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Hill's equations arise in a wide variety of physical problems, and are specified by a natural frequency, a periodic forcing function, and a forcing strength parameter. This classic problem is generalized here in two ways: [A] to Random…

Mathematical Physics · Physics 2015-06-15 Fred C. Adams , Anthony M. Bloch

We characterize the complex, heavy-tailed probability distribution functions (pdf) describing the response and its local extrema for structural systems subjected to random forcing that includes extreme events. Our approach is based on the…

Chaotic Dynamics · Physics 2017-06-02 Han Kyul Joo , Mustafa A. Mohamad , Themistoklis P. Sapsis

Recently, it was shown that the probability distribution function (PDF) of the free energy of a single continuum directed polymer (DP) in a random potential, equivalently of the height of a growing interface described by the…

Statistical Mechanics · Physics 2017-03-29 Andrea De Luca , Pierre Le Doussal

We study several probability distributions relevant to the avalanche dynamics of elastic interfaces driven on a random substrate: The distribution of size, duration, lateral extension or area, as well as velocities. Results from the…

Disordered Systems and Neural Networks · Physics 2019-10-18 Alejandro B. Kolton , Pierre Le Doussal , Kay Joerg Wiese

In this paper we analyze the relaxed form of a shape optimization problem with state equation $\{{array}{ll} -div \big(a(x)Du\big)=f\qquad\hbox{in}D \hbox{boundary conditions on}\partial D. {array}.$ The new fact is that the term $f$ is…

Optimization and Control · Mathematics 2010-02-16 Giuseppe Buttazzo , Faustino Maestre

We discretize a risk-neutral optimal control problem governed by a linear elliptic partial differential equation with random inputs using a Monte Carlo sample-based approximation and a finite element discretization, yielding finite…

Optimization and Control · Mathematics 2023-11-10 Johannes Milz

Equations of motion for an electrically charged string with a current in an external electromagnetic field with regard to the first correction due to the self-action are derived. It is shown that the reparametrization invariance of the free…

High Energy Physics - Theory · Physics 2014-11-18 P. O. Kazinski

A polymer chain pinned in space exerts a fluctuating force on the pin point in thermal equilibrium. The average of such fluctuating force is well understood from statistical mechanics as an entropic force, but little is known about the…

Statistical Mechanics · Physics 2015-07-22 James T. Waters , Harold D. Kim

The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with…

Optimization and Control · Mathematics 2012-11-19 Eveline Rosseel , Garth N. Wells

We use the macroscopic fluctuation theory (MFT) to evaluate the probability distribution P of extreme values of integrated current J at a specified time t=T in the symmetric simple exclusion process (SSEP) on an infinite line. As shown…

Statistical Mechanics · Physics 2015-06-19 Arkady Vilenkin , Baruch Meerson , Pavel V. Sasorov

We study the complete probability distribution $\mathcal{P}\left(\bar{H},t\right)$ of the time-averaged height $\bar{H}=(1/t)\int_0^t h(x=0,t')\,dt'$ at point $x=0$ of an evolving 1+1 dimensional Kardar-Parisi-Zhang (KPZ) interface…

Statistical Mechanics · Physics 2019-07-09 Naftali R. Smith , Baruch Meerson , Arkady Vilenkin

This paper deals with the homogenization problem of one-dimensional pseudo-elliptic equations with a rapidly varying random potential. The main purpose is to characterize the homogenization error (random fluctuations), i.e., the difference…

Probability · Mathematics 2018-08-02 Atef Lechiheb , Ezeddine Haouala

We study height fluctuations of interfaces in the $(1+1)$-dimensional Kardar-Parisi-Zhang (KPZ) class, growing at different speeds in the left half and the right half of space. Carrying out simulations of the discrete polynuclear growth…

Statistical Mechanics · Physics 2018-04-18 Yasufumi Ito , Kazumasa A. Takeuchi

A fundamental problem in statistics is estimating the shape matrix of an Elliptical distribution. This generalizes the familiar problem of Gaussian covariance estimation, for which the sample covariance achieves optimal estimation error.…

Statistics Theory · Mathematics 2025-10-16 Lap Chi Lau , Akshay Ramachandran

Polymers in a turbulent flow are stretched out by the fluctuating velocity gradient; the stationary probability distribution function (p.d.f.) of extensions $R$ has a power-law tail with an exponent that increases with the Weissenberg…

Fluid Dynamics · Physics 2023-01-10 Jason R. Picardo , Emmanuel L. C. VI M. Plan , Dario Vincenzi

We investigate the statistics of the maximal fluctuation of two-dimensional Gaussian interfaces. Its relation to the entropic repulsion between rigid walls and a confined interface is used to derive the average maximal fluctuation $<m> \sim…

Statistical Mechanics · Physics 2007-05-23 Deok-Sun Lee

Stretched exponential probability density functions (pdf), having the form of the exponential of minus a fractional power of the argument, are commonly found in turbulence and other areas. They can arise because of an underlying random…

Statistical Mechanics · Physics 2009-10-30 U. Frisch , D. Sornette

The emergence of non-gaussian distributions for macroscopic quantities in nonequilibrium steady states is discussed with emphasis on the effective criticality and on the ensuing universality of distribution functions. The following problems…

Statistical Mechanics · Physics 2009-11-10 Zoltan Racz

We consider the Random Euclidean Assignment Problem in dimension $d=1$, with linear cost function. In this version of the problem, in general, there is a large degeneracy of the ground state, i.e. there are many different optimal matchings…

Probability · Mathematics 2021-07-16 Sergio Caracciolo , Vittorio Erba , Andrea Sportiello

In this study, we develop a stochastic optimal control approach with reinforcement learning structure to learn the unknown parameters appeared in the drift and diffusion terms of the stochastic differential equation. By choosing an…

Optimization and Control · Mathematics 2023-08-22 Shuzhen Yang
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