QInfer: Statistical inference software for quantum applications

TL;DR

QInfer is an open-source software library that facilitates robust, reproducible statistical analysis of quantum experimental data, supporting various characterization methods and performance prediction for quantum technologies.

Contribution

It introduces a comprehensive, user-friendly library for statistical inference in quantum experiments, enhancing analysis robustness and reproducibility.

Findings

Supports analysis of tomography, benchmarking, and Hamiltonian learning data

Enables online and post-processing data analysis

Provides simulation tools for experimental protocol performance prediction

Abstract

Characterizing quantum systems through experimental data is critical to applications as diverse as metrology and quantum computing. Analyzing this experimental data in a robust and reproducible manner is made challenging, however, by the lack of readily-available software for performing principled statistical analysis. We improve the robustness and reproducibility of characterization by introducing an open-source library, QInfer, to address this need. Our library makes it easy to analyze data from tomography, randomized benchmarking, and Hamiltonian learning experiments either in post-processing, or online as data is acquired. QInfer also provides functionality for predicting the performance of proposed experimental protocols from simulated runs. By delivering easy-to-use characterization tools based on principled statistical analysis, QInfer helps address many outstanding challenges facing quantum technology.