computing_magnetisation_with_suzuki_trotter_approximation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A key application for quantum computers is the simulation of quantum systems. This tutorial demonstrates a CUDA-Q implementation of a Suzuki-Trotter simulation of a Heisenberg Model Hamiltonian to compute the magnetization of a spin chain.\n",
    "\n",
    "This example leverages CUDA-Q’s state handling capabilities to perform recursive Trotter simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cudaq\n",
    "import time\n",
    "import numpy as np\n",
    "from typing import List"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The goal of this problem is to estimate the time evolution of an initial quantum state governed by a Hamiltonian and compute the average magnetization of the final state. The time evolution is approximated using the Trotter method:\n",
    "\n",
    "The Heisenberg Hamiltonian is defined below, parameterized by these predefined constants: \\(J_x\\), \\(J_y\\), \\(J_z\\), and \\(h\\). The time step \\(\\Delta t\\) is selected for this problem, along with \\(n\\_steps\\) and \\(n\\_spins\\) (\\(n\\_spins = 11\\), \\(n\\_steps = 10\\)), determining the size of the simulation. The default setup considers 11 spins and 10 steps, which can easily be simulated on a CPU. If you have access to at least one GPU, the problem can be increased to around 25 spins and 100 time steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = 1.0\n",
    "Jx = 1.0\n",
    "Jy = 1.0\n",
    "Jz = g\n",
    "dt = 0.05\n",
    "n_steps = 10\n",
    "n_spins = 11\n",
    "omega = 2 * np.pi\n",
    "\n",
    "\n",
    "def heisenbergModelHam(t: float) -> cudaq.SpinOperator:\n",
    "    tdOp = cudaq.SpinOperator(num_qubits=n_spins)\n",
    "    for i in range(0, n_spins - 1):\n",
    "        tdOp += (Jx * cudaq.spin.x(i) * cudaq.spin.x(i + 1))\n",
    "        tdOp += (Jy * cudaq.spin.y(i) * cudaq.spin.y(i + 1))\n",
    "        tdOp += (Jz * cudaq.spin.z(i) * cudaq.spin.z(i + 1))\n",
    "    for i in range(0, n_spins):\n",
    "        tdOp += (np.cos(omega * t) * cudaq.spin.x(i))\n",
    "    return tdOp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "@cudaq.kernel\n",
    "def getInitState(numSpins: int):\n",
    "    q = cudaq.qvector(numSpins)\n",
    "    for qId in range(0, numSpins, 2):\n",
    "        x(q[qId])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"\"\"\n",
    "Performs a single Trotter step given an initial state and returns the resulting state.\n",
    "\n",
    "Notes:\n",
    "1. Utilizes CUDA-Q’s state handling capabilities, allowing each step to proceed from the previous state still stored in GPU memory during the simulation. This results in a significant speedup, as demonstrated in the plot at the end of this tutorial.\n",
    "2. Leverages the pauli_word object, which allows a list of Pauli words and their coefficients to be passed into the kernel and applied as an exponentiated matrix operation using exp_pauli.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "@cudaq.kernel\n",
    "def trotter(state: cudaq.State, coefficients: List[complex],\n",
    "            words: List[cudaq.pauli_word], dt: float):\n",
    "    q = cudaq.qvector(state)\n",
    "    for i in range(len(coefficients)):\n",
    "        exp_pauli(coefficients[i].real * dt, q, words[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The functions below are used to strip the Hamiltonian spin operator into a list of coefficients and Pauli words."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def termCoefficients(op: cudaq.SpinOperator) -> List[complex]:\n",
    "    result = []\n",
    "    ham.for_each_term(lambda term: result.append(term.get_coefficient()))\n",
    "    return result\n",
    "\n",
    "\n",
    "def termWords(op: cudaq.SpinOperator) -> List[str]:\n",
    "    result = []\n",
    "    ham.for_each_term(lambda term: result.append(term.to_string(False)))\n",
    "    return result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, a second spin operator is defined to compute the expectation value corresponding to the average magnetization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "average_magnetization = cudaq.SpinOperator(num_qubits=n_spins)\n",
    "for i in range(0, n_spins):\n",
    "    average_magnetization += ((1.0 / n_spins) * cudaq.spin.z(i))\n",
    "average_magnetization -= 1.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Running the Simulation\n",
    "\n",
    "Before looping through the Trotter steps, the initial state is constructed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "state = cudaq.get_state(getInitState, n_spins)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we loop through the time steps. At each step, we define the time-dependent Hamiltonian. This Hamiltonian is used to construct the Trotter kernel for that time step, which is then used to compute the average magnetization expectation value. The state is saved and used as the initial state for the subsequent time step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 0: time [s]: 0.0375676155090332, result: -0.09042024163828166\n",
      "Step 1: time [s]: 0.002967357635498047, result: -0.08898564687193886\n",
      "Step 2: time [s]: 0.003292083740234375, result: -0.08698024360923415\n",
      "Step 3: time [s]: 0.003481626510620117, result: -0.08507694741170907\n",
      "Step 4: time [s]: 0.0036933422088623047, result: -0.08394118068746997\n",
      "Step 5: time [s]: 0.003942966461181641, result: -0.08394076573115139\n",
      "Step 6: time [s]: 0.00487065315246582, result: -0.08502222139504187\n",
      "Step 7: time [s]: 0.0049800872802734375, result: -0.08677832064885871\n",
      "Step 8: time [s]: 0.003471851348876953, result: -0.08863390649349775\n",
      "Step 9: time [s]: 0.003048419952392578, result: -0.09005513983609514\n",
      "Step times: [0.0375676155090332, 0.002967357635498047, 0.003292083740234375, 0.003481626510620117, 0.0036933422088623047, 0.003942966461181641, 0.00487065315246582, 0.0049800872802734375, 0.003471851348876953, 0.003048419952392578]\n",
      "Results: [-0.09042024163828166, -0.08898564687193886, -0.08698024360923415, -0.08507694741170907, -0.08394118068746997, -0.08394076573115139, -0.08502222139504187, -0.08677832064885871, -0.08863390649349775, -0.09005513983609514]\n"
     ]
    }
   ],
   "source": [
    "results = []\n",
    "times = []\n",
    "for i in range(0, n_steps):\n",
    "    start_time = time.time()\n",
    "    ham = heisenbergModelHam(i * dt)\n",
    "    coefficients = termCoefficients(ham)\n",
    "    words = termWords(ham)\n",
    "    magnetization_exp_val = cudaq.observe(trotter, average_magnetization, state,\n",
    "                                          coefficients, words, dt)\n",
    "    result = magnetization_exp_val.expectation()\n",
    "    results.append(result)\n",
    "    state = cudaq.get_state(trotter, state, coefficients, words, dt)\n",
    "    stepTime = time.time() - start_time\n",
    "    times.append(stepTime)\n",
    "    print(f\"Step {i}: time [s]: {stepTime}, result: {result}\")\n",
    "\n",
    "print(f\"Step times: {times}\")\n",
    "print(f\"Results: {results}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CUDA-Q’s state handling capabilities significantly enhance the performance of this algorithm. By storing the previous state in GPU memory, the simulation can proceed without resimulating all prior operations at each time step. This approach reduces the number of operations required, resulting in a substantial performance boost. The figure below illustrates a 24X speedup achieved by a 100-step Trotter simulation."
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cuda-quantum",
   "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": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}