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Related papers: Direct evaluation of large-deviation functions

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Quantization for probability distributions refers broadly to estimating a given probability measure by a discrete probability measure supported by a finite number of points. We consider general geometric approaches to quantization using…

Dynamical Systems · Mathematics 2020-02-11 Joseph Rosenblatt , Mrinal Kanti Roychowdhury

This paper introduces coordinate-independent methods for analysing multiscale dynamical systems using numerical techniques based on the transfer operator and its adjoint. In particular, we present a method for testing whether an arbitrary…

Dynamical Systems · Mathematics 2014-09-30 Gary Froyland , Georg A. Gottwald , Andy Hammerlindl

Laws of large numbers, starting from certain nonequilibrium measures, have been shown for the integrated current across a bond, and a tagged particle in one-dimensional symmetric nearest-neighbor simple exclusion [Ann. Inst. Henri Poincare…

Probability · Mathematics 2013-05-28 Sunder Sethuraman , S. R. S. Varadhan

We study the probability of arbitrary density profiles in conserving diffusive fields which are driven by the boundaries. We demonstrate the existence of singularities in the large-deviation functional, the direct analog of the free-energy…

Statistical Mechanics · Physics 2015-10-07 Guy Bunin , Yariv Kafri , Daniel Podolsky

We establish large deviation type estimates for i.i.d. products of two dimensional random matrices with finitely supported probability distribution. The estimates are stable under perturbations and require no irreducibility assumptions. In…

Dynamical Systems · Mathematics 2019-10-23 Pedro Duarte , Silvius Klein

This work is a continuation of [7]. We consider a continuous-time birth-and-death process in which the transition rates have an asymptotical power-law dependence upon the position of the process. We establish rough exponential asymptotic…

Probability · Mathematics 2019-11-12 A. V. Logachov , Y. M. Suhov , N. D. Vvedenskaya , A. A. Yambartsev

We consider two Ito equations that evolve on different time scales. The equations are fully coupled in the sense that all coefficients may depend on both the "slow" and the "fast" processes and the diffusion terms may be correlated. The…

Probability · Mathematics 2016-12-13 Anatolii A. Puhalskii

We consider large deviations of empirical measures of diffusion processes. In a first part, we present conditions to obtain a large deviations principle (LDP) for a precise class of unbounded functions. This provides an analogue to the…

Probability · Mathematics 2020-09-23 Grégoire Ferré , Gabriel Stoltz

We extend the work of Kurchan on the Gallavotti-Cohen fluctuation theorem, which yields a symmetry property of the large deviation function, to general Markov processes. These include jump processes describing the evolution of stochastic…

Statistical Mechanics · Physics 2015-06-25 Joel. L. Lebowitz , Herbert Spohn

When applying the finite-differences method to numerically solve the one-dimensional diffusion equation, one must choose discretization steps $\Delta x$, $\Delta t$ in space and time, respectively. By applying large-deviation theory on the…

Statistical Mechanics · Physics 2024-04-09 Naftali R. Smith

We present an exact method for calculating the large deviation function describing rare fluctuations in the number of particles for product-kernel aggregation. Starting from the master equation, we derive an exact integral representation…

Statistical Mechanics · Physics 2026-02-05 R. Goutham , R. Rajesh , V. Subashri , Oleg Zaboronski

The accurate numerical solution of partial differential equations is a central task in numerical analysis allowing to model a wide range of natural phenomena by employing specialized solvers depending on the scenario of application. Here,…

Numerical Analysis · Mathematics 2022-12-13 Moritz Reh , Martin Gärttner

We consider the symmetric simple exclusion with open boundaries that are in contact with particle reservoirs at different densities. The reservoir densities changes at a slower time scale with respect to the natural time scale the system…

Probability · Mathematics 2019-04-30 Anna De Masi , Stefano Olla

We employ optimal control theory to study the problem of estimating the probability density function from a data set originating from an unknown probability distribution. The original variational problem is reformulated as a multi-stage…

Optimization and Control · Mathematics 2025-10-02 Markus Hegland , C. Yalçın Kaya

In this paper we discuss a closed-form approximation of the likelihood functions of an arbitrary diffusion process. The approximation is based on an exponential ansatz of the transition probability for a finite time step $\Delta t$, and a…

Physics and Society · Physics 2008-12-10 Luca Capriotti

Several numerical evaluations of the density and distribution of convolution of independent gamma variables are compared in their accuracy and speed. In application to renewal processes, an efficient formula is derived for the probability…

Computation · Statistics 2022-12-15 Chaoran Hu , Vladimir Pozdnyakov , Jun Yan

The symmetric simple exclusion process (SSEP) is a paradigmatic model of classical non-equilibrium dynamics. Exact results for large deviations of particle current in the SSEP have been obtained in various settings using integrability-based…

Statistical Mechanics · Physics 2026-05-26 Soumyabrata Saha , Sandeep Jangid , Kapil Sharma , Tridib Sadhu

Open, dissipative systems subject to a random force are directly quantized. The starting point is the effective action derived using the method of Parisi-Sourlas. Since the effective action is second-order, the method of Ostrogradsky was…

Condensed Matter · Physics 2007-05-23 Jose A. Magpantay

These lecture notes give a short review of methods such as the matrix ansatz, the additivity principle or the macroscopic fluctuation theory, developed recently in the theory of non-equilibrium phenomena. They show how these methods allow…

Statistical Mechanics · Physics 2009-11-13 B. Derrida

The Large Deviation Principle is established for stochastic models defined by past-dependent non linear recursions with small noise. In the Markov case we use the result to obtain an explicit expression for the asymptotics of exit time.

Probability · Mathematics 2007-05-23 F. Klebaner , R. Liptser
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