Integrated error-suppressed pipeline for quantum optimization of nontrivial binary combinatorial optimization problems on gate-model hardware at the 156-qubit scale

We introduce a novel hybrid quantum–classical variational optimization method for unconstrained binary combinatorial optimization problems on gate-model quantum computers, integrating a custom variational ansatz, staged feedback-based dual variational parameter update strategies, efficient parametri...

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Hlavní autoři:	Natasha Sachdeva, Gavin S Hartnett, Smarak Maity, Samuel Marsh, Yulun Wang, Adam Winick, Ryan Dougherty, Daniel Canuto, You Quan Chong, G Adam Cox, Michael Hush, Pranav S Mundada, Christopher D B Bentley, Michael J Biercuk, Yuval Baum
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IOP Publishing 2026-01-01
Edice:	New Journal of Physics
Témata:	quantum optimization QAOA variational quantum algorithms combinatorial optimization
On-line přístup:	https://doi.org/10.1088/1367-2630/ae7150
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