{ "cells": [ { "cell_type": "markdown", "id": "1535208b", "metadata": {}, "source": [ "# Rabi experiment" ] }, { "cell_type": "markdown", "id": "efe1e14e", "metadata": { "tags": [] }, "source": [ "In this tutorial we will combine the techniques explained in the other tutorials and show how to perform a Rabi experiment. For this tutorial we will need one QCM to generate the Rabi pulses and one QRM to perform the readout, although the QCM could be replaced by another QRM if needed.\n", "\n", "Ports $\\text{O}^{[1-2]}$ of the QCM are used for the driving pulse, while $\\text{O}^{[1-2]}$ of the QRM are used for the readout pulse. Finally, ports $\\text{I}^{[1-2]}$ are used for the acquisition of the readout tone. In this tutorial it is assumed $\\text{O}^{1}$ of the QRM is connected to $\\text{I}^{1}$ of the QRM for time of flight calibration.\n", "Furthermore we assume that $\\text{O}^{1}$ of the QCM and $\\text{O}^{2}$ of the QRM are connected to an external oscilloscope to view the Rabi experiment pattern. The scope can be triggered of marker 1 of the QCM.\n", "\n", "As demonstrated in the synchronization tutorial, the SYNQ technology synchronizes the programs in the two modules." ] }, { "cell_type": "markdown", "id": "634d9679", "metadata": { "tags": [] }, "source": [ "## Setup\n", "\n", "\n", "First, we are going to import the required packages and connect to the instrument." ] }, { "cell_type": "code", "execution_count": 1, "id": "9d99a688", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:28.650995Z", "iopub.status.busy": "2024-03-28T14:27:28.649986Z", "iopub.status.idle": "2024-03-28T14:27:29.922969Z", "shell.execute_reply": "2024-03-28T14:27:29.921945Z" }, "tags": [] }, "outputs": [], "source": [ "\n", "from __future__ import annotations\n", "\n", "import json\n", "from typing import TYPE_CHECKING, Callable\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from qcodes.instrument import find_or_create_instrument\n", "\n", "from qblox_instruments import Cluster, ClusterType\n", "\n", "if TYPE_CHECKING:\n", " from qblox_instruments.qcodes_drivers.module import QcmQrm" ] }, { "cell_type": "markdown", "id": "5da96a75", "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)." ] }, { "cell_type": "code", "execution_count": 2, "id": "e5860567", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:29.929021Z", "iopub.status.busy": "2024-03-28T14:27:29.928018Z", "iopub.status.idle": "2024-03-28T14:27:32.255267Z", "shell.execute_reply": "2024-03-28T14:27:32.253755Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Devices:\n", " - 10.10.200.13 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QSE_1\" and serial number 00015_2321_005\n", " - 10.10.200.42 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"QAE-I\" and serial number 00015_2321_004\n", " - 10.10.200.43 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QAE-2\" and serial number 00015_2206_003\n", " - 10.10.200.50 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2219_003\n", " - 10.10.200.53 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2320_004\n", " - 10.10.200.70 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number 123-456-789\n", " - 10.10.200.80 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number not_valid\n" ] } ], "source": [ "!qblox-pnp list" ] }, { "cell_type": "code", "execution_count": 3, "id": "0fd1a9da", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:32.262267Z", "iopub.status.busy": "2024-03-28T14:27:32.261203Z", "iopub.status.idle": "2024-03-28T14:27:32.270566Z", "shell.execute_reply": "2024-03-28T14:27:32.269190Z" } }, "outputs": [], "source": [ "cluster_ip = \"10.10.200.42\"\n", "cluster_name = \"cluster0\"" ] }, { "cell_type": "markdown", "id": "90732fbb", "metadata": {}, "source": [ "### Connect to Cluster\n", "\n", "We now make a connection with the Cluster." ] }, { "cell_type": "code", "execution_count": 4, "id": "413bc72b", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:32.275942Z", "iopub.status.busy": "2024-03-28T14:27:32.275942Z", "iopub.status.idle": "2024-03-28T14:27:33.451863Z", "shell.execute_reply": "2024-03-28T14:27:33.450338Z" }, "lines_to_next_cell": 2 }, "outputs": [], "source": [ "\n", "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": "0ce48f76", "metadata": { "lines_to_next_cell": 2 }, "source": [ "#### Get connected modules" ] }, { "cell_type": "code", "execution_count": 5, "id": "7723d16f", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.456239Z", "iopub.status.busy": "2024-03-28T14:27:33.456239Z", "iopub.status.idle": "2024-03-28T14:27:33.467223Z", "shell.execute_reply": "2024-03-28T14:27:33.466152Z" } }, "outputs": [], "source": [ "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, QcmQrm]:\n", " def checked_filter_fn(mod: ClusterType) -> bool:\n", " if filter_fn is not None:\n", " return filter_fn(mod)\n", " return True\n", "\n", " return {\n", " mod.slot_idx: mod for mod in cluster.modules if mod.present() and checked_filter_fn(mod)\n", " }" ] }, { "cell_type": "code", "execution_count": 6, "id": "e9e264a8", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.473062Z", "iopub.status.busy": "2024-03-28T14:27:33.472056Z", "iopub.status.idle": "2024-03-28T14:27:33.653232Z", "shell.execute_reply": "2024-03-28T14:27:33.651977Z" } }, "outputs": [ { "data": { "text/plain": [ "{4: }" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# QRM baseband modules\n", "readout_modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)\n", "readout_modules" ] }, { "cell_type": "code", "execution_count": 7, "id": "3624ed1e", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.661624Z", "iopub.status.busy": "2024-03-28T14:27:33.660370Z", "iopub.status.idle": "2024-03-28T14:27:33.668168Z", "shell.execute_reply": "2024-03-28T14:27:33.667169Z" } }, "outputs": [], "source": [ "readout_module = readout_modules[4]" ] }, { "cell_type": "code", "execution_count": 8, "id": "fb08ff71", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.674676Z", "iopub.status.busy": "2024-03-28T14:27:33.673674Z", "iopub.status.idle": "2024-03-28T14:27:33.793127Z", "shell.execute_reply": "2024-03-28T14:27:33.792120Z" } }, "outputs": [ { "data": { "text/plain": [ "{2: }" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# QCM baseband modules\n", "control_modules = get_connected_modules(\n", " cluster, lambda mod: not mod.is_qrm_type and not mod.is_rf_type\n", ")\n", "control_modules" ] }, { "cell_type": "code", "execution_count": 9, "id": "d1d577d0", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.799008Z", "iopub.status.busy": "2024-03-28T14:27:33.799008Z", "iopub.status.idle": "2024-03-28T14:27:33.809183Z", "shell.execute_reply": "2024-03-28T14:27:33.808190Z" } }, "outputs": [], "source": [ "control_module = control_modules[2]" ] }, { "cell_type": "markdown", "id": "3a07f745", "metadata": {}, "source": [ "## Sequencer Setup \n" ] }, { "cell_type": "markdown", "id": "157bf505", "metadata": {}, "source": [ "Set `sync_en` to synchronize across modules." ] }, { "cell_type": "code", "execution_count": 10, "id": "ccb28cda", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.814735Z", "iopub.status.busy": "2024-03-28T14:27:33.813227Z", "iopub.status.idle": "2024-03-28T14:27:33.856109Z", "shell.execute_reply": "2024-03-28T14:27:33.854991Z" } }, "outputs": [], "source": [ "# Set sync_en\n", "readout_module.sequencer0.sync_en(True)\n", "control_module.sequencer0.sync_en(True)" ] }, { "cell_type": "markdown", "id": "349a0a30", "metadata": {}, "source": [ "Configure the `NCO` of both the QRM and QCM to 100 MHz and enable the up- and down-conversion in the sequencers" ] }, { "cell_type": "code", "execution_count": 11, "id": "4ff8ca56", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.861870Z", "iopub.status.busy": "2024-03-28T14:27:33.860857Z", "iopub.status.idle": "2024-03-28T14:27:33.949241Z", "shell.execute_reply": "2024-03-28T14:27:33.948185Z" } }, "outputs": [], "source": [ "readout_module.sequencer0.nco_freq(100e6)\n", "readout_module.sequencer0.mod_en_awg(True)\n", "readout_module.sequencer0.demod_en_acq(True)\n", "\n", "control_module.sequencer0.nco_freq(100e6)\n", "control_module.sequencer0.mod_en_awg(True)" ] }, { "cell_type": "markdown", "id": "78f7ae24", "metadata": {}, "source": [ "Configure the outputs of the QRM and QCM such that sequencer0 is the only enabled sequencer and maps to $\\text{O}^{[1-2]}$" ] }, { "cell_type": "code", "execution_count": 12, "id": "85959e6e", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:33.953999Z", "iopub.status.busy": "2024-03-28T14:27:33.953999Z", "iopub.status.idle": "2024-03-28T14:27:34.087329Z", "shell.execute_reply": "2024-03-28T14:27:34.086331Z" } }, "outputs": [], "source": [ "# Map sequencer of the QCM to specific outputs (but first disable all sequencer connections)\n", "control_module.disconnect_outputs()\n", "\n", "control_module.sequencer0.connect_sequencer(\"out0_1\")\n", "\n", "# Map sequencer of the QRM to specific outputs (but first disable all sequencer connections)\n", "readout_module.disconnect_outputs()\n", "readout_module.disconnect_inputs()\n", "\n", "readout_module.sequencer0.connect_sequencer(\"io0_1\")" ] }, { "cell_type": "markdown", "id": "133238f9", "metadata": {}, "source": [ "## Define waveforms" ] }, { "cell_type": "markdown", "id": "11b1cfc1", "metadata": {}, "source": [ "To readout the systems we define constant pulses `one` and `zero` which will be up converted by the `NCO` to create the appropriate tones for an IQ mixer.\n", "Similarly for driving the qubit, we define a Gaussian pulse, together with a zero pulse of equal length to serve as inputs for an IQ mixer. In this tutorial we do not assume mixers to be connected to the inputs and outputs of the QCM/QRM." ] }, { "cell_type": "code", "execution_count": 13, "id": "f66b1de2", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.094027Z", "iopub.status.busy": "2024-03-28T14:27:34.092998Z", "iopub.status.idle": "2024-03-28T14:27:34.119928Z", "shell.execute_reply": "2024-03-28T14:27:34.117829Z" } }, "outputs": [], "source": [ "t = np.arange(-80, 81, 1)\n", "sigma = 20\n", "wfs = {\n", " \"zero\": {\"index\": 0, \"data\": [0.0] * 1024},\n", " \"one\": {\"index\": 1, \"data\": [1.0] * 1024},\n", " \"gauss\": {\"index\": 2, \"data\": list(np.exp(-(0.5 * t**2 / sigma**2)))},\n", " \"empty\": {\"index\": 3, \"data\": list(0.0 * t)},\n", "}" ] }, { "cell_type": "markdown", "id": "723c3a2b", "metadata": {}, "source": [ "Hence we obtain the following waveforms for readout:" ] }, { "cell_type": "code", "execution_count": 14, "id": "404255c5", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.124003Z", "iopub.status.busy": "2024-03-28T14:27:34.124003Z", "iopub.status.idle": "2024-03-28T14:27:34.337383Z", "shell.execute_reply": "2024-03-28T14:27:34.335863Z" } }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(wfs[\"zero\"][\"data\"])\n", "plt.plot(wfs[\"one\"][\"data\"])" ] }, { "cell_type": "markdown", "id": "e8b65f29", "metadata": {}, "source": [ "And for drive:" ] }, { "cell_type": "code", "execution_count": 15, "id": "ab0ae878", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.341999Z", "iopub.status.busy": "2024-03-28T14:27:34.341999Z", "iopub.status.idle": "2024-03-28T14:27:34.490070Z", "shell.execute_reply": "2024-03-28T14:27:34.489049Z" } }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(wfs[\"gauss\"][\"data\"])\n", "plt.plot(wfs[\"empty\"][\"data\"])" ] }, { "cell_type": "markdown", "id": "71a7889e", "metadata": {}, "source": [ "Finally, we define two acquisitions. A single readout to perform the calibration measurements. Secondly we create a `rabi` readout sequence that contains 50 different bins for saving the results, one for each of the different amplitudes used for the drive tone." ] }, { "cell_type": "code", "execution_count": 16, "id": "0da2b760", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.496196Z", "iopub.status.busy": "2024-03-28T14:27:34.495055Z", "iopub.status.idle": "2024-03-28T14:27:34.505504Z", "shell.execute_reply": "2024-03-28T14:27:34.504145Z" } }, "outputs": [], "source": [ "num_bins = 50 # Number of amplitudes to be measured\n", "acquisitions = {\n", " \"single\": {\"num_bins\": 1, \"index\": 0},\n", " \"rabi\": {\"num_bins\": num_bins, \"index\": 1},\n", "}" ] }, { "cell_type": "markdown", "id": "a1104a65", "metadata": {}, "source": [ "## Calibration experiments" ] }, { "cell_type": "markdown", "id": "f6ae3f48", "metadata": {}, "source": [ "### TOF calibration" ] }, { "cell_type": "markdown", "id": "9e00db28", "metadata": {}, "source": [ "As a first step, we calibrate the time of flight (tof) for the QRM module. In order to do so, we play a readout pulse and analyze the obtained signal on the oscilloscope to find the travel time of the pulse through the system." ] }, { "cell_type": "code", "execution_count": 17, "id": "5577c713", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.511276Z", "iopub.status.busy": "2024-03-28T14:27:34.511276Z", "iopub.status.idle": "2024-03-28T14:27:34.521057Z", "shell.execute_reply": "2024-03-28T14:27:34.520064Z" } }, "outputs": [], "source": [ "qrm_prog = \"\"\"\n", "play 1, 0, 4 # start readout pulse\n", "acquire 0, 0, 16384 # start the 'single' acquisition sequence and wait for the length of the scope acquisition window\n", "stop\n", "\"\"\"" ] }, { "cell_type": "markdown", "id": "ac665f53", "metadata": {}, "source": [ "Upload the program, together with the waveforms and acquisitions to the QRM" ] }, { "cell_type": "code", "execution_count": 18, "id": "54f9b89d", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.526407Z", "iopub.status.busy": "2024-03-28T14:27:34.525399Z", "iopub.status.idle": "2024-03-28T14:27:34.644512Z", "shell.execute_reply": "2024-03-28T14:27:34.643449Z" } }, "outputs": [], "source": [ "sequence = {\n", " \"waveforms\": wfs,\n", " \"weights\": {},\n", " \"acquisitions\": acquisitions,\n", " \"program\": qrm_prog,\n", "}\n", "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n", " json.dump(sequence, file, indent=4)\n", " file.close()\n", "# Upload sequence.\n", "readout_module.sequencer0.sequence(\"sequence.json\")" ] }, { "cell_type": "markdown", "id": "cbd7ba62", "metadata": {}, "source": [ "Perform the calibration experiment" ] }, { "cell_type": "code", "execution_count": 19, "id": "a718b53e", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.649031Z", "iopub.status.busy": "2024-03-28T14:27:34.649031Z", "iopub.status.idle": "2024-03-28T14:27:34.692093Z", "shell.execute_reply": "2024-03-28T14:27:34.690090Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:3210: FutureWarning: \n", " After June 2024, this feature is subject to removal in future releases.\n", " Transition to an alternative is advised.\n", " See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n", " \n", " warnings.warn(\n", "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:2414: FutureWarning: \n", " After June 2024, this feature is subject to removal in future releases.\n", " Transition to an alternative is advised.\n", " See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n", " \n", " warnings.warn(\n", "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:85: FutureWarning: \n", " After June 2024, this feature is subject to removal in future releases.\n", " Transition to an alternative is advised.\n", " See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n", " \n", " self._deprecation_warning()\n", "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:77: FutureWarning: \n", " After June 2024, this feature is subject to removal in future releases.\n", " Transition to an alternative is advised.\n", " See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n", " \n", " self._deprecation_warning()\n", "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:129: FutureWarning: \n", " After June 2024, this feature is subject to removal in future releases.\n", " Transition to an alternative is advised.\n", " See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n", " \n", " self._deprecation_warning()\n" ] } ], "source": [ "# Arm and start sequencer.\n", "readout_module.arm_sequencer(0)\n", "readout_module.start_sequencer()\n", "\n", "# Wait for the sequencer and acquisition to finish with a timeout period of one minute.\n", "readout_module.get_acquisition_state(0, 1)\n", "readout_module.store_scope_acquisition(0, \"single\")\n", "# Print status of sequencer.\n", "print(readout_module.get_sequencer_state(0))" ] }, { "cell_type": "markdown", "id": "7a3c39a0", "metadata": {}, "source": [ "Analyze the resulting signal on the scope to find the tof" ] }, { "cell_type": "code", "execution_count": 20, "id": "e578bb47", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.698307Z", "iopub.status.busy": "2024-03-28T14:27:34.696854Z", "iopub.status.idle": "2024-03-28T14:27:34.797946Z", "shell.execute_reply": "2024-03-28T14:27:34.796830Z" } }, "outputs": [], "source": [ "p0 = np.array(readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"])\n", "p1 = np.array(readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"])\n", "# Determine when the signal crosses half-max for the first time (in ns)\n", "t_halfmax = np.where(np.abs(p0) > np.max(p0) / 2)[0][0]\n", "\n", "# The time it takes for a sine wave to reach its half-max value is (in ns)\n", "correction = 1 / readout_module.sequencer0.nco_freq() * 1e9 / 12\n", "\n", "tof_measured = t_halfmax - correction" ] }, { "cell_type": "markdown", "id": "136add4a", "metadata": {}, "source": [ "Plot the signal on the scope, around the rising and falling edge of the acquisition signal, as determined by the tof analysis above:" ] }, { "cell_type": "code", "execution_count": 21, "id": "7833bf99", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:34.804205Z", "iopub.status.busy": "2024-03-28T14:27:34.803179Z", "iopub.status.idle": "2024-03-28T14:27:35.262774Z", "shell.execute_reply": "2024-03-28T14:27:35.261764Z" } }, "outputs": [ { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "r = readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"]\n", "plt.plot(r[\"path0\"][\"data\"], \".-\")\n", "plt.plot(r[\"path1\"][\"data\"], \".-\")\n", "plt.axvline(tof_measured, c=\"k\")\n", "plt.xlim(\n", " tof_measured - 10 / readout_module.sequencer0.nco_freq() * 1e9,\n", " tof_measured + 10 / readout_module.sequencer0.nco_freq() * 1e9,\n", ")\n", "plt.show()\n", "\n", "plt.plot(r[\"path0\"][\"data\"], \".-\")\n", "plt.plot(r[\"path1\"][\"data\"], \".-\")\n", "plt.axvline(1024 + tof_measured, c=\"k\")\n", "plt.xlim(\n", " 1024 + tof_measured - 10 / readout_module.sequencer0.nco_freq() * 1e9,\n", " 1024 + tof_measured + 10 / readout_module.sequencer0.nco_freq() * 1e9,\n", ")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "669c7229", "metadata": {}, "source": [ "## Parameters" ] }, { "cell_type": "markdown", "id": "77e82d2f", "metadata": {}, "source": [ "Set the parameters for the Rabi experiment" ] }, { "cell_type": "code", "execution_count": 22, "id": "b91a4434", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:35.269077Z", "iopub.status.busy": "2024-03-28T14:27:35.268038Z", "iopub.status.idle": "2024-03-28T14:27:35.278379Z", "shell.execute_reply": "2024-03-28T14:27:35.277020Z" }, "tags": [] }, "outputs": [], "source": [ "# all times must be divisible by 4\n", "reset_time = 200 # reset time for the qubit in microseconds\n", "tof = int(tof_measured / 4) * 4 # time of flight must be divisible by 4\n", "readout_delay = 164 # time to delay the readout pulse after the start of the rotation pulse\n", "\n", "navg = 1000 # number of averages\n", "stepsize = int(65535 / 100)" ] }, { "cell_type": "markdown", "id": "44fbc883", "metadata": {}, "source": [ "## Rabi" ] }, { "cell_type": "markdown", "id": "5ef86a13", "metadata": {}, "source": [ "Normally, a Rabi experiment would be performed by changing the amplitude in the inner loop, and averaging in the outer loop. To make the resulting experiment visible on an oscilloscope however, in this tutorial we swapped these two loops" ] }, { "cell_type": "code", "execution_count": 23, "id": "cac00df9", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:35.284905Z", "iopub.status.busy": "2024-03-28T14:27:35.283538Z", "iopub.status.idle": "2024-03-28T14:27:35.294790Z", "shell.execute_reply": "2024-03-28T14:27:35.293054Z" } }, "outputs": [], "source": [ "# QCM sequence program.\n", "qcm_seq_prog = f\"\"\"\n", "# Registers used:\n", "# R0 loops over the different awg amplitudes used for the rabi driving pulse\n", "# R2 is used to count the averages needed for a single amplitude\n", "# R3 contains the qubit reset time in microseconds\n", "\n", " move 0, R0 # start with awg amplitude 0\n", " wait_sync 4 # Synchronize the QRM with the QCM\n", "\n", "\n", "ampl_loop: add R0, {stepsize}, R0 # increase the pulse amplitude by the stepsize\n", " move {navg}, R2 # reset the number of averages and save in the R2 register\n", "\n", " # let the qubit relax to its groundstate\n", "navg_loop: move {reset_time}, R3 # reset the number of microseconds to wait and save in the R3 register\n", "rst_loop: wait 1000 # wait 1 microsecond\n", " loop R3,@rst_loop # repeat the 1 microsecond wait as much as needed to let the qubit relax\n", "\n", " set_awg_gain R0, R0 # Set the new amplitude used for the drive pulse\n", " set_mrk 1 # Set marker 1 high for to enable synchronization with external oscilloscope\n", " wait_sync 4 # Synchronize with the qrm to signify a measurement is coming\n", " play 2,3,16384 # Play waveforms and wait remaining duration of scope acquisition\n", "\n", " set_mrk 0 # Reset marker 1\n", " upd_param 4\n", "\n", " loop R2,@navg_loop # Repeat the experiment to average, until R2 becomes 0\n", " jlt R0,{num_bins*stepsize},@ampl_loop # Repeat the experiment for different pulse amplitudes from 0 to num_bins\n", " stop # Stop.\n", "\n", "\"\"\"\n", "\n", "# QRM sequence program.\n", "qrm_seq_prog = f\"\"\"\n", "# Registers used:\n", "# R0 counts which bin to acquire into, a new bin for every new amplitude\n", "# R2 is used to count the averages needed for a single amplitude\n", "\n", " wait_sync 4 # Synchronize the QRM with the QCM.\n", " move 0, R0 # the first acquisition uses bin 0\n", "ampl_loop: move {navg}, R2 # reset the amount of averages to be taken to the initial value\n", "\n", "navg_loop: wait_sync {readout_delay} # wait for the QCM to signal a pulse is coming and wait the readout_delay\n", " play 1,0,{tof} # play readout pulse and wait for the tof\n", " acquire 1,R0,16384 # Acquire waveforms and wait remaining duration of scope acquisition.\n", "\n", " loop R2, @navg_loop # Repeat this measurement for every average\n", " add R0,1,R0 # Increment the bin into which we are measuring\n", " jmp @ampl_loop # repeat\n", "\"\"\"" ] }, { "cell_type": "markdown", "id": "07881889", "metadata": {}, "source": [ "Upload programs and waveforms to QRM and QCM" ] }, { "cell_type": "code", "execution_count": 24, "id": "cdc1ecf4", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:35.298877Z", "iopub.status.busy": "2024-03-28T14:27:35.298877Z", "iopub.status.idle": "2024-03-28T14:27:35.496109Z", "shell.execute_reply": "2024-03-28T14:27:35.495102Z" } }, "outputs": [], "source": [ "# Add QCM sequence to single dictionary and write to JSON file.\n", "sequence = {\n", " \"waveforms\": wfs,\n", " \"weights\": {},\n", " \"acquisitions\": acquisitions,\n", " \"program\": qcm_seq_prog,\n", "}\n", "with open(\"qcm_sequence.json\", \"w\", encoding=\"utf-8\") as file:\n", " json.dump(sequence, file, indent=4)\n", " file.close()\n", "\n", "# Add QRM sequence to single dictionary and write to JSON file.\n", "sequence = {\n", " \"waveforms\": wfs,\n", " \"weights\": {},\n", " \"acquisitions\": acquisitions,\n", " \"program\": qrm_seq_prog,\n", "}\n", "with open(\"qrm_sequence.json\", \"w\", encoding=\"utf-8\") as file:\n", " json.dump(sequence, file, indent=4)\n", " file.close()\n", "\n", "# Upload sequence to QCM.\n", "control_module.sequencer0.sequence(\"qcm_sequence.json\")\n", "\n", "# Upload sequence to QRM.\n", "readout_module.sequencer0.sequence(\"qrm_sequence.json\")" ] }, { "cell_type": "markdown", "id": "c227a68f", "metadata": {}, "source": [ "Arm and start sequencer0 of both the QCM and QRM. The `wait_sync` command together with the SYNQ technology ensures both modules start simultaneously." ] }, { "cell_type": "code", "execution_count": 25, "id": "662dd65e", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:35.502050Z", "iopub.status.busy": "2024-03-28T14:27:35.502050Z", "iopub.status.idle": "2024-03-28T14:27:46.433745Z", "shell.execute_reply": "2024-03-28T14:27:46.433217Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "QCM:\n", "Status: RUNNING, Flags: NONE\n", "\n", "QRM:\n", "Status: RUNNING, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE\n", "QCM:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Status: STOPPED, Flags: NONE\n", "QRM:\n", "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE\n" ] } ], "source": [ "# Arm and start sequencer of the QCM (only sequencer 0).\n", "control_module.arm_sequencer(0)\n", "control_module.start_sequencer(0)\n", "\n", "# Print status of sequencer of the QCM.\n", "print(\"QCM:\")\n", "print(control_module.get_sequencer_state(0))\n", "print()\n", "\n", "# Arm and start sequencer of the QRM (only sequencer 0).\n", "readout_module.arm_sequencer(0)\n", "readout_module.start_sequencer(0)\n", "\n", "# Print status of sequencer of the QRM.\n", "print(\"QRM:\")\n", "print(readout_module.get_sequencer_state(0))\n", "print(\"QCM:\")\n", "print(control_module.get_sequencer_state(0, 1))\n", "readout_module.stop_sequencer(\n", " 0\n", ") # We didn't tell the QRM how many different amplitudes would be measured, so here we tell it to stop.\n", "print(\"QRM:\")\n", "print(readout_module.get_sequencer_state(0, 1))" ] }, { "cell_type": "markdown", "id": "753e4704", "metadata": {}, "source": [ "## Stop\n", "\n", "Finally, let's stop the sequencers if they haven't already and close the instrument connection. One can also display a detailed snapshot containing the instrument parameters before\n", "closing the connection by uncommenting the corresponding lines." ] }, { "cell_type": "code", "execution_count": 26, "id": "c046bc44", "metadata": { "execution": { "iopub.execute_input": "2024-03-28T14:27:46.439921Z", "iopub.status.busy": "2024-03-28T14:27:46.438885Z", "iopub.status.idle": "2024-03-28T14:27:57.965709Z", "shell.execute_reply": "2024-03-28T14:27:57.963643Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "QCM :\n", "Status: STOPPED, Flags: FORCED_STOP\n", "\n", "QRM :\n", "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE\n", "\n", "QCM snapshot:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "marker0_inv_en :\tFalse \n", "marker1_inv_en :\tFalse \n", "marker2_inv_en :\tFalse \n", "marker3_inv_en :\tFalse \n", "out0_offset :\t0 (V)\n", "out1_offset :\t0 (V)\n", "out2_offset :\t0 (V)\n", "out3_offset :\t0 (V)\n", "present :\tTrue \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer0:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\tI \n", "connect_out1 :\tQ \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tTrue \n", "nco_freq :\t1e+08 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tTrue \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer1:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer2:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer3:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer4:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module2_sequencer5:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "connect_out2 :\toff \n", "connect_out3 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n", "\n", "QRM snapshot:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "in0_gain :\t-6 (dB)\n", "in0_offset :\t0 (V)\n", "in1_gain :\t-6 (dB)\n", "in1_offset :\t0 (V)\n", "marker0_inv_en :\tFalse \n", "marker1_inv_en :\tFalse \n", "marker2_inv_en :\tFalse \n", "marker3_inv_en :\tFalse \n", "out0_offset :\t0 (V)\n", "out1_offset :\t0 (V)\n", "present :\tTrue \n", "scope_acq_avg_mode_en_path0 :\tFalse \n", "scope_acq_avg_mode_en_path1 :\tFalse \n", "scope_acq_sequencer_select :\t0 \n", "scope_acq_trigger_level_path0 :\t0 \n", "scope_acq_trigger_level_path1 :\t0 \n", "scope_acq_trigger_mode_path0 :\tsequencer \n", "scope_acq_trigger_mode_path1 :\tsequencer \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer0:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\tin0 \n", "connect_acq_Q :\tin1 \n", "connect_out0 :\tI \n", "connect_out1 :\tQ \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tTrue \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tTrue \n", "nco_freq :\t1e+08 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tTrue \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer1:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\toff \n", "connect_acq_Q :\toff \n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tFalse \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer2:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\toff \n", "connect_acq_Q :\toff \n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tFalse \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer3:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\toff \n", "connect_acq_Q :\toff \n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tFalse \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer4:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\toff \n", "connect_acq_Q :\toff \n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tFalse \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "cluster0_module4_sequencer5:\n", "\tparameter value\n", "--------------------------------------------------------------------------------\n", "connect_acq_I :\toff \n", "connect_acq_Q :\toff \n", "connect_out0 :\toff \n", "connect_out1 :\toff \n", "cont_mode_en_awg_path0 :\tFalse \n", "cont_mode_en_awg_path1 :\tFalse \n", "cont_mode_waveform_idx_awg_path0 :\t0 \n", "cont_mode_waveform_idx_awg_path1 :\t0 \n", "demod_en_acq :\tFalse \n", "gain_awg_path0 :\t1 \n", "gain_awg_path1 :\t1 \n", "integration_length_acq :\t1024 \n", "marker_ovr_en :\tFalse \n", "marker_ovr_value :\t0 \n", "mixer_corr_gain_ratio :\t1 \n", "mixer_corr_phase_offset_degree :\t-0 \n", "mod_en_awg :\tFalse \n", "nco_freq :\t0 (Hz)\n", "nco_phase_offs :\t0 (Degrees)\n", "nco_prop_delay_comp :\t0 (ns)\n", "nco_prop_delay_comp_en :\tFalse (ns)\n", "offset_awg_path0 :\t0 \n", "offset_awg_path1 :\t0 \n", "sync_en :\tFalse \n", "thresholded_acq_marker_address :\t1 \n", "thresholded_acq_marker_en :\tFalse \n", "thresholded_acq_marker_invert :\tFalse \n", "thresholded_acq_rotation :\t0 (Degrees)\n", "thresholded_acq_threshold :\t0 \n", "thresholded_acq_trigger_address :\t1 \n", "thresholded_acq_trigger_en :\tFalse \n", "thresholded_acq_trigger_invert :\tFalse \n", "trigger10_count_threshold :\t1 \n", "trigger10_threshold_invert :\tFalse \n", "trigger11_count_threshold :\t1 \n", "trigger11_threshold_invert :\tFalse \n", "trigger12_count_threshold :\t1 \n", "trigger12_threshold_invert :\tFalse \n", "trigger13_count_threshold :\t1 \n", "trigger13_threshold_invert :\tFalse \n", "trigger14_count_threshold :\t1 \n", "trigger14_threshold_invert :\tFalse \n", "trigger15_count_threshold :\t1 \n", "trigger15_threshold_invert :\tFalse \n", "trigger1_count_threshold :\t1 \n", "trigger1_threshold_invert :\tFalse \n", "trigger2_count_threshold :\t1 \n", "trigger2_threshold_invert :\tFalse \n", "trigger3_count_threshold :\t1 \n", "trigger3_threshold_invert :\tFalse \n", "trigger4_count_threshold :\t1 \n", "trigger4_threshold_invert :\tFalse \n", "trigger5_count_threshold :\t1 \n", "trigger5_threshold_invert :\tFalse \n", "trigger6_count_threshold :\t1 \n", "trigger6_threshold_invert :\tFalse \n", "trigger7_count_threshold :\t1 \n", "trigger7_threshold_invert :\tFalse \n", "trigger8_count_threshold :\t1 \n", "trigger8_threshold_invert :\tFalse \n", "trigger9_count_threshold :\t1 \n", "trigger9_threshold_invert :\tFalse \n", "ttl_acq_auto_bin_incr_en :\tFalse \n", "ttl_acq_input_select :\t0 \n", "ttl_acq_threshold :\t0 \n", "upsample_rate_awg_path0 :\t0 \n", "upsample_rate_awg_path1 :\t0 \n" ] } ], "source": [ "# Stop sequencers.\n", "control_module.stop_sequencer()\n", "readout_module.stop_sequencer()\n", "\n", "# Print status of sequencers.\n", "print(\"QCM :\")\n", "print(control_module.get_sequencer_state(0))\n", "print()\n", "\n", "print(\"QRM :\")\n", "print(readout_module.get_sequencer_state(0))\n", "print()\n", "\n", "# Uncomment the following to print an overview of the instrument parameters.\n", "# Print an overview of instrument parameters.\n", "print(\"QCM snapshot:\")\n", "control_module.print_readable_snapshot(update=True)\n", "print()\n", "\n", "print(\"QRM snapshot:\")\n", "readout_module.print_readable_snapshot(update=True)\n", "\n", "# Close the instrument connections.\n", "cluster.close()" ] }, { "cell_type": "code", "execution_count": null, "id": "a168f336", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:percent" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.18" } }, "nbformat": 4, "nbformat_minor": 5 }