A test suite for quantum networks

Assessing an application’s effectiveness as a benchmark for quantum networks

Bachelor thesis (2023)

Authors

C.R. Dekeling Electrical Engineering, Mathematics and Computer Science

Contributors

R. Ashok Kumar Vattekkat QID/Wehner Group - QuTech Advanced Research Centre (mentor)
S.D.C. Wehner QID/Wehner Group - QuTech Advanced Research Centre (mentor)
A.E. Zaidman Software Engineering - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Casper Dekeling
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Published Date

29-06-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In the development of any new technology, it is essential to have methods to assess the quality of a system, to compare different systems to one another, and to compare different versions of the same system, to see if changes to the system can actually be classified as improvements. For quantum networks, this is no different. To further develop quantum networks, we need a benchmarking suite to judge the quality of such systems.

The aim of this research is to determine the effectiveness of blind quantum computation - a quantum network algorithm - as a benchmark. We determine what changes to the system affect the results of executing this application, and we use this to determine whether it would be effective to use this application as part of a larger benchmarking suite. We do this by simulating a quantum network, and manually varying system parameters one by one, to see if they have an effect on the results.

What we observed from these experiments is that blind quantum computation is sensitive to almost all system parameters. This means that introducing an imperfection into almost any system parameter will negatively affect the results of the application. This means the application is useful as a full-system benchmark, because it is affected by almost the entire system. However, it also means that the application is less useful as a benchmark for individual parameters.

This means that to make the most useful benchmarking suite, blind quantum computation would have to be combined with other quantum network applications that are more suitable for benchmarking individual system parameters.