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We review various methods to investigate the statics and the dynamics of collective composition fluctuations in dense polymer mixtures within fluctuating-field approaches. The central idea of fluctuating-field theories is to rewrite the…

Soft Condensed Matter · Physics 2007-05-23 Marcus Mueller , Friederike Schmid

In this paper, we develop an efficient numerical solver for unsteady diffusion-type partial differential equations with random coefficients. A major computational challenge in such problems lies in repeatedly handling large-scale linear…

Numerical Analysis · Mathematics 2026-01-19 Yujun Zhu , Min Li , Yulan Ning , Ju Ming

Some recent publications by authors from the University of Maryland analyse the fluctuations of multi-port model parameters in stochastic environments. These authors use random matrix theory (RMT) for estimates concerning eigenfunction…

Mathematical Physics · Physics 2011-11-10 Bastiaan Michielsen , Francois Issac , Isabelle Junqua , Cecile Fiachetti

This paper is concerned with a stochastic linear-quadratic optimal control problem in a finite time horizon, where the coefficients of the control system are allowed to be random, and the weighting matrices in the cost functional are…

Optimization and Control · Mathematics 2019-11-12 Jingrui Sun , Jie Xiong , Jiongmin Yong

We show that the limiting minimal eigenvalue distributions for a natural generalization of Gaussian sample-covariance structures (the "beta ensembles") are described by the spectrum of a random diffusion generator. By a Riccati…

Probability · Mathematics 2009-11-13 Jose A. Ramirez , Brian Rider

Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary…

Soft Condensed Matter · Physics 2015-09-10 Vladimir Mityushev

We derive a reduced-order state estimator for discrete-time infinite dimensional linear systems with finite dimensional Gaussian input and output noise. This state estimator is the optimal one-step estimate that takes values in a fixed…

Optimization and Control · Mathematics 2014-10-08 Atte Aalto

Contraction properties of the Riccati operator are studied within the context of non-stationary linear-quadratic optimal control. A lifting approach is used to obtain a bound on the rate of strict contraction, with respect to the Riemannian…

Systems and Control · Electrical Eng. & Systems 2023-09-06 Jintao Sun , Michael Cantoni

The empirical velocity of a reaction-diffusion front, propagating into an unstable state, fluctuates because of the shot noises of the reactions and diffusion. Under certain conditions these fluctuations can be described as a diffusion…

Statistical Mechanics · Physics 2020-08-26 Evgeniy Khain , Baruch Meerson , Pavel Sasorov

We study fluctuations of the empirical processes of a non-equilibrium interacting particle system consisting of two species over a domain that is recently introduced in [8] and establish its functional central limit theorem. This…

Probability · Mathematics 2021-01-12 Zhen-Qing Chen , Wai-Tong Louis Fan

In this paper we consider a diffusion process obtained as a small random perturbation of a dynamical system attracted to a stable equilibrium point. The drift and the diffusive perturbation are assumed to evolve slowly in time. We describe…

Probability · Mathematics 2016-10-23 Mark Freidlin , Leonid Koralov

This article develops a comprehensive framework for stability analysis of a broad class of commonly used continuous and discrete time-filters for stochastic dynamic systems with non-linear state dynamics and linear measurements under…

Methodology · Statistics 2020-06-11 Toni Karvonen , Silvère Bonnabel , Eric Moulines , Simo Särkkä

Estimating eigenvectors and low-dimensional subspaces is of central importance for numerous problems in statistics, computer science, and applied mathematics. This paper characterizes the behavior of perturbed eigenvectors for a range of…

Statistics Theory · Mathematics 2018-09-14 Joshua Cape , Minh Tang , Carey E. Priebe

In this paper, we propose a non-parametric method for state estimation of high-dimensional nonlinear stochastic dynamical systems, which evolve according to gradient flows with isotropic diffusion. We combine diffusion maps, a manifold…

Signal Processing · Electrical Eng. & Systems 2019-02-26 Tal Shnitzer , Ronen Talmon , Jean-Jacques Slotine

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

The paper studies the asymptotic behavior of Random Algebraic Riccati Equations (RARE) arising in Kalman filtering when the arrival of the observations is described by a Bernoulli i.i.d. process. We model the RARE as an order-preserving,…

Information Theory · Computer Science 2010-05-31 Soummya Kar , Bruno Sinopoli , Jose M. F. Moura

This note concerns a class of matrix Riccati equations associated with stochastic linear-quadratic optimal control problems with indefinite state and control weighting costs. A novel sufficient condition of solvability of such equations is…

Optimization and Control · Mathematics 2013-12-30 Kai Du

We consider ray propagation in a waveguide with a designed sound-speed profile perturbed by a range-dependent perturbation caused by internal waves in deep ocean environments. The Hamiltonian formalism in terms of the action and angle…

Chaotic Dynamics · Physics 2009-11-10 D. V. Makarov , M. Yu. Uleysky , S. V. Prants

In this article we consider the estimation of the log-normalization constant associated to a class of continuous-time filtering models. In particular, we consider ensemble Kalman-Bucy filter based estimates based upon several nonlinear…

Computation · Statistics 2021-01-28 Dan Crisan , Pierre Del Moral , Ajay Jasra , Hamza Ruzayqat

Consistency models have been proposed for fast generative modeling, achieving results competitive with diffusion and flow models. However, these methods exhibit inherent instability and limited reproducibility when training from scratch,…

Machine Learning · Computer Science 2026-02-02 Youngjoong Kim , Duhoe Kim , Woosung Kim , Jaesik Park