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 TMF, 2000, Volume 123, Number 1, Pages 94–106 (Mi tmf589)

Stochastic model of phase transition and metastability

A. I. Kirillovab, V. Yu. Mamakinb

a Moscow Power Engineering Institute (Technical University)
b Independent University of Moscow

Abstract: The evolution of a system with phase transition is simulated by a Markov process whose transition probabilities depend on a parameter. The change of the stationary distribution of the Markov process with a change of this parameter is interpreted as a phase transition of the system from one thermodynamic equilibrium state to another. Calculations and computer experiments are performed for condensation of a vapor. The sample paths of the corresponding Markov process have parts where the radius of condensed drops is approximately constant. These parts are interpreted as metastable states. Two metastable states occur, initial (gaseous steam) and intermediate (fog). The probability distributions of the drop radii in the metastable states are estimated.

DOI: https://doi.org/10.4213/tmf589

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English version:
Theoretical and Mathematical Physics, 2000, 123:1, 494–503

Bibliographic databases:

Citation: A. I. Kirillov, V. Yu. Mamakin, “Stochastic model of phase transition and metastability”, TMF, 123:1 (2000), 94–106; Theoret. and Math. Phys., 123:1 (2000), 494–503

Citation in format AMSBIB
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