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

preprint2022arXivOpen access

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 (T→∞T \to \infty) scaling form of the distribution is of the anomalous form P(A;T)∼e−Tμfn(ΔA/Tν)P\left(A;T\right)\sim e^{-T^μf_{n}\left(ΔA/T^ν\right)} where ΔAΔA is the difference between AA and its mean value, and the anomalous exponents are μ=2/(2n−2)μ=2/\left(2n-2\right), and ν=n/(2n−2)ν=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.

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