{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "52f35b8f",
   "metadata": {},
   "source": [
    "RF control\n",
    "=================\n",
    "\n",
    "In this tutorial, we demonstrate control and calibration of RF modules. The tutorial is divided into two sections:\n",
    "\n",
    "- **[Spectroscopy measurements](#Spectroscopy-Measurements)** - in which we measure the transmission parameter (S21) of the device under test;\n",
    "\n",
    "    * Over a large frequency range ($2.0$ - $18.0$ GHz) by sweeping the LO frequency;\n",
    "\n",
    "    * Over a smaller frequency range ($5.0$ - $5.2$ GHz) by sweeping the NCO frequency.\n",
    "\n",
    "\n",
    "- **[Mixer calibration](#Mixer-calibration)** - in which we calibrate the mixer parameters (I/Q DC offsets and IF phase/amplitude) to remove unwanted signals.\n",
    "\n",
    "\n",
    "To run this tutorial, you will need:\n",
    "\n",
    "* [QRM-RF](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/cluster/qcm_rf.html)\n",
    "\n",
    "* Spectrum analyzer\n",
    "\n",
    "* Device under test: a T-connector\n",
    "\n",
    "* Two SMA-cables\n",
    "\n",
    "* Installation and enabling of ipywidgets:\n",
    "\n",
    "```\n",
    "        pip install ipywidgets\n",
    "        jupyter nbextension enable --py widgetsnbextension\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e26f4dd",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bfef45cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:34.853044Z",
     "iopub.status.busy": "2023-11-08T16:46:34.851963Z",
     "iopub.status.idle": "2023-11-08T16:46:35.860518Z",
     "shell.execute_reply": "2023-11-08T16:46:35.858516Z"
    }
   },
   "outputs": [],
   "source": [
    "# Import ipython widgets\n",
    "import contextlib\n",
    "import json\n",
    "\n",
    "import ipywidgets as widgets\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Set up the environment\n",
    "from IPython.display import display\n",
    "from ipywidgets import interact\n",
    "from qcodes import Instrument\n",
    "\n",
    "from qblox_instruments import Cluster, PlugAndPlay"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa9c7988",
   "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/master/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0c6e64d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:35.864519Z",
     "iopub.status.busy": "2023-11-08T16:46:35.864519Z",
     "iopub.status.idle": "2023-11-08T16:46:37.799109Z",
     "shell.execute_reply": "2023-11-08T16:46:37.798127Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Devices:\n",
      " - 10.10.200.42: cluster_mm 0.6.1 with name \"QAE_1\" and serial number 00015_2320_004\n",
      " - 10.10.200.50: cluster_mm 0.6.2 with name \"cluster-mm\" and serial number 00015_2219_003\n",
      " - 10.10.200.51: pulsar_qcm 0.11.1 with name \"pulsar-qcm\" and serial number 00012_2039_005\n",
      " - 10.10.200.52: pulsar_qrm 0.11.1 with name \"pulsar-qrm\" and serial number 00013_2120_008\n",
      " - 10.10.200.53: cluster_mm 0.6.1 with name \"cluster-mm\" and serial number 00015_2320_003\n",
      " - 10.10.200.70: cluster_mm 0.6.0 with name \"cluster-mm\" and serial number 123-456-789\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7df0510b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:37.804118Z",
     "iopub.status.busy": "2023-11-08T16:46:37.803123Z",
     "iopub.status.idle": "2023-11-08T16:46:37.815076Z",
     "shell.execute_reply": "2023-11-08T16:46:37.814075Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c983bbc",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "420cd803",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:37.819662Z",
     "iopub.status.busy": "2023-11-08T16:46:37.818635Z",
     "iopub.status.idle": "2023-11-08T16:46:38.278656Z",
     "shell.execute_reply": "2023-11-08T16:46:38.277654Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "try:  # Close the chosen QCodes instrument to prevent name clash\n",
    "    Cluster.find_instrument(cluster_name).close()\n",
    "except KeyError:\n",
    "    pass\n",
    "\n",
    "cluster = Cluster(\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg={\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",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b56a9de6",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cc3a8d69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:38.283654Z",
     "iopub.status.busy": "2023-11-08T16:46:38.282656Z",
     "iopub.status.idle": "2023-11-08T16:46:38.293965Z",
     "shell.execute_reply": "2023-11-08T16:46:38.292963Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster, filter_fn=None):\n",
    "    def checked_filter_fn(mod):\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": "d2806e7b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:38.298493Z",
     "iopub.status.busy": "2023-11-08T16:46:38.298493Z",
     "iopub.status.idle": "2023-11-08T16:46:38.400961Z",
     "shell.execute_reply": "2023-11-08T16:46:38.399707Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{8: <QcmQrm: cluster0_module8 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QRM RF modules\n",
    "modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and mod.is_rf_type)\n",
    "modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ef8df1f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:38.405001Z",
     "iopub.status.busy": "2023-11-08T16:46:38.405001Z",
     "iopub.status.idle": "2023-11-08T16:46:38.416693Z",
     "shell.execute_reply": "2023-11-08T16:46:38.415681Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "readout_module = modules[8]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a466782",
   "metadata": {},
   "source": [
    "### Reset the Cluster\n",
    "\n",
    "We reset the Cluster to enter a well-defined state. Note that resetting will clear all stored parameters, so resetting between experiments is usually not desirable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1039037e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:38.422053Z",
     "iopub.status.busy": "2023-11-08T16:46:38.421028Z",
     "iopub.status.idle": "2023-11-08T16:46:41.704449Z",
     "shell.execute_reply": "2023-11-08T16:46:41.703247Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_state())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2230818e",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "Spectroscopy Measurements\n",
    "-----------------------------------------\n",
    "\n",
    "A common experimental step is to find the resonance frequency of a resonator. To showcase the experience flow in this case we will sweep close to the full frequency range of the QRM-RF module ($2$ - $18$ GHz) and plot the frequency response.\n",
    "\n",
    "We start by defining a function to plot the amplitude and phase of the output signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f19e5b30",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:41.708148Z",
     "iopub.status.busy": "2023-11-08T16:46:41.708148Z",
     "iopub.status.idle": "2023-11-08T16:46:41.719669Z",
     "shell.execute_reply": "2023-11-08T16:46:41.718548Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_spectrum(freq_sweep_range, I_data, Q_data):\n",
    "    amplitude = np.sqrt(I_data**2 + Q_data**2)\n",
    "    phase = np.arctan2(Q_data, I_data) * 180 / np.pi\n",
    "\n",
    "    plt.rcParams[\"axes.labelsize\"] = 18\n",
    "    plt.rcParams[\"xtick.labelsize\"] = 16\n",
    "    plt.rcParams[\"ytick.labelsize\"] = 16\n",
    "\n",
    "    fig, [ax1, ax2] = plt.subplots(2, 1, sharex=True, figsize=(15, 7))\n",
    "\n",
    "    ax1.plot(freq_sweep_range / 1e9, amplitude, color=\"#00839F\", linewidth=2)\n",
    "    ax1.set_ylabel(\"Amplitude (V)\")\n",
    "\n",
    "    ax2.plot(freq_sweep_range / 1e9, phase, color=\"#00839F\", linewidth=2)\n",
    "    ax2.set_ylabel(r\"Phase ($\\circ$)\")\n",
    "    ax2.set_xlabel(\"Frequency (GHz)\")\n",
    "    fig.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e57d8d38",
   "metadata": {},
   "source": [
    "### Setup\n",
    "Connect the output of QRM-RF to its input via a T-connector (one end of the T-connector should be left open so as to produce a resonator) as shown in the figure below.\n",
    "\n",
    "**Note**: this will not work if a splitter is used.\n",
    "\n",
    "![Diagram.png](RF_Tutorial_Diagram.png)\n",
    "\n",
    "Initially, we need to define the waveforms and acquisition memory. As we are using the NCO to generate an IF signal, we can use a constant (DC) waveform. We need to make sure that the waveform is long enough to run during the whole acquisition integration length and to compensate for the delay of output to input (the `holdoff_length`). Finally, we will also add averaging to increase the signal-to-noise ratio (SNR) of the measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "40e782ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:41.723875Z",
     "iopub.status.busy": "2023-11-08T16:46:41.723875Z",
     "iopub.status.idle": "2023-11-08T16:46:41.734677Z",
     "shell.execute_reply": "2023-11-08T16:46:41.734677Z"
    }
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "no_averages = 10\n",
    "integration_length = 1024\n",
    "holdoff_length = 200\n",
    "waveform_length = integration_length + holdoff_length"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58b73996",
   "metadata": {},
   "source": [
    "For simplicity, a single bin is used in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "098d5cb4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:41.739488Z",
     "iopub.status.busy": "2023-11-08T16:46:41.739488Z",
     "iopub.status.idle": "2023-11-08T16:46:41.751045Z",
     "shell.execute_reply": "2023-11-08T16:46:41.749931Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "647880c2",
   "metadata": {},
   "source": [
    "Now that the waveform and acquisition have been specified for the sequence, we need a Q1ASM program that sequences the waveforms and triggers the acquisitions. This program plays a DC wave, waits for the specified hold-off time and then acquires the signal. This process is repeated for the specified number of averages, with the average being done within the hardware."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "39835096",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:41.756050Z",
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     "shell.execute_reply": "2023-11-08T16:46:42.166585Z"
    }
   },
   "outputs": [],
   "source": [
    "seq_prog = f\"\"\"\n",
    "      move    {no_averages},R0           # Average iterator.\n",
    "      nop\n",
    "      reset_ph\n",
    "      set_awg_offs 10000, 10000          # set amplitude of signal\n",
    "      nop\n",
    "loop:\n",
    "      wait     {holdoff_length}          # Wait time of flight\n",
    "      acquire  0,0,{integration_length}  # Acquire data and store them in bin_n0 of acq_index.\n",
    "      loop     R0,@loop                  # Run until number of average iterations is done.\n",
    "      stop                               # Stop the sequencer\n",
    "      \"\"\"\n",
    "\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": {},\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": seq_prog,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()\n",
    "\n",
    "# Upload sequence\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20c4de6a",
   "metadata": {},
   "source": [
    "The device and sequencer can now be configured. In the RF modules, there is a switch directly before the output connector, which needs to be turned on to get a signal out of the device. The switch is controlled through the marker interface, first we must enable to override of the marker, then we must set the appropriate bits to enable the signal at the output.\n",
    "\n",
    "Additionally, we set the output paths DC offset to known values. We look into the details of this parameter further on in this tutorial. Additionally, we configure the sequencer, the acquisition and set the NCO frequency. More information on these configurations can be found in the [Basic Sequencing](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/tutorials/q1asm_tutorials/basic/rf/basic_sequencing.html), [Scope Acquisition](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/tutorials/q1asm_tutorials/basic/rf/scope_acquisition.html) and [NCO](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/tutorials/q1asm_tutorials/basic/baseband/nco_control.html) tutorials, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60cb662a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:42.172201Z",
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     "shell.execute_reply": "2023-11-08T16:46:42.412523Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# Configure channel map\n",
    "readout_module.sequencer0.connect_sequencer(\"io0\")\n",
    "\n",
    "readout_module.sequencer0.marker_ovr_en(True)\n",
    "readout_module.sequencer0.marker_ovr_value(3)  # Enables output on QRM-RF\n",
    "\n",
    "# Set offset in mV\n",
    "readout_module.out0_offset_path0(5.5)\n",
    "readout_module.out0_offset_path1(5.5)\n",
    "\n",
    "# Configure scope mode\n",
    "readout_module.scope_acq_sequencer_select(0)\n",
    "readout_module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "readout_module.scope_acq_trigger_mode_path1(\"sequencer\")\n",
    "\n",
    "# Configure the sequencer\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "readout_module.sequencer0.nco_freq(100e6)\n",
    "readout_module.sequencer0.integration_length_acq(integration_length)\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "\n",
    "# NCO delay compensation\n",
    "readout_module.sequencer0.nco_prop_delay_comp_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da91e824",
   "metadata": {},
   "source": [
    "Now we are ready to start the spectroscopy measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "88fe62d1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:42.417210Z",
     "iopub.status.busy": "2023-11-08T16:46:42.417210Z",
     "iopub.status.idle": "2023-11-08T16:46:55.734446Z",
     "shell.execute_reply": "2023-11-08T16:46:55.733284Z"
    }
   },
   "outputs": [],
   "source": [
    "lo_sweep_range = np.linspace(2e9, 18e9, 161)\n",
    "\n",
    "lo_data_0 = []\n",
    "lo_data_1 = []\n",
    "\n",
    "for lo_val in lo_sweep_range:\n",
    "    # Update the LO frequency.\n",
    "    readout_module.out0_in0_lo_freq(lo_val)\n",
    "\n",
    "    # Clear acquisitions\n",
    "    readout_module.sequencer0.delete_acquisition_data(\"acq\")\n",
    "\n",
    "    readout_module.arm_sequencer(0)\n",
    "    readout_module.start_sequencer()\n",
    "\n",
    "    # Wait for the sequencer to stop with a timeout period of one minute.\n",
    "    readout_module.get_acquisition_state(0, timeout=1)\n",
    "\n",
    "    # Move acquisition data from temporary memory to acquisition list.\n",
    "    readout_module.store_scope_acquisition(0, \"acq\")\n",
    "\n",
    "    # Get acquisition list from instrument.\n",
    "    data = readout_module.get_acquisitions(0)[\"acq\"]\n",
    "\n",
    "    # Store the acquisition data.\n",
    "    lo_data_0.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"][0])\n",
    "    lo_data_1.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40837471",
   "metadata": {},
   "source": [
    "We plot the acquired signal's amplitude and phase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8a5721cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:55.739920Z",
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     "shell.execute_reply": "2023-11-08T16:46:56.135912Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The result still needs to be divided by the integration length to make sure\n",
    "# the units are correct.\n",
    "lo_data_0 = np.asarray(lo_data_0) / integration_length\n",
    "lo_data_1 = np.asarray(lo_data_1) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(lo_sweep_range, lo_data_0, lo_data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33e3903",
   "metadata": {},
   "source": [
    "From the spectroscopy measurements, we can see that the resonance dip of the resonator is at roughly $6.5$ GHz."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7c18240",
   "metadata": {},
   "source": [
    "### Frequency sweep using NCO\n",
    "\n",
    "Instead of sweeping the LO frequency, we can instead sweep the NCO. More information on the NCO can be found in the [NCO Control Tutorial](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/tutorials/q1asm_tutorials/basic/baseband/nco_control.html). We perform a frequency sweep from $5.0$ to $5.2$ GHz by setting the LO frequency to $4.95$ GHz, such that the NCO frequency is swept from $50$ to $250$ MHz. Due to possible LO leakage we avoid NCO frequencies below $\\pm10$ MHz. Additionally, due to the analog filters, which cause a decrease in the output signal as the frequency increases, see [NCO Control Tutorial](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/tutorials/q1asm_tutorials/basic/baseband/nco_control.html), we choose to remain below $250$ MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f4c936c3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:56.141914Z",
     "iopub.status.busy": "2023-11-08T16:46:56.140915Z",
     "iopub.status.idle": "2023-11-08T16:46:56.199641Z",
     "shell.execute_reply": "2023-11-08T16:46:56.198148Z"
    }
   },
   "outputs": [],
   "source": [
    "freq_sweep_range = np.linspace(5.0e9, 5.2e9, 200)\n",
    "\n",
    "# LO settings\n",
    "lo_freq = 4.95e9\n",
    "readout_module.out0_in0_lo_freq(lo_freq)\n",
    "\n",
    "# NCO delay compensation\n",
    "readout_module.sequencer0.nco_prop_delay_comp_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abec1854",
   "metadata": {},
   "source": [
    "We run the frequency sweep. This is simply a loop where we set the frequency by updating the QCoDeS NCO frequency parameter and then run the Q1ASM program defined in the previous example. We measure the run time using the `%%time` IPython magic command."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c93a53da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:46:56.205093Z",
     "iopub.status.busy": "2023-11-08T16:46:56.204088Z",
     "iopub.status.idle": "2023-11-08T16:47:09.187755Z",
     "shell.execute_reply": "2023-11-08T16:47:09.185731Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 469 ms\n",
      "Wall time: 13 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "data_0 = []\n",
    "data_1 = []\n",
    "\n",
    "for freq_val in freq_sweep_range:\n",
    "    # Update the NCO frequency.\n",
    "    readout_module.sequencer0.nco_freq(freq_val - lo_freq)\n",
    "\n",
    "    # Clear acquisitions\n",
    "    readout_module.sequencer0.delete_acquisition_data(\"acq\")\n",
    "\n",
    "    readout_module.arm_sequencer(0)\n",
    "    readout_module.start_sequencer()\n",
    "\n",
    "    # Wait for the sequencer to stop with a timeout period of one minute.\n",
    "    readout_module.get_acquisition_state(0, timeout=1)\n",
    "\n",
    "    # Move acquisition data from temporary memory to acquisition list.\n",
    "    readout_module.store_scope_acquisition(0, \"acq\")\n",
    "\n",
    "    # Get acquisition list from instrument.\n",
    "    data = readout_module.get_acquisitions(0)[\"acq\"]\n",
    "\n",
    "    # Store the acquisition data.\n",
    "    data_0.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"][0])\n",
    "    data_1.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bd28df18",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.192263Z",
     "iopub.status.busy": "2023-11-08T16:47:09.191274Z",
     "iopub.status.idle": "2023-11-08T16:47:09.467541Z",
     "shell.execute_reply": "2023-11-08T16:47:09.466168Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The result still needs to be divided by the integration length to make sure\n",
    "# the units are correct.\n",
    "data_0 = np.asarray(data_0) / integration_length\n",
    "data_1 = np.asarray(data_1) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c68c60bb",
   "metadata": {},
   "source": [
    "### Fast frequency sweep\n",
    "\n",
    "The same spectroscopy measurement can be done by sweeping the NCO frequency directly in the Q1ASM sequence, with a considerable time speed-up in comparison with updating the QCoDes parameters.\n",
    "\n",
    "The Q1ASM sequencer program only supports integer values. However, the NCO has a frequency resolution of 0.25 Hz. As such, the frequency values in the sequencer program must be given as integer multiples of $1/4$ Hz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "80cbe8cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.471990Z",
     "iopub.status.busy": "2023-11-08T16:47:09.471325Z",
     "iopub.status.idle": "2023-11-08T16:47:09.499406Z",
     "shell.execute_reply": "2023-11-08T16:47:09.498357Z"
    }
   },
   "outputs": [],
   "source": [
    "freq_sweep_range = np.linspace(5.0e9, 5.2e9, 200)\n",
    "\n",
    "lo_freq = 4.95e9\n",
    "readout_module.out0_in0_lo_freq(lo_freq)\n",
    "\n",
    "start_freq = np.min(freq_sweep_range) - lo_freq\n",
    "stop_freq = np.max(freq_sweep_range) - lo_freq\n",
    "n_steps = len(freq_sweep_range)\n",
    "step_freq = (stop_freq - start_freq) / n_steps\n",
    "\n",
    "# NCO frequency range settings\n",
    "nco_int_start_freq = int(4 * start_freq)\n",
    "nco_int_step_freq = int(4 * step_freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d7c7da4",
   "metadata": {},
   "source": [
    "We set up the QRM-RF for continuous wave output, similarly to what was done in the previous example, and binned acquisition with multiple bins - equal to the number of frequency steps. The maximum number of points that can be measured using this method is $131072$ per sequencer, which corresponds to the maximum number of bins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4d254da5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.504791Z",
     "iopub.status.busy": "2023-11-08T16:47:09.503786Z",
     "iopub.status.idle": "2023-11-08T16:47:09.515327Z",
     "shell.execute_reply": "2023-11-08T16:47:09.514286Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"multi\": {\"num_bins\": n_steps, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "362672e3",
   "metadata": {},
   "source": [
    "The Q1ASM sequence program is defined with two loops, one for the averaging and a second one for the frequency sweep, i.e. the measurement itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ed6dab2f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.519282Z",
     "iopub.status.busy": "2023-11-08T16:47:09.519282Z",
     "iopub.status.idle": "2023-11-08T16:47:09.593549Z",
     "shell.execute_reply": "2023-11-08T16:47:09.592087Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program sequence\n",
    "program = f\"\"\"\n",
    "        move            {no_averages}, R0                   # Include number of averages\n",
    "avg:\n",
    "        move            {nco_int_start_freq}, R1            # Start frequency\n",
    "        move            0, R2                               # Step counter\n",
    "        reset_ph                                         # Reset phase of signal\n",
    "        set_awg_offs    10000, 10000                        # Set amplitude of signal\n",
    "nco_f:\n",
    "        set_freq        R1                               # Set the frequency\n",
    "        add             R1, {nco_int_step_freq}, R1      # Update the frequency register\n",
    "        upd_param       200                              # Update settings and wait for time of flight\n",
    "        acquire         0, R2, {integration_length}      # Acquire data and store them in bin_n0 of acq_index.\n",
    "        add             R2, 1, R2                        # Update the step register\n",
    "        nop\n",
    "        jlt             R2, {n_steps}, @nco_f            # Loop over all frequencies\n",
    "        loop            R0, @avg\n",
    "        stop                                             # Stop\n",
    "\"\"\"\n",
    "\n",
    "# Upload sequence\n",
    "readout_module.sequencer0.sequence(\n",
    "    {\n",
    "        \"waveforms\": {},\n",
    "        \"weights\": {},\n",
    "        \"acquisitions\": acquisitions,\n",
    "        \"program\": program,\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13e0e91a",
   "metadata": {},
   "source": [
    "We perform the spectroscopy measurement using `%%time` magic command again, so that we can compare the run time of both measurement methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "edcfc002",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.597126Z",
     "iopub.status.busy": "2023-11-08T16:47:09.596115Z",
     "iopub.status.idle": "2023-11-08T16:47:09.654621Z",
     "shell.execute_reply": "2023-11-08T16:47:09.653394Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 0 ns\n",
      "Wall time: 46.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "readout_module.delete_acquisition_data(0, \"multi\")\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "readout_module.get_acquisition_state(0, timeout=1)\n",
    "readout_module.store_scope_acquisition(0, \"multi\")\n",
    "data = readout_module.get_acquisitions(0)[\"multi\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f198aa0",
   "metadata": {},
   "source": [
    "Comparing the run time of performing the same spectroscopy measurement by updating the QCoDes parameters and by sweeping the frequency within the Q1ASM sequence program, we see that the latter is two orders of magnitude faster. We now plot the results, to verify that they are equal to those measured in the first example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3255a52d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.658105Z",
     "iopub.status.busy": "2023-11-08T16:47:09.658105Z",
     "iopub.status.idle": "2023-11-08T16:47:09.918273Z",
     "shell.execute_reply": "2023-11-08T16:47:09.916800Z"
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_0 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) / integration_length\n",
    "data_1 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60337da2",
   "metadata": {},
   "source": [
    "### Signal Attenuation\n",
    "\n",
    "The QRM-RF module provides the possibility of attenuating both the output and input signals. The attenuation values can be set within the range from $0$ to $60$ dB, in $2$ dB steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "699fee65",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:09.921906Z",
     "iopub.status.busy": "2023-11-08T16:47:09.921906Z",
     "iopub.status.idle": "2023-11-08T16:47:10.197219Z",
     "shell.execute_reply": "2023-11-08T16:47:10.196232Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Output Attenuation (dB)\n",
    "readout_module.out0_att(4)\n",
    "\n",
    "# Input Attenuation (dB)\n",
    "readout_module.in0_att(0)\n",
    "\n",
    "# Fast NCO frequency sweep\n",
    "readout_module.delete_acquisition_data(0, \"multi\")\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "readout_module.get_acquisition_state(0, timeout=1)\n",
    "data = readout_module.get_acquisitions(0)[\"multi\"]\n",
    "\n",
    "data_0 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) / integration_length\n",
    "data_1 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b604e825",
   "metadata": {},
   "source": [
    "Mixer calibration\n",
    "------------------------\n",
    "For this section, we are going to look at the output spectrum of the QRM at a fixed output frequency of 5 GHz, by connecting $\\text{O}^{1}$ to the spectrum analyzer. We start by resetting the device to make sure it's in a well-defined state. Note that resetting will clear all stored parameters, so resetting between experiments is usually not desirable.\n",
    "We then upload a simple sequence program that keeps playing the DC waveform. This will be modulated and upconverted within the QRM-RF before outputting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1b69fb15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:10.201309Z",
     "iopub.status.busy": "2023-11-08T16:47:10.201309Z",
     "iopub.status.idle": "2023-11-08T16:47:13.517958Z",
     "shell.execute_reply": "2023-11-08T16:47:13.516949Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_state())\n",
    "\n",
    "# Sequence program.\n",
    "seq_prog = \"\"\"\n",
    "      wait_sync 4\n",
    "\n",
    "loop: play    0,0,1200\n",
    "      jmp     @loop\n",
    "\"\"\"\n",
    "waveforms = {\"dc\": {\"data\": [0.5 for i in range(0, 1200)], \"index\": 0}}\n",
    "\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": waveforms,\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": seq_prog,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()\n",
    "\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea6c103c",
   "metadata": {},
   "source": [
    "Let's configure the sequencer to generate an IF frequency of $100$ MHz. To get an output frequency of $5.0$ GHz, we then have to configure the LO to run at $4.9$ GHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f2452dd7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:13.525184Z",
     "iopub.status.busy": "2023-11-08T16:47:13.524183Z",
     "iopub.status.idle": "2023-11-08T16:47:13.641664Z",
     "shell.execute_reply": "2023-11-08T16:47:13.640649Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: RUNNING, Flags: NONE\n"
     ]
    }
   ],
   "source": [
    "# Configure the Local oscillator\n",
    "if readout_module.is_qrm_type:\n",
    "    readout_module.out0_in0_lo_freq(5e9 - 100e6)\n",
    "else:\n",
    "    readout_module.out0_lo_freq(5e9 - 100e6)\n",
    "\n",
    "readout_module.sequencer0.marker_ovr_en(True)\n",
    "readout_module.sequencer0.marker_ovr_value(3)  # Enables output on QRM-RF\n",
    "\n",
    "# Configure the sequencer\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.nco_freq(100e6)\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer(0)\n",
    "\n",
    "print(readout_module.get_sequencer_state(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "455bf88d",
   "metadata": {},
   "source": [
    "Connect the output of the QRM-RF (O1) to the spectrum analyzer. This is what the output looks like on the spectrum analyzer (center frequency at 4.85 GHz with 600 MHz bandwidth)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecf4de9b",
   "metadata": {},
   "source": [
    "![IQ_Mixer_Calib_before.png](IQ_Mixer_Calib_before.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77378ce6",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "As we can see from this image, the output is not exactly the single peak at 5 GHz that we want. We seem to have some LO leakage (at 4.9 GHz) and an unwanted sideband (4.8 GHz). This is due to mixer imperfections. We can suppress these by calibrating the mixer:\n",
    "\n",
    "* Using DC offsets we can lower the LO leakage.\n",
    "* By changing the gain ratio and phase of the IF signal we can cancel the unwanted sideband.\n",
    "\n",
    "Create control sliders for theses parameters. Each time the value of a parameter is updated, the sequencer is automatically stopped from the embedded firmware for safety reasons and has to be manually restarted. The sliders cover the valid parameter range. If the code below is modified to input invalid values, the Cluster QRM-RF firmware will not program the values.\n",
    "\n",
    "Execute the code below, move the sliders and observe the result on the spectrum analyzer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1d41110c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:13.647376Z",
     "iopub.status.busy": "2023-11-08T16:47:13.645867Z",
     "iopub.status.idle": "2023-11-08T16:47:13.764841Z",
     "shell.execute_reply": "2023-11-08T16:47:13.763815Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1fee458d34524e7b95aefb222802362f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='offset0', layout=Layout(width='1200px'), max=14.0, m…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fb75b238360e4896aff11b5f387f28b9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='offset1', layout=Layout(width='1200px'), max=14.0, m…"
      ]
     },
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       "<function __main__.set_phase_offset(phase_offset)>"
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    "def set_offset0(offset0):\n",
    "    readout_module.out0_offset_path0(offset0)\n",
    "\n",
    "\n",
    "def set_offset1(offset1):\n",
    "    readout_module.out0_offset_path1(offset1)\n",
    "\n",
    "\n",
    "def set_gain_ratio(gain_ratio):\n",
    "    readout_module.sequencer0.mixer_corr_gain_ratio(gain_ratio)\n",
    "    # Start\n",
    "    readout_module.arm_sequencer(0)\n",
    "    readout_module.start_sequencer(0)\n",
    "\n",
    "\n",
    "def set_phase_offset(phase_offset):\n",
    "    readout_module.sequencer0.mixer_corr_phase_offset_degree(phase_offset)\n",
    "    # Start\n",
    "    readout_module.arm_sequencer(0)\n",
    "    readout_module.start_sequencer(0)\n",
    "\n",
    "\n",
    "interact(\n",
    "    set_offset0,\n",
    "    offset0=widgets.FloatSlider(\n",
    "        min=-14.0,\n",
    "        max=14.0,\n",
    "        step=0.001,\n",
    "        start=0.0,\n",
    "        layout=widgets.Layout(width=\"1200px\"),\n",
    "    ),\n",
    ")\n",
    "interact(\n",
    "    set_offset1,\n",
    "    offset1=widgets.FloatSlider(\n",
    "        min=-14.0,\n",
    "        max=14.0,\n",
    "        step=0.001,\n",
    "        start=0.0,\n",
    "        layout=widgets.Layout(width=\"1200px\"),\n",
    "    ),\n",
    ")\n",
    "interact(\n",
    "    set_gain_ratio,\n",
    "    gain_ratio=widgets.FloatSlider(\n",
    "        min=0.9, max=1.1, step=0.001, start=1.0, layout=widgets.Layout(width=\"1200px\")\n",
    "    ),\n",
    ")\n",
    "interact(\n",
    "    set_phase_offset,\n",
    "    phase_offset=widgets.FloatSlider(\n",
    "        min=-45.0,\n",
    "        max=45.0,\n",
    "        step=0.001,\n",
    "        start=0.0,\n",
    "        layout=widgets.Layout(width=\"1200px\"),\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c86adeaf",
   "metadata": {},
   "source": [
    "![IQ_Mixer_Calib_after.png](IQ_Mixer_Calib_after.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ffc666b",
   "metadata": {},
   "source": [
    "Stop\n",
    "----\n",
    "\n",
    "Finally, let's stop the sequencers if they haven't already and close the instrument connection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a37c4ba6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:13.769886Z",
     "iopub.status.busy": "2023-11-08T16:47:13.769886Z",
     "iopub.status.idle": "2023-11-08T16:47:13.795863Z",
     "shell.execute_reply": "2023-11-08T16:47:13.794774Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: FORCED_STOP\n"
     ]
    }
   ],
   "source": [
    "# Stop sequencer.\n",
    "readout_module.stop_sequencer()\n",
    "\n",
    "# Print status of sequencer.\n",
    "print(readout_module.get_sequencer_state(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "280bee52",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-08T16:47:13.799515Z",
     "iopub.status.busy": "2023-11-08T16:47:13.798487Z",
     "iopub.status.idle": "2023-11-08T16:47:13.811094Z",
     "shell.execute_reply": "2023-11-08T16:47:13.809681Z"
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   },
   "outputs": [],
   "source": [
    "# Close the connection to the Cluster\n",
    "cluster.close()"
   ]
  }
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