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Spatial fields in the Earth and environmental sciences are often available at multiple scales or resolutions. While coarse-scale data (e.g., from global circulation models) are often abundant, they lack the local detail provided by…

Methodology · Statistics 2026-04-01 Alejandro Calle-Saldarriaga , Paul F. V. Wiemann , Matthias Katzfuss

We have studied a model of a random walk in a quenched random environment. In addition to featuring anomalous diffusion and localization, for special regimes of disorder parameters the particle density decomposes into multi-Gaussian…

Statistical Mechanics · Physics 2010-11-24 Tapio Simula , Mikko Stenlund

The decentralized gradient descent (DGD) algorithm, and its sibling, diffusion, are workhorses in decentralized machine learning, distributed inference and estimation, and multi-agent coordination. We propose a novel, principled framework…

Signal Processing · Electrical Eng. & Systems 2025-06-04 Erik G. Larsson , Nicolo Michelusi

We investigate the generalization of the spin-boson model to arbitrary spin size. The Born-Markov approximation is employed to derive a master equation in the regime of small coupling strengths to the environment. For spin one half, the…

Quantum Physics · Physics 2009-11-10 T. Vorrath , T. Brandes , B. Kramer

Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap…

Statistical Mechanics · Physics 2018-04-25 Liang Luo , Ming Yi

The autoresonant approach to excitation and control of large amplitude uniformly precessing magnetization structures in finite length easy axis ferromagnetic nanoparticles is suggested and analyzed within the Landau-Lifshitz-Gilbert model.…

Mesoscale and Nanoscale Physics · Physics 2020-01-13 A. G. Shagalov , L. Friedland

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

We present a Galerkin-Collocation domain decomposition algorithm applied to the evolution of cylindrical unpolarized gravitational waves. We show the effectiveness of the algorithm in reproducing initial data with high localized gradients…

General Relativity and Quantum Cosmology · Physics 2019-10-17 W. O. Barreto , J. A. Crespo , H. P. de Oliveira , E. L. Rodrigues

The dynamics of a magnetic moment or spin are of high interest to applications in technology. Dissipation in these systems is therefore of importance for improvement of efficiency of devices, such as the ones proposed in spintronics. A…

Mesoscale and Nanoscale Physics · Physics 2023-08-29 Robin C. Verstraten , Tim Ludwig , Rembert A. Duine , Cristiane Morais Smith

A generalized approach derived from Blochs equation of motion of nuclear magnetic moments is presented to model the frequency, magnetic field, spin density, and temperature dependencies in the electromagnetic permeability tensor for…

We are interested in numerically solving a transitional model derived from the Bloch model. The Bloch equation describes the time evolution of the density matrix of a quantum system forced by an electromagnetic wave. In a high frequency and…

Analysis of PDEs · Mathematics 2023-08-02 Brigitte Bidégaray-Fesquet , Clément Jourdana , Léopold Trémant

This study investigates nonlinear gravity waves in the compressible atmosphere from the Earth's surface to the deep atmosphere. These waves are effectively described by Grimshaw's dissipative modulation equations which provide the basis for…

Atmospheric and Oceanic Physics · Physics 2020-04-27 Mark Schlutow , Erik Wahlén

Using a semi-parametric approach based on the fourth-order Edgeworth expansion for the unknown signal distribution, we derive an explicit expression for the likelihood detection statistic in the presence of non-normally distributed…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-19 Lionel Martellini , Tania Regimbau

We have developed in the previous works a statistical model of quantum fluctuation based on a chaotic deviation from infinitesimal stationary action which is constrained by the principle of Locality to have a unique exponential distribution…

Quantum Physics · Physics 2015-06-19 Agung Budiyono

Recently, a nonlinear stability theory has been developed for wave trains in reaction-diffusion systems relying on pure $L^\infty$-estimates. In the absence of localization of perturbations, it exploits diffusive decay caused by smoothing…

Analysis of PDEs · Mathematics 2024-10-24 Joannis Alexopoulos , Björn de Rijk

A possible mechanism leading to anomalous diffusion is the presence of long-range correlations in time between the displacements of the particles. Fractional Brownian motion, a non-Markovian self-similar Gaussian process with stationary…

Statistical Mechanics · Physics 2019-04-03 Alexander H O Wada , Alex Warhover , Thomas Vojta

When nano-magnets are coupled to random external sources, their magnetization becomes a random variable, whose properties are defined by an induced probability density, that can be reconstructed from its moments, using the Langevin…

Statistical Mechanics · Physics 2017-03-21 Stam Nicolis , Pascal Thibaudeau , Julien Tranchida

We report on novel Brownian, yet non-Gaussian diffusion, in which the mean square displacement of the particle grows linearly with time, the probability density for the particle spreading is Gaussian-like, however, the probability density…

Statistical Mechanics · Physics 2020-10-28 K. Białas , J. Łuczka , P. Hänggi , J. Spiechowicz

In this paper we provide some uniqueness results for the (multi-)coefficient identification problem of reconstructing the spatially varying spin density as well as the spin-lattice and spin-spin relaxation times and the local field…

Analysis of PDEs · Mathematics 2026-03-27 Barbara Kaltenbacher

In this paper, we propose a new covering technique localized for the trajectories of SGD. This localization provides an algorithm-specific complexity measured by the covering number, which can have dimension-independent cardinality in…

Machine Learning · Statistics 2022-09-20 Sejun Park , Umut Şimşekli , Murat A. Erdogdu
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