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When solving rank-deficient or discrete ill-posed problems by regularization methods, the choice of the regularization parameter is crucial. It is also of interest, the regularization norm used in the selection of the solution. In this…

Numerical Analysis · Mathematics 2024-10-30 Ibrahima Dione

Regularisation allows one to handle ill-posed inverse problems. Here we focus on discrete unfolding problems. The properties of the results are characterised by the consistency between measurements and unfolding result and by the posterior…

Data Analysis, Statistics and Probability · Physics 2023-09-07 Michael Schmelling

Regular expressions are a classical concept in formal language theory. Regular expressions in programming languages (RegEx) such as JavaScript, feature non-standard semantics of operators (e.g. greedy/lazy Kleene star), as well as…

Locomotion in Stokes flow is an intensively-studied problem because it describes important biological phenomena such as the motility of many species' sperm, bacteria, algae and protozoa. Numerical computations can be challenging,…

Fluid Dynamics · Physics 2018-05-15 Meurig T. Gallagher , David J. Smith

We present a fast, high-order accurate and adaptive boundary integral scheme for solving the Stokes equations in complex---possibly nonsmooth---geometries in two dimensions. The key ingredient is a set of panel quadrature rules capable of…

Numerical Analysis · Mathematics 2020-04-22 Bowei Wu , Hai Zhu , Alex Barnett , Shravan Veerapaneni

Boundary integral equation methods are widely used in the solution of many partial differential equations. The kernels that appear in these surface integrals are nearly singular when evaluated near the boundary, and straightforward…

Numerical Analysis · Mathematics 2025-07-02 Joseph Siebor , Svetlana Tlupova

We develop and analyze numerical discretization to the constrained high-index saddle dynamics, the dynamics searching for the high-index saddle points confined on the high-dimensional unit sphere. Compared with the saddle dynamics without…

Numerical Analysis · Mathematics 2022-06-22 Lei Zhang , Pingwen Zhang , Xiangcheng Zheng

Recently, the Shifted Boundary Method (SBM) was proposed within the class of unfitted (or immersed, or embedded) finite element methods. By reformulating the original boundary value problem over a surrogate (approximate) computational…

Numerical Analysis · Mathematics 2023-07-19 Nabil M. Atallah , Claudio Canuto , Guglielmo Scovazzi

In this paper a time dependent Stokes problem that is motivated by a standard sharp interface model for the fluid dynamics of two-phase flows is studied. This Stokes interface problem has discontinuous density and viscosity coefficients and…

Numerical Analysis · Mathematics 2018-07-12 Igor Voulis , Arnold Reusken

We study the Stokes system with the localized boundary data in the half-space. We are concerned with the local regularity of its solution near the boundary away from the support of the given boundary data which are product forms of each…

Analysis of PDEs · Mathematics 2023-07-06 Kyungkeun Kang , Chanhong Min

There is growing body of learning problems for which it is natural to organize the parameters into matrix, so as to appropriately regularize the parameters under some matrix norm (in order to impose some more sophisticated prior knowledge).…

Machine Learning · Computer Science 2010-10-19 Sham M. Kakade , Shai Shalev-Shwartz , Ambuj Tewari

Slender-body approximations have been successfully used to explain many phenomena in low-Reynolds number fluid mechanics. These approximations typically use a line of singularity solutions to represent the flow. These singularities can be…

Fluid Dynamics · Physics 2021-09-17 Boan Zhao , Lyndon Koens

Data-driven predictive control methods based on the Willems' fundamental lemma have shown great success in recent years. These approaches use receding horizon predictive control with nonparametric data-driven predictors instead of…

Systems and Control · Electrical Eng. & Systems 2023-12-06 Mingzhou Yin , Andrea Iannelli , Roy S. Smith

The equations of a planar elastica under pressure can be rewritten in a useful form by parametrising the variables in terms of the local orientation angle, $\theta$, instead of the arc length. This ``$\theta$-formulation'' lends itself to a…

Soft Condensed Matter · Physics 2023-07-25 Gregory Kozyreff , Emmanuel Siéfert , Basile Radisson , Fabian Brau

We develop and implement a Bayesian approach for the estimation of the shape of a two dimensional annular domain enclosing a Stokes flow from sparse and noisy observations of the enclosed fluid. Our setup includes the case of direct…

Optimization and Control · Mathematics 2023-07-19 Jeff Borggaard , Nathan E. Glatt-Holtz , Justin A. Krometis

The Stokes problem with non-homogeneous Dirichlet boundary condition is solved numerically using conforming discretizations and an approximation of the boundary datum in the corresponding trace space. Optimal discretization error estimates…

Numerical Analysis · Mathematics 2026-04-14 Thomas Apel , Katharina Lorenz , Johannes Pfefferer

In this work it is shown how the immersed boundary method of (Peskin2002) for modeling flexible structures immersed in a fluid can be extended to include thermal fluctuations. A stochastic numerical method is proposed which deals with…

Soft Condensed Matter · Physics 2023-02-28 P. J. Atzberger , P. R. Kramer , C. S. Peskin

We consider a simplified extensible version of a dynamic free boundary problem for a thin filament with radius $\epsilon>0$ immersed in 3D Stokes flow. The 3D fluid is coupled to the quasi-1D filament dynamics via a novel type of…

Analysis of PDEs · Mathematics 2025-09-23 Laurel Ohm

This paper introduces the 3D Peskin problem: a two-dimensional elastic membrane immersed in a three-dimensional steady Stokes flow. We obtain the equations that model this free boundary problem and show that they admit a boundary integral…

Analysis of PDEs · Mathematics 2023-01-31 Eduardo García-Juárez , Po-Chun Kuo , Yoichiro Mori , Robert M. Strain

We propose and analyze a regularization approach for structured prediction problems. We characterize a large class of loss functions that allows to naturally embed structured outputs in a linear space. We exploit this fact to design…

Machine Learning · Computer Science 2017-07-31 Carlo Ciliberto , Alessandro Rudi , Lorenzo Rosasco