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Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct…

Fluid Dynamics · Physics 2023-12-13 Shengyu Chen , Tianshu Bao , Peyman Givi , Can Zheng , Xiaowei Jia

A new two-step renormalization procedure is proposed. In the first step, the effects of high-energy states are considered in the conventional (Feynman) perturbation theory. In the second step, the coupling to many-body states is eliminated…

High Energy Physics - Theory · Physics 2009-10-30 Koji Harada , Atsushi Okazaki

We consider a noninteracting disordered system designed to model particle diffusion, relaxation in glasses, and impurity bands of semiconductors. Disorder originates in the random spatial distribution of sites. We find strong numerical…

Disordered Systems and Neural Networks · Physics 2015-03-17 Jacob J. Krich , Alán Aspuru-Guzik

We obtain decay rates of probabilities of tails of polynomials in several independent random variables with heavy tails and derive stable limit theorems for nonconventional sums of such polynomials

Probability · Mathematics 2016-08-26 Yuri Kifer , S. R. S. Varadhan

In this paper, we consider the linearly reinforced and the once-reinforced random walk models in the transient phase on trees. We show the large deviations for the upper tails for both models. We also show the exponential decay for the…

Probability · Mathematics 2013-10-15 Yu Zhang

A statistical field theory is developed to explore the density of states and spatial profile of `tail states' at the edge of the spectral support of a general class of disordered non-Hermitian operators. These states, which are identified…

Disordered Systems and Neural Networks · Physics 2009-11-07 Francesca M. Marchetti , B. D. Simons

Image reconstruction from computed tomography (CT) measurement is a challenging statistical inverse problem since a high-dimensional conditional distribution needs to be estimated. Based on training data obtained from high-quality…

Image and Video Processing · Electrical Eng. & Systems 2020-06-12 Alexander Denker , Maximilian Schmidt , Johannes Leuschner , Peter Maass , Jens Behrmann

We study phenomenological scaling theories of the polymer dynamics in random media, employing the existing scaling theories of polymer chains and the percolation statistics. We investigate both the Rouse and the Zimm model for Brownian…

Soft Condensed Matter · Physics 2015-06-24 Bikas K. Chakrabarti , Amit K. Chattopadhyay , Amit Dutta

Many real-world systems studied are governed by complex, nonlinear dynamics. By modeling these dynamics, we can gain insight into how these systems work, make predictions about how they will behave, and develop strategies for controlling…

Machine Learning · Statistics 2019-06-05 Josue Nassar , Scott W. Linderman , Monica Bugallo , Il Memming Park

We consider the non-equilibrium dynamics of disordered systems as defined by a master equation involving transition rates between configurations (detailed balance is not assumed). To compute the important dynamical time scales in…

Disordered Systems and Neural Networks · Physics 2010-02-15 Cecile Monthus , Thomas Garel

Given $n$ samples of a regular discrete distribution $\pi$, we prove in this article first a serial of SLLNs results (of Dvoretzky and Erd\"{o}s' type) which implies a typical power law when $\pi$ is heavy-tailed. Constructing a (random)…

Probability · Mathematics 2013-12-12 Xin-Xing Chen , Jian-Sheng Xie , Jiangang Ying

Regularizing neural networks is important for anticipating model behavior in regions of the data space that are not well represented. In this work, we propose a regularization technique for enforcing a level of smoothness in the mapping…

Machine Learning · Computer Science 2025-03-05 Ali Hasan , Haoming Yang , Yuting Ng , Vahid Tarokh

Layers of two-dimensional materials arranged at a twist angle with respect to each other lead to enlarged unit cells with potentially strongly altered band structures, offering a new arena for novel and engineered many-body ground states.…

Strongly Correlated Electrons · Physics 2020-08-18 Lennart Klebl , Dante M. Kennes , Carsten Honerkamp

Scaling of the Reynolds stresses has been sought by many researchers, since it provides a template of universal dynamical patterns across a range of Reynolds numbers. Various statistical and normalization schemes have been attempted, but…

Fluid Dynamics · Physics 2024-07-18 T. -W. Lee , J. E. Park

Using a finite size scaling form for reunion probability, we show numerically the existence of a binding-unbinding transition for Directed polymers with random interaction. The cases studied are (A1) two chains in 1+1 dimensions, (A2) two…

Condensed Matter · Physics 2009-10-28 Sutapa Mukherji , Somendra M. Bhattacharjee , A. Baumgärtner

The Vosk-Altman Strong Disorder Renormalization for the unitary dynamics of various random quantum spin chains is reformulated as follows : the local degree of freedom characterized by the highest eigenfrequency $\Omega$ can be considered…

Disordered Systems and Neural Networks · Physics 2018-06-05 Cecile Monthus

A general strategy to solve the non-perturbative renormalization problem in lattice QCD, using finite-size techniques and numerical simulations, is described. As an illustration we discuss the computation of the axial current normalization…

High Energy Physics - Lattice · Physics 2009-10-28 Karl Jansen , Chuan Liu , Martin Luescher , Hubert Simma , Stefan Sint , Rainer Sommer , Peter Weisz , Ulli Wolff

Markov processes with stochastic resetting towards the origin generically converge towards non-equilibrium steady-states. Long dynamical trajectories can be thus analyzed via the large deviations at Level 2.5 for the joint probability of…

Statistical Mechanics · Physics 2021-05-07 Cecile Monthus

A perturbative renormalization group method is used to obtain steady-state density profiles of a particle non-conserving asymmetric simple exclusion process. This method allows us to obtain a globally valid solution for the density profile…

Statistical Mechanics · Physics 2017-04-05 Sutapa Mukherji

The non-perturbative renormalization-group approach is extended to lattice models, considering as an example a $\phi^4$ theory defined on a $d$-dimensional hypercubic lattice. Within a simple approximation for the effective action, we solve…

Statistical Mechanics · Physics 2009-03-02 N. Dupuis , K. Sengupta