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Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier…

Statistical Mechanics · Physics 2017-01-04 Hamid Seyed-Allaei , Lutz Schimansky-Geier , Mohammad Reza Ejtehadi

The dynamics of induced fission of $^{226}$Th is investigated in a theoretical framework based on the finite-temperature time-dependent generator coordinate method (TDGCM) in the Gaussian overlap approximation (GOA). The thermodynamical…

Nuclear Theory · Physics 2019-01-29 Jie Zhao , Tamara Nikšić , Dario Vretenar , Shan-Gui Zhou

Machine learning systems operate under the assumption that training and test data are sampled from a fixed probability distribution. However, this assumptions is rarely verified in practice, as the conditions upon which data was acquired…

Machine Learning · Computer Science 2025-07-09 Eduardo Fernandes Montesuma , Fred Maurice Ngolè Mboula , Antoine Souloumiac

We formulate a new model for transport in stochastic media with long-range spatial correlations where exponential attenuation (controlling the propagation part of the transport) becomes power law. Direct transmission over optical distance…

Optics · Physics 2021-07-13 Anthony B. Davis , Feng Xu

The geometric transportation problem takes as input a set of points $P$ in $d$-dimensional Euclidean space and a supply function $\mu : P \to \mathbb{R}$. The goal is to find a transportation map, a non-negative assignment $\tau : P \times…

Computational Geometry · Computer Science 2022-05-03 Kyle Fox , Jiashuai Lu

We introduce $\textit{Stein transport}$, a novel methodology for Bayesian inference designed to efficiently push an ensemble of particles along a predefined curve of tempered probability distributions. The driving vector field is chosen…

Machine Learning · Statistics 2024-12-02 Nikolas Nüsken

Directly computing mass transport coefficients in stochastic models requires integrating over time the equilibrium correlations between atomic displacements. Here, we show how to accelerate the computations via \green{correlation splitting…

Materials Science · Physics 2021-12-06 Manuel Athènes , Gilles Adjanor , Jérôme Creuze

In this paper, we present a kernel-based, multi-task Gaussian Process (GP) model for approximating the underlying function of an individual's mobility state using a time-inhomogeneous Markov Process with two states: moves and pauses. Our…

Machine Learning · Statistics 2023-06-22 Ekin Ugurel

Trajectory data mining is crucial for smart city management. However, collecting large-scale trajectory datasets is challenging due to factors such as commercial conflicts and privacy regulations. Therefore, we urgently need trajectory…

Machine Learning · Computer Science 2025-02-04 Jingyuan Wang , Yujing Lin , Yudong Li

An extension of time-dependent density functional theory (TDDFT), the generalized time-dependent generator coordinate method (TDGCM), is applied to a study of induced nuclear fission dynamics. In the generalized TDGCM, the correlated…

Nuclear Theory · Physics 2025-04-11 B. Li , D. Vretenar , T. Nikši\' c , P. W. Zhao , J. Meng

Gromov--Wasserstein optimal transport (GWOT) aligns metric measure spaces by matching their within-domain relational structures, but large-scale GWOT remains challenging because its objective is nonconvex and projection onto the transport…

Machine Learning · Computer Science 2026-05-07 Ling Liang , Lei Yang

Reactive transport in saturated/unsaturated porous media is numerically upscaled to the space-time scale of a hypothetical measurement through coarse-grained space-time (CGST) averages. The reactive transport is modeled at the fine-grained…

Numerical Analysis · Mathematics 2023-03-30 Nicolae Suciu , Florin A. Radu , Iuliu S. Pop

Boltzmann transport calculations based on band structures generated with density functional theory (DFT) are often used in the discovery and analysis of thermoelectric materials. In standard implementations, such calculations require dense…

Materials Science · Physics 2018-07-04 Kristian Berland , Clas Persson

We develop generalized polynomial chaos (gPC) based stochastic Galerkin (SG) methods for a class of highly oscillatory transport equations that arise in semiclassical modeling of non-adiabatic quantum dynamics. These models contain…

Numerical Analysis · Mathematics 2017-04-05 Nicolas Crouseilles , Shi Jin , Mohammed Lemou , Liu Liu

We use a generalized Master equation (GME) formalism to describe the non-equilibrium time-dependent transport through a short quantum wire connected to semi-infinite biased leads. The contact strength between the leads and the wire are…

Mesoscale and Nanoscale Physics · Physics 2013-05-15 Kristinn Torfason , Andrei Manolescu , Valeriu Molodoveanu , Vidar Gudmundsson

We present a geometric formulation of optical, thermoelectric, and thermal linear response in clean, zero temperature band insulators based on a single object: a generalized time-dependent quantum geometric tensor (g-tQGT) built from…

Mesoscale and Nanoscale Physics · Physics 2026-03-12 M. Nabil Y. Lhachemi , Jennifer Cano

A major concern in modern power systems is that the popularity and fluctuating characteristics of renewable energy may cause more and more transmission congestion events. Traditional congestion management modeling involves AC or DC power…

Systems and Control · Electrical Eng. & Systems 2022-12-27 Shutong Pu , Guangchun Ruan , Xinfei Yan , Haiwang Zhong

In this paper, we generalize a high order semi-Lagrangian (SL) discontinuous Galerkin (DG) method for multi-dimensional linear transport equations without operator splitting developed in Cai et al. (J. Sci. Comput. 73: 514-542, 2017) to the…

Numerical Analysis · Mathematics 2018-04-09 Xiaofeng Cai , Wei Guo , Jingmei Qiu

A generator of spatio-temporal pseudo-random Gaussian fields that satisfy the "proportionality of scales" property (Tsyroulnikov, 2001) is presented. The generator is based on a third-order in time stochastic differential equation with a…

Data Analysis, Statistics and Probability · Physics 2018-05-15 Michael Tsyrulnikov , Dmitry Gayfulin

Most optimal routing problems focus on minimizing travel time or distance traveled. Oftentimes, a more useful objective is to maximize the probability of on-time arrival, which requires statistical distributions of travel times, rather than…