Cluster moves with an entropic reservoir accelerate low-temperature simulations of three-dimensional spin glasses

Abstract

We present an algorithm for the simulation of three-dimensional spin glasses deep in the low-temperature phase: Parallel Tempering enhanced with Houdayer moves and with an entropic reservoir (PTHR). Although differences with the standard Houdayer algorithm are small, PTHR allows us to equilibrate a large number of samples of $L=16$ lattices with Gaussian couplings for temperatures $T\geq 0.2$. We show that the computational complexity displays better size scaling than standard Parallel Tempering. For finite sizes, our method outperforms other cluster algorithms by a speedup factor of around 64. In close analogy with standard Parallel Tempering, PTHR's computational complexity strongly relates to temperature chaos.