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Experimental demonstration of improved quantum optimization with linear Ising penalties [dataset] Open Access

The standard approach to encoding constraints in quantum optimization is the quadratic penalty method. Quadratic penalties introduce additional couplings and energy scales, which can be detrimental to the performance of a quantum optimizer. In quantum annealing experiments performed on a D-Wave Advantage, we explore an alternative penalty method that only involves linear Ising terms and apply it to a customer data science problem. Our findings support our hypothesis that the linear Ising penalty method should improve the performance of quantum optimization compared to using the quadratic penalty method due to its more efficient use of physical resources. Although the linear Ising penalty method is not guaranteed to exactly implement the desired constraint in all cases, it is able to do so for the majority of problem instances we consider. For problems with many constraints, where making all penalties linear is unlikely to be feasible, we investigate strategies for combining linear Ising penalties with quadratic penalties to satisfy constraints for which the linear method is not well-suited. We find that this strategy is most effective when the penalties that contribute most to limiting the dynamic range are removed.

Descriptions

Resource type
Dataset
Contributors
Editor: Mirkarimi, Puya 1
Creator: Mirkarimi, Puya 1
Data collector: Mirkarimi, Puya 1
Contact person: Mirkarimi, Puya 1
Data curator: Mirkarimi, Puya 1
Creator: Hoyle, David C. 2
Creator: Williams, Ross 2
Creator: Chancellor, Nicholas 3
1 Durham University, United Kingdom
2 dunnhumby, United Kingdom
3 Newcastle University, United Kingdom
Funder
Engineering and Physical Sciences Research Council
dunnhumby
Research methods
Computer assisted numerical calculations and quantum annealing experiments
Other description
Keyword
quantum computing
quantum annealing
combinatorial optimization
Subject
Quantum computing
Location
Language
English
Cited in
doi:10.48550/arXiv.2404.05476
Identifier
ark:/32150/r2j6731386t
doi:10.15128/r2j6731386t
Rights
Creative Commons Attribution 4.0 International (CC BY)

Publisher
Durham University
Date Created
2024-05-10

File Details

Depositor
P. Mirkarimi
Date Uploaded
Date Modified
13 May 2024, 10:05:36
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File format: zip (ZIP Format)
Mime type: application/zip
File size: 313808063
Last modified: 2024:05:10 12:50:23+01:00
Filename: ExperimentalLinearPenalties.zip
Original checksum: 70a242611e585620cf43058b9ce595b6
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User N. Syrotiuk has updated Experimental demonstration of improved quantum optimization with linear Ising penalties [dataset] 15 days ago