Add notebook showing qiskit vqe

docs/_toc.yml

@@ -11,6 +11,7 @@ parts:
       - file: tutorials/generating_lattices
       - file: tutorials/pulser-calc-example
       - file: tutorials/finite-geometries
+      - file: tutorials/vqe_qiskit
   - caption: Use-Cases
     chapters:
       - file: use-cases/ssh_model

docs/tutorials/vqe_qiskit.ipynb

@@ -0,0 +1,205 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "56fc15e4",
+   "metadata": {},
+   "source": [
+    "# VQE for a spin model using `qse` Operators\n",
+    "\n",
+    "This notebook builds a spin model using the `qse` `Operator` / `Operators` classes,\n",
+    "converts it to a Qiskit `SparsePauliOp` via `to_qiskit()` method, and runs VQE to find the ground state energy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "116e033e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import qse\n",
+    "from qse.operator.operator import Operator\n",
+    "from qse.operator.operators import Operators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7b142901",
+   "metadata": {},
+   "source": [
+    "## 1. Build the spin model.\n",
+    "\n",
+    "We build a 1D **transverse-field Ising model** (TFIM) on $N=10$ qubits:\n",
+    "\n",
+    "$$H = -J \\sum_{i=0}^{N-2} Z_i Z_{i+1} - h \\sum_{i=0}^{N-1} X_i$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b1ec8bad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "N = 10\n",
+    "J = 1.0\n",
+    "h = 0.5\n",
+    "spacing = 1.0\n",
+    "\n",
+    "qbits = qse.lattices.chain(spacing, N)\n",
+    "\n",
+    "# ZZ interaction terms between neighbouring qubits\n",
+    "hamiltonian = qbits.compute_interaction_hamiltonian(\n",
+    "    distance_func=lambda d: -J * np.isclose(d, spacing),\n",
+    "    interaction=\"Z\",\n",
+    ")\n",
+    "\n",
+    "# Transverse field X terms on each qubit\n",
+    "for i in range(N):\n",
+    "    hamiltonian += qse.Operator(\"X\", i, N, coef=-h)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be80c5c1",
+   "metadata": {},
+   "source": [
+    "## 2. Convert to Qiskit `SparsePauliOp`\n",
+    "\n",
+    "Once we have the Hamiltonian $H$, we can use the `to_qiskit()` method to transform it to a Qiskit Sparse Pauli Operator. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "51b961bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SparsePauliOp(['ZZIIIIIIII', 'IZZIIIIIII', 'IIZZIIIIII', 'IIIZZIIIII', 'IIIIZZIIII', 'IIIIIZZIII', 'IIIIIIZZII', 'IIIIIIIZZI', 'IIIIIIIIZZ', 'XIIIIIIIII', 'IXIIIIIIII', 'IIXIIIIIII', 'IIIXIIIIII', 'IIIIXIIIII', 'IIIIIXIIII', 'IIIIIIXIII', 'IIIIIIIXII', 'IIIIIIIIXI', 'IIIIIIIIIX'],\n",
+      "              coeffs=[-1. +0.j, -1. +0.j, -1. +0.j, -1. +0.j, -1. +0.j, -1. +0.j, -1. +0.j,\n",
+      " -1. +0.j, -1. +0.j, -0.5+0.j, -0.5+0.j, -0.5+0.j, -0.5+0.j, -0.5+0.j,\n",
+      " -0.5+0.j, -0.5+0.j, -0.5+0.j, -0.5+0.j, -0.5+0.j])\n"
+     ]
+    }
+   ],
+   "source": [
+    "pauli_op = hamiltonian.to_qiskit()\n",
+    "print(pauli_op)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a006d641",
+   "metadata": {},
+   "source": [
+    "## 3. Set up and run VQE.\n",
+    "\n",
+    "We set up and run the VQE in qiskit. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7e8986ad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.primitives import StatevectorEstimator\n",
+    "from qiskit.circuit.library import efficient_su2\n",
+    "\n",
+    "import numpy as np\n",
+    "from scipy.optimize import minimize"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "55201685",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ansatz = efficient_su2(num_qubits=N, reps=2, entanglement=\"linear\")\n",
+    "estimator = StatevectorEstimator()\n",
+    "energies_list = []\n",
+    "\n",
+    "\n",
+    "def cost_function(params):\n",
+    "    result = estimator.run([(ansatz, pauli_op, params)]).result()\n",
+    "    energy = result[0].data.evs\n",
+    "    energies_list.append(float(energy))\n",
+    "    return float(energy)\n",
+    "\n",
+    "\n",
+    "# Random initial parameters\n",
+    "rng = np.random.default_rng(42)\n",
+    "x0 = rng.uniform(-np.pi, np.pi, ansatz.num_parameters)\n",
+    "\n",
+    "result = minimize(\n",
+    "    cost_function, x0, method=\"COBYLA\", options={\"maxiter\": 2000, \"rhobeg\": 0.5}\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "94b26131",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "VQE ground state energy : -9.745759\n",
+      "Exact ground state energy: -9.76550395792718\n"
+     ]
+    }
+   ],
+   "source": [
+    "ground_state = np.linalg.eigh(pauli_op.to_matrix())[0][0]\n",
+    "print(f\"VQE ground state energy : {result.fun:.6f}\")\n",
+    "print(f\"Exact ground state energy: {ground_state}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ab8e9a6d",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "87c3414d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env_qse",
+   "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": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

pyproject.toml

@@ -53,6 +53,7 @@ docs = [
     "ipywidgets",
     "ipympl",
     "pulser",  # required for creating the docs
+    "qiskit"
 ]
 
 [tool.black]