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Finite element simulations have been used to solve various partial differential equations (PDEs) that model physical, chemical, and biological phenomena. The resulting discretized solutions to PDEs often do not satisfy requisite physical…

Numerical Analysis · Mathematics 2022-03-17 Vidhi Zala , Robert M. Kirby , Akil Narayan

In scientific fields such as quantum computing, physics, chemistry, and machine learning, high dimensional data are typically represented using sparse tensors. Tensor contraction is a popular operation on tensors to exploit meaning or alter…

Data Structures and Algorithms · Computer Science 2024-10-15 Andrew Ensinger , Gabriel Kulp , Victor Agostinelli , Dennis Lyakhov , Lizhong Chen

In this paper, we develop a nonlinear reduction framework based on our recently introduced extended group finite element method. By interpolating nonlinearities onto approximation spaces defined with the help of finite elements, the…

Numerical Analysis · Mathematics 2021-06-07 Kevin Tolle , Nicole Marheineke

Tensor contractions are ubiquitous in computational chemistry and physics, where tensors generally represent states or operators and contractions express the algebra of these quantities. In this context, the states and operators often…

Computational Physics · Physics 2022-09-27 Yang Gao , Phillip Helms , Garnet Kin-Lic Chan , Edgar Solomonik

This paper recalls the principles of the finite-element methods (FEM) theory and declines its application in the EN-MME group, for the numerical modelling and study of particle accelerator equipment. Implicit and explicit methods are…

We present trainsum, a versatile Python package for doing computations with multidimensional quantics tensor trains: https://github.com/fh-igd-iet/trainsum. Using the Array API standard together with opt_einsum, trainsum allows the…

Mathematical Software · Computer Science 2026-02-25 Paul Haubenwallner , Matthias Heller

A coarse-grained computational procedure based on the Finite Element Method is proposed to calculate the normal modes and mechanical response of proteins and their supramolecular assemblies. Motivated by the elastic network model, proteins…

Biomolecules · Quantitative Biology 2007-05-23 Mark Bathe

Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. \emph{Tensor power method} (TPM) is one of the widely-used techniques in the decomposition of tensors. This paper presents a novel tensor…

Machine Learning · Computer Science 2023-06-02 Yichuan Deng , Zhao Song , Junze Yin

Nonlinearities and instabilities in mechanical structures have shown great promise for embedding advanced functionalities. However, simulating structures subject to nonlinearities can be challenging due to the complexity of their behavior,…

Soft Condensed Matter · Physics 2025-10-23 Paul Ducarme , Bart Weber , Martin van Hecke , Johannes T. B. Overvelde

This paper studies the numerical analysis of a parameter identification problem governed by elliptic equations with power-type nonlinearity. We propose a numerical reconstruction via a suitable least-squares minimization problem based on…

Numerical Analysis · Mathematics 2026-03-10 De-Han Chen , Yi-Hsuan Lin , Irwin Yousept

We construct a finite element approximation of a strain-limiting elastic model on a bounded open domain in $\mathbb{R}^d$, $d \in \{2,3\}$. The sequence of finite element approximations is shown to exhibit strong convergence to the unique…

Numerical Analysis · Mathematics 2020-04-02 Andrea Bonito , Vivette Girault , Endre Süli

A large class of Feynman integrals, like e.g., two-point parameter integrals with at most one mass and containing local operator insertions, can be transformed to multi-sums over hypergeometric expressions. In this survey article we present…

Symbolic Computation · Computer Science 2015-06-17 Carsten Schneider

This paper presents a new data-driven finite element framework that is applicable to a broad range of engineering simulation problems. In the data-driven approach, the conservation laws and boundary conditions are satisfied by means of the…

Computational Engineering, Finance, and Science · Computer Science 2025-09-09 Adriana Kuliková , Andrei G. Shvarts , Łukasz Kaczmarczyk , Chris J. Pearce

In 2011, einsum was introduced to NumPy as a practical and convenient notation for tensor expressions in machine learning, quantum circuit simulation, and other fields. It has since been implemented in additional Python frameworks such as…

Programming Languages · Computer Science 2025-10-21 Maurice Wenig , Paul G. Rump , Mark Blacher , Joachim Giesen

This work proposes the extended functional tensor train (EFTT) format for compressing and working with multivariate functions on tensor product domains. Our compression algorithm combines tensorized Chebyshev interpolation with a low-rank…

Numerical Analysis · Mathematics 2024-05-30 Christoph Strössner , Bonan Sun , Daniel Kressner

A finite element approach to solve numerically the Takagi-Taupin equations expressed in a weak form is presented and applied to simulate X-ray reflectivity curves, spatial intensity distributions and focusing properties of bent perfect…

We present a differentiable weak-form learning approach for accelerating finite element simulations. Rather than introducing black-box source terms in the strong form of the governing equations, we augment the momentum equation directly in…

Fluid Dynamics · Physics 2026-01-29 Junoh Jung , Emil Constantinescu

In this paper, we investigate a model describing induction hardening of steel. The related system consists of an energy balance, an ODE for the different phases of steel, and Maxwell's equations in a potential formulation. The existence of…

Analysis of PDEs · Mathematics 2023-12-22 Dietmar Hömberg , Robert Lasarzik

This paper shows how to optimize sparse tensor algebraic expressions by introducing temporary tensors, called workspaces, into the resulting loop nests. We develop a new intermediate language for tensor operations called concrete index…

Mathematical Software · Computer Science 2023-10-18 Fredrik Kjolstad , Willow Ahrens , Shoaib Kamil , Saman Amarasinghe

A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…

Numerical Analysis · Mathematics 2017-12-08 Brendan Keith , Socratis Petrides , Federico Fuentes , Leszek Demkowicz