Constrained Quantum Optimization meets Model Reduction

Fuente: arXiv
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Main Authors: Tschaikowski, Max, Vandin, Andrea
Format: Preprint
Published: 2026
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author Tschaikowski, Max
Vandin, Andrea
author_facet Tschaikowski, Max
Vandin, Andrea
contents Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines. Recently, constrained quantum optimization has been investigated through the lens of Quantum Zeno dynamics, an approach which constrains the search to a subspace by means of quantum measurements. Exploiting that quantum measurements are projections, we propose a model reduction approach and show that simulations can be conducted in a lower-dimensional space. As possible applications, we demonstrate exponential state-space reduction of constrained quantum optimization in case of random 3-SAT and agent coordination problems over graphs.
format Preprint
id arxiv_https___arxiv_org_abs_2604_23317
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Constrained Quantum Optimization meets Model Reduction
Tschaikowski, Max
Vandin, Andrea
Quantum Physics
Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines. Recently, constrained quantum optimization has been investigated through the lens of Quantum Zeno dynamics, an approach which constrains the search to a subspace by means of quantum measurements. Exploiting that quantum measurements are projections, we propose a model reduction approach and show that simulations can be conducted in a lower-dimensional space. As possible applications, we demonstrate exponential state-space reduction of constrained quantum optimization in case of random 3-SAT and agent coordination problems over graphs.
title Constrained Quantum Optimization meets Model Reduction
topic Quantum Physics
url https://arxiv.org/abs/2604.23317