Rank Dependent Branching-Selection Particle Systems
P. Groisman, N. Soprano-Loto

TL;DR
This paper introduces a broad class of branching-selection particle systems with rank-dependent branching rates and killing measures, analyzing their asymptotic behavior and velocities, including well-known models as special cases.
Contribution
It proposes a conjectured scaling limit for these systems and proves it for a related class, establishing universal asymptotic velocities based on model parameters.
Findings
Asymptotic velocity converges to for total mass of D equal to one.
Velocity remains when total mass of D is less than one, despite exponential growth in particle number.
The behavior depends only on the value of b(1) and the total mass of D.
Abstract
We consider a large family of branching-selection particle systems. The branching rate of each particle depends on its rank and is given by a function defined on the unit interval. There is also a killing measure supported on the unit interval as well. At branching times, a particle is chosen among all particles to the left of the branching one by sampling its rank according to . The measure is allowed to have total mass less than one, which corresponds to a positive probability of no killing. Between branching times, particles perform independent Brownian Motions in the real line. This setting includes several well known models like Branching Brownian Motion (BBM), -BBM, rank dependent BBM, and many others. We conjecture a scaling limit for this class of processes and prove such a limit for a related class of branching-selection particle system. This family is rich…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Stochastic processes and financial applications · Theoretical and Computational Physics
