src/examples/2_unitary_compilation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "69a855f1-55dd-482e-94f2-9ad02804be4d",
   "metadata": {},
   "source": [
    "# Compile unitaries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e41e2465-49d8-46b8-b046-6ae1becfb268",
   "metadata": {},
   "source": [
    "In this notebook we want use the unitary compilation model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bde494e-9091-41a4-a601-bbcf9712c564",
   "metadata": {},
   "outputs": [],
   "source": [
    "from genQC.imports import *\n",
    "from genQC.pipeline.diffusion_pipeline import DiffusionPipeline\n",
    "from qiskit import QuantumCircuit\n",
    "from genQC.inference.infer_compilation import generate_comp_tensors, get_gate_and_U_acc\n",
    "from genQC.printing import display_colums\n",
    "from genQC.platform.simulation.qcircuit_sim import instruction_name_to_qiskit_gate\n",
    "import genQC.platform.qcircuit_dataset_construction as data_const\n",
    "import qiskit.quantum_info as qi\n",
    "import genQC.util as util\n",
    "import ast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "029be4f3-0d9a-4d0a-93d9-2338fda7a983",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO]: Cuda device has a capability of 8.6 (>= 8), allowing tf32 matmul.\n"
     ]
    }
   ],
   "source": [
    "device = util.infer_torch_device()  # use cuda if we can\n",
    "util.MemoryCleaner.purge_mem()      # clean existing memory alloc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d4ad484-835f-45fd-8772-212ec7ff00c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def str_cond_to_gate_indices(y):   # helper function, used to check if only allowed gates were used by the model!\n",
    "    assert y[:15] == \"Compile using: \"\n",
    "    c            = ast.literal_eval(y[15:]) \n",
    "    gate_classes = data_const.gate_pool_to_gate_classes([instruction_name_to_qiskit_gate(gate) for gate in pipeline.gate_pool])\n",
    "    gate_clrs    = [0] + [gate_classes[ic] for ic in c]  # 0 is empty, always allowed!\n",
    "    return gate_clrs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f77a3020-247c-4ac0-aaf1-ee5c371b5f06",
   "metadata": {},
   "source": [
    "## Setup and load"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "742ae430-46f2-4099-ac8f-f422a4ddc1dc",
   "metadata": {},
   "source": [
    "Load the pre-trained model directly from [Hugging Face: Floki00/qc_unitary_3qubit](https://huggingface.co/Floki00/qc_unitary_3qubit)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5d60c23-9514-4432-bc82-622c088fced6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "95b3e6a8ad944d45b38703e92799bc84",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Fetching 2 files:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO]: `genQC.models.unet_qc.QC_Compilation_UNet` instantiated from given config on cuda.\n",
      "[INFO]: `genQC.models.frozen_open_clip.CachedFrozenOpenCLIPEmbedder` instantiated from given config on cuda.\n",
      "[INFO]: `genQC.models.frozen_open_clip.CachedFrozenOpenCLIPEmbedder`. No save_path` provided. No state dict loaded.\n"
     ]
    }
   ],
   "source": [
    "pipeline = DiffusionPipeline.from_pretrained(\"Floki00/qc_unitary_3qubit\", device)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "431d3e29-f121-4c61-95bc-bfd7960a4870",
   "metadata": {},
   "source": [
    "Set 20 sample steps and use rescaled guidance-formula."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96702fba-5a10-44e6-bef9-634d9e41a1af",
   "metadata": {},
   "outputs": [],
   "source": [
    "pipeline.guidance_sample_mode = \"rescaled\"\n",
    "pipeline.scheduler.set_timesteps(20) \n",
    "g = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b557151-ba81-423e-8f28-8e35a781b92b",
   "metadata": {},
   "source": [
    "The model was trained with a gate pool of:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6a15d3a-b658-429f-99d5-2bcbdcb955cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['h', 'cx', 'z', 'x', 'ccx', 'swap']"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline.gate_pool"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65acff8f-8486-42c9-8e78-b44f31de568b",
   "metadata": {},
   "source": [
    "## Compile a unitary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37444b73-0b79-4fd3-9e91-2dd521f428d3",
   "metadata": {},
   "source": [
    "Compile a given unitary $U$. Note, there has to be a solution with the `pipeline.gate_pool` in order to find the exact solution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a78b750-181c-4060-bbce-d829c190ffbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compile_and_plot(U, prompt):\n",
    "    U_r, U_i = torch.Tensor(np.real(U)), torch.Tensor(np.imag(U))\n",
    "    U_tensor = torch.stack([U_r, U_i], dim=0)\n",
    "    \n",
    "    out_tensor                           = generate_comp_tensors(pipeline, prompt, U_tensor, samples, num_of_qubits, num_of_qubits, max_gates, g, unique=True)\n",
    "    _, _, _, _, _, comb_corr_qc, _, _, _ = get_gate_and_U_acc(out_tensor, str_cond_to_gate_indices(prompt), U_tensor, pipeline.gate_pool, num_of_qubits, max_gates)\n",
    "    comb_corr_qc                         = sorted(comb_corr_qc, key=lambda x: len(x.data)) #sort to get the shortest solutions\n",
    "\n",
    "    fig, axs = plt.subplots(1,4, figsize=(18,5), constrained_layout=True)\n",
    "    axs[0].set_title(f\"{prompt}\")\n",
    "    for qc,ax in zip(comb_corr_qc, axs.flatten()): \n",
    "        qc.draw(\"mpl\", plot_barriers=False, ax=ax)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b49dc061-6ad1-4e64-ab63-3c2a6b7c092e",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples       = 512\n",
    "num_of_qubits = 3\n",
    "max_gates     = 12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7f3744d1-fa19-4403-bd0c-d0dadac805a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Compile using: ['h', 'cx', 'z', 'x', 'ccx', 'swap']\""
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompt = \"Compile using: ['h', 'cx', 'z', 'x', 'ccx', 'swap']\" # model was trained with phrases like this, allow full gate set\n",
    "prompt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f38e035-f39c-4abd-bdc9-6386305cd4ca",
   "metadata": {},
   "source": [
    "#### Exercise 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "204dbc2d-b69f-45bd-9a48-d10e4d6bde84",
   "metadata": {},
   "source": [
    "Inspired from [(quantumcomputing.stackexchange.com/questions/13821/generate-a-3-qubit-swap-unitary-in-terms-of-elementary-gates/13826)](https://quantumcomputing.stackexchange.com/questions/13821/generate-a-3-qubit-swap-unitary-in-terms-of-elementary-gates/13826). Note, this unitary WAS in the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b826437-bcc8-40fd-9c99-f69082fe2efe",
   "metadata": {},
   "outputs": [],
   "source": [
    "U = np.matrix([[1,0,0,0,0,0,0,0],\n",
    "               [0,1,0,0,0,0,0,0],\n",
    "               [0,0,1,0,0,0,0,0],\n",
    "               [0,0,0,0,1,0,0,0],\n",
    "               [0,0,0,1,0,0,0,0],\n",
    "               [0,0,0,0,0,1,0,0],\n",
    "               [0,0,0,0,0,0,1,0],\n",
    "               [0,0,0,0,0,0,0,1]], dtype=np.complex128) \n",
    "\n",
    "assert np.allclose(U.H@U, np.identity(2**num_of_qubits)) and np.allclose(U@U.H, np.identity(2**num_of_qubits)) #check if unitary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16dd2cd2-2ff5-4e7f-94d2-be51713fa322",
   "metadata": {},
   "source": [
    "Plot correct (exact) compiled circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7b35524-f303-4744-b948-1c7dac4fa2e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compile_and_plot(U, prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8914651c-a30e-4a5b-aaa4-d98debd7147a",
   "metadata": {},
   "source": [
    "#### Exercise 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d0c618b-2e8d-4037-a1ec-482324112fb8",
   "metadata": {},
   "source": [
    "Inspired from [(quantumcomputing.stackexchange.com/questions/12439/procedures-and-intuition-for-designing-simple-quantum-circuits/12440)](https://quantumcomputing.stackexchange.com/questions/12439/procedures-and-intuition-for-designing-simple-quantum-circuits/12440). Note, this unitary WAS in the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1b170062-d7aa-4bef-b1d1-a68e85e682ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "U = np.matrix([[1,0,0,0,0,0,0,0],\n",
    "               [0,0,0,0,0,0,0,1],\n",
    "               [0,1,0,0,0,0,0,0],\n",
    "               [0,0,1,0,0,0,0,0],\n",
    "               [0,0,0,1,0,0,0,0],\n",
    "               [0,0,0,0,1,0,0,0],\n",
    "               [0,0,0,0,0,1,0,0],\n",
    "               [0,0,0,0,0,0,1,0]], dtype=np.complex128) \n",
    "\n",
    "assert np.allclose(U.H@U, np.identity(2**num_of_qubits)) and np.allclose(U@U.H, np.identity(2**num_of_qubits)) #check if unitary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc81558e-a227-4490-94bc-044ba6dcd502",
   "metadata": {},
   "source": [
    "Plot correct (exact) compiled circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3886fbf5-3f6f-4a44-89b7-d0a332a69334",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compile_and_plot(U, prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46d42b16-2fcf-422a-a206-3eee667f4d4b",
   "metadata": {},
   "source": [
    "#### Exercise 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9824ae0-f3c6-4755-8a5b-aacb22678ec9",
   "metadata": {},
   "source": [
    "A randomly generated unitary (from a random circuit). This unitary WAS NOT in the training set, it is new to the model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63c51c9b-638a-42c4-8029-9add147d2255",
   "metadata": {},
   "outputs": [],
   "source": [
    "U = np.matrix([[ 0.70710678,  0.        ,  0.        , 0.        ,  0.70710678,  0.        , 0.        ,  0.        ],\n",
    "               [ 0.        , -0.70710678,  0.        , 0.        ,  0.        , -0.70710678, 0.        ,  0.        ],\n",
    "               [-0.70710678,  0.        ,  0.        , 0.        ,  0.70710678,  0.        , 0.        ,  0.        ],\n",
    "               [ 0.        ,  0.70710678,  0.        , 0.        ,  0.        , -0.70710678, 0.        ,  0.        ],\n",
    "               [ 0.        ,  0.        ,  0.70710678, 0.        ,  0.        ,  0.        , 0.        ,  0.70710678],\n",
    "               [ 0.        ,  0.        ,  0.        , 0.70710678,  0.        ,  0.        , 0.70710678,  0.        ],\n",
    "               [ 0.        ,  0.        , -0.70710678, 0.        ,  0.        ,  0.        , 0.        ,  0.70710678],\n",
    "               [ 0.        ,  0.        ,  0.        ,-0.70710678,  0.        ,  0.        , 0.70710678,  0.        ]], dtype=np.complex128)\n",
    "\n",
    "assert np.allclose(U.H@U, np.identity(2**num_of_qubits)) and np.allclose(U@U.H, np.identity(2**num_of_qubits)) #check if unitary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b5e50fd-da8d-47fb-aabb-92044aaba2ce",
   "metadata": {},
   "source": [
    "Plot correct (exact) compiled circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6d5023f-b3f4-4cc6-81cb-eead8ffee190",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compile_and_plot(U, prompt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60d35449-67b2-4ce0-9b5f-ac60670538e5",
   "metadata": {},
   "source": [
    "## Transpile and discover"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41449006-9c42-4109-bb54-95581f90679a",
   "metadata": {},
   "source": [
    "Set an initial circuit we want to transpile, optimize or use for discovering sub-arrangements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1c82de5-3645-403b-a54e-5185860b0f7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 538.33x284.278 with 1 Axes>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(3)\n",
    "qc.h(2)\n",
    "qc.cx(0,1)\n",
    "qc.cx(2,1)\n",
    "qc.h(1)\n",
    "qc.x(1)\n",
    "qc.h(1)\n",
    "qc.x(2)\n",
    "\n",
    "U = qi.Operator(qc).to_matrix() # the unitary of the circuit\n",
    "\n",
    "#-----------------------------------------\n",
    "\n",
    "fig = qc.draw(\"mpl\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db8fb061-d950-4727-a1b1-56ea46e48f1b",
   "metadata": {},
   "source": [
    "We set different gate pool targets to see what the model gives us:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a35405a-d98d-460b-9b0c-92d167266ad0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(\"Compile using: ['h', 'cx', 'z', 'x', 'ccx', 'swap']\", 'all'),\n",
       " (\"Compile using: ['h', 'cx', 'z', 'ccx']\", 'no x, no swap'),\n",
       " (\"Compile using: ['h', 'cx', 'x', 'ccx']\", 'no z, no swap'),\n",
       " (\"Compile using: ['h', 'x', 'ccx']\", 'no cx, no z, no swap'),\n",
       " (\"Compile using: ['h', 'z', 'x', 'ccx']\", 'no cx, no swap')]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cs_1 = f\"Compile using: {[x for x in pipeline.gate_pool]}\", \"all\"\n",
    "\n",
    "cs_2 = \"Compile using: ['h', 'cx', 'z', 'ccx']\" , \"no x, no swap\"    \n",
    "cs_3 = \"Compile using: ['h', 'cx', 'x', 'ccx']\" , \"no z, no swap\"    \n",
    "cs_4 = \"Compile using: ['h', 'x', 'ccx']\"       , \"no cx, no z, no swap\" \n",
    "cs_5 = \"Compile using: ['h', 'z', 'x', 'ccx']\"  , \"no cx, no swap\"  \n",
    "\n",
    "cs = [cs_1, cs_2, cs_3, cs_4, cs_5]\n",
    "cs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "67e3aa4e-e7e0-4f7a-9a5c-14a70dd6b77b",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples       = 512\n",
    "num_of_qubits = 3\n",
    "max_gates     = 12"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adfbef8e-d91a-4ed3-b756-0e76c33674fa",
   "metadata": {},
   "source": [
    "Compile with the different gate-sets and plot correct (exact) compiled circuits. Note, some of the circuits might look the same but the gate time-sequences are distinct. Qiskit reorders \"parallel\" gates to make smaller plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6268abb3-1965-4a0e-b5dc-0f3c8db8264a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for c, note in cs: compile_and_plot(U, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "acee9cc1-5b36-45d3-9844-2dbb885d6bfe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef5f0dc2-ad3a-467a-89dd-36d296d458ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "genQC Version 0.1.0\n"
     ]
    }
   ],
   "source": [
    "import genQC\n",
    "print(\"genQC Version\", genQC.__version__)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3",
   "language": "python",
   "name": "python3"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}