On the affine random walk on the torus

Abstract

Let μ be a borelian probability measure on G:=SLd(Z) Td. Define, for x∈ Td, a random walk starting at x denoting for n∈ N, \[ \arrayrcl X0 &=&x\\ Xn+1 &=& an+1 Xn + bn+1 array. \] where ((an,bn))∈ GN is an iid sequence of law μ. Then, we denote by Px the measure on (Td)N that is the image of μ N by the map ((gn) (x,g1 x, g2 g1 x, … , gn … g1 x, …)) and for any ∈ L1((Td)N, Px), we set Ex ((Xn)) = ∫ ((Xn)) dPx((Xn)). Bourgain, Furmann, Lindenstrauss and Mozes studied this random walk when μ is concentrated on SLd(Z) \0\ and this allowed us to study, for any h\"older-continuous function f on the torus, the sequence (f(Xn)) when x is not too well approximable by rational points. In this article, we are interested in the case where μ is not concentrated on SLd(Z) Qd/Zd and we prove that, under assumptions on the group spanned by the support of μ, the Lebesgue's measure on the torus is the only stationary probability measure and that for any h\"older-continuous function f on the torus, Ex f(Xn) converges exponentially fast to ∫ fd. Then, we use this to prove the law of large numbers, a non-concentration inequality, the functional central limit theorem and it's almost-sure version for the sequence (f(Xn)). In the appendix, we state a non-concentration inequality for products of random matrices without any irreducibility assumption.

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