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Form factor bootstrap approach is applied for diagonal scattering theories. We consider the ADE theories and determine the functional equations satisfied by the minimal two-particle form factors. We also determine the parameterization of…

High Energy Physics - Theory · Physics 2009-10-28 Takeshi Oota

Ensuring the safe and reliable operation of integrated electricity and gas systems (IEGS) requires dynamic energy flow (DEF) simulation tools that achieve high accuracy and computational efficiency. However, the inherent strong nonlinearity…

Systems and Control · Electrical Eng. & Systems 2025-02-28 Zhikai Huang , Shuai Lu , Wei Gu , Ruizhi Yu , Suhan Zhang , Yijun Xu , Yuan Li

Tensor decompositions play a crucial role in numerous applications related to multi-way data analysis. By employing a Bayesian framework with sparsity-inducing priors, Bayesian Tensor Ring (BTR) factorization offers probabilistic estimates…

Machine Learning · Computer Science 2024-12-05 Zerui Tao , Toshihisa Tanaka , Qibin Zhao

In this paper, we study a novel second-order energy stable Backward Differentiation Formula (BDF) finite difference scheme for the epitaxial thin film equation with slope selection (SS). One major challenge for the higher oder in time…

Numerical Analysis · Mathematics 2017-06-29 Wenqiang Feng , Cheng Wang , Steven M. Wise , Zhengru Zhang

In black-box combinatorial optimization, objective evaluations are often expensive, so high quality solutions must be found under a limited budget. Factorization machine with quantum annealing (FMQA) builds a quadratic surrogate model from…

Machine Learning · Computer Science 2026-02-11 Tetsuro Abe , Masashi Yamashita , Shu Tanaka

Applying proper orthogonal decomposition to a usual finite element (FE) formulation for space fractional partial differential equation, we get a reduced FE model, which greatly reduces the complexity of computation. Then, the stability…

Numerical Analysis · Mathematics 2019-01-04 Jing Sun , Daxin Nie , Weihua Deng

In this paper, we propose forward and backward stochastic differential equations (FBSDEs) based deep neural network (DNN) learning algorithms for the solution of high dimensional quasilinear parabolic partial differential equations (PDEs),…

Numerical Analysis · Mathematics 2021-05-10 Wenzhong Zhang , Wei Cai

We derive analytical shape derivative formulas of the system matrix representing electric field integral equation discretized with Raviart-Thomas basis functions. The arising integrals are easy to compute with similar methods as the entries…

Numerical Analysis · Mathematics 2012-06-12 Juhani Kataja , Jukka I. Toivanen

A highly efficient fast boundary element method (BEM) for solving large-scale engineering acoustic problems in a broad frequency range is developed and implemented. The acoustic problems are modeled by the Burton-Miller boundary integral…

Numerical Analysis · Computer Science 2015-11-16 Yanchuang Cao , Lihua Wen , Jinyou Xiao

In this paper we propose a simple method for building exactly solvable multi-parameter spectral equations which in turn can be used for constructing completely integrable and exactly solvable quantum systems. The method is based on the use…

High Energy Physics - Theory · Physics 2007-05-23 Dieter Mayer , Alexander Ushveridze , Zbigniew Walczak

The proposed two-dimensional geometrically exact beam element extends our previous work by including the effects of shear distortion, and also of distributed forces and moments acting along the beam. The general flexibility-based…

Numerical Analysis · Mathematics 2025-08-06 Milan Jirasek , Martin Horak , Emma La Malfa Ribolla , Chiara Bonvissuto

Differential-algebraic equations (DAEs) have been used in modeling various dynamical systems in science and engineering. Several preprocessing methods for DAEs, such as consistent initialization and index reduction, use structural…

Symbolic Computation · Computer Science 2024-03-18 Taihei Oki , Yujin Song

Various numerical linear algebra problems can be formulated as evaluating bivariate function of matrices. The most notable examples are the Fr\'echet derivative along a direction, the evaluation of (univariate) functions of…

Numerical Analysis · Mathematics 2021-04-02 Stefano Massei , Leonardo Robol

When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when…

Computational Physics · Physics 2025-06-25 Stephen Jon Quiton , Juan D. F. Pottecher , Xin Xing , Martin Head-Gordon , Lin Lin

A spectral decomposition method is used to obtain solutions to a class of nonlinear differential equations. We extend this approach to the analysis of the fractional form of these equations and demonstrate the method by applying it to the…

Mathematical Physics · Physics 2015-08-14 Malgorzata Turalska , Bruce J. West

We are investigating the first strong convergence analysis of a numerical method for stochastic differential algebraic equations (SDAEs) under a non-global Lipschitz setting. It is well known that the explicit Euler scheme fails to converge…

Numerical Analysis · Mathematics 2025-09-12 Guy Tsafack , Antoine Tambue

A surface integral equation (SIE) formulation under the magneto-quasi-static assumption is proposed to efficiently and accurately model arbitrarily shaped interconnects in packages. Through decently transferring all electromagnetic…

Computational Engineering, Finance, and Science · Computer Science 2022-10-12 Zekun Zhu , Zhizhang Chen , Shunchuan Yang

Operator splitting methods allow to split the operator describing a complex dynamical system into a sequence of simpler subsystems and treat each part independently. In the modeling of dynamical problems, systems of (possibly coupled)…

Dynamical Systems · Mathematics 2023-09-01 Andreas Bartel , Malak Diab , Andreas Frommer , Michael Günther

For single-carrier systems with frequency domain equalization, decision feedback equalization (DFE) performs better than linear equalization and has much lower computational complexity than sequence maximum likelihood detection. The main…

Information Theory · Computer Science 2015-05-27 Jovana Ilic , Thomas Strohmer

In this work, we propose a novel backward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations (BSDEs), where the deep neural network (DNN) models are trained not only…

Numerical Analysis · Mathematics 2024-04-15 Lorenc Kapllani , Long Teng
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