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Gaussian Process Bayesian Optimization for QUBO Penalty Weight Auto-Setting on a Distributed Quantum and Quantum-Inspired Annealing Platform

Year: 2026

Type: conference-paper

Abstract: This paper proposes the use of Gaussian process Bayesian optimization (GPBO) to address the challenging problem of penalty weight auto-setting (PWAS) in quadratic unconstrained binary optimization (QUBO) formulations on a distributed quantum and quantum-inspired annealing platform called National Central University Annealer (NCUA). The GPBO approach is compared with a PWAS method, namely maximum QUBO coefficient (MQC), to show its superiority.

Source: IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)

DOI: 10.1109/icce-taiwan71481.2026.11652773

Authors: Jehn-Ruey Jiang, Dai-Lun Chiang, Wen-Han Huang

Institutions: National Central University, Tunghai University

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7204124151

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Cites: 6

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Related to: 10