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We establish a large deviation theorem for the empirical spectral distribution of random covariance matrices whose entries are independent random variables with mean 0, variance 1 and having controlled forth moments. Some new properties of…

Complex Variables · Mathematics 2017-07-25 Tien-Cuong Dinh , Duc-Viet Vu

The large deviations at Level 2.5 are applied to Markov processes with absorbing states in order to obtain the explicit extinction rate of metastable quasi-stationary states in terms of their empirical time-averaged density and of their…

Statistical Mechanics · Physics 2022-01-13 Cecile Monthus

A general theory is developed to study individual based models which are discrete in time. We begin by constructing a Markov chain model that converges to a one-dimensional map in the infinite population limit. Stochastic fluctuations are…

Statistical Mechanics · Physics 2014-06-03 Joseph D. Challenger , Duccio Fanelli , Alan J. McKane

We investigate the large deviation behaviour of a point process sequence based on a stationary symmetric stable non-Gaussian discrete-parameter random field using the framework of Hult and Samorodnitsky (2010). Depending on the ergodic…

Probability · Mathematics 2014-10-21 Vicky Fasen , Parthanil Roy

The study of chaotic systems, where rare events play a pivotal role, is essential for understanding complex dynamics due to their sensitivity to initial conditions. Recently, tools from large deviation theory, typically applied in the…

Chaotic Dynamics · Physics 2026-05-06 Lucianno Defaveri , Naftali R. Smith

We develop the connection between large deviation theory and more applied approaches to stochastic hybrid systems by highlighting a common underlying Hamiltonian structure. A stochastic hybrid system involves the coupling between a…

Probability · Mathematics 2015-09-23 Paul Bressloff , Olivier Faugeras

We consider a stochastic 2D Navier-Stokes equation in a bounded domain. The random force is assumed to be non-degenerate and periodic in time, its law has a support localised with respect to both time and space. Slightly strengthening the…

Probability · Mathematics 2022-05-10 Xuhui Peng , Lihu Xu

We show an extension of Sanov's theorem on large deviations, controlling the tail probabilities of i.i.d. random variables with matching concentration and anti-concentration bounds. This result has a general scope, applies to samples of any…

Machine Learning · Computer Science 2021-10-12 Akshay Balsubramani

The large deviations principles are established for a class of multidimensional degenerate stochastic differential equations with reflecting boundary conditions. The results include two cases where the initial conditions are adapted and…

Probability · Mathematics 2007-05-23 Zongxia Liang

We survey the recent advance in the rigorous qualitative theory of the 2d stochastic Navier-Stokes system that are relevant to the description of turbulence in two-dimensional fluids. After discussing briefly the initial-boundary value…

Mathematical Physics · Physics 2017-12-29 Sergei Kuksin , Armen Shirikyan

We derive a new maximal inequality for stationary sequences under a martingale-type condition introduced by Maxwell and Woodroofe [Ann. Probab. 28 (2000) 713-724]. Then, we apply it to establish the Donsker invariance principle for this…

Probability · Mathematics 2007-05-23 Magda Peligrad , Sergey Utev

A strictly stationary sequence of random variables is constructed with the following properties: (i) the random variables take the values -1 and +1 with probability 1/2 each, (ii) every five of the random variables are independent, (iii)…

Probability · Mathematics 2009-11-17 Richard C. Bradley

This paper establishes a central limit theorem and an invariance principle for a wide class of stationary random fields under natural and easily verifiable conditions. More precisely, we deal with random fields of the form $X_k =…

Probability · Mathematics 2012-07-13 Mohamed El Machkouri , Dalibor Volny , Wei Biao Wu

We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate…

Statistical Mechanics · Physics 2018-03-28 Stephen Whitelam

In this paper we investigate the continuum limits of a class of Markov chains. The investigation of such limits is motivated by the desire to model very large networks. We show that under some conditions, a sequence of Markov chains…

Networking and Internet Architecture · Computer Science 2011-06-22 Yang Zhang , Edwin K. P. Chong , Jan Hannig , Donald Estep

We establish the large deviation principle for solutions of one-dimensional SDEs with discontinuous coefficients. The main statement is formulated in a form similar to the classical Wentzel--Freidlin theorem, but under the considerably…

Probability · Mathematics 2016-07-14 Alexei Kulik , Daryna Sobolieva

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

We use the large deviation approach to sum rules pioneered by Gamboa, Nagel and Rouault to prove higher order sum rules for orthogonal polynomials on the unit circle. In particular, we prove one half of a conjectured sum rule of Lukic in…

Spectral Theory · Mathematics 2018-11-14 Jonathan Breuer , Barry Simon , Ofer Zeitouni

We consider finite-dimensional systems of linear stochastic differential equations ${\partial_t}{x_k}\left( t \right) = {A_{kp}}\left( t \right){x_p}\left( t \right)$, ${\bf A}(t)$ being a stationary continuous statistically isotropic…

Probability · Mathematics 2023-10-26 A. S. Il'yn , A. V. Kopyev , V. A. Sirota , K. P. Zybin

This paper is mainly concerned with the large deviation principle of the fractional McKean-Vlasov stochastic reaction-diffusion equation defined on R^n with polynomial drift of any degree. We first prove the well-posedness of the underlying…

Probability · Mathematics 2024-06-18 Zhang Chen , Bixiang Wang
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