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For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical…

Applications · Statistics 2014-07-22 Xiao Lin , Gabriel Terejanu

This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function…

Probability · Mathematics 2023-08-10 Anatolii A. Puhalskii

The paper is devoted to a design of a common bounded feedback control steering a system of an arbitrary number of linear oscillators to the equilibrium. At high energies, the control is based on the asymptotic theory of reachable sets of…

Optimization and Control · Mathematics 2015-11-16 Alexander Ovseevich , Aleksey Fedorov

The variational method is very important in mathematical and theoretical physics because it allows us to describe the natural systems by physical quantities independently from the frame of reference used. A global and statistical approach…

Mathematical Physics · Physics 2011-01-10 Umberto Lucia

The maximum entropy technique (MENT) is used to determine the distribution functions of physical values. MENT naturally combines required maximum entropy, the properties of a system and connection conditions in the form of restrictions…

High Energy Physics - Experiment · Physics 2007-05-23 B. Z. Belashev , M. K. Suleymanov

In order to transmit biochemical signals, biological regulatory systems dissipate energy with concomitant entropy production. Additionally, signaling often takes place in challenging environmental conditions. In a simple model regulatory…

Molecular Networks · Quantitative Biology 2015-09-30 Francesca Mancini , Matteo Marsili , Aleksandra M. Walczak

We present a feedback protocol that is able to confine a system to a single micro-state without heat dissipation. The protocol adjusts the Hamiltonian of the system in such a way that the Bayesian posterior distribution after measurement is…

Statistical Mechanics · Physics 2017-07-04 Léo Granger , Luis Dinis , Jordan M. Horowitz , Juan MR Parrondo

Feedback optimization has emerged as a promising approach for regulating dynamical systems to optimal steady states that are implicitly defined by underlying optimization problems. Despite their effectiveness, existing methods face two key…

Optimization and Control · Mathematics 2025-09-18 Gianluca Bianchin , Bryan Van Scoy

This paper is about output-feedback control problems for general linear systems in the presence of given state-, control-, disturbance-, and measurement error constraints. Because the traditional separation theorem in stochastic control is…

Optimization and Control · Mathematics 2023-07-11 Boris Houska

A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property…

Statistics Theory · Mathematics 2010-02-24 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

The theory of large deviations constitutes a mathematical cornerstone in the foundations of Boltzmann-Gibbs statistical mechanics, based on the additive entropy $S_{BG}=- k_B\sum_{i=1}^W p_i \ln p_i$. Its optimization under appropriate…

Statistical Mechanics · Physics 2011-10-31 Guiomar Ruiz , Constantino Tsallis

Entropy production is a universal measure of irreversibility and energy dissipation in physical, chemical, and biological systems operating far from equilibrium. However, quantifying and spatiotemporally localising it in complex processes…

Statistical Mechanics · Physics 2026-05-18 Biswajit Das , Sreekanth K Manikandan

We propose a new perspective on Turbulence using Information Theory. We compute the entropy rate of a turbulent velocity signal and we particularly focus on its dependence on the scale. We first report how the entropy rate is able to…

Statistical Mechanics · Physics 2016-11-03 Carlos Granero-Belinchon , Stephane G. Roux , Nicolas B. Garnier

Birth-death processes form a natural class where ideas and results on large deviations can be tested. In this paper, we derive a large deviation principle under the assumption that the rate of a jump down (death) is growing asymptotically…

Probability · Mathematics 2023-08-21 N. D. Vvedenskaya , A. V. Logachov , Y. M. Suhov , A. A. Yambartsev

The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy--like quantities from small samples. We apply a recently introduced Bayesian entropy estimator to…

Data Analysis, Statistics and Probability · Physics 2009-09-29 Ilya Nemenman , William Bialek , Rob de Ruyter van Steveninck

We derive statistical-mechanical speed limits on dissipation from the classical, chaotic dynamics of many-particle systems. In one, the rate of irreversible entropy production in the environment is the maximum speed of a deterministic…

Statistical Mechanics · Physics 2024-06-19 Swetamber Das , Jason R. Green

We study two problems. First, we consider the large deviation behavior of empirical measures of certain diffusion processes as, simultaneously, the time horizon becomes large and noise becomes vanishingly small. The law of large numbers…

Probability · Mathematics 2023-09-14 Amarjit Budhiraja , Pavlos Zoubouloglou

The large deviation function for entropy production is calculated for a particle driven along a periodic potential by solving a time-independent eigenvalue problem. In an intermediate force regime, the large deviation function shows…

Statistical Mechanics · Physics 2009-01-15 Jakob Mehl , Thomas Speck , Udo Seifert

This work studies the design problem of feedback stabilizers for discrete-time systems with input delays. A backstepping procedure is proposed for disturbance-free discrete-time systems. The feedback law designed by using backstepping…

Optimization and Control · Mathematics 2012-12-05 Iasson Karafyllis , Miroslav Krstic

The climate system is a complex, chaotic system with many degrees of freedom and variability on a vast range of temporal and spatial scales. Attaining a deeper level of understanding of its dynamical processes is a scientific challenge of…

Statistical Mechanics · Physics 2021-06-28 Vera Melinda Galfi , Valerio Lucarini , Francesco Ragone , Jeroen Wouters
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