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The Shifted Boundary Method (SBM) trades some part of the burden of body-fitted meshing for increased algebraic complexity. While the resulting linear systems retain the standard $\mathcal{O}(h^{-2})$ conditioning of second-order operators,…

Numerical Analysis · Mathematics 2026-01-16 Michał Wichrowski , Ajay Ajith

The scaled boundary finite element method (SBFEM) is a semi-analytical computational scheme, which is based on the characteristics of the finite element method (FEM) and combines the advantages of the boundary element method (BEM). This…

Numerical Analysis · Mathematics 2024-10-22 Yang Yang , Zongliang Zhang , Yelin Feng

When numerical solution of elliptic and parabolic partial differential equations is required to be highly accurate in space, the discrete problem usually takes the form of large-scale and sparse linear systems. In this work, as an…

Numerical Analysis · Mathematics 2024-07-23 Massimo Frittelli , Ivonne Sgura

Many entropy-conservative and entropy-stable (summarized as entropy-preserving) methods for hyperbolic conservation laws rely on Tadmor's theory for two-point entropy-preserving numerical fluxes and its higher-order extension via flux…

Numerical Analysis · Mathematics 2026-03-26 Marco Artiano , Hendrik Ranocha

Self-consistent field theory (SCFT) has proven to be a powerful tool for modeling equilibrium microstructures of soft materials, particularly for multiblock polymers. A very successful approach to numerically solving the SCFT set of…

Soft Condensed Matter · Physics 2017-01-04 David M. Ackerman , Kris Delaney , Glenn H. Fredrickson , Baskar Ganapathysubramanian

We analyze two types of summation-by-parts finite difference operators for approximating the second derivative with variable coefficient. The first type uses ghost points, while the second type does not use any ghost points. A previously…

Numerical Analysis · Mathematics 2019-07-25 Siyang Wang , N. Anders Petersson

In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden process and then to design Markov chain Monte Carlo (MCMC)…

Computation · Statistics 2022-11-02 Mohamed Maama , Ajay Jasra , Hernando Ombao

For positive semi-definite block-matrix $M,$ we say that $M$ is P.S.D. and we write $M=\begin{pmatrix} A \& X\\ {X^*} \& B\end{pmatrix} \in {\mathbb{M}}\_{n+m}^+$, with $A\in {\mathbb{M}}\_n^+$, $B \in {\mathbb{M}}\_m^+.$ The focus is on…

Functional Analysis · Mathematics 2015-09-15 Antoine Mhanna

Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. However, their theoretical foundation relies on a complex, multi-stage process of…

Machine Learning · Computer Science 2025-12-23 Sutashu Tomonaga , Kenji Doya , Noboru Murata

We show that the standard boundary integral operators, defined on the unit sphere, for the Stokes equations diagonalize on a specific set of vector spherical harmonics and provide formulas for their spectra. We also derive analytical…

Numerical Analysis · Mathematics 2018-04-04 Eduardo Corona , Shravan Veerapaneni

This work presents a polyhedral scaled boundary finite element method (PSBFEM) for three dimensional seepage analysis. We first derive the scaled boundary formulation for 3D seepage problems, and subsequently incorporate Wachspress shape…

Numerical Analysis · Mathematics 2025-06-11 Mingjiao Yan , Yang Yang , Zongliang Zhang , Dengmiao Hao , Chao Su , Qingsong Duan

In this paper, a new method, named the Fragile Points Method (FPM), is developed for computer modeling in engineering and sciences. In the FPM, simple, local, polynomial, discontinuous and Point-based trial and test functions are proposed…

Computational Physics · Physics 2019-12-10 Leiting Dong , Tian Yang , Kailei Wang , Satya N. Atluri

Smooth parametrization consists in a subdivision of the mathematical objects under consideration into simple pieces, and then parametric representation of each piece, while keeping control of high order derivatives. The main goal of the…

Computational Geometry · Computer Science 2014-07-14 Y. Yomdin

This paper is concerned with a data-driven technique for constructing finite Markov decision processes (MDPs) as finite abstractions of discrete-time stochastic control systems with unknown dynamics while providing formal closeness…

Systems and Control · Electrical Eng. & Systems 2022-06-30 Abolfazl Lavaei , Sadegh Soudjani , Emilio Frazzoli , Majid Zamani

The Laplacian appears in several partial differential equations used to model wave propagation. Summation-by-parts--simultaneous approximation term (SBP-SAT) finite difference methods are often used for such equations, as they combine…

Numerical Analysis · Mathematics 2020-02-11 Martin Almquist , Eric M. Dunham

This paper studies a fundamental problem in convex optimization, which is to solve semidefinite programming (SDP) with high accuracy. This paper follows from the existing robust SDP-based interior point method analysis due to [Huang, Jiang,…

Quantum Physics · Physics 2023-02-08 Baihe Huang , Shunhua Jiang , Zhao Song , Runzhou Tao , Ruizhe Zhang

Koopman operators are infinite-dimensional operators that linearize nonlinear dynamical systems, facilitating the study of their spectral properties and enabling the prediction of the time evolution of observable quantities. Recent methods…

Dynamical Systems · Mathematics 2025-06-06 Nicolas Boullé , Matthew J. Colbrook

We consider the small deviation probabilities (SDP) for sums of stationary Gaussian sequences. For the cases of constant boundaries and boundaries tending to zero, we obtain quite general results. For the case of the boundaries tending to…

Probability · Mathematics 2020-02-11 Frank Aurzada , Mikhail Lifshits

The peridynamic theory brings advantages in dealing with discontinuities, dynamic loading, and non-locality. The integro-differential formulation of peridynamics poses challenges to numerical solutions of complicated and practical problems.…

Numerical Analysis · Mathematics 2021-06-01 Xue Liang , Linjuan Wang , Jifeng Xu , Jianxiang Wang

Low-rank methods for semidefinite programming (SDP) have gained a lot of interest recently, especially in machine learning applications. Their analysis often involves determinant-based or Schatten-norm penalties, which are hard to implement…

Optimization and Control · Mathematics 2021-12-07 Mikhail Krechetov , Jakub Marecek , Yury Maximov , Martin Takac