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We develop the general form of the variational multiscale method in a discontinuous Galerkin framework. Our method is based on the decomposition of the true solution into discontinuous coarse-scale and discontinuous fine-scale parts. The…

Numerical Analysis · Mathematics 2017-09-20 Stein K. F. Stoter , Sergio R. Turteltaub , Steven J. Hulshoff , Dominik Schillinger

A fundamental question in nonequilibrium statistical physics is whether effective equilibrium behavior can emerge at coarse-grained scales in strongly driven systems. Here, we investigate this question in the context of human mobility by…

Physics and Society · Physics 2026-03-24 Lei Dong

Recently a cubic Galileon cosmological model was derived by the assumption that the field equations are invariant under the action of point transformations. The cubic Galileon model admits a second conservation law which means that the…

General Relativity and Quantum Cosmology · Physics 2017-11-28 Alex Giacomini , Sameerah Jamal , Genly Leon , Andronikos Paliathanasis , Joel Saavedra

This work presents a rigorous framework based on coarse-graining to analyze highly compressible turbulence. We show how the requirement that viscous effects on the dynamics of large-scale momentum and kinetic energy be negligible ---an…

Fluid Dynamics · Physics 2012-12-27 Hussein Aluie

Filtering is a general name for inferring the states of a dynamical system given observations. The most common filtering approach is Gaussian Filtering (GF) where the distribution of the inferred states is a Gaussian whose mean is an affine…

Signal Processing · Electrical Eng. & Systems 2018-11-21 Arash Mehrjou , Bernhard Schölkopf

The identification of the constrained dynamics of mechanical systems is often challenging. Learning methods promise to ease an analytical analysis, but require considerable amounts of data for training. We propose to combine insights from…

Machine Learning · Computer Science 2020-09-16 A. Rene Geist , Sebastian Trimpe

Gaussian processes (GPs) are a good choice for function approximation as they are flexible, robust to over-fitting, and provide well-calibrated predictive uncertainty. Deep Gaussian processes (DGPs) are multi-layer generalisations of GPs,…

Machine Learning · Statistics 2017-11-15 Hugh Salimbeni , Marc Deisenroth

We develop a coarse grained (CG) approach for efficiently simulating calcium dynamics in the endoplasmic reticulum membrane based on a fine stochastic lattice gas model. By grouping neighboring microscopic sites together into CG cells and…

Chemical Physics · Physics 2015-06-15 Chuansheng Shen , Hanshuang Chen

We introduce a scalable variational method for simulating the dynamics of interacting open quantum bosonic systems deep in the quantum regime. The method is based on a multi-dimensional Wigner phase-space representation and employs a…

Quantum Physics · Physics 2025-07-21 Jacopo Tosca , Francesco Carnazza , Luca Giacomelli , Cristiano Ciuti

We study the decoherence properties of a certain class of Markovian quantum open systems from both the Decohering Histories and Environment Induced Superselection paradigms. The class studied includes many familiar quantum optical cases.…

General Relativity and Quantum Cosmology · Physics 2007-05-23 J. Twamley

We obtain invariance principles for a wide class of fractionally integrated nonlinear processes. The limiting distributions are shown to be fractional Brownian motions. Under very mild conditions, we extend earlier ones on long memory…

Probability · Mathematics 2007-06-13 Wei Biao Wu , Xiaofeng Shao

It has recently been argued that quantization can be established within classical theory as a consequence of lost information. In this view, classical mechanics is regarded as a union of quantum mechanics and what are called 'hidden…

General Physics · Physics 2007-05-23 J. Towe

Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner of additive models and via a link function (like in…

Machine Learning · Statistics 2016-04-19 Alan D. Saul , James Hensman , Aki Vehtari , Neil D. Lawrence

Discrete scale invariance, which corresponds to a partial breaking of the scaling symmetry, is reflected in the existence of a hierarchy of characteristic scales l0, c l0, c^2 l0,... where c is a preferred scaling ratio and l0 a microscopic…

Statistical Mechanics · Physics 2015-06-25 A. Johansen , D. Sornette

The bivariate copulas that describe the dependencies and partial dependencies of lagged variables in strictly stationary, first-order GARCH-type processes are investigated. It is shown that the copulas of symmetric GARCH processes are…

Methodology · Statistics 2025-10-10 Alexandra Dias , Jialing Han , Alexander J. McNeil

Coarse-grained descriptions can be used to account for physical processes in which information is lost or not entirely accessible. In this paper, we start by proposing a connection between effective, coarse-grained descriptions of quantum…

A novel principle is presented which allows for the proof of bounded weak solutions to a class of physically relevant, strongly coupled parabolic systems exhibiting a formal gradient-flow structure. The main feature of these systems is that…

Analysis of PDEs · Mathematics 2015-06-11 Ansgar Jüngel

In nonequilibrium classical thermostatistics, the state of a system may be described by not only dynamical/thermodynamical variables but also a kinetic distribution function. This "double structure" bears some analogy with that in quantum…

Statistical Mechanics · Physics 2021-03-17 Sumiyoshi Abe

The Galerkin difference (GD) basis is a set of continuous, piecewise polynomials defined using a finite difference like grid of degrees of freedom. The one dimensional GD basis functions are naturally extended to multiple dimensions using…

Numerical Analysis · Mathematics 2021-06-03 Jeremy E. Kozdon , Lucas C. Wilcox , Thomas Hagstrom , Jeffrey W. Banks

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger
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