We study the statistics of a tagged particle in single-file diffusion, a one-dimensional interacting infinite-particle system in which the order of particles never changes. We compute the two-time correlation function for the displacement of the tagged particle for an arbitrary single-file system. We also discuss single-file analogs of the arcsine law and the law of the iterated logarithm characterizing the behavior of Brownian motion. Using a macroscopic fluctuation theory we devise a formalism giving the cumulant generating functional. In principle, this functional contains the full statistics of the tagged particle trajectory---the full single-time statistics, all multiple-time correlation functions, etc. are merely special cases.
We investigate the evolution of a light impurity particle in a Lorentz gas where the background atoms are in thermal equilibrium. As in the standard Lorentz gas, we assume that the particle is negligibly light in comparison with the background atoms. The thermal motion of atoms causes the average particle speed to grow. In the case of the hard-sphere particle-atom interaction, the temporal growth is ballistic, while generally it is sub-linear. For the particle-atom potential that diverges as r^{-lambda} in the small separation limit, the average particle speed grows as t^{lambda /(2(d-1)+ lambda)} in d dimensions. The particle displacement exhibits a universal growth, linear in time and the average (thermal) speed of the atoms. Surprisingly, the asymptotic growth is independent on the gas density and the particle-atom interaction. The velocity and position distributions approach universal scaling forms which are non-Gaussian. We determine the velocity distribution in arbitrary dimension and for arbitrary interaction exponent lambda. For the hard-sphere particle-atom interaction, we compute the position distribution and the joint velocity-position distribution.
We investigate the evolution of a particle in a Lorentz gas where the background scatters move and collide with each other. As in the standard Lorentz gas, we assume that the particle is negligibly light in comparison with scatters. We show that the average particle speed grows in time as t^{lambda/(4+lambda)} in three dimensions when the particle-scatter potential diverges as r^{-lambda} in the small separation limit. The typical displacement of the particle exhibits a universal linear growth in time independently on the density of the background gas and the particle-scatter interaction. The velocity and position distributions approach universal scaling forms. We determine the former, while for the position distribution we establish conjecturally exact scaling forms for the one and two-dimensional Lorentz gas.
We study the survival of a prey that is hunted by N predators. The predators perform independent random walks on a square lattice with V sites and start a direct chase whenever the prey appears within their sighting range. The prey is caught when a predator jumps to the site occupied by the prey. We analyze the efficacy of a lazy, minimal-effort evasion strategy according to which the prey tries to avoid encounters with the predators by making a hop only when any of the predators appears within its sighting range; otherwise the prey stays still. We show that if the sighting range of such a lazy prey is equal to 1 lattice spacing, at least 3 predators are needed in order to catch the prey on a square lattice. In this situation, we establish a simple asymptotic relation ln(Pev)(t) sim (N/V)2ln(Pimm(t)) between the survival probabilities of an evasive and an immobile prey. Hence, when the density of the predators is low N/V<<1, the lazy evasion strategy leads to the spectacular increase of the survival probability. We also argue that a short-sighting prey (its sighting range is smaller than the sighting range of the predators) undergoes an effective superdiffusive motion, as a result of its encounters with the predators, whereas a far-sighting prey performs a diffusive-type motion.
We study partition of networks into basins of attraction based on a steepest ascent search for the node of highest degree. Each node is associated with, or attracted to its neighbor of maximal degree, as long as the degree is increasing. A node that has no neighbors of higher degree is a peak, attracting all the nodes in its basin. Maximally random scale-free networks exhibit different behavior based on their degree distribution exponent $gamma$: for small $gamma$ (broad distribution) networks are dominated by a giant basin, whereas for large $gamma$ (narrow distribution) there are numerous basins, with peaks attracting mainly their nearest neighbors. We derive expressions for the first two moments of the number of basins. We also obtain the complete distribution of basin sizes for a class of hierarchical deterministic scale-free networks that resemble random nets. Finally, we generalize the problem to regular networks and lattices where all degrees are equal, and thus the attractiveness of a node must be determined by an assigned weight, rather than the degree. We derive the complete distribution of basins of attraction resulting from randomly assigned weights in one-dimensional chains.
We examine the global organization of growing networks in which a new vertex is attached to already existing ones with a probability depending on their age. We find that the network is infinite- or finite-dimensional depending on whether the attachment probability decays slower or faster than $(age)^{-1}$. The network becomes one-dimensional when the attachment probability decays faster than $(age)^{-2}$. We describe structural characteristics of these phases and transitions between them.
