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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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