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

Naftali R. Smith

2022Physical review. E32 citationsDOIOpen Access PDF

Abstract

We study the full distribution of $A={\ensuremath{\int}}_{0}^{T}{x}^{n}(t)dt, n=1,2,\ensuremath{\cdots}$, where $x(t)$ is an Ornstein-Uhlenbeck process. We find that for $n>2$ the long-time ($T\ensuremath{\rightarrow}\ensuremath{\infty}$) scaling form of the distribution is of the anomalous form $P(A;T)\ensuremath{\sim}{e}^{\ensuremath{-}{T}^{\ensuremath{\mu}}{f}_{n}(\mathrm{\ensuremath{\Delta}}A/{T}^{\ensuremath{\nu}})}$ where $\mathrm{\ensuremath{\Delta}}A$ is the difference between $A$ and its mean value, and the anomalous exponents are $\ensuremath{\mu}=2/(2n\ensuremath{-}2)$ and $\ensuremath{\nu}=n/(2n\ensuremath{-}2)$. The rate function ${f}_{n}(y)$, which 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 $\mathcal{A}(t)={\ensuremath{\int}}_{0}^{t}{x}^{n}(s)ds$ and the distribution of $x(t)$ at an intermediate time $t$ conditioned on a given value of $A$. Extensions and implications to other continuous-time systems are discussed.

Topics & Concepts

ScalingStatistical physicsLarge deviations theoryDistribution (mathematics)Distribution functionGaussianPhase transitionPhysicsPhase (matter)MathematicsFunction (biology)HomogeneousRate functionDynamical systems theoryProbability distributionGaussian processExponentCritical exponentScale invarianceScale (ratio)Dynamical system (definition)Mathematical analysisWork (physics)Process (computing)Stochastic processTheoretical and Computational Physicsstochastic dynamics and bifurcationStatistical Mechanics and Entropy
Anomalous scaling and first-order dynamical phase transition in large deviations of the Ornstein-Uhlenbeck process | Litcius