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The Shirley reduced basis (SRB) represents the periodic parts of Bloch functions as linear combi- nations of eigenvectors taken from a coarse sample of the Brillouin zone, orthogonalized and reduced through proper orthogonal decomposition.…

Materials Science · Physics 2014-03-07 Maxwell Hutchinson , David Prendergast

Using neural networks to solve variational problems, and other scientific machine learning tasks, has been limited by a lack of consistency and an inability to exactly integrate expressions involving neural network architectures. We address…

Machine Learning · Computer Science 2021-10-28 Jonas A. Actor , Andy Huang , Nathaniel Trask

Rhodonea curves are classical planar curves in the unit disk with the characteristic shape of a rose. In this work, we use point samples along such rose curves as node sets for a novel spectral interpolation scheme on the disk. By deriving…

Numerical Analysis · Mathematics 2018-12-04 Wolfgang Erb

Consider a large system of $N$ Brownian motions in $\R ^d$ fixed on a time interval $[0,\beta]$ with symmetrized initial and terminal conditions, under the influence of a trap potential. Such systems describe systems of bosons at positive…

Probability · Mathematics 2024-12-02 Stefan Adams , Spyros Garouniatis

For the first time in mathematical finance field, we propose the local weak form meshless methods for option pricing; especially in this paper we select and analysis two schemes of them named local boundary integral equation method (LBIE)…

Computational Engineering, Finance, and Science · Computer Science 2014-12-19 Jamal Amani Rad , Kourosh Parand , Saeid Abbasbandy

We estimate the Lebesgue constants for Lagrange interpolation processes on one or several intervals by rational functions with fixed poles. We admit that the poles have accumulation points on the intervals. To prove it we use an analog of…

Complex Variables · Mathematics 2024-06-19 Sergei Kalmykov , Alexey Lukashov

The purpose of this article is to introduce a new class of kernels on SO(3) for approximation and interpolation, and to estimate the approximation power of the associated spaces. The kernels we consider arise as linear combinations of…

Classical Analysis and ODEs · Mathematics 2011-06-14 Thomas Hangelbroek , Dominik Schmid

We consider a singularly perturbed semilinear boundary value problem of a general form that allows various types of turning points. A solution decomposition is derived that separates the potential exponential boundary layer terms. The…

Numerical Analysis · Mathematics 2017-01-24 Simon Becher

We consider a continuum percolation model on $\R^d$, $d\geq 1$.For $t,\lambda\in (0,\infty)$ and $d\in\{1,2,3\}$, the occupied set is given by the union of independent Brownian paths running up to time $t$ whoseinitial points form a Poisson…

Probability · Mathematics 2015-12-31 Dirk Erhard , Julián Martínez , Julien Poisat

We consider an optimal control problem constrained by a parabolic partial differential equation (PDE) with Robin boundary conditions. We use a well-posed space-time variational formulation in Lebesgue--Bochner spaces with minimal…

Numerical Analysis · Mathematics 2022-12-06 Nina Beranek , M. Alexander Reinhold , Karsten Urban

In this paper a general theory for interpolation methods on a rectangular grid is introduced. By the use of this theory an efficient B-spline based interpolation method for spectral codes is presented. The theory links the order of the…

Computational Physics · Physics 2012-01-20 M. A. T. van Hinsberg , J. H. M. ten Thije Boonkkamp , F. Toschi , H. J. H. Clercx

A numerical investigation of grain-boundary grooving by means of a Level Set method is carried out. An idealized polygranular interconnect which consists of grains separated by parallel grain boundaries aligned normal to the average…

Materials Science · Physics 2009-10-31 M. Khenner , A. Averbuch , M. Israeli , M. Nathan

Data sites selected from modeling high-dimensional problems often appear scattered in non-paternalistic ways. Except for sporadic clustering at some spots, they become relatively far apart as the dimension of the ambient space grows. These…

Numerical Analysis · Mathematics 2021-09-28 Shao-Bo Lin , Xiangyu Chang , Xingping Sun

Mean value interpolation is a method for fitting a smooth function to piecewise-linear data prescribed on the boundary of a polygon of arbitrary shape, and has applications in computer graphics and curve and surface modelling. The method…

Numerical Analysis · Mathematics 2019-06-21 Michael S. Floater , Francesco Patrizi

The Immersed Boundary Method (IBM) is one of the popular one-fluid mixed Eulerian-Lagrangian methods to simulate motion of droplets. While the treatment of a moving complex boundary is an extremely time consuming and formidable task in a…

Computational Physics · Physics 2018-07-30 Chia Rui Ong , Hiroaki Miura

We consider random genus-0 hyperbolic surfaces $\mathcal{S}_n$ with $n + 1$ punctures, sampled according to the Weil-Petersson measure. We show that, after rescaling the metric by $n^{-1/4}$, the surface $\mathcal{S}_n$ converges in…

Probability · Mathematics 2025-08-27 Timothy Budd , Nicolas Curien

The paper studies scaling limits of random skew plane partitions confined to a box when the inner shapes converge uniformly to a piecewise linear function V of arbitrary slopes in [-1,1]. It is shown that the correlation kernels in the bulk…

Mathematical Physics · Physics 2011-10-21 Sevak Mkrtchyan

The neutral $B$-anomalies are analysed in terms of the tree-level exchange of a (pseudo)scalar gauge singlet $a$. Solutions to both $R_{K^{(*)}}$ central bin anomalies are found within $1\sigma$ for ${m_{a}^2 \in…

High Energy Physics - Phenomenology · Physics 2022-11-11 Jesus Bonilla , Arturo de Giorgi , Maria Ramos

This paper is addressed to a stabilization problem of a system coupled by a wave and a Euler-Bernoulli plate equation. Only one equation is supposed to be damped. Under some assumption about the damping and the coupling terms, it is shown…

Optimization and Control · Mathematics 2018-01-03 Xiaoyu Fu , Qi Lu

Regularized empirical risk minimization using kernels and their corresponding reproducing kernel Hilbert spaces (RKHSs) plays an important role in machine learning. However, the actually used kernel often depends on one or on a few…

Machine Learning · Statistics 2017-09-25 Andreas Christmann , Daohong Xiang , Ding-Xuan Zhou
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