{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "80fcea98",
   "metadata": {},
   "source": [
    "# Conditional Playback"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b031fa89",
   "metadata": {},
   "source": [
    "In this tutorial we show how our Cluster Feedback capability (see section [Feedback](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/feedback.html)) can be used to send pulses dependent on the measurement outcome. Concretely, this tutorial will show how to perform active reset, which means sending a $\\pi$-pulse if (and only if) the qubit state equals $\\left|1\\right\\rangle$, to flip the qubit back to the $\\left|0\\right\\rangle$ state.\n",
    "\n",
    "This tutorial should be ran on a Cluster with at least two modules. A QRM or QRM-RF module is used to emulate qubit readout. For this tutorial we connect $\\text{O}^{1}$ and $\\text{O}^{2}$ to $\\text{I}^{1}$ and $\\text{I}^{2}$ of the QRM. Depending on the result acquired by this QRM, a second module (called QCM in this tutorial) is used to conditionally generate a $\\pi$-pulse. The output of this QCM can be visualized on an oscilloscope to verify the behavior of the system.\n",
    "\n",
    "To display the behavior of the QRM, its marker 1 should be used to trigger an oscilloscope. Marker 2 and marker 4 need to be connected to the oscilloscope when running the section `Active reset`.\n",
    "\n",
    "The tutorial will go through the following steps:\n",
    "- Calibrate the time of flight (TOF) from QRM output to QRM input.\n",
    "- Set up the thresholding to separate the $\\left|0\\right\\rangle$ and $\\left|1\\right\\rangle$ state.\n",
    "- Sending the qubit state through the feedback infrastructure.\n",
    "- Performing conditional pulses depending on the qubit state.\n",
    "\n",
    "To synchronize the modules, we use the SYNQ technology."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26c322a1",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "First, we are going to import the required packages and connect to the instrument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a050c032",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:24.363033Z",
     "iopub.status.busy": "2024-09-02T01:43:24.362820Z",
     "iopub.status.idle": "2024-09-02T01:43:24.985829Z",
     "shell.execute_reply": "2024-09-02T01:43:24.985059Z"
    }
   },
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib import colors\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 Module"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9bdab1f",
   "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": "4f260f2f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:24.988855Z",
     "iopub.status.busy": "2024-09-02T01:43:24.988674Z",
     "iopub.status.idle": "2024-09-02T01:43:26.974237Z",
     "shell.execute_reply": "2024-09-02T01:43:26.970598Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No devices found\r\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "85f62f25",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:26.982626Z",
     "iopub.status.busy": "2024-09-02T01:43:26.982428Z",
     "iopub.status.idle": "2024-09-02T01:43:26.985668Z",
     "shell.execute_reply": "2024-09-02T01:43:26.984995Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8f82a3e",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0a97a787",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:26.988135Z",
     "iopub.status.busy": "2024-09-02T01:43:26.987944Z",
     "iopub.status.idle": "2024-09-02T01:43:27.641691Z",
     "shell.execute_reply": "2024-09-02T01:43:27.641025Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster = find_or_create_instrument(\n",
    "    Cluster,\n",
    "    recreate=True,\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg=(\n",
    "        {\n",
    "            2: ClusterType.CLUSTER_QCM,\n",
    "            4: ClusterType.CLUSTER_QRM,\n",
    "            6: ClusterType.CLUSTER_QCM_RF,\n",
    "            8: ClusterType.CLUSTER_QRM_RF,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fd2d45a",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6317a771",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.644591Z",
     "iopub.status.busy": "2024-09-02T01:43:27.644410Z",
     "iopub.status.idle": "2024-09-02T01:43:27.648414Z",
     "shell.execute_reply": "2024-09-02T01:43:27.647771Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, Module]:\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": "59d7f33a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.650558Z",
     "iopub.status.busy": "2024-09-02T01:43:27.650394Z",
     "iopub.status.idle": "2024-09-02T01:43:27.675739Z",
     "shell.execute_reply": "2024-09-02T01:43:27.675114Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <Module: cluster0_module4 of Cluster: cluster0>}"
      ]
     },
     "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": "35d8f51a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.677860Z",
     "iopub.status.busy": "2024-09-02T01:43:27.677692Z",
     "iopub.status.idle": "2024-09-02T01:43:27.680878Z",
     "shell.execute_reply": "2024-09-02T01:43:27.680266Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8fdec03c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.683055Z",
     "iopub.status.busy": "2024-09-02T01:43:27.682887Z",
     "iopub.status.idle": "2024-09-02T01:43:27.705101Z",
     "shell.execute_reply": "2024-09-02T01:43:27.704614Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: <Module: cluster0_module2 of Cluster: cluster0>}"
      ]
     },
     "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": "104512b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.707205Z",
     "iopub.status.busy": "2024-09-02T01:43:27.707034Z",
     "iopub.status.idle": "2024-09-02T01:43:27.710204Z",
     "shell.execute_reply": "2024-09-02T01:43:27.709580Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "control_module = control_modules[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce7a1f9f",
   "metadata": {},
   "source": [
    "## Sequencer configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dc41bf2",
   "metadata": {},
   "source": [
    "Define all waveforms necessary for this tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0a23bf2a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.712419Z",
     "iopub.status.busy": "2024-09-02T01:43:27.712250Z",
     "iopub.status.idle": "2024-09-02T01:43:27.717049Z",
     "shell.execute_reply": "2024-09-02T01:43:27.716454Z"
    }
   },
   "outputs": [],
   "source": [
    "waveform_length = 120\n",
    "t = np.arange(-80, 81, 1)\n",
    "sigma = 20\n",
    "# waveforms for readout pulses\n",
    "waveforms = {\n",
    "    \"zero\": {\"data\": [0.0] * 1024, \"index\": 0},\n",
    "    \"one\": {\"data\": [1.0] * 1024, \"index\": 1},\n",
    "    \"state0_I\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 2,\n",
    "    },  # I waveform emulating a qubit in the 0 state\n",
    "    \"state0_Q\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 3,\n",
    "    },  # Q waveform emulating a qubit in the 0 state\n",
    "    \"state1_I\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 4,\n",
    "    },  # I waveform emulating a qubit in the 1 state\n",
    "    \"state1_Q\": {\n",
    "        \"data\": [0.003] * waveform_length,\n",
    "        \"index\": 5,\n",
    "    },  # Q waveform emulating a qubit in the 1 state\n",
    "    \"gauss\": {\"data\": list(np.exp(-(0.5 * t**2 / sigma**2))), \"index\": 6},\n",
    "    \"empty\": {\"data\": list(0.0 * t), \"index\": 7},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10277f21",
   "metadata": {},
   "source": [
    "Specify acquisitions that are used in the tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d303d143",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.719314Z",
     "iopub.status.busy": "2024-09-02T01:43:27.719143Z",
     "iopub.status.idle": "2024-09-02T01:43:27.722178Z",
     "shell.execute_reply": "2024-09-02T01:43:27.721640Z"
    }
   },
   "outputs": [],
   "source": [
    "acquisitions = {\n",
    "    \"state0\": {\"index\": 0, \"num_bins\": 1024},\n",
    "    \"state1\": {\"index\": 1, \"num_bins\": 1024},\n",
    "    \"single\": {\"index\": 2, \"num_bins\": 1},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b692e863",
   "metadata": {},
   "source": [
    "Set up sequencer parameters for both QRM and QCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "89bb1bd5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.724441Z",
     "iopub.status.busy": "2024-09-02T01:43:27.724272Z",
     "iopub.status.idle": "2024-09-02T01:43:27.810904Z",
     "shell.execute_reply": "2024-09-02T01:43:27.807828Z"
    }
   },
   "outputs": [],
   "source": [
    "integration_length = 120\n",
    "readout_module.sequencer0.integration_length_acq(integration_length)\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.nco_freq(50e6)\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "\n",
    "control_module.sequencer1.sync_en(False)  # We will turn on the sync enable of the QCM later\n",
    "control_module.sequencer1.nco_freq(50e6)\n",
    "control_module.sequencer1.mod_en_awg(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61af5a64",
   "metadata": {},
   "source": [
    "## Calibrate TOF"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1b49470",
   "metadata": {},
   "source": [
    "To ensure proper measurements, we must calibrate the time-of-flight (TOF). This is the time it takes for a signal to travel from the output to the input of the module. To do so, we first play an excitation pulse and acquire it back into"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1ee38a9a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.819626Z",
     "iopub.status.busy": "2024-09-02T01:43:27.819424Z",
     "iopub.status.idle": "2024-09-02T01:43:27.822722Z",
     "shell.execute_reply": "2024-09-02T01:43:27.822017Z"
    }
   },
   "outputs": [],
   "source": [
    "prog = \"\"\"\n",
    "play    1, 0, 4     # start readout pulse\n",
    "acquire 2, 0, 16384 # start the 'single' acquisition sequence and wait for the length of the scope acquisition window\n",
    "stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6971a5d7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.825034Z",
     "iopub.status.busy": "2024-09-02T01:43:27.824855Z",
     "iopub.status.idle": "2024-09-02T01:43:27.940326Z",
     "shell.execute_reply": "2024-09-02T01:43:27.936970Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "daed5646",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.952042Z",
     "iopub.status.busy": "2024-09-02T01:43:27.951050Z",
     "iopub.status.idle": "2024-09-02T01:43:27.988347Z",
     "shell.execute_reply": "2024-09-02T01:43:27.985097Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\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_status(0)\n",
    "readout_module.store_scope_acquisition(0, \"single\")\n",
    "# Print status of sequencer.\n",
    "print(readout_module.get_sequencer_status(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dfee8e24",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:27.999241Z",
     "iopub.status.busy": "2024-09-02T01:43:27.998353Z",
     "iopub.status.idle": "2024-09-02T01:43:28.103791Z",
     "shell.execute_reply": "2024-09-02T01:43:28.102050Z"
    }
   },
   "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": "code",
   "execution_count": 17,
   "id": "2a08eee9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.109776Z",
     "iopub.status.busy": "2024-09-02T01:43:28.109325Z",
     "iopub.status.idle": "2024-09-02T01:43:28.561796Z",
     "shell.execute_reply": "2024-09-02T01:43:28.561100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "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.ylabel(\"Amplitude (V)\")\n",
    "plt.xlabel(\"Time (ns)\")\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.ylabel(\"Amplitude (V)\")\n",
    "plt.xlabel(\"Time (ns)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2f701a85",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.564205Z",
     "iopub.status.busy": "2024-09-02T01:43:28.564001Z",
     "iopub.status.idle": "2024-09-02T01:43:28.567670Z",
     "shell.execute_reply": "2024-09-02T01:43:28.566924Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Measured TOF: 151.33333333333334\n",
      "Rounded TOF:  151\n"
     ]
    }
   ],
   "source": [
    "tof = int(tof_measured)  # time of flight must be an integer\n",
    "print(\"Measured TOF:\", tof_measured)\n",
    "print(\"Rounded TOF: \", tof)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52d745d5",
   "metadata": {},
   "source": [
    "## Measure qubit histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "81b1503d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.569940Z",
     "iopub.status.busy": "2024-09-02T01:43:28.569760Z",
     "iopub.status.idle": "2024-09-02T01:43:28.572703Z",
     "shell.execute_reply": "2024-09-02T01:43:28.572056Z"
    }
   },
   "outputs": [],
   "source": [
    "prog = f\"\"\"\n",
    "    move 0, R0\n",
    "    start: set_mrk 1\n",
    "    play 2, 3, {tof}\n",
    "    acquire 0, R0, 120\n",
    "    play 4, 5, {tof}\n",
    "    acquire 1, R0, 120\n",
    "    add R0, 1, R0\n",
    "    wait 4000\n",
    "    jlt R0, 1024, @start\n",
    "    set_mrk 0\n",
    "    upd_param 4\n",
    "    stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "93ae64cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.574899Z",
     "iopub.status.busy": "2024-09-02T01:43:28.574706Z",
     "iopub.status.idle": "2024-09-02T01:43:28.693806Z",
     "shell.execute_reply": "2024-09-02T01:43:28.690593Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "84337ef9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.704128Z",
     "iopub.status.busy": "2024-09-02T01:43:28.703227Z",
     "iopub.status.idle": "2024-09-02T01:43:28.754216Z",
     "shell.execute_reply": "2024-09-02T01:43:28.751026Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "print(readout_module.sequencer0.get_sequencer_status(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b61e17d6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.765209Z",
     "iopub.status.busy": "2024-09-02T01:43:28.764317Z",
     "iopub.status.idle": "2024-09-02T01:43:28.794725Z",
     "shell.execute_reply": "2024-09-02T01:43:28.791322Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "05404568",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.806175Z",
     "iopub.status.busy": "2024-09-02T01:43:28.805250Z",
     "iopub.status.idle": "2024-09-02T01:43:28.821299Z",
     "shell.execute_reply": "2024-09-02T01:43:28.818648Z"
    }
   },
   "outputs": [],
   "source": [
    "state0 = np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) + 1j * np.array(\n",
    "    data[\"state0\"][\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]\n",
    ")\n",
    "state1 = np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) + 1j * np.array(\n",
    "    data[\"state1\"][\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a18ce4b9",
   "metadata": {},
   "source": [
    "Given this data, we can now determine the rotation and thresholding values to discriminate the $\\left|0\\right\\rangle$ state from the $\\left|1\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e924e965",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.831780Z",
     "iopub.status.busy": "2024-09-02T01:43:28.830884Z",
     "iopub.status.idle": "2024-09-02T01:43:28.846542Z",
     "shell.execute_reply": "2024-09-02T01:43:28.843449Z"
    }
   },
   "outputs": [],
   "source": [
    "rotation = np.mod(-np.angle(np.mean(state1) - np.mean(state0)), 2 * np.pi)\n",
    "threshold = (np.exp(1j * rotation) * (np.mean(state1) + np.mean(state0))).real / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "660ef8a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:28.853975Z",
     "iopub.status.busy": "2024-09-02T01:43:28.853397Z",
     "iopub.status.idle": "2024-09-02T01:43:29.087683Z",
     "shell.execute_reply": "2024-09-02T01:43:29.086906Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaling = 1000 / integration_length\n",
    "maxr = max(np.max(np.abs(state0)), np.max(np.abs(state1))) * scaling\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "cmap_blue = colors.LinearSegmentedColormap.from_list(\"qblox\", [\"#00839F00\", \"#00839FFF\"])\n",
    "cmap_red = colors.LinearSegmentedColormap.from_list(\"qblox_red\", [\"#F2300000\", \"#F23000FF\"])\n",
    "ax.hexbin(state0.real * scaling, state0.imag * scaling, cmap=cmap_blue)\n",
    "ax.hexbin(state1.real * scaling, state1.imag * scaling, cmap=cmap_red)\n",
    "\n",
    "ax.set_xlim(-maxr, maxr)\n",
    "ax.set_ylim(-maxr, maxr)\n",
    "ax.plot(\n",
    "    ((1j * np.linspace(-maxr, maxr, 100) + threshold) * np.exp(-1j * rotation)).real * scaling,\n",
    "    ((1j * np.linspace(-maxr, maxr, 100) + threshold) * np.exp(-1j * rotation)).imag * scaling,\n",
    "    \"k\",\n",
    ")\n",
    "ax.set_xlabel(\"I (mV)\")\n",
    "ax.set_ylabel(\"Q (mV)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4630ed96",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.090358Z",
     "iopub.status.busy": "2024-09-02T01:43:29.090151Z",
     "iopub.status.idle": "2024-09-02T01:43:29.115634Z",
     "shell.execute_reply": "2024-09-02T01:43:29.114824Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_threshold(threshold)\n",
    "readout_module.sequencer0.thresholded_acq_rotation(rotation * 360 / (2 * np.pi))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56d46c6c",
   "metadata": {},
   "source": [
    "Now that the rotation and thresholding values are programmed into the QRM module, the module will automatically assign a qubit state to every acquisition. By running the same sequence as before, we can check the the module is assigning the correct state to the qubit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ef8c36ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.118453Z",
     "iopub.status.busy": "2024-09-02T01:43:29.118255Z",
     "iopub.status.idle": "2024-09-02T01:43:29.160958Z",
     "shell.execute_reply": "2024-09-02T01:43:29.160106Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "readout_module.sequencer0.delete_acquisition_data(all=True)\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "print(readout_module.sequencer0.get_sequencer_status(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "62bf0462",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.163781Z",
     "iopub.status.busy": "2024-09-02T01:43:29.163554Z",
     "iopub.status.idle": "2024-09-02T01:43:29.182814Z",
     "shell.execute_reply": "2024-09-02T01:43:29.181854Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cddd6352",
   "metadata": {},
   "source": [
    "To check that the assignments are made correctly, we calculate the confusion matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3193b98f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.186547Z",
     "iopub.status.busy": "2024-09-02T01:43:29.186303Z",
     "iopub.status.idle": "2024-09-02T01:43:29.192064Z",
     "shell.execute_reply": "2024-09-02T01:43:29.191029Z"
    }
   },
   "outputs": [],
   "source": [
    "confusion_matrix = [\n",
    "    [\n",
    "        np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 0),\n",
    "        np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    "    ],\n",
    "    [\n",
    "        np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 0),\n",
    "        np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    "    ],\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7d1a06ee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.195846Z",
     "iopub.status.busy": "2024-09-02T01:43:29.195609Z",
     "iopub.status.idle": "2024-09-02T01:43:29.267275Z",
     "shell.execute_reply": "2024-09-02T01:43:29.266289Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 621x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = plt.matshow(confusion_matrix, cmap=\"Blues\", vmin=0, vmax=1024)\n",
    "ax = plt.gca()\n",
    "for i in [0, 1]:\n",
    "    for j in [0, 1]:\n",
    "        ax.annotate(\n",
    "            confusion_matrix[i][j],\n",
    "            xy=(j, i),\n",
    "            horizontalalignment=\"center\",\n",
    "            verticalalignment=\"center\",\n",
    "            color=p.cmap(1024 - confusion_matrix[i][j]),\n",
    "        )\n",
    "plt.xlabel(\"Assigned state\")\n",
    "plt.ylabel(\"Qubit state\")\n",
    "plt.xticks([0, 1], [\"|0>\", \"|1>\"])\n",
    "plt.yticks([0, 1], [\"|0>\", \"|1>\"])\n",
    "ax.xaxis.set_ticks_position(\"bottom\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68e8e262",
   "metadata": {},
   "source": [
    "## Sending results on the trigger network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37e2851f",
   "metadata": {},
   "source": [
    "Now that the module can correctly identify the qubit state, we want to send this result to all other modules in the Cluster. Hence we must enable this functionality and specify an address used for sending these triggers. In this tutorial, we will only use address 1. Note that only one trigger can be sent simultaneously, even if the address is different."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "330e743c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.271014Z",
     "iopub.status.busy": "2024-09-02T01:43:29.270804Z",
     "iopub.status.idle": "2024-09-02T01:43:29.292581Z",
     "shell.execute_reply": "2024-09-02T01:43:29.291745Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_trigger_address(1)\n",
    "readout_module.sequencer0.thresholded_acq_trigger_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cd02e08",
   "metadata": {},
   "source": [
    "To verify that the correct triggers are being sent, we can use the trigger monitor. This monitor can be reset with the following command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fc9b254c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.295538Z",
     "iopub.status.busy": "2024-09-02T01:43:29.295339Z",
     "iopub.status.idle": "2024-09-02T01:43:29.299718Z",
     "shell.execute_reply": "2024-09-02T01:43:29.298807Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster.reset_trigger_monitor_count(address=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c263ef3",
   "metadata": {},
   "source": [
    "Such that the monitor reports both a total trigger count of 0 and no latest trigger (also represented by the value 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "36a42543",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.303064Z",
     "iopub.status.busy": "2024-09-02T01:43:29.302868Z",
     "iopub.status.idle": "2024-09-02T01:43:29.309743Z",
     "shell.execute_reply": "2024-09-02T01:43:29.308888Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 1)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger1_monitor_count(), cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f9d7195",
   "metadata": {},
   "source": [
    "Now, to verify the Cluster is configured correctly, let us run the above program one more time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "9aab907d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.313230Z",
     "iopub.status.busy": "2024-09-02T01:43:29.313035Z",
     "iopub.status.idle": "2024-09-02T01:43:29.380903Z",
     "shell.execute_reply": "2024-09-02T01:43:29.377648Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.delete_acquisition_data(all=True)\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "readout_module.sequencer0.get_sequencer_status(1)\n",
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "befb2d4b",
   "metadata": {},
   "source": [
    "The number of triggers received by the monitor should be equal to the number of measurements that have been classified as the $\\left|1\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c77ad374",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.393097Z",
     "iopub.status.busy": "2024-09-02T01:43:29.392219Z",
     "iopub.status.idle": "2024-09-02T01:43:29.407238Z",
     "shell.execute_reply": "2024-09-02T01:43:29.405312Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acquisition: 1024\n",
      "Monitor:     1024\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Acquisition:\",\n",
    "    np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1)\n",
    "    + np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    ")\n",
    "print(\"Monitor:    \", cluster.trigger1_monitor_count())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f2e7a63",
   "metadata": {},
   "source": [
    "The most recent trigger that has been received should now be equal to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8b02b635",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.412658Z",
     "iopub.status.busy": "2024-09-02T01:43:29.412317Z",
     "iopub.status.idle": "2024-09-02T01:43:29.420318Z",
     "shell.execute_reply": "2024-09-02T01:43:29.419155Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34afd865",
   "metadata": {},
   "source": [
    "Besides investigating the sent triggers using this monitor, it can be convenient to visualize the triggers on an oscilloscope as they are being sent. In order the enable sending the trigger on marker 4, use the following commands. Enabling triggers on the marker outputs can also be used to control external equipment based on the measurement results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "a00bcc79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.423771Z",
     "iopub.status.busy": "2024-09-02T01:43:29.423514Z",
     "iopub.status.idle": "2024-09-02T01:43:29.452775Z",
     "shell.execute_reply": "2024-09-02T01:43:29.450105Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_marker_en(True)\n",
    "readout_module.sequencer0.thresholded_acq_marker_address(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a5d9ece",
   "metadata": {},
   "source": [
    "Now connect your marker output 4 to the oscilloscope and run the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "29242efe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.462728Z",
     "iopub.status.busy": "2024-09-02T01:43:29.462012Z",
     "iopub.status.idle": "2024-09-02T01:43:29.474217Z",
     "shell.execute_reply": "2024-09-02T01:43:29.472997Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fba1c6ff",
   "metadata": {},
   "source": [
    "The following image can be obtained on the oscilloscope (C1 (yellow) is the marker 1 output whereas C3(blue) is marker 4 output:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8311e40a",
   "metadata": {},
   "source": [
    "![SDS6204A_PNG_5 (2).png](9d786b40-430b-47ab-9721-94f3e25fd196.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68b9b49d",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Active reset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7915b783",
   "metadata": {},
   "source": [
    "As the final part of this tutorial, we will show how the triggers we have been generating above, can be used to affect the behavior of other sequencers in the Cluster. We will show this capability using a active reset protocol as an example. Basically, in order to perform active reset on a qubit, we must first measure the qubit state, and if the state equals $\\left|1\\right\\rangle$, we must play a $\\pi$-pulse to flip the qubit back to the $\\left|0\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef22fb87",
   "metadata": {},
   "source": [
    "In a real qubit setup, the QRM would play identical readout pulses and the actual qubit state would influence the acquisition result. For this tutorial, in lieu of a qubit, we determine the qubit state results in advance for the QRM, and play a different waveform depending on this pre-determined state. To still properly demonstrate the feedback capability, we ensure that the QCM is not aware of the pre-determined choices in advance, as it can figure out from the acquisitions results whether it should play a $\\pi$-pulse."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2658f8bd",
   "metadata": {},
   "source": [
    "Generate 100 random qubit states:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "455014db",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.479385Z",
     "iopub.status.busy": "2024-09-02T01:43:29.479099Z",
     "iopub.status.idle": "2024-09-02T01:43:29.485793Z",
     "shell.execute_reply": "2024-09-02T01:43:29.484750Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,\n",
       "       0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0,\n",
       "       1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1,\n",
       "       0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1,\n",
       "       0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "length = 100\n",
    "states = np.random.choice(2, length)\n",
    "states"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8cb06bc",
   "metadata": {},
   "source": [
    "For the QRM program, this means playing waveforms `'state0_I'` and `'state0_Q'` if the qubit state has to appear as $\\left|0\\right\\rangle$ while playing waveforms `'state1_I'` and `'state1_Q'` if the qubit state has to appear as $\\left|1\\right\\rangle$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "b8bcdbda",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.490637Z",
     "iopub.status.busy": "2024-09-02T01:43:29.490421Z",
     "iopub.status.idle": "2024-09-02T01:43:29.494542Z",
     "shell.execute_reply": "2024-09-02T01:43:29.493696Z"
    }
   },
   "outputs": [],
   "source": [
    "qrm_prog = \"\"\"\n",
    "wait_sync 4\n",
    "set_mrk 1\n",
    "upd_param 1000\n",
    "move 0, R0\n",
    "\"\"\"\n",
    "for s in states:\n",
    "    if s == 1:\n",
    "        qrm_prog += f\"\"\"set_mrk 3\n",
    "        play 4, 5, {tof}\n",
    "        set_mrk 1\"\"\"\n",
    "    else:\n",
    "        qrm_prog += f\"play 2, 3, {tof}\"\n",
    "    qrm_prog += \"\"\"\n",
    "    acquire 0, R0, 120\n",
    "    wait 1000\n",
    "    \"\"\"\n",
    "qrm_prog += \"\"\"set_mrk 0\n",
    "upd_param 1000\n",
    "stop\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "454563a4",
   "metadata": {},
   "source": [
    "So, in order to achieve feedback from the QRM module, we only had to set the thresholding and trigger parameters without any changes to the Q1ASM program. On the receiving side, for the QCM, the feedback is controlled via Q1ASM, however. Let's build up the program step by step."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33da0167",
   "metadata": {},
   "source": [
    "First, we need to tell the module to listen for triggers on address 1 with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f6639473",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.497271Z",
     "iopub.status.busy": "2024-09-02T01:43:29.497076Z",
     "iopub.status.idle": "2024-09-02T01:43:29.500196Z",
     "shell.execute_reply": "2024-09-02T01:43:29.499409Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog = \"set_latch_en 1, 4     # Enabling listening to triggers on address 1\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a4d0c3f",
   "metadata": {},
   "source": [
    "We can then sync with the other module and program our loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4e558ec8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.503314Z",
     "iopub.status.busy": "2024-09-02T01:43:29.503137Z",
     "iopub.status.idle": "2024-09-02T01:43:29.506127Z",
     "shell.execute_reply": "2024-09-02T01:43:29.505414Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += f\"\"\"\n",
    "wait_sync 4\n",
    "wait 1000\n",
    "move {len(states)}, R0\n",
    "s:\n",
    "\"\"\"\n",
    "# Here we need to write the code to receive and react to triggers\n",
    "# Therefore, we store then end of the program in a separate variable for now\n",
    "qcm_prog_tail = \"\"\"\n",
    "loop R0, @s\n",
    "stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95c97d5e",
   "metadata": {},
   "source": [
    "For every iteration of our loop, we first need to clear any received triggers and then wait for any new trigger to come in:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f7551379",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.509440Z",
     "iopub.status.busy": "2024-09-02T01:43:29.509274Z",
     "iopub.status.idle": "2024-09-02T01:43:29.512199Z",
     "shell.execute_reply": "2024-09-02T01:43:29.511450Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += f\"\"\"\n",
    "latch_rst {tof+120}   # Deletes all previously received triggers\n",
    "wait      300         # gives the acquisition result time to be received by the QCM\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b462396",
   "metadata": {},
   "source": [
    "Next, we program a conditional play instruction. In order to mark a `play`, `acquire`, `acquire_weighed` or `wait` instruction as conditional, we open a conditionality block using the `set_cond <enable> <address_mask> <operator> <else_wait>` instruction.\n",
    "\n",
    "The `<enable>` argument sets whether subsequent real-time pipeline instructions are conditional or not. In case a conditional instruction is skipped, the `<else_wait>` argument determines how long the real-time pipeline will stall (minimum is 4 ns).\n",
    "\n",
    "The `<address_mask>` and `<operator>` determine the conditionality, if the condition evaluates to `True` the instruction es executed, otherwise the instruction will be skipped (equivalent to a `wait <else_wait>` instruction).\n",
    "\n",
    "When only listening to a single trigger address, the `<address mask>` should be made equal to `2**(address-1)` and the `<operator>` should be `0` for `OR` or `2` for `AND` (both having the same effect for a single input, feedback based on multiple trigger addresses is not covered in this tutorial). To invert the conditional, `<operator>` `1` for `NOR` or `3` for `NAND` can be used.\n",
    "\n",
    "For active reset, we can enable the conditional with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0ba4423d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.515286Z",
     "iopub.status.busy": "2024-09-02T01:43:29.515120Z",
     "iopub.status.idle": "2024-09-02T01:43:29.517981Z",
     "shell.execute_reply": "2024-09-02T01:43:29.517245Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"\"\"\n",
    "set_cond 1, 1, 0, 700 # Enable conditional commands\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc29b223",
   "metadata": {},
   "source": [
    "Next we can invoke our play command as usual:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "8ebc30c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.520274Z",
     "iopub.status.busy": "2024-09-02T01:43:29.520110Z",
     "iopub.status.idle": "2024-09-02T01:43:29.522865Z",
     "shell.execute_reply": "2024-09-02T01:43:29.522188Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"play 6, 7, 700\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52603b63",
   "metadata": {},
   "source": [
    "Finally, do not forget to disable the conditional commands again (after the first `0`, the parameters do not matter):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "9f6af64c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.525167Z",
     "iopub.status.busy": "2024-09-02T01:43:29.525001Z",
     "iopub.status.idle": "2024-09-02T01:43:29.527903Z",
     "shell.execute_reply": "2024-09-02T01:43:29.527187Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += (\n",
    "    \"\"\"\n",
    "set_cond 0, 1, 0, 700 # Disable conditional commands again\n",
    "\"\"\"\n",
    "    + qcm_prog_tail\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f19a7d",
   "metadata": {},
   "source": [
    "In summary, the complete QCM program is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b3fa1ec7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.531363Z",
     "iopub.status.busy": "2024-09-02T01:43:29.531196Z",
     "iopub.status.idle": "2024-09-02T01:43:29.534525Z",
     "shell.execute_reply": "2024-09-02T01:43:29.533772Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "set_latch_en 1, 4     # Enabling listening to triggers on address 1\n",
      "wait_sync 4\n",
      "wait 1000\n",
      "move 100, R0\n",
      "s:\n",
      "\n",
      "latch_rst 271   # Deletes all previously received triggers\n",
      "wait      300         # gives the acquisition result time to be received by the QCM\n",
      "\n",
      "set_cond 1, 1, 0, 700 # Enable conditional commands\n",
      "play 6, 7, 700\n",
      "set_cond 0, 1, 0, 700 # Disable conditional commands again\n",
      "\n",
      "loop R0, @s\n",
      "stop\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(qcm_prog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "06c8ed43",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.538179Z",
     "iopub.status.busy": "2024-09-02T01:43:29.537772Z",
     "iopub.status.idle": "2024-09-02T01:43:29.765782Z",
     "shell.execute_reply": "2024-09-02T01:43:29.762555Z"
    }
   },
   "outputs": [],
   "source": [
    "control_module.sequencer1.sync_en(True)  # We did not enable the sync on the QCM sequencer yet\n",
    "\n",
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": qrm_prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "\n",
    "control_module.sequencer1.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": qcm_prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")\n",
    "control_module.sequencer1.arm_sequencer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f110013",
   "metadata": {},
   "source": [
    "We are all set to witness the conditional playback! Please make sure that you have connected the QCM output 0 to the oscilloscope along with the marker 1 of QRM as trigger and marker 4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "e8f8ac9b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.777410Z",
     "iopub.status.busy": "2024-09-02T01:43:29.776443Z",
     "iopub.status.idle": "2024-09-02T01:43:29.788116Z",
     "shell.execute_reply": "2024-09-02T01:43:29.787374Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.start_sequencer()\n",
    "control_module.start_sequencer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1cd62191",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.790762Z",
     "iopub.status.busy": "2024-09-02T01:43:29.790573Z",
     "iopub.status.idle": "2024-09-02T01:43:29.800144Z",
     "shell.execute_reply": "2024-09-02T01:43:29.799468Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QRM:\n",
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "QCM:\n",
      "Status: OKAY, State: STOPPED, Info Flags: NONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "print(\"QRM:\")\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print(\"QCM:\")\n",
    "print(control_module.get_sequencer_status(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "472004d5",
   "metadata": {},
   "source": [
    "On the oscilloscope, you should see an image as below (CH1 (yellow) : Marker 1, CH2 (pink): Marker 2, CH3(blue) : QCM Output 0, CH4(green) : Marker 4). Marker 2 activation corresponds to a state 1 signal by QRM which is confirmed by the Marker 4\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e17997e",
   "metadata": {},
   "source": [
    "![image.png](5a08cf99-6cfa-49a0-94c7-accea41f8c21.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08da6221",
   "metadata": {},
   "source": [
    "## Stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "551f47b8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-02T01:43:29.802808Z",
     "iopub.status.busy": "2024-09-02T01:43:29.802617Z",
     "iopub.status.idle": "2024-09-02T01:43:32.125272Z",
     "shell.execute_reply": "2024-09-02T01:43:32.124559Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QCM :\n",
      "Status: OKAY, State: STOPPED, Info Flags: NONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n",
      "QRM :\n",
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\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_status(0))\n",
    "print()\n",
    "\n",
    "print(\"QRM :\")\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print()\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
 ],
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