Comprehensive Library of Variational LSE Solvers

Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for large systems. Although there is a wealth of theoretical research on these algorithms, only fragmentary implementations exist. To fill this gap, we have developed the variational-lse-solver framework, which realizes existing approaches in literature, and introduces several enhancements. The user-friendly interface is designed for researchers that work at the abstraction level of identifying and developing end-to-end applications.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.10242
Citations
1
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
0.73
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Comprehensive Library of Variational LSE Solvers

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1 citations
Numerical methods for differential equations
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Comprehensive Library of Variational LSE Solvers

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Abstract

Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for large systems. Although there is a wealth of theoretical research on these algorithms, only fragmentary implementations exist. To fill this gap, we have developed the variational-lse-solver framework, which realizes existing approaches in literature, and introduces several enhancements. The user-friendly interface is designed for researchers that work at the abstraction level of identifying and developing end-to-end applications.

Fraunhofer Institute for Integrated Circuits (DE)
Openalex Percentile: Top 26%
Numerical methods for differential equations
0.73
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