Published November 30, 2018 | Version v1
Journal article

Equivalence between nonlinear dynamical systems and urn processes

  • 1. Service de Physique des Systèmes Dynamiques, Faculté des Sciences, Université Libre de Bruxelles, 1050 Brussels (Belgium)
  • 2. Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil)
  • 3. Instituto de Física and International Center for Condensed Matter Physics, Universidade de Brasília, 70919-970 Brasília, DF (Brazil)
  • 4. Departamento de Biologia y Geologia, Fí sica y Quí mica Inorgánica, Universidad Rey Juan Carlos, Calle Tulipán S/N, 28933-Móstoles-Madrid (Spain)

Description

An equivalence is shown between a large class of deterministic dynamical systems and a class of stochastic processes, the balanced urn processes. These dynamical systems are governed by quasi-polynomial differential systems that are widely used in mathematical modeling while urn processes are actively studied in combinatorics and probability theory. The presented equivalence extends a theorem by Flajolet et al (2006 Discrete Mathematics and Theoretical Computer Science, AG (DMTCS Proc.) pp 59–118) already establishing an isomorphism between urn processes and a particular class of differential systems with monomial vector fields. The present result is based on the fact that such monomial differential systems are canonical forms for more general dynamical systems. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1751-8121/aae770

Additional details

Identifiers

Publishing Information

Journal Title
Journal of Physics. A, Mathematical and Theoretical (Online)
Journal Volume
51
Journal Issue
48
Journal Page Range
[14 p.]
ISSN
1751-8121

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52026326
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
BALANCES; DYNAMICAL SYSTEMS; MATHEMATICAL MODELS; NONLINEAR PROBLEMS; POLYNOMIALS; PROBABILITY; STOCHASTIC PROCESSES; VECTOR FIELDS
Descriptors DEC
FUNCTIONS; MEASURING INSTRUMENTS; WEIGHT INDICATORS