QHyper: an integration library for hybrid quantum-classical optimization

TL;DR

QHyper is a versatile library that simplifies the formulation, execution, and hyperparameter tuning of hybrid quantum-classical optimization algorithms, supporting various quantum and classical solvers.

Contribution

It introduces an extensible, user-friendly library for hybrid quantum-classical optimization experiments with flexible configuration and solver integration.

Findings

Supports multiple quantum and classical solvers

Enables flexible hyperparameter optimization

Facilitates experimental reproducibility and extensibility

Abstract

We propose the QHyper library, which is aimed at researchers working on computational experiments with a variety of quantum combinatorial optimization solvers. The library offers a simple and extensible interface for formulating combinatorial optimization problems, selecting and running solvers, and optimizing hyperparameters. The supported solver set includes variational gate-based algorithms, quantum annealers, and classical solutions. The solvers can be combined with provided local and global (hyper)optimizers. The main features of the library are its extensibility on different levels of use as well as a straightforward and flexible experiment configuration format presented in the paper.