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A continuous nonlinear optimization perspective on the Spin Glass Problem
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DOI：10.1016/j.physa.2026.131356.png)
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Abstract
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• The paper builds on Rosenberg’s classical result for multilinear optimization over box constraints and applies it to the Spin Glass Problem (SGP), showing that the continuous relaxation can be used (together with a simple problem-specific argument) to recover optimal discrete spin configurations. • The proposed continuous formulation, solved with a modern global optimization solver, attains high-quality solutions on standard benchmark instances and often matches or surpasses the best results obtained by recent integer programming linearization techniques.
Keywords:
Spin Glass Problem
Max cut problem
Continuous optimization
Integer programming
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