What type of study is this?

This is a Quantitative Study study.

September 17, 2025Proceedings of the International Conference on Automated Planning and SchedulingOpen Access

Quality Diversity for Variational Quantum Circuit Optimization

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Authors

MZMaximilian Zorn JSJonas Stein MMMaximilian Balthasar Mansky

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Overview

This work introduces a matrix-based approach to optimize quantum circuits, demonstrating improved speed and solution quality using quality diversity methods.

Key Points

Empirical results show our quality diversity optimization improves circuit solution scores compared to benchmark algorithms.
Using matrix-based circuit engineering facilitates the application of quality diversity methods like covariance matrix adaptation.
Diversity-driven optimization effectively assesses circuit qualities such as expressivity and gate-diversity for better optimization insights.
This research addresses ongoing challenges in the optimization of variational quantum circuits, enhancing practical quantum computing applications.

Cite This Study

Zorn et al. (2025) studied this question.

synapsesocial.com/papers/68d4566c31b076d99fa5bade https://doi.org/10.1609/icaps.v35i1.36139

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September 17, 2025Proceedings of the International Conference on Automated Planning and SchedulingOpen Access

Quality Diversity for Variational Quantum Circuit Optimization

View Full Paper

Ask AI

Bookmark

Authors

MZMaximilian Zorn JSJonas Stein MMMaximilian Balthasar Mansky

Discussion

Member takes

Overview

This work introduces a matrix-based approach to optimize quantum circuits, demonstrating improved speed and solution quality using quality diversity methods.

Key Points

Empirical results show our quality diversity optimization improves circuit solution scores compared to benchmark algorithms.
Using matrix-based circuit engineering facilitates the application of quality diversity methods like covariance matrix adaptation.
Diversity-driven optimization effectively assesses circuit qualities such as expressivity and gate-diversity for better optimization insights.
This research addresses ongoing challenges in the optimization of variational quantum circuits, enhancing practical quantum computing applications.

Cite This Study

Zorn et al. (2025) studied this question.

synapsesocial.com/papers/68d4566c31b076d99fa5bade https://doi.org/10.1609/icaps.v35i1.36139

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