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Ordinary differential equation system for population of individuals and the corresponding probabilistic model

Journal article
Authors Eugen Mamontov
Published in Mathl. Computer Modelling
ISSN 0895-7177
Publication year 2008
Published at Department of Physics (GU)
Language en
Links dx.doi.org/10.1016/j.mcm.2008.09.01...
Subject categories Applied mathematics, Informatics and systems science, Bioinformatics (Computational Biology), Biostatistics, Biological physics, Mathematical physics, Statistical physics, Non-linear dynamics, chaos, Statistical mechanics, Structural Biology, Biophysics, Bioinformatics and Systems Biology, Signal Processing, Fluid mechanics, Sociology

Abstract

The key model for particle populations in statistical mechanics is the Bogolyubov–Born– Green–Kirkwood–Yvon (BBGKY) equation chain. It is derived mainly from the Hamilton ordinary differential equation (ODE) system for the vectors of the particle states in the particle position-momentum phase space. Many problems beyond physics or chemistry, for instance, in the living-matter sciences (biology, medicine, ecology, and scoiology) make it necessary to extend the notion of a particle to an individual, or active particle. This challenge is met by the generalized kinetic theory. It implements the extension by extending the phase space from the space of the position-momentum vectors to more rich spaces formed by the state vectors with the entries which need not be limited to the entries of the position and momentum: they include other scalar variables (e.g., those associated with modelling homeorhesis or other features inherent to the individuals). One can assume that the dynamics of the state vector in the extended space, i.e. the states of the individuals (rather than common particles) is also described by an ODE system. The latter, however, need not be the Hamilton one. The question is how one can derive the analogue of the BBGKY paradigm for the new settings. The present work proposes an answer to this question. It applies a very limited number of carefully selected tools of probability theory and common statistical mechanics. It in particular uses the well-known feature that the maximum number of the individuals which can mutually interact simultaneously is bounded by a fixed value of a few units. The present approach results in the finite system of equations for the reduced many-individual distribution functions thereby eliminating the so-called closure problem inevitable in the BBGKY theory. The thermodynamic-limit assumption is not needed either. The system includes consistently derived terms of all of the basic types known in kinetic theory, in particular, both the “mean-field” and scattering-integral terms, and admits the kinetic equation of the form allowing a direct chemical-reaction reading. The present approach can deal with Hamilton’s equation systems which are nonmonogenic and not treated in statistical mechanics. The proposed modelling suggests the basis of the generalized kinetic theory and may serve as the stochastic mechanics of population of individuals.

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http://gu.se/english/research/publication/?publicationId=71276
Utskriftsdatum: 2019-12-16