Application-oriented Quantum Computing Benchmarking with QUARK

The Quantum Computing Application Benchmarking (QUARK) framework is designed to evaluate quantum computing applications through a comprehensive benchmarking methodology that emphasizes application-relevant metrics. As quantum technologies advance, the need for robust frameworks to assess their performance in real-world scenarios becomes increasingly critical for end users and use case providers. QUARK addresses this need by providing a structured approach to benchmarking quantum and hybrid solutions, focusing on industry-relevant applications such as the optimization of robot paths and quantum machine learning use cases like generative modeling.

By integrating classical and quantum methodologies, QUARK enables researchers and practitioners to systematically evaluate the effectiveness of quantum algorithms and devices and compare their performance with their classical counterparts. The framework facilitates the identification of key performance indicators, allowing for a nuanced understanding of how quantum solutions can be leveraged to solve complex problems more efficiently. Through its application in various domains, QUARK not only benchmarks the computational capabilities of quantum systems but also highlights their potential impact on industry practices.

QUARK is the standard benchmarking tool in a number of projects in the German quantum ecosystem and aims to continue its substantial growth over the last three years. The concomitant challenges in terms of scaling, modularity, and code complexity are currently addressed in one of the largest structural updates of the framework to date. These changes will facilitate the addition of new modules significantly and will contribute to a lower barrier for users of QUARK.