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

In this report, we explore benchmarking gate-based quantum devices based on the certification of quantum measurements, which can be viewed as an extension of quantum hypothesis testing. Here, we are interested in a binary certification scheme in which the null and alternative hypotheses are qubit von Neumann measurements. The certification procedure can be used to evaluate the accuracy of Noisy Intermediate-Scale Quantum devices. To support this methodology, we contribute benchmarks to PyQBench, an open-source Python library for benchmarking gate-based quantum computers. We provide a user-friendly command-line interface for certifying measurements from the Fourier family. For more advanced scenarios, PyQBench can also be used as a Python library, allowing users to define custom measurement schemes and error models. The latest version of PyQBench is 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.