New approach to dynamical Monte Carlo methods: application to an epidemic model
| Autor: | Marco Antonio Alves da Silva, O. E. Aiello |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Statistics and Probability
Mesoscopic physics Computer science Monte Carlo method FOS: Physical sciences Markov process Computational Physics (physics.comp-ph) Condensed Matter Physics Euler method symbols.namesake General Physics (physics.gen-ph) Physics - General Physics symbols Statistical physics Epidemic model Physics - Computational Physics |
| Zdroj: | Physica A: Statistical Mechanics and its Applications. 327:525-534 |
| ISSN: | 0378-4371 |
| DOI: | 10.1016/s0378-4371(03)00504-1 |
| Popis: | A new approach to Dynamical Monte Carlo Methods is introduced to simulate markovian processes. We apply this approach to formulate and study an epidemic Generalized SIRS model. The results are in excellent agreement with the forth order Runge-Kutta Method in a region of deterministic solution. We also demonstrate that purely local interactions reproduce a poissonian-like process at mesoscopic level. The simulations for this case are checked self-consistently using a stochastic version of the Euler Method. Written with Scientific WorkPlace 3.51 in REVTex4 format, 11 pages with 2 figures in postscript format |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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