A CLuP algorithm to practically achieve $\sim 0.76$ SK--model ground state free energy
Mihailo Stojnic

TL;DR
This paper introduces a practical CLuP algorithm for the SK spin glass model that efficiently approximates the ground state free energy, achieving near-optimal results with polynomial complexity.
Contribution
The paper develops a novel CLuP-based algorithm for SK models and provides theoretical and empirical evidence of its effectiveness in approximating the ground state free energy.
Findings
Achieves approximately 0.76 ground state free energy for n~thousands.
Performance closely matches theoretical predictions for large n.
Computing near ground state energy becomes typically easy with the proposed method.
Abstract
We consider algorithmic determination of the -dimensional Sherrington-Kirkpatrick (SK) spin glass model ground state free energy. It corresponds to a binary maximization of an indefinite quadratic form and under the \emph{worst case} principles of the classical NP complexity theory it is hard to approximate within a factor. On the other hand, the SK's random nature allows (polynomial) spectral methods to \emph{typically} approach the optimum within a constant factor. Naturally one is left with the fundamental question: can the residual (constant) \emph{computational gap} be erased? Following the success of \emph{Controlled Loosening-up} (CLuP) algorithms in planted models, we here devise a simple practical CLuP-SK algorithmic procedure for (non-planted) SK models. To analyze the \emph{typical} success of the algorithm we associate to it (random) CLuP-SK models.…
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Taxonomy
TopicsComputational Physics and Python Applications · Parallel Computing and Optimization Techniques
