qvmc 0.1.0

Quantum variational Monte Carlo tools for research workflows.

qvmc

qvmc is a research-oriented Python library for quantum variational Monte Carlo workflows. It packages the reusable core of this repository into an importable library with:

• restricted Boltzmann machine wavefunction models
• classical sampling helpers for spin systems
• Pauli operator construction and connection utilities
• a lightweight NumPy Adam optimizer
• an optional Qiskit backend for quantum-inspired proposal sampling

Installation

Install the core package:

pip install qvmc

Install the optional Qiskit backend:

pip install "qvmc[qiskit]"

For local development from this repository:

pip install -e ".[test]"

Quickstart

import numpy as np

from qvmc import RBM, SpinOperator

spin = SpinOperator(n_qubits=2)
hamiltonian = -spin.z(0) * spin.z(1) - 0.5 * spin.x(0) - 0.5 * spin.x(1)

rbm = RBM(N=2, M=2, seed=7)
energy = rbm.energy_exact(hamiltonian)

print(np.real(energy))

Package layout

• qvmc.models: RBM-based variational models
• qvmc.sampling: classical sampling and probability helpers
• qvmc.operators: Pauli algebra and spin-operator utilities
• qvmc.optim: optimization helpers
• qvmc.backends.qiskit: optional Qiskit integration

Documentation

Sphinx docs live in docs/ and are structured around:

• installation and quickstart
• conceptual overview of the core workflow
• API reference
• Qiskit backend guide
• examples that replace the old script-style entrypoints

Build them locally with:

sphinx-build -b html docs docs/_build/html

Examples

Examples live in examples/ and are import-first workflows rather than command-line scripts:

• examples/core_ground_state_workflow.py
• examples/qiskit_sampling_demo.py

Development validation

Recommended local validation steps:

python -m pytest
python -m build