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Quantum Simulation

Constrained Quantum Optimization meets Model Reduction

arXiv
Authors: Max Tschaikowski, Andrea Vandin

Year

2026

Paper ID

56828

Status

Preprint

Abstract Read

~2 min

Abstract Words

92

Citations

N/A

Abstract

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.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Quantum optimization algorithms promise advantages for difficult problems but are costly to simulate and analyze on classical machines.

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