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Physics

Probabilistic cellular automata are used in statistical and condensed matter physics to study phenomena like fluid dynamics and phase transitions. The Ising model is a prototypical example, in which each cell can be in either of two states called "up" and "down", making an idealized representation of a magnet. By adjusting the parameters of the model, the proportion of cells being in the same state can be varied, in ways that help explicate how ferromagnets become demagnetized when heated. Moreover, results from studying the demagnetization phase transition can be transferred to other phase transitions, like the evaporation of a liquid into a gas; this convenient cross-applicability is known as universality. The phase transition in the two-dimensional Ising model and other systems in its universality class has been of particular interest, as it requires conformal field theory to understand in depth. Other cellular automata that have been of significance in physics include lattice gas automata, which simulate fluid flows.