English

Anomalous scaling and first-order dynamical phase transition in large deviations of the Ornstein-Uhlenbeck process

Statistical Mechanics 2022-01-21 v2

Abstract

We study the full distribution of A=0Txn(t)dtA=\int_{0}^{T}x^{n}\left(t\right)dt, n=1,2,n=1,2,\dots, where x(t)x\left(t\right) is an Ornstein-Uhlenbeck process. We find that for n>2n>2 the long-time (TT \to \infty) scaling form of the distribution is of the anomalous form P(A;T)eTμfn(ΔA/Tν)P\left(A;T\right)\sim e^{-T^{\mu}f_{n}\left(\Delta A/T^{\nu}\right)} where ΔA\Delta A is the difference between AA and its mean value, and the anomalous exponents are μ=2/(2n2)\mu=2/\left(2n-2\right), and ν=n/(2n2)\nu=n/\left(2n-2\right). The rate function fn(y)f_n\left(y\right), that we calculate exactly, exhibits a first-order dynamical phase transition which separates between a homogeneous phase that describes the Gaussian distribution of typical fluctuations, and a "condensed" phase that describes the tails of the distribution. We also calculate the most likely realizations of A(t)=0txn(s)ds\mathcal{A}(t)=\int_{0}^{t}x^{n}\left(s\right)ds and the distribution of x(t)x(t) at an intermediate time tt conditioned on a given value of AA. Extensions and implications to other continuous-time systems are discussed.

Keywords

Cite

@article{arxiv.2109.14972,
  title  = {Anomalous scaling and first-order dynamical phase transition in large deviations of the Ornstein-Uhlenbeck process},
  author = {Naftali R. Smith},
  journal= {arXiv preprint arXiv:2109.14972},
  year   = {2022}
}

Comments

9 pages, 2 figures