A Continuous-Time Urn Model for a System of Activated Particles

Rafik Aguech () and Hanene Mohamed
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Rafik Aguech: Department of Statistics and Operation Research, King Saud University, Riyadh 11451, Saudi Arabia
Hanene Mohamed: MODAL’X, UPL, University Paris Nanterre, CNRS, F92000 Nanterre, France

Mathematics, 2023, vol. 11, issue 24, 1-13

Abstract: We study a system of M particles with jump dynamics on a network of N sites. The particles can exist in two states, active or inactive. Only the former can jump. The state of each particle depends on its position. A given particle is inactive when it is at a given site, and active when it moves to a change site. Indeed, each sleeping particle activates at a rate λ > 0 , leaves its initial site, and moves for an exponential random time of parameter μ > 0 before uniformly landing at a site and immediately returning to sleep. The behavior of each particle is independent of that of the others. These dynamics conserve the total number of particles; there is no limit on the number of particles at a given site. This system can be represented by a continuous-time Pólya urn with M balls where the colors are the sites, with an additional color to account for particles on the move at a given time t . First, using this Pólya interpretation for fixed M and N , we obtain the average number of particles at each site over time and, therefore, those on the move due to mass conservation. Secondly, we consider a large system in which the number of particles M and the number of sites N grow at the same rate, so that the M / N ratio tends to a scaling constant α > 0 . Using the moment-generating function technique added to some probabilistic arguments, we obtain the long-term distribution of the number of particles at each site.

Keywords: random structure; stochastic process; continuous-time Pólya urn; moment-generating method; partial differential equation; stochastic approximation; renewable energy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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