Quasi-Monte Carlo Software

TL;DR

This paper reviews and introduces QMCPy, an open-source Python library designed to facilitate the application of quasi-Monte Carlo methods for multivariate integration, emphasizing software robustness and community support.

Contribution

It presents QMCPy, a comprehensive, open-source Python library that consolidates key QMC components for practitioners and researchers.

Findings

QMCPy provides a modular framework for QMC applications.

The library aims to improve accessibility and robustness of QMC methods.

QMCPy is open-source and community-oriented.

Abstract

Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, robust, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software available. We highlight the key software components required by QMC to approximate multivariate integrals or expectations of functions of vector random variables. We have combined these components in QMCPy, a Python open-source library, which we hope will draw the support of the QMC community. Here we introduce QMCPy.