Convergence guarantee for linearly-constrained combinatorial optimization with a quantum alternating operator ansatz

Fuente: arXiv
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Hauptverfasser: Goldstein-Gelb, Brayden, Lotshaw, Phillip C.
Format: Preprint
Veröffentlicht: 2024
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author Goldstein-Gelb, Brayden
Lotshaw, Phillip C.
author_facet Goldstein-Gelb, Brayden
Lotshaw, Phillip C.
contents We present a quantum alternating operator ansatz (QAOA$^+$) that solves a class of linearly constrained optimization problems by evolving a quantum state within a Hilbert subspace of feasible problem solutions. Our main focus is on a class of problems with a linear constraint containing sequential integer coefficients. For problems in this class, we devise QAOA$^+$ circuits that provably converge to the optimal solution as the number of circuit layers increases, generalizing previous guarantees for solving unconstrained problems or problems with symmetric constraints. Our approach includes asymmetric ``mixing" Hamiltonians that drive transitions between feasible states, as well as a method to incorporate an arbitrary known feasible solution as the initial state, each of which can be applied beyond the specific linear constraints considered here. This analysis extends QAOA$^+$ performance guarantees to a more general set of linearly-constrained problems and provides tools for future generalizations.
format Preprint
id arxiv_https___arxiv_org_abs_2409_18829
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence guarantee for linearly-constrained combinatorial optimization with a quantum alternating operator ansatz
Goldstein-Gelb, Brayden
Lotshaw, Phillip C.
Quantum Physics
We present a quantum alternating operator ansatz (QAOA$^+$) that solves a class of linearly constrained optimization problems by evolving a quantum state within a Hilbert subspace of feasible problem solutions. Our main focus is on a class of problems with a linear constraint containing sequential integer coefficients. For problems in this class, we devise QAOA$^+$ circuits that provably converge to the optimal solution as the number of circuit layers increases, generalizing previous guarantees for solving unconstrained problems or problems with symmetric constraints. Our approach includes asymmetric ``mixing" Hamiltonians that drive transitions between feasible states, as well as a method to incorporate an arbitrary known feasible solution as the initial state, each of which can be applied beyond the specific linear constraints considered here. This analysis extends QAOA$^+$ performance guarantees to a more general set of linearly-constrained problems and provides tools for future generalizations.
title Convergence guarantee for linearly-constrained combinatorial optimization with a quantum alternating operator ansatz
topic Quantum Physics
url https://arxiv.org/abs/2409.18829