Random Walk with Barycentric Self-interaction

We study the asymptotic behaviour of a d-dimensional self-interacting random walk (X _n ) _n∈? (?:={1,2,3,…}) which is repelled or attracted by the centre of mass (G_{n} = n^{-1} sum_{i=1}^{n} X_{i}) of its previous trajectory. The walk’s trajectory (X ₁,…,X _n ) models a random polymer chain in either poor or good solvent. In addition to some natural regularity conditions, we assume that the walk has one-step mean drift

$mathbb{E}[X_{n+1} - X_n mid X_n - G_n = mathbf{x}] approxrho|mathbf{x}|^{-beta}hat{ mathbf{x}}$

for ρ∈? and β≥0. When β<1 and ρ>0, we show that X _n is transient with a limiting (random) direction and satisfies a super-diffusive law of large numbers: n ^?1/(1+β) X _n converges almost surely to some random vector. When β∈(0,1) there is sub-ballistic rate of escape. When β≥0 and ρ∈? we give almost-sure bounds on the norms ‖X _n ‖, which in the context of the polymer model reveal extended and collapsed phases.

Analysis of the random walk, and in particular of X _n ?G _n , leads to the study of real-valued time-inhomogeneous non-Markov processes (Z _n ) _n∈? on [0,∞) with mean drifts of the form

$ mathbb{E}[ Z_{n+1} - Z_n mid Z_n = x ] approxrho x^{-beta} - frac {x}{n},$

(0.1)

where β≥0 and ρ∈?. The study of such processes is a time-dependent variation on a classical problem of Lamperti; moreover, they arise naturally in the context of the distance of simple random walk on ? ^d from its centre of mass, for which we also give an apparently new result. We give a recurrence classification and asymptotic theory for processes Z _n satisfying (0.1), which enables us to deduce the complete recurrence classification (for any β≥0) of X _n ?G _n for our self-interacting walk.