English

Computational Phase Transition Signature in Gibbs Sampling

Quantum Physics 2019-06-27 v1 Disordered Systems and Neural Networks Statistical Mechanics Computational Complexity Machine Learning

Abstract

Gibbs sampling is fundamental to a wide range of computer algorithms. Such algorithms are set to be replaced by physics based processors-be it quantum or stochastic annealing devices-which embed problem instances and evolve a physical system into an ensemble to recover a probability distribution. At a critical constraint to variable ratio, decision problems-such as propositional satisfiability-appear to statistically exhibit an abrupt transition in required computational resources. This so called, algorithmic or computational phase transition signature, has yet-to-be observed in contemporary physics based processors. We found that the computational phase transition admits a signature in Gibbs' distributions and hence we predict and prescribe the physical observation of this effect. We simulate such an experiment, that when realized experimentally, we believe would represent a milestone in the physical theory of computation.

Keywords

Cite

@article{arxiv.1906.10705,
  title  = {Computational Phase Transition Signature in Gibbs Sampling},
  author = {H. Philathong and V. Akshay and I. Zacharov and J. Biamonte},
  journal= {arXiv preprint arXiv:1906.10705},
  year   = {2019}
}

Comments

feedback welcome; RevTeX; 7 pages; 2 composite figures

R2 v1 2026-06-23T10:03:27.555Z