Benchmarking gate-based quantum devices via certification of qubit von Neumann measurements

TL;DR

This paper introduces an enhanced version of PyQBench, a Python library for benchmarking quantum computers, now capable of certifying qubit von Neumann measurements and evaluating measurement accuracy on real NISQ devices.

Contribution

The paper presents an extended PyQBench tool that includes measurement certification and supports IBM Q devices, advancing benchmarking methods for quantum hardware.

Findings

PyQBench now certifies measurement accuracy on noisy quantum devices.

Supports seamless benchmarking on IBM Q hardware.

Open-source code fosters community-driven improvements.

Abstract

We present an updated version of PyQBench, an open-source Python library designed for benchmarking gate-based quantum computers, with a focus on certifying qubit von Neumann measurements. This version extends PyQBench's capabilities by incorporating a certification scheme of quantum measurements that evaluates the accuracy on Noisy Intermediate-Scale Quantum devices, alongside its original functionality of von Neumann measurements' discrimination. PyQBench offers a user-friendly command-line interface and Python library integration, allowing users to implement custom measurement schemes and error models for more advanced benchmarking tasks. The new version is specifically designed to support IBM Q devices through integration with the Qiskit library, enabling seamless benchmarking on real quantum hardware. By providing flexible benchmarking tools, PyQBench addresses the critical need for reliable performance metrics in the NISQ era, contributing to the development of error mitigation techniques and the verification of quantum measurement fidelity. The source code is available on GitHub under an open-source license, encouraging community collaboration and further advancements in quantum hardware benchmarking.