English
Related papers

Related papers: Reduced model for deep bed filtration of binary hi…

200 papers

Energy-based models (EBMs) are a simple yet powerful framework for generative modeling. They are based on a trainable energy function which defines an associated Gibbs measure, and they can be trained and sampled from via well-established…

Machine Learning · Computer Science 2021-05-06 Carles Domingo-Enrich , Alberto Bietti , Eric Vanden-Eijnden , Joan Bruna

The processes responsible for the effective longitudinal transport of solar energetic particles (SEPs) are still not completely understood. We address this issue by simulating SEP electron propagation using a spatially 2D transport model…

Solar and Stellar Astrophysics · Physics 2018-04-12 R. D. Strauss , N. Dresing , N. E. Engelbrecht

We study theoretically the bulk modulus (inverse of the compressibility) of a suspension of charged objects (macro-ions), making use of a cell model to account for the finite density of macro-ions. The diffuse layer of charged micro-species…

Soft Condensed Matter · Physics 2007-05-23 Gabriel Tellez , Emmanuel Trizac

The stopping of baryons in heavy ion collisions at beam momenta of $p_{\rm lab} = 20-160A$ GeV is lacking a quantitative description within theoretical calculations. Heavy ion reactions at these energies are experimentally explored at the…

Nuclear Theory · Physics 2020-03-10 Justin Mohs , Sangwook Ryu , Hannah Elfner

Thermodynamic properties of charge-stabilised colloidal suspensions are commonly modeled by implementing the mean-field Poisson-Boltzmann (PB) theory within a cell model. This approach models a bulk system by a single macroion, together…

Soft Condensed Matter · Physics 2015-05-18 Alan R. Denton

A two-parameter extension of the density-scaled double hybrid approach of Sharkas et al. [J. Chem. Phys. 134, 064113 (2011)] is presented. It is based on the explicit treatment of a fraction of multideterminantal exact exchange. The…

Chemical Physics · Physics 2012-01-12 Emmanuel Fromager

The hindered diffusion model is introduced. It is a continuum model giving the dynamics of a conserved density. Similar to the spin-facilitated models, the kinetics are hindered by a fluctuating diffusion coefficient that decreases as the…

Statistical Mechanics · Physics 2007-05-23 Gene F Mazenko

We study bulk recombination in a medium with energetic disorder by using the multiple trapping (MT) model under continuous irradiation with excitation light. Charge densities are shown to obey power law as a function of the intensity of…

Materials Science · Physics 2013-03-08 Kazuhiko Seki , M. Tachiya

Deep learning has become a powerful and popular tool for a variety of machine learning tasks. However, it is challenging to understand the mechanism of deep learning from a theoretical perspective. In this work, we propose a random active…

Machine Learning · Computer Science 2018-10-31 Haiping Huang , Alireza Goudarzi

We uncover a seemingly previously unnoticed algebraic structure of a large class of reaction-diffusion equations and use it, in particular, to study the long time behavior of the solutions and their convergence to traveling waves in the…

Analysis of PDEs · Mathematics 2022-11-30 Jing An , Christopher Henderson , Lenya Ryzhik

We present a simple quantum mechanical model describing excited rotational states of molecules in superfluid helium nanodroplets, as recently studied in non-adiabatic molecular alignment experiments [Cherepanov et al., Phys. Rev. A 104,…

We present a general framework for deriving entropy production rates (EPRs) in active matter systems driven by non-Gaussian active fluctuations. Employing the probability-flow equivalence technique, we rigorously obtain an entropy…

Statistical Mechanics · Physics 2025-12-12 Yuanfei Huang , Chengyu Liu , Bing Miao , Xiang Zhou

De-interleaving of the mixtures of Hidden Markov Processes (HMPs) generally depends on its representation model. Existing representation models consider Markov chain mixtures rather than hidden Markov, resulting in the lack of robustness to…

Machine Learning · Statistics 2024-06-04 Jiadi Bao , Mengtao Zhu , Yunjie Li , Shafei Wang

In this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions with persistent homology analysis, so as to construct a series of…

Biomolecules · Quantitative Biology 2016-12-28 Kelin Xia , Zhiming Li , Lin Mu

We show how a fixed point based boundary-layer analysis technique can be used to obtain the steady-state particle density profiles of driven exclusion processes on two-lane systems with open boundaries. We have considered two distinct…

Statistical Mechanics · Physics 2015-06-11 Vandana Yadav , Rajesh Singh , Sutapa Mukherji

The standing wave model describes the well-known phenomenon of superconductivity in a new way [1]. Starting from a new definition of superconductivity, a microscopic London relation is derived from first principles. The relation between the…

Superconductivity · Physics 2020-06-02 Refael Gatt

The Hubbard model is a "highly oversimplified model" for electrons in a solid which interact with each other through extremely short ranged repulsive (Coulomb) interaction. The Hamiltonian of the Hubbard model consists of two pieces; H_hop…

Strongly Correlated Electrons · Physics 2008-02-03 Hal Tasaki

We discuss a schematic model of mode-coupling theory for force-driven active nonlinear microrheology, where a single probe particle is pulled by a constant external force through a dense host medium. The model exhibits both a glass…

Soft Condensed Matter · Physics 2018-07-11 Manuel Victor Gnann , Thomas Voigtmann

The transport of deformable particles through porous media underlies a wealth of applications ranging from filtration to oil recovery to the transport and spreading of biological agents. Using direct numerical simulations, we analyze the…

Soft Condensed Matter · Physics 2020-06-09 Brato Chakrabarti , Charles Gaillard , David Saintillan

We present and derive a novel double-continuum transport model based on pore-scale characteristics. Our approach relies on building a simplified unit cell made up of immobile and mobile continua. We employ a numerically resolved pore-scale…

Fluid Dynamics · Physics 2019-06-26 Giulia Ceriotti , Anna Russian , Diogo Bolster , Giovanni Porta