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We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

We introduce a tempering approach with stochastic density functional theory (sDFT), labeled t-sDFT, which reduces the statistical errors in the estimates of observable expectation values. This is achieved by rewriting the electronic density…

Computational Physics · Physics 2021-12-15 Minh Nguyen , Wenfei Li , Yangtao Li , Roi Baer , Eran Rabani , Daniel Neuhauser

The challenging problem of conducting fully Bayesian inference for the reaction rate constants governing stochastic kinetic models (SKMs) is considered. Given the challenges underlying this problem, the Markov jump process representation is…

Computation · Statistics 2019-01-10 Andrew Golightly , Emma Bradley , Tom Lowe , Colin S. Gillespie

In the numerical renormalization group (NRG) calculations of the spectral functions of quantum impurity models, the results are affected by discretization and truncation errors. The discretization errors can be alleviated by averaging over…

Strongly Correlated Electrons · Physics 2011-11-15 Rok Zitko

A stress equilibration procedure for linear elasticity is proposed and analyzed in this paper with emphasis on the behavior for (nearly) incompressible materials. Based on the displacement-pressure approximation computed with a stable…

Numerical Analysis · Mathematics 2019-11-01 Fleurianne Bertrand , Bernhard Kober , Marcel Moldenhauer , Gerhard Starke

The Ensemble Kalman methodology in an inverse problems setting can be viewed as an iterative scheme, which is a weakly tamed discretization scheme for a certain stochastic differential equation (SDE). Assuming a suitable approximation…

Probability · Mathematics 2018-06-19 Dirk Blömker , Claudia Schillings , Philipp Wacker

Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorporate thermodynamic structure into neural networks have recently shown strong performance…

Machine Learning · Computer Science 2026-03-17 Karim K. Ben Hicham , Moreno Ascani , Jan G. Rittig , Alexander Mitsos

Previous Knowledge Distillation based efficient image retrieval methods employs a lightweight network as the student model for fast inference. However, the lightweight student model lacks adequate representation capacity for effective…

Computer Vision and Pattern Recognition · Computer Science 2023-10-06 Yi Xie , Huaidong Zhang , Xuemiao Xu , Jianqing Zhu , Shengfeng He

The focus of this paper is on the concurrent reconstruction of both the diffusion and potential coefficients present in an elliptic/parabolic equation, utilizing two internal measurements of the solutions. A decoupled algorithm is…

Numerical Analysis · Mathematics 2023-08-08 Siyu Cen , Zhi Zhou

A family of implicit-in-time mixed finite element schemes is presented for the numerical approximation of the acoustic wave equation. The mixed space discretization is based on the displacement form of the wave equation and the…

Numerical Analysis · Mathematics 2015-04-17 Samir Karaa

Knowledge distillation is a popular approach for enhancing the performance of ''student'' models, with lower representational capacity, by taking advantage of more powerful ''teacher'' models. Despite its apparent simplicity and widespread…

Machine Learning · Computer Science 2023-12-12 Mher Safaryan , Alexandra Peste , Dan Alistarh

This article considers a model problem of elastoplasticity with linearly kinematic hardening and presents hp-finite element discretizations of two equivalent weak formulations each having their respective advantages. A mixed variational…

Numerical Analysis · Mathematics 2026-05-12 Patrick Bammer , Lothar Banz , Miriam Schönauer , Andreas Schröder

In this work, we mainly present the optimal convergence rates of the temporally second-order finite element scheme for solving the electrohydrodynamic equation. Suffering from the highly coupled nonlinearity, the convergence analysis of the…

Numerical Analysis · Mathematics 2025-05-06 Shengfeng Wang , Zeyu Xia , Maojun Li

Time discretization along with space discretization is important in the numerical simulation of subsurface flow applications for long run. In this paper, we derive theoretical convergence error estimates in discrete-time setting for…

Numerical Analysis · Mathematics 2020-03-04 Yerlan Amanbek , Mary Wheeler

A discretization scheme is introduced for a set of convection-diffusion equations with a non-linear reaction term, where the convection velocity is constant for each reactant. This constancy allows a transformation to new spatial variables,…

Computational Physics · Physics 2017-09-19 József Vass , Sergey N. Krylov

A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the…

Nuclear Theory · Physics 2022-09-28 Pablo Giuliani , Kyle Godbey , Edgard Bonilla , Frederi Viens , Jorge Piekarewicz

We develop an unconditionally energy-stable tensor-product space-time discretization framework for the solution of a linear kinetic transport equation in one space dimension. The kinetic equation is a simplified model of radiative transfer…

Numerical Analysis · Mathematics 2026-04-24 Anita Gjesteland , Sigrun Ortleb , Salim Elghawi , David C. Del Rey Fernández

Sharp asymptotic lower bounds of the expected quadratic variation of discretization error in stochastic integration are given. The theory relies on inequalities for the kurtosis and skewness of a general random variable which are themselves…

Probability · Mathematics 2012-04-04 Masaaki Fukasawa

A discrete-to-continuum analysis for free-boundary problems related to crystalline films deposited on substrates is performed by $\Gamma$-convergence. The discrete model here introduced is characterized by an energy with two contributions,…

Analysis of PDEs · Mathematics 2019-02-19 Leonard Kreutz , Paolo Piovano

This paper establishes a continuous time approximation, a piece-wise continuous differential equation, for the discrete Heavy-Ball (HB) momentum method with explicit discretization error. Investigating continuous differential equations has…

Machine Learning · Computer Science 2025-10-23 Bochen Lyu , Xiaojing Zhang , Fangyi Zheng , He Wang , Zheng Wang , Zhanxing Zhu