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We investigate numerical differentiation formulas on irregular centers in two or more variables that are exact for polynomials of a given order and minimize an absolute seminorm of the weight vector. Error bounds are given in terms of a…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Robert Schaback

We develop lower bounds for the energy of configurations in $\mathbb{R}^d$ periodic with respect to a lattice. In certain cases, the construction of sharp bounds can be formulated as a finite dimensional, multivariate polynomial…

Classical Analysis and ODEs · Mathematics 2025-10-16 Doug Hardin , Nathaniel Tenpas

We prove optimal convergence rates for certain low-regularity integrators applied to the one-dimensional periodic nonlinear Schr\"odinger and wave equations under the assumption of $H^1$ solutions. For the Schr\"odinger equation we analyze…

Numerical Analysis · Mathematics 2026-04-15 Maximilian Ruff

In this paper we study the application of the Sobolev gradients technique to the problem of minimizing several Schr\"odinger functionals related to timely and difficult nonlinear problems in Quantum Mechanics and Nonlinear Optics. We show…

Numerical Analysis · Mathematics 2025-10-20 Juan Jose Garcia-Ripoll , Victor M. Perez-Garcia

We consider the optimization problem corresponding to the sharp constant in a conformally invariant Sobolev inequality on the $n$-sphere involving an operator of order $2s> n$. In this case the Sobolev exponent is negative. Our results…

Analysis of PDEs · Mathematics 2023-07-24 Rupert L. Frank , Tobias König , Hanli Tang

The solvability in Sobolev spaces is proved for divergence form second order elliptic equations in the whole space, a half space, and a bounded Lipschitz domain. For equations in the whole space or a half space, the leading coefficients…

Analysis of PDEs · Mathematics 2009-11-13 Hongjie Dong , Doyoon Kim

We develop a numerical method for solving shape optimization of functionals involving Steklov eigenvalues and apply it to the problem of maximization of the $k$-th Steklov eigenvalue, under volume constraint. A similar study in the planar…

Optimization and Control · Mathematics 2021-09-07 Pedro R. S. Antunes

We address the problem of finding worst-case nonparametric bounds for T-statistic by considering the extremal problem of maximising the mid-quantile (a special case of 'smoothed quantile' as discussed in \cite{St77} and \cite{W11}) $\tilde…

Statistics Theory · Mathematics 2025-09-03 David Edelman

Corrected trapezoidal rules are proved for $\int_a^b f(x)\,dx$ under the assumption that $f"\in L^p([a,b])$ for some $1\leq p\leq\infty$. Such quadrature rules involve the trapezoidal rule modified by the addition of a term…

Classical Analysis and ODEs · Mathematics 2012-05-17 Erik Talvila , Matthew Wiersma

It has been widely recognized that the 0/1 loss function is one of the most natural choices for modelling classification errors, and it has a wide range of applications including support vector machines and 1-bit compressed sensing. Due to…

Optimization and Control · Mathematics 2021-12-20 Shenglong Zhou , Lili Pan , Naihua Xiu , Houduo Qi

We establish equivalence between the boundedness of specific supremum operators and the optimality of function spaces in Sobolev embeddings acting on domains in ambient Euclidean space with a prescribed isoperimetric behavior. Our approach…

Functional Analysis · Mathematics 2024-07-10 David Kubíček

Using optimal mass transport arguments, we prove weighted Sobolev inequalities of the form \[\left(\int_E |u(x)|^q\,\omega(x) \,dx\right)^{1/q}\leq K_0\,\left(\int_E |\nabla u(x)|^p\,\sigma(x)\,dx\right)^{1/p},\ \ u\in C_0^\infty(\mathbb…

Analysis of PDEs · Mathematics 2020-08-05 Zoltán M. Balogh , Cristian E. Gutiérrez , Alexandru Kristály

We consider Nonlinear Schrodinger type equations on $S^1$. In this paper, we obtain polynomial bounds on the growth in time of high Sobolev norms of their solutions. The key is to derive an iteration bound based on a frequency decomposition…

Analysis of PDEs · Mathematics 2024-07-08 Vedran Sohinger

A method of deriving quadrature rules has been developed which gives nodes and weights for a Gaussian-type rule which integrates functions of the form: f(x,y,t) = a(x,y,t)/((x-t)^2+y^2) + b(x,y,t)/([(x-t)^2+y^2]^{1/2}) +…

Numerical Analysis · Mathematics 2010-09-21 Michael Carley

Gauss-Lobatto quadrature nodes and weights are optimal for closed summation-by-parts (SBP) formulations based on polynomial approximation spaces in the sense that for a prescribed function space they yield an SBP operator of minimal…

Numerical Analysis · Mathematics 2026-04-28 Nicholas Hale , Charis Harley , Prince Nchupang , Jan Nordström

We present new tradeoffs between space and query-time for exact distance oracles in directed weighted planar graphs. These tradeoffs are almost optimal in the sense that they are within polylogarithmic, sub-polynomial or arbitrarily small…

Data Structures and Algorithms · Computer Science 2018-11-06 Panagiotis Charalampopoulos , Paweł Gawrychowski , Shay Mozes , Oren Weimann

Let J be a Jacobian variety with toric reduction over a local field K. Let J -> E be an optimal quotient defined over K, where E is an elliptic curve. We give examples in which the functorially induced map \Phi_J -> \Phi_E on component…

Number Theory · Mathematics 2019-08-15 Mihran Papikian , Joseph Rabinoff

In this work, we study a global quadrature scheme for analytic functions on compact intervals based on function values on quasi-uniform grids of quadrature nodes. In practice it is not always possible to sample functions at optimal nodes…

Numerical Analysis · Mathematics 2022-11-28 Giacomo Cappellazzo , Wolfgang Erb , Francesco Marchetti , Davide Poggiali

We consider the imbedding inequality || f ||_{L^r(R^d)} <= S_{r,n,d} || f ||_{H^{n}(R^d)}; H^{n}(R^d) is the Sobolev space (or Bessel potential space) of L^2 type and (integer or fractional) order n. We write down upper bounds for the…

Functional Analysis · Mathematics 2007-05-23 C. Morosi , L. Pizzocchero

We consider the problem of learning an unknown, possibly nonlinear operator between separable Hilbert spaces from supervised data. Inputs are drawn from a prescribed probability measure on the input space, and outputs are (possibly noisy)…

Numerical Analysis · Mathematics 2025-12-15 John Turnage , Matthew Lowery , John Jakeman , Zachary Morrow , Akil Narayan , Varun Shankar