Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion

Fuente: arXiv
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Main Author: Beaujeault-Taudière, Yann
Format: Preprint
Published: 2025
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author Beaujeault-Taudière, Yann
author_facet Beaujeault-Taudière, Yann
contents The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant advantage. In this work, I study the enhancement of the QAOA with a generator coordinate method (GCM), and achieve systematic performances improvements in the approximation ratio and fidelity for the maximal independent set on Erdös-Rényi graphs. The cost-to-solution of the present method and the QAOA are compared by analysing the number of logical CNOT and $T$ gates required for either algorithm. Extrapolating on the numerical results obtained, it is estimated that for this specific problem and setup, the approach surpasses QAOA for graphs of size greater than 75 using as little as eight trial states. The potential of the method for other combinatorial optimisation problems is briefly discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2506_18594
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion
Beaujeault-Taudière, Yann
Quantum Physics
Nuclear Theory
The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant advantage. In this work, I study the enhancement of the QAOA with a generator coordinate method (GCM), and achieve systematic performances improvements in the approximation ratio and fidelity for the maximal independent set on Erdös-Rényi graphs. The cost-to-solution of the present method and the QAOA are compared by analysing the number of logical CNOT and $T$ gates required for either algorithm. Extrapolating on the numerical results obtained, it is estimated that for this specific problem and setup, the approach surpasses QAOA for graphs of size greater than 75 using as little as eight trial states. The potential of the method for other combinatorial optimisation problems is briefly discussed.
title Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion
topic Quantum Physics
Nuclear Theory
url https://arxiv.org/abs/2506.18594