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Optical beams propagating through atmospheric turbulence undergo spatiotemporal intensity fluctuations that deviate significantly from an ideal Gaussian profile. In this work, we present a unified theoretical and experimental framework for…

Optics · Physics 2026-03-10 Shouvik Sadhukhan , C. S. Narayanamurthy

We establish Cram\'er-type moderate deviation theorems for sums of locally dependent random variables and combinatorial central limit theorems. Under some mild exponential moment conditions, optimal error bounds and convergence ranges are…

Probability · Mathematics 2021-12-22 Song-Hao Liu , Zhuo-Song Zhang

We develop a straightforward analytical framework for the propagation of spatial light modes through a turbulent atmosphere. Built upon the split-step approach with the mode-based optical field representation, it directly assesses how…

Quantum Physics · Physics 2026-05-29 Konstantin Kravtsov

We consider nonlinear transport equations with non-local velocity, describing the time-evolution of a measure, which in practice may represent the density of a crowd. Such equations often appear by taking the mean-field limit of…

Optimization and Control · Mathematics 2017-01-06 Marco Caponigro , Benedetto Piccoli , Francesco Rossi , Emmanuel Trélat

We consider theoretically a driven-dissipative quantum many-body system consisting of an atomic ensemble in a single-mode optical cavity as described by the open Tavis-Cummings model. In this hybrid light-matter system the interplay between…

We consider the diffusion of independent particles experiencing random accelerations by a space- and time-dependent force as well as viscous damping. This model can exhibit several asymptotic behaviours, depending upon the limiting cases…

Chaotic Dynamics · Physics 2012-06-13 B. Mehlig , M. Wilkinson , V. Bezuglyy , K. Gustavsson , K. Nakamura

We show, through a refinement of the work theorem, that the average dissipation, upon perturbing a Hamiltonian system arbitrarily far out of equilibrium in a transition between two canonical equilibrium states, is exactly given by…

Statistical Mechanics · Physics 2008-05-14 R. Kawai , J. M. R. Parrondo , C. Van den Broeck

We establish the moderate deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, we derive the moderate deviation principle for two…

Probability · Mathematics 2016-11-04 Parisa Fatheddin , Jie Xiong

Cram\'er type moderate deviation theorems quantify the accuracy of the relative error of the normal approximation and provide theoretical justifications for many commonly used methods in statistics. In this paper, we develop a new…

Probability · Mathematics 2016-06-07 Qi-Man Shao , Wen-Xin Zhou

The dynamics of a quantum-many body system subject to measurements is naturally described by an ensemble of quantum trajectories, which can feature measurement-induced phase transitions (MIPTs). This phenomenon cannot be revealed through…

Expansions in the oscillation modes of tidally perturbed bodies provide a useful framework for representing tidally induced flows. However, recent work has demonstrated that such expansions produce inaccurate predictions for secular orbital…

Solar and Stellar Astrophysics · Physics 2023-10-16 Janosz W. Dewberry , Samantha C. Wu

By considering a lattice model of extended phase space, and using techniques of noncommutative differential geometry, we are led to: (a) the conception of vector fields as generators of motion and transition probability distributions on the…

Mathematical Physics · Physics 2014-11-18 A. Dimakis , C. Tzanakis

We describe how to characterize dynamical phase transitions in open quantum systems from a purely dynamical perspective, namely, through the statistical behavior of quantum jump trajectories. This approach goes beyond considering only…

Statistical Mechanics · Physics 2013-04-26 Igor Lesanovsky , Merlijn van Horssen , Madalin Guta , Juan P. Garrahan

We give new and explicitly computable examples of Gibbs-non-Gibbs transitions of mean-field type, using the large deviation approach introduced in [4]. These examples include Brownian motion with small variance and related diffusion…

Probability · Mathematics 2012-12-05 Frank Redig , Feijia Wang

We develop a generalization of the time-varying Drude model, treating carrier density, effective mass, and collision rate as explicit functions of time. We derive expressions for polarization, susceptibility, displacement, and permittivity…

Many problems of interest in computer science and information theory can be phrased in terms of a probability distribution over discrete variables associated to the vertices of a large (but finite) sparse graph. In recent years,…

Probability · Mathematics 2009-11-11 Amir Dembo , Andrea Montanari

We investigate the effect of disorder on the Curie-Weiss model with Glauber dynamics. In particular, we study metastability for spin-flip dynamics on the Erd\H{o}s-R\'enyi random graph $ER_n(p)$ with $n$ vertices and with edge retention…

Probability · Mathematics 2020-07-24 Frank den Hollander , Oliver Jovanovski

The flow of two macroscopically immiscible, viscous, incompressible fluids with unmatched densities is studied, where a transfer of mass between the constituents by phase transition is taken into account. To this end, two…

Analysis of PDEs · Mathematics 2025-05-09 Helmut Abels , Harald Garcke , Julia Wittmann

We study the critical droplet for a close-to-equilibrium Widom-Rowlinson model of interacting particles, represented by disks of radius $1$, in the two-dimensional plane at low temperature. The critical droplet is the set of macroscopic…

Mathematical Physics · Physics 2026-03-16 Frank den Hollander , Sabine Jansen , Roman Kotecký , Elena Pulvirenti

We propose a way to break symmetry in stochastic dynamics by introducing a dissipation term. We show in a specific mean-field model, that if the reversible model undergoes a phase transition of ferromagnetic type, then its dissipative…

Probability · Mathematics 2015-02-09 Francesca Collet , Paolo Dai Pra , Marco Formentin