QCQMC notebooks

conftest.py

@@ -21,9 +21,7 @@
 from recirq.qcqmc.hamiltonian import (
     HamiltonianData,
     HamiltonianFileParams,
-    build_hamiltonian_from_file,
 )
-from recirq.qcqmc.optimize_wf import build_pp_plus_trial_wavefunction
 from recirq.qcqmc.trial_wf import (
     PerfectPairingPlusTrialWavefunctionParams,
     TrialWavefunctionData,
@@ -45,7 +43,7 @@ def fixture_4_qubit_ham(package_tmp_path) -> HamiltonianData:
         path_prefix=str(package_tmp_path),
     )
 
-    hamiltonian_data = build_hamiltonian_from_file(params)
+    hamiltonian_data = HamiltonianData.build_hamiltonian_from_file(params)
 
     return hamiltonian_data
 
@@ -60,7 +58,7 @@ def fixture_8_qubit_ham(package_tmp_path) -> HamiltonianData:
         path_prefix=str(package_tmp_path),
     )
 
-    hamiltonian_data = build_hamiltonian_from_file(params)
+    hamiltonian_data = HamiltonianData.build_hamiltonian_from_file(params)
 
     return hamiltonian_data
 
@@ -76,7 +74,7 @@ def fixture_12_qubit_ham(package_tmp_path) -> HamiltonianData:
         path_prefix=str(package_tmp_path),
     )
 
-    hamiltonian_data = build_hamiltonian_from_file(params)
+    hamiltonian_data = HamiltonianData.build_hamiltonian_from_file(params)
 
     return hamiltonian_data
 
@@ -94,7 +92,7 @@ def fixture_4_qubit_ham_and_trial_wf(
         path_prefix=fixture_4_qubit_ham.params.path_prefix,
     )
 
-    trial_wf = build_pp_plus_trial_wavefunction(
+    trial_wf = TrialWavefunctionData.build_pp_plus_trial_from_dependencies(
         params, dependencies={fixture_4_qubit_ham.params: fixture_4_qubit_ham}
     )
 
@@ -115,7 +113,7 @@ def fixture_8_qubit_ham_and_trial_wf(
         path_prefix=fixture_8_qubit_ham.params.path_prefix,
     )
 
-    trial_wf = build_pp_plus_trial_wavefunction(
+    trial_wf = TrialWavefunctionData.build_pp_plus_trial_from_dependencies(
         params, dependencies={fixture_8_qubit_ham.params: fixture_8_qubit_ham}
     )
 

dev_tools/check_notebooks.py

@@ -91,6 +91,9 @@ def check_notebook(notebook_fn: str):
     'docs/hfvqe/quickstart.ipynb',
     'docs/fermi_hubbard/publication_results.ipynb',
     'docs/fermi_hubbard/experiment_example.ipynb',
+    'docs/qcqmc/high_level.ipynb',
+    'docs/qcqmc/full_workflow.ipynb',
+    'docs/qcqmc/experimental_wavefunctions.ipynb',
 ]
 
 

docs/qcqmc/experimental_wavefunctions.ipynb

@@ -0,0 +1,203 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analyzing the Experimentally Reconstructed Wavefunctions\n",
+    "\n",
+    "The wavefunctions produced in the\n",
+    "[QCQMC](https://www.nature.com/articles/s41586-021-04351-z) paper are available\n",
+    "for download  from [zenodo](https://zenodo.org/records/10141262)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import urllib.request\n",
+    "import tarfile\n",
+    "\n",
+    "stream = urllib.request.urlopen(\"https://zenodo.org/records/10141262/files/qcqmc_data.tar.gz\")\n",
+    "\n",
+    "with tarfile.open(fileobj=stream, mode='r|gz') as tf:\n",
+    "    tf.extractall()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Look at the README from the downloaded data\n",
+    "from IPython.display import Markdown, display\n",
+    "display(Markdown('qcqmc_data/README.md'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Loading the wavefunctions\n",
+    "\n",
+    "Here we will reproduce some of the results from Section E of the SI from [QCQMC](https://www.nature.com/articles/s41586-021-04351-z).\n",
+    "\n",
+    "The variational energy of the trial wavefunction as a function of the number of cliffords is reported in Table S1, which we have reproduced here:\n",
+    "\n",
+    "| NCliffords | repeat 1 | repeat 2 | repeat 3 | repeat 4 |\n",
+    "|---|---|---|---|---|\n",
+    "| 10 | -1.800644 | -1.764747 | -1.813274 | -1.658202 |\n",
+    "| 16 | -1.823041 | -1.802192 | -1.840494 | -1.730591 |\n",
+    "| 28 | -1.906644 | -1.839835 | -1.843326 | -1.746749 |\n",
+    "| 47 | -1.925654 | -1.888527 | -1.860863 | -1.809656 |\n",
+    "| 80 | -1.909567 | -1.869456 | -1.887139 | -1.846339 |\n",
+    "| 136 | -1.930880 | -1.902309 | -1.889992 | -1.879164 |\n",
+    "| 229 | -1.944249 | -1.921523 | -1.903710 | -1.890947 |\n",
+    "| 387 | -1.947362 | -1.934682 | -1.910477 | -1.901883 |\n",
+    "| 652 | -1.952416 | -1.939853 | -1.912790 | -1.905250 |\n",
+    "| 1100 | -1.955544 | -1.944651 | -1.915073 | -1.909122 |\n",
+    "| 1856 | -1.955028 | -1.945966 | -1.909558 | -1.908038 |\n",
+    "| 3129 | -1.953877 | -1.947763 | -1.913386 | -1.908835 |\n",
+    "| 5276 | -1.954697 | -1.947323 | -1.912284 | -1.909315 |\n",
+    "| 8896 | -1.954930 | -1.947458 | -1.913889 | -1.913068 |\n",
+    "| 15000 | -1.954356 | -1.948894 | -1.913894 | -1.913082 |\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import fqe\n",
+    "import h5py\n",
+    "import numpy as np\n",
+    "\n",
+    "def compute_energy(wfn_file: str, ham_file: str) -> float:\n",
+    "    \"\"\"Compute the variational energy of the experimentally reconstructed wavefunction.\n",
+    "\n",
+    "    Args:\n",
+    "        wfn_file: The path to the FQE wavefunction. \n",
+    "        ham_file: The path to the hamiltonian.\n",
+    "\n",
+    "    Returns:\n",
+    "        The variational energy\n",
+    "    \"\"\"\n",
+    "    fqe_wfn = fqe.wavefunction.Wavefunction()\n",
+    "    fqe_wfn.read(filename=wfn_file)\n",
+    "    with h5py.File(ham_file, 'r') as fh5:\n",
+    "        ecore = fh5[\"e0\"][()]\n",
+    "        h1e_act = fh5[\"h1\"][:]\n",
+    "        eri_act = fh5[\"h2\"][:]\n",
+    "    # get integrals into openfermion order\n",
+    "    of_eris = np.transpose(eri_act, (0, 2, 3, 1))\n",
+    "    # ... and then into FQE format\n",
+    "    fqe_ham = fqe.hamiltonians.restricted_hamiltonian.RestrictedHamiltonian((h1e_act, np.einsum('ijlk', -0.5 * of_eris)), e_0=ecore)\n",
+    "    return fqe_wfn.expectationValue(fqe_ham)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import glob\n",
+    "import pandas as pd\n",
+    "for column in [1, 2, 3, 4]:\n",
+    "    wavefunctions = glob.glob(f'qcqmc_data/h4_sto3g/fqe_wfns/column{column}/wfn*')\n",
+    "    n_cliffords = [int(x.split('/')[-1].split('_')[-1]) for x in wavefunctions]\n",
+    "    energies = [compute_energy(wfn_file, f'qcqmc_data/h4_sto3g/fqe_hams/column{column}/chem_ham.h5').real for wfn_file in wavefunctions]\n",
+    "    if column == 1:\n",
+    "        df = pd.DataFrame({'n_clifford': n_cliffords, f'repeat {column}': energies})\n",
+    "    else:\n",
+    "        new_df = pd.DataFrame({'n_clifford': n_cliffords, f'repeat {column}': energies})\n",
+    "        df = pd.merge(df, new_df, on='n_clifford', how='outer')\n",
+    "\n",
+    "reproduced_table = df.sort_values(by='n_clifford')\n",
+    "print(reproduced_table)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next run an AFQMC simulation for one of the data points: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ipie.qmc.afqmc import AFQMC\n",
+    "\n",
+    "num_elec = (2, 2) # H4 molecule, 4 electrons, ms = 0 \n",
+    "n_clifford = 15_000\n",
+    "ham_file = 'qcqmc_data/h4_sto3g/ipie_ham/column3/ham.h5'\n",
+    "wfn_file = f'qcqmc_data/h4_sto3g/ipie_wfns/column3/wfn_{n_clifford}.h5' \n",
+    "afqmc = AFQMC.build_from_hdf5(num_elec, ham_file, wfn_file, num_blocks=1_000, num_walkers=100)\n",
+    "afqmc.trial.calculate_energy(afqmc.system, afqmc.hamiltonian)\n",
+    "afqmc.run(estimator_filename=f'h4_sto3g_n_clifford_{n_clifford}.h5')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally we can analyze the result and compare it to the literature value which we agree with within error bars."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ipie.analysis.extraction import extract_observable\n",
+    "import matplotlib.pyplot as plt\n",
+    "from ipie.analysis.blocking import reblock_minimal \n",
+    "\n",
+    "paper_result = -1.96922\n",
+    "analyzed_result = reblock_minimal(afqmc.estimators.filename, start_block=100)\n",
+    "notebook_energy = analyzed_result.ETotal_ac.values[0]\n",
+    "notebook_error = analyzed_result.ETotal_error_ac.values[0]\n",
+    "\n",
+    "data = extract_observable(afqmc.estimators.filename)\n",
+    "plt.plot(data.ETotal, marker='o', label=\"AFQMC\", color=\"C0\")\n",
+    "plt.axhline(paper_result, label=\"Exact Result\", color=\"C1\")\n",
+    "plt.axhline(notebook_energy, label=\"Notebook result\", color=\"C2\")\n",
+    "plt.legend()\n",
+    "plt.xlabel(\"Block number\")\n",
+    "plt.ylabel(\"Total Energy (Ha)\")\n",
+    "print(f\"paper result = {paper_result}\")\n",
+    "print(f\"notebook result = {notebook_energy} +/ {notebook_error}\")"
+   ]
+  }
+ ],
+ "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}