GPU accelerated Monte Carlo simulations of lattice spin models

We consider Monte Carlo simulations of classical spin models of statistical mechanics using the massively parallel architecture provided by graphics processing units (GPUs). We discuss simulations of models with discrete and continuous variables, and using an array of algorithms ranging from single-spin flip Metropolis updates over cluster algorithms to multicanonical and Wang-Landau techniques to judge the scope and limitations of GPU accelerated computation in this field. For most simulations discussed, we find significant speed-ups by two to three orders of magnitude as compared to single-threaded CPU implementations.Comment: 5 pages, 4 figures, 1 table; Physics Procedia 15, 92 (2011

Far-from-equilibrium monopole dynamics in spin ice

Condensed matter in the low-temperature limit reveals exotic physics associated with unusual orders and excitations, with examples ranging from helium superfluidity1 to magnetic monopoles in spin ice2, 3. The far-from-equilibrium physics of such low-temperature states may be even more exotic, yet to access it in the laboratory remains a challenge. Here we demonstrate a simple and robust technique—the ‘magnetothermal avalanche quench’—and its use in the controlled creation of non-equilibrium populations of magnetic monopoles in spin ice at millikelvin temperatures. These populations are found to exhibit spontaneous dynamical effects that typify far-from-equilibrium systems and yet are captured by simple models. Our method thus opens new directions in the study of far-from-equilibrium states in spin ice and other exotic magnets