-0.000081j \n", "\n", " \\\n", " 2 3 \n", "(((readoutreceiver_0))) 0.000290-0.000252j -0.000126-0.000030j \n", "(((readoutreceiver_1))) 0.000404+0.000285j -0.000619-0.000269j \n", "(((readoutreceiver_2))) -0.000081+0.000279j 0.000265-0.000322j \n", "(((readoutreceiver_3))) -0.000009+0.000215j 0.000104+0.000032j \n", "\n", " \\\n", " 4 5 \n", "(((readoutreceiver_0))) 0.000081+0.000200j 0.000281-0.000253j \n", "(((readoutreceiver_1))) -0.000079+0.000723j 0.000246+0.000136j \n", "(((readoutreceiver_2))) -0.000437-0.000284j -0.000292+0.000412j \n", "(((readoutreceiver_3))) -0.000207+0.000012j 0.000041+0.000437j \n", "\n", " \\\n", " 6 7 \n", "(((readoutreceiver_0))) -0.000226-0.000165j 0.000205+0.000234j \n", "(((readoutreceiver_1))) -0.000124-0.000674j -0.000112+0.000165j \n", "(((readoutreceiver_2))) 0.000202-0.000232j -0.000108-0.000409j \n", "(((readoutreceiver_3))) 0.000226-0.000166j -0.000123-0.000006j \n", "\n", " \n", " 8 9 \n", "(((readoutreceiver_0))) 0.000370-0.000073j -0.000272-0.000114j \n", "(((readoutreceiver_1))) 0.000463-0.000247j -0.000024-0.000089j \n", "(((readoutreceiver_2))) 0.000152+0.000226j 0.000329-0.000201j \n", "(((readoutreceiver_3))) 0.000186+0.000372j 0.000137-0.000029j \n", "\n", "[4 rows x 50 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "program.get_iq_pandas(stack_channels=True)" ] }, { "cell_type": "raw", "id": "d8d61480", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "We can extract data for a sweep and repeat using the following" ] }, { "cell_type": "code", "execution_count": 8, "id": "51d20926", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:47.764171Z", "iopub.status.busy": "2025-10-02T01:24:47.763987Z", "iopub.status.idle": "2025-10-02T01:24:47.796903Z", "shell.execute_reply": "2025-10-02T01:24:47.796063Z" }, "lines_to_next_cell": 0 }, "outputs": [ { "data": { "text/plain": [ "(0.0023512427568418183-0.0026169676054433096j)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = program.get_iq_pandas(stack_channels=True)\n", "channel0_rf_4_05_data = df[\"(rf, 4.05 GHz)\"][\"0\"][digs[0]]\n", "channel0_rf_4_05_data" ] }, { "cell_type": "raw", "id": "0fafad35", "metadata": { "lines_to_next_cell": 0, "raw_mimetype": "text/restructuredtext" }, "source": [ "This is the data for channel (labels=[0], name=readoutreceiver), 4.05 GHz frequency\n", "and 0th repeat.\n", "\n", "Also, using the results class we can get the data directly as a numpy array:" ] }, { "cell_type": "code", "execution_count": 9, "id": "d225f200", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:47.799763Z", "iopub.status.busy": "2025-10-02T01:24:47.799531Z", "iopub.status.idle": "2025-10-02T01:24:47.814448Z", "shell.execute_reply": "2025-10-02T01:24:47.813806Z" } }, "outputs": [ { "data": { "text/plain": [ "array([[ 2.35124276e-03-2.61696761e-03j, 1.56245443e-03-3.16220147e-03j,\n", " 1.99869235e-03-3.44414807e-03j, 2.33420904e-03-2.81241797e-03j,\n", " 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-1.11222287e-02-1.06291578e-03j, 6.35371604e-03-9.03682141e-03j,\n", " 4.56529070e-03+1.01961803e-02j, -1.09632058e-02-1.02351663e-03j,\n", " 6.24255967e-03-9.00895436e-03j, 4.78976786e-03+1.02531960e-02j,\n", " -1.10242711e-02-1.02314139e-03j, 6.49037177e-03-8.99366121e-03j],\n", " [-3.52554585e-04-2.42393203e-04j, -5.56220660e-05+3.56588658e-04j,\n", " 2.89539537e-04-2.52136938e-04j, -1.25781980e-04-2.96531565e-05j,\n", " 8.11054827e-05+2.00224330e-04j, 2.81490092e-04-2.52850340e-04j,\n", " -2.25801394e-04-1.64635471e-04j, 2.04950458e-04+2.34214862e-04j,\n", " 3.69634580e-04-7.28241968e-05j, -2.71968595e-04-1.13773288e-04j]])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "program.results.get_iq()[digs[0]]" ] }, { "cell_type": "raw", "id": "be2c4149", "metadata": { "lines_to_next_cell": 0, "raw_mimetype": "text/restructuredtext" }, "source": [ "We can extract data for a sweep, repeat, acquisition using the following:\n" ] }, { 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       "Coordinates:\n",
       "  * channel  (channel) <U17 272B 'readoutreceiver_0' ... 'readoutreceiver_3'\n",
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "program.plot_iq(channel_subplots=False)" ] }, { "cell_type": "raw", "id": "3d249192", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "In typical applications, we typically have larger sweep ranges and storing all the\n", "trace data and performing the I/Q demodulation in software adds timing overhead.\n", "Instead, we can perform the demodulation on hardware, and only I/Q data will be\n", "stored." ] }, { "cell_type": "code", "execution_count": 17, "id": "3b781062", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:48.262376Z", "iopub.status.busy": "2025-10-02T01:24:48.262096Z", "iopub.status.idle": "2025-10-02T01:24:48.756874Z", "shell.execute_reply": "2025-10-02T01:24:48.755912Z" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "(%{x}, %{y})", "legendgroup": "readoutreceiver, 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"domain": [ 0.26875, 0.4625 ], "title": { "text": "rf" } }, "yaxis4": { "anchor": "x4", "domain": [ 0.0, 0.19375 ], "title": { "text": "rf" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "program.plot_classified(avg=True, plot_type=\"2d\")" ] }, { "cell_type": "raw", "id": "cb44a04e", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ " .. note::\n", "\n", " It is possible to perform variable sweeps both on hardware and software. To\n", " enable hardware sweeping, the program's\n", " :py:meth:`~keysight.qcs.programs.Program.sweep` method needs to be called before\n", " the :py:meth:`~keysight.qcs.programs.Program.n_shots` method. This will execute\n", " both the sweep and the repetitions on hardware. Any other sweeps defined\n", " after those will be performed in software.\n" ] }, { "cell_type": "raw", "id": "3ba23ecd", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Nested sweeps\n", "-------------\n", "Sweeps can be nested by calling the :py:meth:`~keysight.qcs.programs.Program.sweep`\n", "method multiple times. For example, we can sweep the frequency and amplitude in our\n", "program from above:" ] }, { "cell_type": "code", "execution_count": 24, "id": "a2b2d5ec", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:49.474806Z", "iopub.status.busy": "2025-10-02T01:24:49.474567Z", "iopub.status.idle": "2025-10-02T01:24:49.481440Z", "shell.execute_reply": "2025-10-02T01:24:49.480787Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[Sweep(amp=Array(name=amplitude, shape=(5,), dtype=float, unit=none)), Sweep(rf=Array(name=frequencies, shape=(5,), dtype=float, unit=none)), Repeat(10)]\n" ] } ], "source": [ "program = make_program()\n", "\n", "# specify the frequency values to be swept over\n", "frequencies = qcs.Array(\n", " \"frequencies\", value=[4.05e9, 4.1e9, 4.15e9, 4.2e9, 4.25e9], dtype=float\n", ")\n", "\n", "# specify the amplitude values to be swept over\n", "amplitudes = qcs.Array(\"amplitude\", value=[0.2, 0.4, 0.6, 0.8, 1], dtype=float)\n", "\n", "program.sweep(frequencies, frequency)\n", "program.sweep(amplitudes, amplitude)\n", "\n", "print(program.repetitions.items)" ] }, { "cell_type": "raw", "id": "b5da8aff", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "We execute this program as before and load in the results:" ] }, { "cell_type": "code", "execution_count": 25, "id": "18b0bae6", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:49.483938Z", "iopub.status.busy": "2025-10-02T01:24:49.483707Z", "iopub.status.idle": "2025-10-02T01:24:49.691633Z", "shell.execute_reply": "2025-10-02T01:24:49.690868Z" } }, "outputs": [ { "data": { "text/html": [ "
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When plotting the I/Q data, we can easily switch between sweep axes by\n", "specifying the ``plot_axis`` argument. The default, ``plot_axis=0`` will plot\n", "the data over the first sweep (zeroth index of the dataframe columns). Note that\n", "this can also be used to plot the I/Q data as a function of shots, when the method\n", "is called with ``avg=False``\\." ] }, { "cell_type": "code", "execution_count": 26, "id": "751046b2", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:49.693626Z", "iopub.status.busy": "2025-10-02T01:24:49.693449Z", "iopub.status.idle": "2025-10-02T01:24:49.878776Z", "shell.execute_reply": "2025-10-02T01:24:49.877945Z" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "(rf, 4.05 GHz): (%{x}, %{y})", "legendgroup": "readoutreceiver, labels: (0,)", "legendgrouptitle": { "text": "readoutreceiver, labels: (0,)" }, "marker": { "color": "#ff005c", "symbol": "circle" }, "mode": "markers", "name": "I/Q for (amp, 0.2)", "showlegend": true, "type": "scatter", "x": [ 5.431267643879143e-05 ], "xaxis": "x", "y": [ -2.42512742032763e-05 ], "yaxis": "y" }, { "hovertemplate": "(rf, 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot over frequency for each amplitude\n", "program.plot_iq(channel_subplots=False, plot_axis=1)" ] }, { "cell_type": "raw", "id": "5182a333", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Simultaneous sweeps\n", "-------------------\n", "\n", "Sweeps can also be performed simultaneously by passing the sweep values and targets\n", "as lists:" ] }, { "cell_type": "code", "execution_count": 28, "id": "a36720af", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:50.086672Z", "iopub.status.busy": "2025-10-02T01:24:50.086465Z", "iopub.status.idle": "2025-10-02T01:24:50.107646Z", "shell.execute_reply": "2025-10-02T01:24:50.106648Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", "
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot the results\n", "program.plot_iq(channel_subplots=False)" ] }, { "cell_type": "raw", "id": "a9403847", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Hardware Sweeps\n", "---------------\n", "\n", "So far, all examples shown were constructed as a Software sweep.\n", "This means that after each point in the sweep, the hardware stops and waits for the\n", "software to compile the next steps and load all the information into the FPGAs.\n", "For large sweeps or for nested sweeps, this can be a slow process.\n", "\n", "Hardware Sweep provides a way to preload every step of the sweep into the hardware,\n", "so it can execute the whole sweep without interruptions.\n", "\n", "To enable this, we only need to change the order of the sweeps: The repetitions\n", "(:py:meth:`~keysight.qcs.programs.Program.n_shots`) needs to be placed after the\n", "sweeps like in the example below." ] }, { "cell_type": "code", "execution_count": 31, "id": "a6c81cd2", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:50.264643Z", "iopub.status.busy": "2025-10-02T01:24:50.264407Z", "iopub.status.idle": "2025-10-02T01:24:50.290233Z", "shell.execute_reply": "2025-10-02T01:24:50.289605Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", "
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\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": { "text/html": { "isolated": true } }, "output_type": "display_data" } ], "source": [ "frequency = qcs.Scalar(\"rf\", dtype=float)\n", "\n", "\"\"\"Creates a simple program with a single RF waveform\"\"\"\n", "program = qcs.Program()\n", "# define the waveform using this frequency variable & add it to the program\n", "gauss = qcs.RFWaveform(80e-9, qcs.GaussianEnvelope(num_sigma=4), 1, frequency)\n", "program.add_waveform(gauss, awgs)\n", "\n", "# define an integration filter using the same RF waveform but with fixed frequency\n", "int_filter = qcs.RFWaveform(80e-9, qcs.GaussianEnvelope(num_sigma=4), 1, 4.15e9)\n", "program.add_acquisition(int_filter, digs)\n", "\n", "# specify the frequency values to be swept over\n", "frequencies = qcs.Array(\n", " \"frequencies\", value=[4.05e9, 4.1e9, 4.15e9, 4.2e9, 4.25e9], dtype=float\n", ")\n", "\n", "# add the sweep, targeting the `frequency` variable\n", "program.sweep(frequencies, frequency)\n", "\n", "# specify the number of shots\n", "program.n_shots(10)\n", "\n", "program.draw()" ] }, { "cell_type": "raw", "id": "c6d8bd91", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "This constructs the program to have the sweep of frequencies as the inner-loop, and\n", "then the repeat (i.e. ``n_shots``) as the outer loop. Both the sweep and the repeat\n", "are executed as a hardware loop, so the entire program is executed without\n", "interruption.\n", "\n", "It is possible to perform multi-dimensional sweeps. More than one sweep can be\n", "executed as a software sweep or a hardware sweep.\n", "\n", "The innermost :py:class:`~keysight.qcs.programs.Repeat` on a program's\n", "repetition structure serves as the boundary between hardware and software sweeps.\n", "To check which operations will be performed in hardware-time, the ``repetitions``\n", "property of the program can be inspected" ] }, { "cell_type": "code", "execution_count": 32, "id": "241286c5", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:50.292933Z", "iopub.status.busy": "2025-10-02T01:24:50.292741Z", "iopub.status.idle": "2025-10-02T01:24:50.298485Z", "shell.execute_reply": "2025-10-02T01:24:50.297952Z" } }, "outputs": [ { "data": { "text/plain": [ "[Repeat(10),\n", " Sweep(rf=Array(name=frequencies, shape=(5,), dtype=float, unit=none))]" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "program.repetitions.hw_items" ] }, { "cell_type": "raw", "id": "56935484", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ "Limitations\n", "-----------\n", "Sweepable parameters\n", "~~~~~~~~~~~~~~~~~~~~\n", "\n", ".. list-table:: Sweepable Parameters\n", " :widths: 15 25 25 25\n", " :header-rows: 1\n", "\n", " * - Instrument\n", " - Operation\n", " - Software sweep variables\n", " - Hardware sweep variables\n", " * - M5300AWG and M5301AWG\n", " - :py:class:`~keysight.qcs.channels.RFWaveform`\n", " - Support for sweeping ``amplitude``, ``frequency``,\n", " ``instantaneous_phase``, ``post_phase``, and ``duration``\n", " - Support for sweeping ``amplitude``, ``frequency``,\n", " ``instantaneous_phase``, and ``post_phase``\n", " The ``duration`` variable is only supported for\n", " the hold duration on flat-top waveforms.\n", " * - M5300AWG and M5301AWG\n", " - :py:class:`~keysight.qcs.channels.DCWaveform`\n", " - Support for sweeping ``amplitude`` and ``duration``\n", " - Support for sweeping ``amplitude``.\n", " The ``duration`` variable is only supported for the\n", " hold duration on flat-top waveforms\n", " * - M5200Digitizer\n", " - :py:class:`~keysight.qcs.channels.Acquisition`\n", " - Support for sweeping all waveform variables on the\n", " Acquisition's :py:class:`~keysight.qcs.channels.IntegrationFilter`.\n", " Support for sweeping the Acquisition's\n", " :py:class:`~keysight.qcs.channels.Classifier` reference points.\n", " Support for changing the acquisition duration is not supported\n", " when ``fpga_postprocessing==False``\n", " - Support for sweeping ``amplitude`` and ``frequency`` of the\n", " Acquisition's :py:class:`~keysight.qcs.channels.IntegrationFilter`.\n", " * - M5300AWG, M5301AWG, and M5200Digitizer\n", " - :py:class:`~keysight.qcs.channels.Delay`\n", " - Support for sweeping ``duration``\n", " - Support for sweeping ``duration``\n", " * - M5300AWG\n", " - :py:class:`~keysight.qcs.channels.RFAWGChannelSettings`\n", " - Support for sweeping ``delay`` and ``lo_frequency``\n", " - No support\n", " * - M5301AWG\n", " - :py:class:`~keysight.qcs.channels.BasebandAWGChannelSettings`\n", " - Support for sweeping ``delay`` and ``offset``\n", " - No support\n", " * - M5200AWG\n", " - :py:class:`~keysight.qcs.channels.DigitizerChannelSettings`\n", " - Support for sweeping ``delay`` and ``range``\n", " - No support\n", " * - M5201AWG\n", " - :py:class:`~keysight.qcs.channels.DownconverterChannelSettings`\n", " - Support for sweeping ``lo_frequency``\n", " - No support\n", "\n", "\n", ".. list-table:: Other limitations per sweep type\n", " :widths: 15 25 25\n", " :header-rows: 1\n", "\n", " * - Limitation\n", " - Software sweep mode\n", " - Hardware sweep mode\n", " * - Supported channel settings\n", " - Both ``absolute_phase=True`` and ``absolute_phase=False``\n", " - Most parameters can only be swept on channels where ``absolute_phase=False``.\n", " The only exceptions are :py:class:`~keysight.qcs.channels.Delay` duration,\n", " ``amplitude``, and ``frequency``,\n", " which can be swept regardless of the channel's absolute phase setting.\n", " * - Demodulation mode\n", " - Both ``fpga_postprocessing=False`` and ``fpga_postprocessing=True``\n", " - Only ``fpga_postprocessing=True``\n", " * - Maximum number of parameter swept on a single waveform.\n", " - No limit\n", " - Three parameters\n", " * - Maximum number of nested sweeping dimensions.\n", " - No limit\n", " - Eight dimensions\n", " * - Sweep length limitation\n", " - No limit\n", " - The sum of all sweep lengths must be less than 24,576 points\n", " (more details below)\n", " * - Minimum value for a delay duration sweep\n", " - 0 ns\n", " - 13.333 ns\n" ] }, { "cell_type": "raw", "id": "ae736794", "metadata": { "raw_mimetype": "text/restructuredtext" }, "source": [ " .. note::\n", "\n", " Sweeping parameters of a :py:class:`~keysight.qcs.channels.IntegrationFilter`\n", " is currently incompatible with\n", " :py:class:`~keysight.qcs.programs.ConditionalOperation` and qubit reset.\n" ] }, { "cell_type": "raw", "id": "7dc78753", "metadata": { "lines_to_next_cell": 2, "raw_mimetype": "text/restructuredtext" }, "source": [ " .. note::\n", "\n", " Sweeping parameters of a :py:class:`~keysight.qcs.channels.IntegrationFilter` is\n", " currently incompatible with invoking\n", " :py:meth:`~keysight.qcs.programs.Program.get_classified_pandas`\n", " or :py:meth:`~keysight.qcs.programs.Program.get_classified_array`\n", " for classified state retrieval. Users may still manually classify data from\n", " demodulated IQ traces, but cannot use the `get_classified()` methods in\n", " this context.\n", "\n", "\n", "Hardware sweep size limitations\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", "\n", "\n", "During compilation, each swept variable is translated into a separate array\n", "stored in FPGA memory. Each instrument channel supports up to eight FPGA arrays.\n", "All eight arrays share the same memory space that can hold 24,576 sweep points.\n", "\n", "When designing an experiment, it can be complicated to determine if all the sweeps\n", "fit inside the hardware due to multiple optimization steps.\n", "This section will go over some common scenarios. This won't be an exhaustive list.\n", "\n", "**Example 1: Simple 1D sweep**\n", "\n", "In the following example, ``amplitude`` will use one FPGA array that contains\n", "10,000 data points.\n", "The total number of points is 10,000 which is less than the 24,576 maximum." ] }, { "cell_type": "code", "execution_count": 33, "id": "330a7e35", "metadata": { "execution": { "iopub.execute_input": "2025-10-02T01:24:50.300849Z", "iopub.status.busy": "2025-10-02T01:24:50.300592Z", "iopub.status.idle": "2025-10-02T01:24:50.320573Z", "shell.execute_reply": "2025-10-02T01:24:50.320076Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", "
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DurationScalar(name=_implicit, value=80 ns, dtype=float, unit=s)
AmplitudeScalar(name=amp1, value=None, dtype=float, unit=none)
Frequency4 GHz
EnvelopeGaussianEnvelope(4.0)
Instantaneous Phase0 rad
Post-phase0 rad
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\n", " RFWaveform on ('readoutawg', 1)\n", "
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DurationScalar(name=_implicit, value=80 ns, dtype=float, unit=s)
AmplitudeScalar(name=amp2, value=None, dtype=float, unit=none)
Frequency4 GHz
EnvelopeGaussianEnvelope(4.0)
Instantaneous Phase0 rad
Post-phase0 rad
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\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": { "text/html": { "isolated": true } }, "output_type": "display_data" }, { "data": { "text/plain": [ "Program([Layer([RFWaveform(duration=Scalar(name=_implicit, value=8e-08, dtype=float, unit=s), envelope={GaussianEnvelope(4.0): Scalar(name=amp1, value=None, dtype=float, unit=none)}, rf_frequency=Scalar(name=_implicit, value=4000000000.0, dtype=float, unit=Hz), instantaneous_phase={GaussianEnvelope(4.0): Scalar(name=_implicit, value=0.0, dtype=float, unit=rad)}, post_phase=Scalar(name=_implicit, value=0.0, dtype=float, unit=rad)), RFWaveform(duration=Scalar(name=_implicit, value=8e-08, dtype=float, unit=s), envelope={GaussianEnvelope(4.0): Scalar(name=amp2, value=None, dtype=float, unit=none)}, rf_frequency=Scalar(name=_implicit, value=4000000000.0, dtype=float, unit=Hz), instantaneous_phase={GaussianEnvelope(4.0): Scalar(name=_implicit, value=0.0, dtype=float, unit=rad)}, post_phase=Scalar(name=_implicit, value=0.0, dtype=float, unit=rad))])])" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "amplitude1 = qcs.Scalar(\"amp1\", dtype=float)\n", "amplitude2 = qcs.Scalar(\"amp2\", dtype=float)\n", "\n", "program = qcs.Program()\n", "\n", "# define the waveform using this frequency variable & add it to the program\n", "gauss1 = qcs.RFWaveform(80e-9, qcs.GaussianEnvelope(num_sigma=4), amplitude1, 4e9)\n", "gauss2 = qcs.RFWaveform(80e-9, qcs.GaussianEnvelope(num_sigma=4), amplitude2, 4e9)\n", "program.add_waveform(gauss1, awgs)\n", "program.add_waveform(gauss2, awgs)\n", "\n", "# define the values for the sweep\n", "amplitudes1 = qcs.Array(\"amplitudes1\", value=np.linspace(0.1, 0.2, 10000), dtype=float)\n", "amplitudes2 = qcs.Array(\"amplitudes2\", value=np.linspace(0.3, 0.4, 10000), dtype=float)\n", "\n", "# sweep the program\n", "program.sweep([amplitudes1, amplitudes2], [amplitude1, amplitude2])\n", "program.n_shots(10)" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "raw_mimetype,nbsphinx,-all", "main_language": "python", "notebook_metadata_filter": "-all", "text_representation": { "extension": ".py", "format_name": "percent" } }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 5 }