SWAP algorithm for lattice spin models
arXiv:2402.04981 · doi:10.1103/PhysRevE.110.L043301
Abstract
We adapted the SWAP molecular dynamics algorithm for use in lattice Ising spin models. We dressed the spins with a randomly distributed length and we alternated long-range spin exchanges with conventional single spin flip Monte Carlo updates, both accepted with a stochastic rule which respects detailed balance. We show that this algorithm, when applied to the bidimensional Edwards-Anderson model, speeds up significantly the relaxation at low temperatures and manages to find ground states with high efficiency and little computational cost. The exploration of spin models should help in understanding why SWAP accelerates the evolution of particle systems and shed light on relations between dynamics and free-energy landscapes.
References in corpus (6)
- Theoretical perspective on the glass transition and amorphous materials
- Thirty milliseconds in the life of a supercooled liquid
- Modern computational studies of the glass transition
- Comparing Monte Carlo methods for finding ground states of Ising spin glasses: population annealing, simulated annealing and parallel tempering
- Limits and performances of algorithms based on simulated annealing in solving sparse hard inference problems
- Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture