Tight Lieb–Robinson Bound for approximation ratio in quantum annealing

Abstract Quantum annealing (QA) holds promise for optimization problems in quantum computing, especially for combinatorial optimization. This analog framework attracts attention for its potential to address complex problems. Its gate-based homologous, QAOA with proven performance, has attracted a lo...

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Main Authors: Arthur Braida, Simon Martiel, Ioan Todinca
Format: Article
Language:English
Published: Nature Portfolio 2024-04-01
Series:npj Quantum Information
Online Access:https://doi.org/10.1038/s41534-024-00832-x
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author Arthur Braida
Simon Martiel
Ioan Todinca
author_facet Arthur Braida
Simon Martiel
Ioan Todinca
author_sort Arthur Braida
collection DOAJ
description Abstract Quantum annealing (QA) holds promise for optimization problems in quantum computing, especially for combinatorial optimization. This analog framework attracts attention for its potential to address complex problems. Its gate-based homologous, QAOA with proven performance, has attracted a lot of attention to the NISQ era. Several numerical benchmarks try to compare these two metaheuristics, however, classical computational power highly limits the performance insights. In this work, we introduce a parametrized version of QA enabling a precise 1-local analysis of the algorithm. We develop a tight Lieb–Robinson bound for regular graphs, achieving the best-known numerical value to analyze QA locally. Studying MaxCut over cubic graph as a benchmark optimization problem, we show that a linear-schedule QA with a 1-local analysis achieves an approximation ratio over 0.7020, outperforming any known 1-local algorithms.
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spelling doaj.art-23aa27b369cf484f9c5889ca4dea95762024-04-21T11:26:15ZengNature Portfolionpj Quantum Information2056-63872024-04-011011910.1038/s41534-024-00832-xTight Lieb–Robinson Bound for approximation ratio in quantum annealingArthur Braida0Simon Martiel1Ioan Todinca2LIFO - Laboratoire d’Informatique Fondamentale d’Orléans, Université d’OrléansEviden Quantum LabLIFO - Laboratoire d’Informatique Fondamentale d’Orléans, Université d’OrléansAbstract Quantum annealing (QA) holds promise for optimization problems in quantum computing, especially for combinatorial optimization. This analog framework attracts attention for its potential to address complex problems. Its gate-based homologous, QAOA with proven performance, has attracted a lot of attention to the NISQ era. Several numerical benchmarks try to compare these two metaheuristics, however, classical computational power highly limits the performance insights. In this work, we introduce a parametrized version of QA enabling a precise 1-local analysis of the algorithm. We develop a tight Lieb–Robinson bound for regular graphs, achieving the best-known numerical value to analyze QA locally. Studying MaxCut over cubic graph as a benchmark optimization problem, we show that a linear-schedule QA with a 1-local analysis achieves an approximation ratio over 0.7020, outperforming any known 1-local algorithms.https://doi.org/10.1038/s41534-024-00832-x
spellingShingle Arthur Braida
Simon Martiel
Ioan Todinca
Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
npj Quantum Information
title Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
title_full Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
title_fullStr Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
title_full_unstemmed Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
title_short Tight Lieb–Robinson Bound for approximation ratio in quantum annealing
title_sort tight lieb robinson bound for approximation ratio in quantum annealing
url https://doi.org/10.1038/s41534-024-00832-x
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