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Autori principali: Huber, Elias X., Tan, Benjamin Y. L., Griffin, Paul R., Angelakis, Dimitris G.
Natura: Preprint
Pubblicazione: 2023
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Accesso online:https://arxiv.org/abs/2307.07193
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author Huber, Elias X.
Tan, Benjamin Y. L.
Griffin, Paul R.
Angelakis, Dimitris G.
author_facet Huber, Elias X.
Tan, Benjamin Y. L.
Griffin, Paul R.
Angelakis, Dimitris G.
contents We extend the qubit-efficient encoding presented in [Tan et al., Quantum 5, 454 (2021)] and apply it to instances of the financial transaction settlement problem constructed from data provided by a regulated financial exchange. Our methods are directly applicable to any QUBO problem with linear inequality constraints. Our extension of previously proposed methods consists of a simplification in varying the number of qubits used to encode correlations as well as a new class of variational circuits which incorporate symmetries, thereby reducing sampling overhead, improving numerical stability and recovering the expression of the cost objective as a Hermitian observable. We also propose optimality-preserving methods to reduce variance in real-world data and substitute continuous slack variables. We benchmark our methods against standard QAOA for problems consisting of 16 transactions and obtain competitive results. Our newly proposed variational ansatz performs best overall. We demonstrate tackling problems with 128 transactions on real quantum hardware, exceeding previous results bounded by NISQ hardware by almost two orders of magnitude.
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id arxiv_https___arxiv_org_abs_2307_07193
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Exponential Qubit Reduction in Optimization for Financial Transaction Settlement
Huber, Elias X.
Tan, Benjamin Y. L.
Griffin, Paul R.
Angelakis, Dimitris G.
Quantum Physics
We extend the qubit-efficient encoding presented in [Tan et al., Quantum 5, 454 (2021)] and apply it to instances of the financial transaction settlement problem constructed from data provided by a regulated financial exchange. Our methods are directly applicable to any QUBO problem with linear inequality constraints. Our extension of previously proposed methods consists of a simplification in varying the number of qubits used to encode correlations as well as a new class of variational circuits which incorporate symmetries, thereby reducing sampling overhead, improving numerical stability and recovering the expression of the cost objective as a Hermitian observable. We also propose optimality-preserving methods to reduce variance in real-world data and substitute continuous slack variables. We benchmark our methods against standard QAOA for problems consisting of 16 transactions and obtain competitive results. Our newly proposed variational ansatz performs best overall. We demonstrate tackling problems with 128 transactions on real quantum hardware, exceeding previous results bounded by NISQ hardware by almost two orders of magnitude.
title Exponential Qubit Reduction in Optimization for Financial Transaction Settlement
topic Quantum Physics
url https://arxiv.org/abs/2307.07193