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Stochastic model of phase transition and metastability

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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.

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Authors and Affiliations

  1. Higher College for Mathematical Physics, Moscow Independent University, Moscow, Russia

    A. I. Kirillov

  2. Moscow Institute of Power Engineering, Moscow, Russia

    A. I. Kirillov

  3. Higher College for Mathematical Physics, Moscow Independent University, Moscow, Russia

    V. Yu. Mamakin

  4. Moscow State University, Moscow, Russia

    V. Yu. Mamakin

Authors
  1. A. I. Kirillov
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  2. V. Yu. Mamakin
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Additional information

Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 123, No. 1, pp. 94–106, April, 2000.

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Kirillov, A.I., Mamakin, V.Y. Stochastic model of phase transition and metastability. Theor Math Phys 123, 494–503 (2000). https://doi.org/10.1007/BF02551056

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  • DOI: https://doi.org/10.1007/BF02551056

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