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Bibliographic Details
Main Authors: Giergiel, Krzysztof, Yang, Y. Sam, Murphy, Anthony B.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2509.04808
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author Giergiel, Krzysztof
Yang, Y. Sam
Murphy, Anthony B.
author_facet Giergiel, Krzysztof
Yang, Y. Sam
Murphy, Anthony B.
contents We evaluate the application of quantum annealing (QA) to a real-world combinatorial optimisation problem-room scheduling for sports camps at the Australian Institute of Sport-using both classical and quantum approaches. Due to current hardware limitations, the full problem cannot be embedded on existing QA platforms, motivating a hybrid method combining classical heuristics with quantum subroutines. We develop an improved formulation and a novel problem-aware calibration scheme, leveraging multi-qubit statistics to enhance the annealing performance. Our results show that the optimal annealing time aligns with the coherence time of the D-Wave Advantage 2 prototype (approximately 100 ns), with longer anneals yielding poorer outcomes before slow thermal recovery. Despite calibration and formulation improvements, QA performance degrades with increased connectivity and problem size, highlighting the need for improved qubit quality and parameter precision. These findings clarify the capabilities and limitations of current QA hardware and suggest strategies for extending its practical utility through hybrid methods and informed calibration.
format Preprint
id arxiv_https___arxiv_org_abs_2509_04808
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hybrid Quantum-Classical Scheduling with Problem-Aware Calibration on a Quantum Annealer
Giergiel, Krzysztof
Yang, Y. Sam
Murphy, Anthony B.
Quantum Physics
We evaluate the application of quantum annealing (QA) to a real-world combinatorial optimisation problem-room scheduling for sports camps at the Australian Institute of Sport-using both classical and quantum approaches. Due to current hardware limitations, the full problem cannot be embedded on existing QA platforms, motivating a hybrid method combining classical heuristics with quantum subroutines. We develop an improved formulation and a novel problem-aware calibration scheme, leveraging multi-qubit statistics to enhance the annealing performance. Our results show that the optimal annealing time aligns with the coherence time of the D-Wave Advantage 2 prototype (approximately 100 ns), with longer anneals yielding poorer outcomes before slow thermal recovery. Despite calibration and formulation improvements, QA performance degrades with increased connectivity and problem size, highlighting the need for improved qubit quality and parameter precision. These findings clarify the capabilities and limitations of current QA hardware and suggest strategies for extending its practical utility through hybrid methods and informed calibration.
title Hybrid Quantum-Classical Scheduling with Problem-Aware Calibration on a Quantum Annealer
topic Quantum Physics
url https://arxiv.org/abs/2509.04808