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Research PaperResearchia:202605.08017

Machine Learning Approaches to Building Quantum Circuits for Sets of Matrices

Matvei Fedin

Abstract

Machine learning nowadays becomes a useful instrument in many subjects. In this paper we use interpretable machine learning to build quantum algorithm. By studying the parameters of the machine learning algorithm we were able to construct universal shortest analytic quantum algorithm for arbitrary diagonal matrix of any size. --- Source: arXiv:2605.06633v1 - http://arxiv.org/abs/2605.06633v1 PDF: https://arxiv.org/pdf/2605.06633v1 Original Link: http://arxiv.org/abs/2605.06633v1

Submitted: May 8, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Machine learning nowadays becomes a useful instrument in many subjects. In this paper we use interpretable machine learning to build quantum algorithm. By studying the parameters of the machine learning algorithm we were able to construct universal shortest analytic quantum algorithm for arbitrary diagonal matrix of any size.


Source: arXiv:2605.06633v1 - http://arxiv.org/abs/2605.06633v1 PDF: https://arxiv.org/pdf/2605.06633v1 Original Link: http://arxiv.org/abs/2605.06633v1

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Submission Info
Date:
May 8, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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Machine Learning Approaches to Building Quantum Circuits for Sets of Matrices | Researchia