Quantum tree generator improves QAOA state-of-the-art for the knapsack problem

Fuente: arXiv
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Auteurs principaux: Christiansen, Paul, Binkowski, Lennart, Ramacciotti, Debora, Wilkening, Sören
Format: Preprint
Publié: 2024
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author Christiansen, Paul
Binkowski, Lennart
Ramacciotti, Debora
Wilkening, Sören
author_facet Christiansen, Paul
Binkowski, Lennart
Ramacciotti, Debora
Wilkening, Sören
contents This paper introduces a novel approach to the Quantum Approximate Optimization Algorithm (QAOA), specifically tailored to the knapsack problem. We combine the recently proposed quantum tree generator as an efficient state preparation circuit for all feasible solutions to the knapsack problem with the framework of Grover-mixer QAOA to form the first representative of Amplitude Amplification-mixer QAOA (AAM-QAOA). On hard benchmark sets with up to 20 knapsack items, we demonstrate our method's improved performance over the current state-of-the-art Copula-QAOA. However, for larger instance sizes, both approaches fail to deliver better outcomes than greedily packing items in descending value-to-weight ratio, at least for the considered circuit depths. For sufficiently high circuit depths, however, we can prove that AAM-QAOA will eventually be able to sample the optimal solution.
format Preprint
id arxiv_https___arxiv_org_abs_2411_00518
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum tree generator improves QAOA state-of-the-art for the knapsack problem
Christiansen, Paul
Binkowski, Lennart
Ramacciotti, Debora
Wilkening, Sören
Quantum Physics
This paper introduces a novel approach to the Quantum Approximate Optimization Algorithm (QAOA), specifically tailored to the knapsack problem. We combine the recently proposed quantum tree generator as an efficient state preparation circuit for all feasible solutions to the knapsack problem with the framework of Grover-mixer QAOA to form the first representative of Amplitude Amplification-mixer QAOA (AAM-QAOA). On hard benchmark sets with up to 20 knapsack items, we demonstrate our method's improved performance over the current state-of-the-art Copula-QAOA. However, for larger instance sizes, both approaches fail to deliver better outcomes than greedily packing items in descending value-to-weight ratio, at least for the considered circuit depths. For sufficiently high circuit depths, however, we can prove that AAM-QAOA will eventually be able to sample the optimal solution.
title Quantum tree generator improves QAOA state-of-the-art for the knapsack problem
topic Quantum Physics
url https://arxiv.org/abs/2411.00518