Bench-QC – Benchmarking of Quantum Computers: Performance Comparisons with Application Orientation

The use of quantum computers holds the potential for revolutionary changes in various areas of academic research and industrial applications. Quantum computers in their optimal implementation could lead to advantages in solving certain problems, such as those arising in mathematical optimization, machine learning or the simulation of quantum systems. The advancement of hardware and software for currently available NISQ devices ("noisy intermediate-scale quantum") is paving the way towards the ideal quantum computer.

Although the benefits of quantum computers can be proven mathematically for some problems, it remains unclear whether specific industrial problems and use cases can benefit from quantum computers in the near future. It is therefore essential to conduct a comprehensive investigation of the potential of quantum computers for practical use cases and provide future users with a realistic understanding of the technology’s capabilities. 

A tailored benchmarking process for quantum computing

Benchmarking is the process of comparison to identify best practices, highlight potential for improvement and defining performance standards. The Bench-QC project aims to compare quantum computers with classical computers and their capabilities will be assessed. To this end, six industrial and research partners are developing a universal framework to compare approaches using quantum computing for industrial applications and reliably assess when advantages over conventional solutions may arise. 

In our benchmarking methodology, different solution approaches for various example use cases with increasing complexity are developed both on real quantum computers and in simulations. These approaches are compared to the theoretical expectations and the classical solutions.

Thanks to the modular architecture, it is always possible to efficiently integrate the latest algorithms and hardware generations, enabling continuous, systematic, and automated evaluations. The unique aspect of the benchmarking framework is its focus on industry-relevant applications, for which comparison metrics are developed.

The result is equally relevant for two parties: While hardware development benefits from the knowledge gained about the requirements, industrial users will be able to identify when the use of quantum computers could be worthwhile.

Development of benchmarks from use cases

Starting from the use case and its mathematical formulation, sequences of problems with increasing complexity are designed. The benchmarking procedure developed in the project compares the classical solution with that of quantum computers.

Our participation as a project partner

With top international research in microelectronic and information technology system solutions, we have extensive experience in transferring new algorithmic technologies into practice. Our core competencies are in the areas of mathematical optimization, reinforcement learning and optimized transpilation.

In the benchmarking procedure, we bring comprehensive experience in defining complexity and performance metrics as well as expertise in the development of quantum algorithms with a special focus on the handling and implementation on various quantum computer hardware.

In collaboration with six project partners from academia and industry, Bench-QC provides us with a holistic approach to reliably assess the benefits of quantum technology in practice.


Project partner

© BMW Group
© Quantinuum
© ML Reply
© OptWare
© Fraunhofer IKS

Further information

Munich Quantum Valley

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