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Quantum Optimization for Maximum Independent Set Using Rydberg Atom Arrays

7 Pith papers cite this work. Polarity classification is still indexing.

7 Pith papers citing it
abstract

We describe and analyze an architecture for quantum optimization to solve maximum independent set (MIS) problems using neutral atom arrays trapped in optical tweezers. Optimizing independent sets is one of the paradigmatic, NP-hard problems in computer science. Our approach is based on coherent manipulation of atom arrays via the excitation into Rydberg atomic states. Specifically, we show that solutions of MIS problems can be efficiently encoded in the ground state of interacting atoms in 2D arrays by utilizing the Rydberg blockade mechanism. By studying the performance of leading classical algorithms, we identify parameter regimes, where computationally hard instances can be tested using near-term experimental systems. Practical implementations of both quantum annealing and variational quantum optimization algorithms beyond the adiabatic principle are discussed.

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2026 6 2025 1

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UNVERDICTED 7

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representative citing papers

Efficient Hamiltonian Engineering for Adiabatic MIS Algorithms

quant-ph · 2026-05-16 · unverdicted · novelty 6.0 · 2 refs

Engineered local Hamiltonian controls in Rydberg arrays accelerate adiabatic convergence to MIS solutions, raise success probabilities over global controls, and cut fidelity decay rate by 25% as graphs harden.

QOuLiPo: What a quantum computer sees when it reads a book

quant-ph · 2026-05-13 · unverdicted · novelty 5.0

Literary texts are turned into graphs for neutral-atom quantum processors, with a new rigidity metric distinguishing structural uniqueness and a QOuLiPo corpus of engineered texts created to match hardware-native graphs.

Reducibility of native weighted graphs on Rydberg Arrays

quant-ph · 2026-05-08 · unverdicted · novelty 5.0

Classical kernelisation fully reduces many small and sparse unit-disk graphs for MIS and MWIS native to Rydberg arrays, but dense graphs retain finite irreducible kernels, with vertex weights increasing reducibility and extended interaction ranges suppressing it.

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