{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fab2ce44",
   "metadata": {},
   "source": [
    "# Reference design 3 — Four-qubit multiplexed readout\n",
    "\n",
    "A four-transmon chip with frequency-multiplexed dispersive readout: four resonators of stepped length share one coplanar-waveguide feedline — the standard readout architecture for small superconducting processors.\n",
    "\n",
    "> **Reference design — attribution.** Adapted, with attribution, from the open-source [SQDMetal](https://github.com/sqdlab/SQDMetal) project (Apache-2.0) and its benchmark devices in D. Sommers, P. Pakkiam, Z. Degnan, C.-C. Chiu, D. Gautam, Y.-H. Chen, and A. Fedorov, *\"Open-Source Highly Parallel Electromagnetic Simulations for Superconducting Circuits,\"* [arXiv:2511.01220](https://arxiv.org/abs/2511.01220) (2025). Re-implemented here with stock Quantum Metal components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "701a211b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:21.206096Z",
     "iopub.status.busy": "2026-06-18T21:27:21.205902Z",
     "iopub.status.idle": "2026-06-18T21:27:21.209634Z",
     "shell.execute_reply": "2026-06-18T21:27:21.208532Z"
    }
   },
   "outputs": [],
   "source": [
    "# In Colab / Binder, uncomment to install Quantum Metal (lite, no Qt):\n",
    "# !pip install -q quantum-metal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "44908ce4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:21.211894Z",
     "iopub.status.busy": "2026-06-18T21:27:21.211638Z",
     "iopub.status.idle": "2026-06-18T21:27:23.244987Z",
     "shell.execute_reply": "2026-06-18T21:27:23.243747Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "09:27PM 23s INFO [_start_renderers]: Renderer=gmsh skipped: runtime dependency not installed (renderer_gmsh requires gmsh. Install with: pip install 'quantum-metal[mesh]' (or the legacy alias 'quantum-metal[fem]')).\n"
     ]
    }
   ],
   "source": [
    "import qiskit_metal as qm\n",
    "from qiskit_metal import Dict, designs\n",
    "from qiskit_metal.qlibrary.qubits.transmon_pocket import TransmonPocket\n",
    "from qiskit_metal.qlibrary.tlines.meandered import RouteMeander\n",
    "from qiskit_metal.qlibrary.tlines.pathfinder import RoutePathfinder\n",
    "from qiskit_metal.qlibrary.couplers.coupled_line_tee import CoupledLineTee\n",
    "from qiskit_metal.qlibrary.terminations.launchpad_wb import LaunchpadWirebond\n",
    "\n",
    "design = designs.DesignPlanar()\n",
    "design.overwrite_enabled = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0514ca85",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.246927Z",
     "iopub.status.busy": "2026-06-18T21:27:23.246728Z",
     "iopub.status.idle": "2026-06-18T21:27:23.251629Z",
     "shell.execute_reply": "2026-06-18T21:27:23.250467Z"
    }
   },
   "outputs": [],
   "source": [
    "def feed(a, ap, b, bp, name):\n",
    "    \"\"\"Auto-route a coplanar-waveguide feedline segment between two pins.\"\"\"\n",
    "    RoutePathfinder(\n",
    "        design,\n",
    "        name,\n",
    "        options=dict(\n",
    "            fillet=\"90um\",\n",
    "            pin_inputs=Dict(\n",
    "                start_pin=Dict(component=a, pin=ap), end_pin=Dict(component=b, pin=bp)\n",
    "            ),\n",
    "        ),\n",
    "    )\n",
    "\n",
    "\n",
    "def readout(clt, q, name, length):\n",
    "    \"\"\"Meandered lambda/4 readout resonator: coupled-line tee -> qubit readout pad.\"\"\"\n",
    "    RouteMeander(\n",
    "        design,\n",
    "        name,\n",
    "        options=dict(\n",
    "            fillet=\"90um\",\n",
    "            total_length=length,\n",
    "            lead=Dict(start_straight=\"100um\", end_straight=\"100um\"),\n",
    "            pin_inputs=Dict(\n",
    "                start_pin=Dict(component=clt, pin=\"second_end\"),\n",
    "                end_pin=Dict(component=q, pin=\"readout\"),\n",
    "            ),\n",
    "        ),\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ebf3888",
   "metadata": {},
   "source": [
    "## 1. Four transmons + four readout tees\n",
    "\n",
    "Four transmons in a row; above each, a coupled-line tee on a single shared feedline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a867848c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.254010Z",
     "iopub.status.busy": "2026-06-18T21:27:23.253762Z",
     "iopub.status.idle": "2026-06-18T21:27:23.468301Z",
     "shell.execute_reply": "2026-06-18T21:27:23.467105Z"
    }
   },
   "outputs": [],
   "source": [
    "xs = [-4.5, -1.5, 1.5, 4.5]\n",
    "for i, x in enumerate(xs, 1):\n",
    "    TransmonPocket(\n",
    "        design,\n",
    "        f\"Q{i}\",\n",
    "        options=dict(\n",
    "            pos_x=f\"{x}mm\",\n",
    "            pos_y=\"-1.8mm\",\n",
    "            pad_width=\"425um\",\n",
    "            pocket_height=\"650um\",\n",
    "            connection_pads=dict(readout=dict(loc_W=1, loc_H=1)),\n",
    "        ),\n",
    "    )\n",
    "    CoupledLineTee(\n",
    "        design,\n",
    "        f\"clt{i}\",\n",
    "        options=dict(\n",
    "            pos_x=f\"{x}mm\",\n",
    "            pos_y=\"1.8mm\",\n",
    "            coupling_length=\"350um\",\n",
    "            down_length=\"300um\",\n",
    "            fillet=\"90um\",\n",
    "            open_termination=False,\n",
    "        ),\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95e3f33b",
   "metadata": {},
   "source": [
    "## 2. One shared feedline through all four tees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "57086ff6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.470317Z",
     "iopub.status.busy": "2026-06-18T21:27:23.470129Z",
     "iopub.status.idle": "2026-06-18T21:27:23.615595Z",
     "shell.execute_reply": "2026-06-18T21:27:23.614550Z"
    }
   },
   "outputs": [],
   "source": [
    "LaunchpadWirebond(\n",
    "    design, \"LPin\", options=dict(pos_x=\"-7.5mm\", pos_y=\"1.8mm\", orientation=\"0\")\n",
    ")\n",
    "LaunchpadWirebond(\n",
    "    design, \"LPout\", options=dict(pos_x=\"7.5mm\", pos_y=\"1.8mm\", orientation=\"180\")\n",
    ")\n",
    "feed(\"LPin\", \"tie\", \"clt1\", \"prime_start\", \"f0\")\n",
    "for i in range(1, 4):\n",
    "    feed(f\"clt{i}\", \"prime_end\", f\"clt{i + 1}\", \"prime_start\", f\"f{i}\")\n",
    "feed(\"clt4\", \"prime_end\", \"LPout\", \"tie\", \"f4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1a4a8ee",
   "metadata": {},
   "source": [
    "## 3. Four frequency-multiplexed readout resonators\n",
    "\n",
    "Stepped lengths -> distinct readout frequencies on the one feedline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "490a431b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.617883Z",
     "iopub.status.busy": "2026-06-18T21:27:23.617593Z",
     "iopub.status.idle": "2026-06-18T21:27:23.721074Z",
     "shell.execute_reply": "2026-06-18T21:27:23.720014Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "09:27PM 23s WARNING [check_lengths]: For path table, component=read1, key=trace has short segments that could cause issues with fillet. Values in (1-2)  are index(es) in shapely geometry.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "09:27PM 23s WARNING [check_lengths]: For path table, component=read1, key=cut has short segments that could cause issues with fillet. Values in (1-2)  are index(es) in shapely geometry.\n"
     ]
    }
   ],
   "source": [
    "for i, L in zip(range(1, 5), [\"6.8mm\", \"7.0mm\", \"7.2mm\", \"7.4mm\"]):\n",
    "    readout(f\"clt{i}\", f\"Q{i}\", f\"read{i}\", L)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea307726",
   "metadata": {},
   "source": [
    "## 4. Visualize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa348c40",
   "metadata": {},
   "source": [
    "## Next steps\n",
    "\n",
    "- **Inspect** the design tree: `design.components.keys()` and `design.qgeometry.tables`.\n",
    "- **Export GDS** for fabrication: `design.renderers.gds.export_to_gds('chip.gds')` (Quantum Metal uses the modern `gdstk` backend).\n",
    "- **Simulate**: render to Ansys HFSS/Q3D (the validation gold standard) or to the open-source FEM path (Gmsh + Elmer today; AWS Palace on the roadmap) to extract eigenmodes, *Q*, and the capacitance matrix.\n",
    "- **Tweak**: every dimension above is a parameter — change `total_length` to retune resonator frequencies, or `pos_x`/`pos_y` to relayout."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f7cb41a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.723025Z",
     "iopub.status.busy": "2026-06-18T21:27:23.722835Z",
     "iopub.status.idle": "2026-06-18T21:27:23.729100Z",
     "shell.execute_reply": "2026-06-18T21:27:23.728050Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Q1',\n",
       " 'clt1',\n",
       " 'Q2',\n",
       " 'clt2',\n",
       " 'Q3',\n",
       " 'clt3',\n",
       " 'Q4',\n",
       " 'clt4',\n",
       " 'LPin',\n",
       " 'LPout',\n",
       " 'f0',\n",
       " 'f1',\n",
       " 'f2',\n",
       " 'f3',\n",
       " 'f4',\n",
       " 'read1',\n",
       " 'read2',\n",
       " 'read3',\n",
       " 'read4']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.components.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8435da30",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-18T21:27:23.730848Z",
     "iopub.status.busy": "2026-06-18T21:27:23.730667Z",
     "iopub.status.idle": "2026-06-18T21:27:23.918647Z",
     "shell.execute_reply": "2026-06-18T21:27:23.917451Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = qm.view(design)\n",
    "qm.show_inline(fig)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}