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Research PaperResearchia:202606.26083

A 0.651-approximation to quantum Max Cut via Rydberg atoms

Tomás Crosta

Abstract

Quantum Max Cut, also known as the anti-ferromagnetic Heisenberg Hamiltonian, is a QMA-complete problem which serves as a benchmark for approximation algorithms in quantum physics. Here we develop a hybrid approximation algorithm to quantum Max Cut, which uses the natural quantum dynamics of Rydberg atom systems in combination with semidefinite programming and randomized rounding. It achieves a conditional approximation ratio of $0.651$, compared to the best-known ratio of $0.614$ that relies on...

Submitted: June 26, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Quantum Max Cut, also known as the anti-ferromagnetic Heisenberg Hamiltonian, is a QMA-complete problem which serves as a benchmark for approximation algorithms in quantum physics. Here we develop a hybrid approximation algorithm to quantum Max Cut, which uses the natural quantum dynamics of Rydberg atom systems in combination with semidefinite programming and randomized rounding. It achieves a conditional approximation ratio of 0.6510.651, compared to the best-known ratio of 0.6140.614 that relies on semidefinite programming alone. The algorithm is robust in the sense that the advantage persists even if the annealing procedure of the Rydberg atom system obtains a state whose energy is only 89%89\% of its true ground state energy. Our approach opens a new route for hybrid quantum-classical algorithms that combine quantum with classical optimization methods.


Source: arXiv:2606.27224v1 - http://arxiv.org/abs/2606.27224v1 PDF: https://arxiv.org/pdf/2606.27224v1 Original Link: http://arxiv.org/abs/2606.27224v1

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Date:
Jun 26, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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