Benchmarking Quantum Computing for Combinatorial Optimization

Quantum computers can be much faster than any classical computers in solving a certain class of problems. One of the interesting problems is the combinatorial optimization problem, which is a challenge for classical computer systems. We encode these problems into the Quadratic Unconstrained Binary Optimization (QUBO) format and then solve them with quantum solvers. In this study, we compare the performance of D-Wave’s quantum annealing system with classical solvers, namely, Gurobi and Fixstars. We demonstrate the current capabilities of the D-Wave system.

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Publication Details

Published
2025-05-20
DOI
https://doi.org/10.1109/ecti-con64996.2025.11100821
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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Benchmarking Quantum Computing for Combinatorial Optimization

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Quantum Computing Algorithms and Architecture
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Benchmarking Quantum Computing for Combinatorial Optimization

Prabhas Chongstitvatana, Kamonluk Suksen, Nathan Kittichaikoonkij, Nutthapat Pongtanyavichai, Poopha Suwananek
article en

Abstract

Quantum computers can be much faster than any classical computers in solving a certain class of problems. One of the interesting problems is the combinatorial optimization problem, which is a challenge for classical computer systems. We encode these problems into the Quadratic Unconstrained Binary Optimization (QUBO) format and then solve them with quantum solvers. In this study, we compare the performance of D-Wave’s quantum annealing system with classical solvers, namely, Gurobi and Fixstars. We demonstrate the current capabilities of the D-Wave system.

Chulalongkorn University (TH)
Ministry of Education
Openalex Percentile: Top 90%
Quantum Computing Algorithms and Architecture
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