The correlation length and its critical exponents are thus accessible with no a-priori knowledge of an order parameter or even the nature of the ordering.
Statistical Mechanics Disordered Systems and Neural Networks Soft Condensed Matter Cellular Automata and Lattice Gases Computational Physics
While the equilibrium properties, states, and phase transitions of interacting systems are well described by statistical mechanics, the lack of suitable state parameters has hindered the understanding of non-equilibrium phenomena in diverse settings, from glasses to driven systems to biology.
Soft Condensed Matter Disordered Systems and Neural Networks Statistical Mechanics Computational Physics
Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences.
Conventional Monte Carlo simulations are stochastic in the sense that the acceptance of a trial move is decided by comparing a computed acceptance probability with a random number, uniformly distributed between 0 and 1.