QMCkl: A Kernel Library for Quantum Monte Carlo Applications

TL;DR

QMCkl is a modular, high-performance kernel library that standardizes and accelerates quantum Monte Carlo calculations, enabling efficient, reproducible, and cross-compatible electronic structure simulations.

Contribution

It introduces a portable, high-performance kernel library with a C API supporting standard input, enhancing efficiency and reproducibility in QMC and quantum chemistry workflows.

Findings

Achieves substantial speedups in energy and derivative evaluations.

Supports a wide range of QMC kernels including orbitals and cusp corrections.

Enables cross-code interoperability and reproducible simulations.

Abstract

Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provides a modular, portable collection of high-performance kernels implementing the core building blocks of QMC calculations. It offers a C-compatible API, supports the TREXIO standard for input, and covers essential QMC kernels including atomic and molecular orbitals, cusp corrections, Jastrow factor, and the necessary derivatives also to perform variational and structural optimization. QMCkl separates algorithmic development from hardware-specific tuning by combining human-readable reference implementations with performance-optimized kernels that produce identical numerical results. The library enables consistent, efficient, and reproducible simulations across different QMC codes and architectures, and achieves substantial speedups in the evaluation of the energy and its derivatives. Beyond QMC, QMCkl can accelerate deterministic quantum chemistry workflows and visualization tools, promoting cross-code interoperability and simplifying high-performance scientific software development.