Survival Probability of a Mobile Particle in a Fluctuating Field
Satya N. Majumdar, Stephen J. Cornell
Abstract
We study the the survival probability P(t) upto time t, of a test particle moving in a fluctuating external field. The particle moves according to some prescribed deterministic or stochastic rules and survives as long as the external field that it sees at its own location does not change sign. This is a natural generalization of the "static persistence" (when the particle is at rest) that has generated considerable recent interests. Two types of motions of the particle are considered. In one case, the particle adopts a strategy to live longer and in the other it just diffuses randomly. Three different external fields were considered: (i) the solution of diffusion equation, (ii) the "colour" profile of the q-state Potts model undergoing zero temperature coarsening dynamics and (iii) spatially uncorrelated Brownian signals. In most cases studied, P(t) t-θm for large t. The exponent θm is calculated via numerically, analytically by approximate methods and in some cases exactly. It is shown in some special cases that the survival probability of the mobile particle is related to the persistence of special "patterns" present in the initial configuration of a phase ordering system.
Create a lesson
Related papers
Robust Golden Ratio universality as a consequence of a circulant symmetry
Luka Paljk, Johannes Schmidt, Vladislav Popkov
Replica Transition at Measurement-Altered Ising Criticality
Kabir Khanna, Sara Murciano, Romain Vasseur
Scalene Yang-Baxter triples realize all nearest-neighbour Hamiltonians with global additive symmetries
Pramod Padmanabhan, Somnath Maity, Akash Sinha et al.
Graph-theoretic framework for semi-Markov networks: transient and stationary occupation probabilities, hitting times and weak ergodicity breaking
Julian Voits
Spectral optimization of spherical lattices and applications to classical and quantum interacting spin systems
Jonas Völler, Grigorios Makris, Fabian Hassler et al.
Entropic-ordered superfluid
Isabella Zane, Andrew Lucas