{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ee7d78a2",
   "metadata": {},
   "source": [
    "# Conditional Playback"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ff99753",
   "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, as demonstrated in the synchronization tutorial. We advise familiarizing yourself with that tutorial before continuing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77087d03",
   "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": "9b5f17d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:24.401508Z",
     "iopub.status.busy": "2024-03-28T14:37:24.400179Z",
     "iopub.status.idle": "2024-03-28T14:37:25.447247Z",
     "shell.execute_reply": "2024-03-28T14:37:25.446251Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "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 qcodes.instrument import find_or_create_instrument\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from qblox_instruments.qcodes_drivers.module import QcmQrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a83461ff",
   "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": "efaf055e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:25.451789Z",
     "iopub.status.busy": "2024-03-28T14:37:25.451789Z",
     "iopub.status.idle": "2024-03-28T14:37:27.508787Z",
     "shell.execute_reply": "2024-03-28T14:37:27.507311Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Devices:\n",
      " - 10.10.200.13 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QSE_1\" and serial number 00015_2321_005\n",
      " - 10.10.200.42 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"QAE-I\" and serial number 00015_2321_004\n",
      " - 10.10.200.43 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QAE-2\" and serial number 00015_2206_003\n",
      " - 10.10.200.50 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2219_003\n",
      " - 10.10.200.53 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2320_004\n",
      " - 10.10.200.70 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number 123-456-789\n",
      " - 10.10.200.80 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number not_valid\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a0117bea",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:27.513084Z",
     "iopub.status.busy": "2024-03-28T14:37:27.513084Z",
     "iopub.status.idle": "2024-03-28T14:37:27.524073Z",
     "shell.execute_reply": "2024-03-28T14:37:27.522704Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdb448ad",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5a07918b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:27.528457Z",
     "iopub.status.busy": "2024-03-28T14:37:27.528457Z",
     "iopub.status.idle": "2024-03-28T14:37:28.419834Z",
     "shell.execute_reply": "2024-03-28T14:37:28.419323Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "cluster = find_or_create_instrument(\n",
    "    Cluster,\n",
    "    recreate=True,\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg=(\n",
    "        {\n",
    "            2: ClusterType.CLUSTER_QCM,\n",
    "            4: ClusterType.CLUSTER_QRM,\n",
    "            6: ClusterType.CLUSTER_QCM_RF,\n",
    "            8: ClusterType.CLUSTER_QRM_RF,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6770fa0",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b41f8ecc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.425382Z",
     "iopub.status.busy": "2024-03-28T14:37:28.424381Z",
     "iopub.status.idle": "2024-03-28T14:37:28.435732Z",
     "shell.execute_reply": "2024-03-28T14:37:28.434726Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, QcmQrm]:\n",
    "    def checked_filter_fn(mod: ClusterType) -> bool:\n",
    "        if filter_fn is not None:\n",
    "            return filter_fn(mod)\n",
    "        return True\n",
    "\n",
    "    return {\n",
    "        mod.slot_idx: mod for mod in cluster.modules if mod.present() and checked_filter_fn(mod)\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8b35abb0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.441404Z",
     "iopub.status.busy": "2024-03-28T14:37:28.440364Z",
     "iopub.status.idle": "2024-03-28T14:37:28.560975Z",
     "shell.execute_reply": "2024-03-28T14:37:28.559424Z"
    }
   },
   "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": "9c8d4748",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.565979Z",
     "iopub.status.busy": "2024-03-28T14:37:28.564997Z",
     "iopub.status.idle": "2024-03-28T14:37:28.577030Z",
     "shell.execute_reply": "2024-03-28T14:37:28.575042Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a796b706",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.581543Z",
     "iopub.status.busy": "2024-03-28T14:37:28.580530Z",
     "iopub.status.idle": "2024-03-28T14:37:28.697807Z",
     "shell.execute_reply": "2024-03-28T14:37:28.697807Z"
    }
   },
   "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": "b4158adb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.702353Z",
     "iopub.status.busy": "2024-03-28T14:37:28.702353Z",
     "iopub.status.idle": "2024-03-28T14:37:28.715850Z",
     "shell.execute_reply": "2024-03-28T14:37:28.713490Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "control_module = control_modules[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a55c98fb",
   "metadata": {},
   "source": [
    "## Sequencer configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "306e69ed",
   "metadata": {},
   "source": [
    "Define all waveforms necessary for this tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "35b7e9b6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.720966Z",
     "iopub.status.busy": "2024-03-28T14:37:28.719886Z",
     "iopub.status.idle": "2024-03-28T14:37:28.730513Z",
     "shell.execute_reply": "2024-03-28T14:37:28.729007Z"
    }
   },
   "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": "34ea653b",
   "metadata": {},
   "source": [
    "Specify acquisitions that are used in the tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a146d03c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.735285Z",
     "iopub.status.busy": "2024-03-28T14:37:28.735285Z",
     "iopub.status.idle": "2024-03-28T14:37:28.745190Z",
     "shell.execute_reply": "2024-03-28T14:37:28.743682Z"
    }
   },
   "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": "c48cdcf8",
   "metadata": {},
   "source": [
    "Set up sequencer parameters for both QRM and QCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ede437a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.750199Z",
     "iopub.status.busy": "2024-03-28T14:37:28.749195Z",
     "iopub.status.idle": "2024-03-28T14:37:28.867213Z",
     "shell.execute_reply": "2024-03-28T14:37:28.866698Z"
    }
   },
   "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": "04406260",
   "metadata": {},
   "source": [
    "## Calibrate TOF"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12336cf3",
   "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": "9f7aa34b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.872829Z",
     "iopub.status.busy": "2024-03-28T14:37:28.871820Z",
     "iopub.status.idle": "2024-03-28T14:37:28.883455Z",
     "shell.execute_reply": "2024-03-28T14:37:28.882089Z"
    }
   },
   "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": "2484a6ef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:28.887993Z",
     "iopub.status.busy": "2024-03-28T14:37:28.887993Z",
     "iopub.status.idle": "2024-03-28T14:37:29.037375Z",
     "shell.execute_reply": "2024-03-28T14:37:29.036284Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "84613c69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.041965Z",
     "iopub.status.busy": "2024-03-28T14:37:29.041965Z",
     "iopub.status.idle": "2024-03-28T14:37:29.083969Z",
     "shell.execute_reply": "2024-03-28T14:37:29.082953Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:3210: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:2414: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:85: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:77: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:129: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\n"
     ]
    }
   ],
   "source": [
    "# Arm and start sequencer.\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer and acquisition to finish with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, 1)\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": "ae15d3e0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.088975Z",
     "iopub.status.busy": "2024-03-28T14:37:29.087572Z",
     "iopub.status.idle": "2024-03-28T14:37:29.207057Z",
     "shell.execute_reply": "2024-03-28T14:37:29.205749Z"
    }
   },
   "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": "8a9f813a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.212776Z",
     "iopub.status.busy": "2024-03-28T14:37:29.211776Z",
     "iopub.status.idle": "2024-03-28T14:37:29.594756Z",
     "shell.execute_reply": "2024-03-28T14:37:29.593239Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 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": "f018f696",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.599784Z",
     "iopub.status.busy": "2024-03-28T14:37:29.598787Z",
     "iopub.status.idle": "2024-03-28T14:37:29.609821Z",
     "shell.execute_reply": "2024-03-28T14:37:29.608827Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Measured TOF: 143.33333333333334\n",
      "Rounded TOF:  143\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": "6d21ed70",
   "metadata": {},
   "source": [
    "## Measure qubit histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ebc8326d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.614823Z",
     "iopub.status.busy": "2024-03-28T14:37:29.613823Z",
     "iopub.status.idle": "2024-03-28T14:37:29.626681Z",
     "shell.execute_reply": "2024-03-28T14:37:29.624902Z"
    }
   },
   "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": "ebdbf24b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.631699Z",
     "iopub.status.busy": "2024-03-28T14:37:29.630692Z",
     "iopub.status.idle": "2024-03-28T14:37:29.809911Z",
     "shell.execute_reply": "2024-03-28T14:37:29.807753Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "50c21fef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.814288Z",
     "iopub.status.busy": "2024-03-28T14:37:29.813283Z",
     "iopub.status.idle": "2024-03-28T14:37:29.869339Z",
     "shell.execute_reply": "2024-03-28T14:37:29.869339Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\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": "dc12e23c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.874845Z",
     "iopub.status.busy": "2024-03-28T14:37:29.873475Z",
     "iopub.status.idle": "2024-03-28T14:37:29.917560Z",
     "shell.execute_reply": "2024-03-28T14:37:29.915454Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "304ac255",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.922507Z",
     "iopub.status.busy": "2024-03-28T14:37:29.921497Z",
     "iopub.status.idle": "2024-03-28T14:37:29.932832Z",
     "shell.execute_reply": "2024-03-28T14:37:29.931110Z"
    }
   },
   "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": "d5722fca",
   "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": "79539c3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.936959Z",
     "iopub.status.busy": "2024-03-28T14:37:29.936959Z",
     "iopub.status.idle": "2024-03-28T14:37:29.948654Z",
     "shell.execute_reply": "2024-03-28T14:37:29.946803Z"
    }
   },
   "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": "ff719e97",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:29.953207Z",
     "iopub.status.busy": "2024-03-28T14:37:29.952207Z",
     "iopub.status.idle": "2024-03-28T14:37:30.088164Z",
     "shell.execute_reply": "2024-03-28T14:37:30.086146Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 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)))\n",
    "hist0, xedges, yedges = np.histogram2d(\n",
    "    state0.real, state0.imag, range=((-maxr, maxr), (-maxr, maxr)), bins=100\n",
    ")\n",
    "hist1, xedges, yedges = np.histogram2d(\n",
    "    state1.real, state1.imag, range=((-maxr, maxr), (-maxr, maxr)), bins=100\n",
    ")\n",
    "\n",
    "plt.imshow(\n",
    "    1 - np.array((hist0, hist0 + hist1, hist1)).transpose(2, 1, 0) / np.max(hist0 + hist1),\n",
    "    extent=(-maxr * scaling, maxr * scaling, -maxr * scaling, maxr * scaling),\n",
    "    origin=\"lower\",\n",
    ")\n",
    "plt.plot(\n",
    "    ((1j * xedges + threshold) * np.exp(-1j * rotation)).real * scaling,\n",
    "    ((1j * xedges + threshold) * np.exp(-1j * rotation)).imag * scaling,\n",
    "    \"k\",\n",
    ")\n",
    "plt.xlabel(\"I (mV)\")\n",
    "plt.ylabel(\"Q (mV)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "172c2d9d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.092165Z",
     "iopub.status.busy": "2024-03-28T14:37:30.092165Z",
     "iopub.status.idle": "2024-03-28T14:37:30.134008Z",
     "shell.execute_reply": "2024-03-28T14:37:30.132984Z"
    }
   },
   "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": "7cf71bb2",
   "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": "d80d1719",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.140154Z",
     "iopub.status.busy": "2024-03-28T14:37:30.139103Z",
     "iopub.status.idle": "2024-03-28T14:37:30.178216Z",
     "shell.execute_reply": "2024-03-28T14:37:30.178216Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\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": "aa756c7a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.183154Z",
     "iopub.status.busy": "2024-03-28T14:37:30.183154Z",
     "iopub.status.idle": "2024-03-28T14:37:30.224842Z",
     "shell.execute_reply": "2024-03-28T14:37:30.223837Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "632d351e",
   "metadata": {},
   "source": [
    "To check that the assignments are made correctly, we calculate the confusion matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2566884f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.231172Z",
     "iopub.status.busy": "2024-03-28T14:37:30.230139Z",
     "iopub.status.idle": "2024-03-28T14:37:30.240001Z",
     "shell.execute_reply": "2024-03-28T14:37:30.238989Z"
    }
   },
   "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": "5189d2ff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.243916Z",
     "iopub.status.busy": "2024-03-28T14:37:30.243916Z",
     "iopub.status.idle": "2024-03-28T14:37:30.348351Z",
     "shell.execute_reply": "2024-03-28T14:37:30.346331Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 480x480 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": "62c40ad6",
   "metadata": {},
   "source": [
    "## Sending results on the trigger network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "770618ca",
   "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": "75128c16",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.351928Z",
     "iopub.status.busy": "2024-03-28T14:37:30.351928Z",
     "iopub.status.idle": "2024-03-28T14:37:30.393471Z",
     "shell.execute_reply": "2024-03-28T14:37:30.391476Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_trigger_address(1)\n",
    "readout_module.sequencer0.thresholded_acq_trigger_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ec50e1e",
   "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": "8a725a03",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.397789Z",
     "iopub.status.busy": "2024-03-28T14:37:30.396769Z",
     "iopub.status.idle": "2024-03-28T14:37:30.407581Z",
     "shell.execute_reply": "2024-03-28T14:37:30.406601Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster.reset_trigger_monitor_count(address=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c7ec577",
   "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": "ddb7ce28",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.413601Z",
     "iopub.status.busy": "2024-03-28T14:37:30.412600Z",
     "iopub.status.idle": "2024-03-28T14:37:30.440032Z",
     "shell.execute_reply": "2024-03-28T14:37:30.439072Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 0)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger1_monitor_count(), cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35a671fe",
   "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": "721d6657",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.444163Z",
     "iopub.status.busy": "2024-03-28T14:37:30.444163Z",
     "iopub.status.idle": "2024-03-28T14:37:30.501510Z",
     "shell.execute_reply": "2024-03-28T14:37:30.499996Z"
    }
   },
   "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": "8a20e4c2",
   "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": "55561f09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.506035Z",
     "iopub.status.busy": "2024-03-28T14:37:30.504546Z",
     "iopub.status.idle": "2024-03-28T14:37:30.517037Z",
     "shell.execute_reply": "2024-03-28T14:37:30.515977Z"
    }
   },
   "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": "464b2ada",
   "metadata": {},
   "source": [
    "The most recent trigger that has been received should now be equal to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "870b7dbf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.521155Z",
     "iopub.status.busy": "2024-03-28T14:37:30.520128Z",
     "iopub.status.idle": "2024-03-28T14:37:30.531954Z",
     "shell.execute_reply": "2024-03-28T14:37:30.530855Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c75de536",
   "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": "5d70ff04",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.538230Z",
     "iopub.status.busy": "2024-03-28T14:37:30.538230Z",
     "iopub.status.idle": "2024-03-28T14:37:30.577850Z",
     "shell.execute_reply": "2024-03-28T14:37:30.576752Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_marker_en(True)\n",
    "readout_module.sequencer0.thresholded_acq_marker_address(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d243e3d",
   "metadata": {},
   "source": [
    "Now connect your marker output 4 to the oscilloscope and run the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7c7b22d2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.582141Z",
     "iopub.status.busy": "2024-03-28T14:37:30.580922Z",
     "iopub.status.idle": "2024-03-28T14:37:30.609305Z",
     "shell.execute_reply": "2024-03-28T14:37:30.607768Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82c06964",
   "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": "f77acdab",
   "metadata": {},
   "source": [
    "![SDS6204A_PNG_5 (2).png](9d786b40-430b-47ab-9721-94f3e25fd196.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6def3edb",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Active reset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5470fe9c",
   "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": "b47c45b2",
   "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": "75a81a43",
   "metadata": {},
   "source": [
    "Generate 100 random qubit states:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6fe2948a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.613312Z",
     "iopub.status.busy": "2024-03-28T14:37:30.613312Z",
     "iopub.status.idle": "2024-03-28T14:37:30.640936Z",
     "shell.execute_reply": "2024-03-28T14:37:30.639358Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0,\n",
       "       0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1,\n",
       "       1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0,\n",
       "       0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 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": "16ba328d",
   "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": "764a1a0f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.645936Z",
     "iopub.status.busy": "2024-03-28T14:37:30.644936Z",
     "iopub.status.idle": "2024-03-28T14:37:30.655793Z",
     "shell.execute_reply": "2024-03-28T14:37:30.654765Z"
    }
   },
   "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": "10ce5c6d",
   "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": "9cd9a0f2",
   "metadata": {},
   "source": [
    "First, we need to tell the module to listen for triggers on address 1 with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "287129de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.659796Z",
     "iopub.status.busy": "2024-03-28T14:37:30.659796Z",
     "iopub.status.idle": "2024-03-28T14:37:30.671794Z",
     "shell.execute_reply": "2024-03-28T14:37:30.670230Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog = \"set_latch_en 1, 4     # Enabling listening to triggers on address 1\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd7b0192",
   "metadata": {},
   "source": [
    "We can then sync with the other module and program our loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "fa4d6530",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.676143Z",
     "iopub.status.busy": "2024-03-28T14:37:30.675148Z",
     "iopub.status.idle": "2024-03-28T14:37:30.687971Z",
     "shell.execute_reply": "2024-03-28T14:37:30.685819Z"
    }
   },
   "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": "ef830273",
   "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": "2338f81b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.693402Z",
     "iopub.status.busy": "2024-03-28T14:37:30.692421Z",
     "iopub.status.idle": "2024-03-28T14:37:30.702547Z",
     "shell.execute_reply": "2024-03-28T14:37:30.701783Z"
    }
   },
   "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": "9916e4b5",
   "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": "aaaf1482",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.708065Z",
     "iopub.status.busy": "2024-03-28T14:37:30.707065Z",
     "iopub.status.idle": "2024-03-28T14:37:30.717822Z",
     "shell.execute_reply": "2024-03-28T14:37:30.716654Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"\"\"\n",
    "set_cond 1, 1, 0, 700 # Enable conditional commands\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cb74a73",
   "metadata": {},
   "source": [
    "Next we can invoke our play command as usual:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "9d43a278",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.722350Z",
     "iopub.status.busy": "2024-03-28T14:37:30.722350Z",
     "iopub.status.idle": "2024-03-28T14:37:30.732613Z",
     "shell.execute_reply": "2024-03-28T14:37:30.731604Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"play 6, 7, 700\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0092c5d",
   "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": "66aa4764",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.738173Z",
     "iopub.status.busy": "2024-03-28T14:37:30.737173Z",
     "iopub.status.idle": "2024-03-28T14:37:30.748146Z",
     "shell.execute_reply": "2024-03-28T14:37:30.746892Z"
    }
   },
   "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": "97d1a80a",
   "metadata": {},
   "source": [
    "In summary, the complete QCM program is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6eb1b668",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.752944Z",
     "iopub.status.busy": "2024-03-28T14:37:30.751183Z",
     "iopub.status.idle": "2024-03-28T14:37:30.764385Z",
     "shell.execute_reply": "2024-03-28T14:37:30.762564Z"
    }
   },
   "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 263   # 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": "9479feaf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:30.769662Z",
     "iopub.status.busy": "2024-03-28T14:37:30.767914Z",
     "iopub.status.idle": "2024-03-28T14:37:31.056091Z",
     "shell.execute_reply": "2024-03-28T14:37:31.054088Z"
    }
   },
   "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": "7453d856",
   "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": "bfbfb871",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:31.059612Z",
     "iopub.status.busy": "2024-03-28T14:37:31.059612Z",
     "iopub.status.idle": "2024-03-28T14:37:31.087833Z",
     "shell.execute_reply": "2024-03-28T14:37:31.085900Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.start_sequencer()\n",
    "control_module.start_sequencer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "7e08865a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:31.092896Z",
     "iopub.status.busy": "2024-03-28T14:37:31.092896Z",
     "iopub.status.idle": "2024-03-28T14:37:31.117334Z",
     "shell.execute_reply": "2024-03-28T14:37:31.115299Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QRM:\n",
      "Status: STOPPED, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n",
      "QCM:\n",
      "Status: STOPPED, Flags: NONE\n"
     ]
    }
   ],
   "source": [
    "print(\"QRM:\")\n",
    "print(readout_module.get_sequencer_status(0, 1))\n",
    "print(\"QCM:\")\n",
    "print(control_module.get_sequencer_status(0, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d3e0d0d",
   "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": "7bd3283f",
   "metadata": {},
   "source": [
    "![image.png](5a08cf99-6cfa-49a0-94c7-accea41f8c21.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0133f7ad",
   "metadata": {},
   "source": [
    "## Stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "537e17d8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:31.123146Z",
     "iopub.status.busy": "2024-03-28T14:37:31.122060Z",
     "iopub.status.idle": "2024-03-28T14:37:34.561628Z",
     "shell.execute_reply": "2024-03-28T14:37:34.559624Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QCM :\n",
      "Status: STOPPED, Flags: NONE\n",
      "\n",
      "QRM :\n",
      "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:1033: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "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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