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We investigate the use of conformal maps for the acceleration of convergence of the trapezoidal rule and Sinc numerical methods. The conformal map is a polynomial adjustment to the $\sinh$ map, and allows the treatment of a finite number of…

Numerical Analysis · Mathematics 2014-06-13 Richard Mikael Slevinsky , Sheehan Olver

We give a new computational method to obtain symmetries of ordinary differential equations. The proposed approach appears as an extension of a recent algorithm to compute variational symmetries of optimal control problems [Comput. Methods…

Classical Analysis and ODEs · Mathematics 2009-11-13 Paulo D. F. Gouveia , Delfim F. M. Torres

We consider variational problems that model the bending behavior of curves that are constrained to belong to given hypersurfaces. Finite element discretizations of corresponding functionals are justified rigorously via Gamma-convergence.…

Numerical Analysis · Mathematics 2020-04-24 Sören Bartels

Deep convolutional networks provide state of the art classifications and regressions results over many high-dimensional problems. We review their architecture, which scatters data with a cascade of linear filter weights and non-linearities.…

Machine Learning · Statistics 2016-04-27 Stéphane Mallat

We present a low entry-level introduction to the Conformal Bootstrap. We review and obtain several basic bounds using Linear Programming in machine precision in Mathematica, making the results accessible even to the most uneducated computer…

High Energy Physics - Theory · Physics 2017-09-07 António Antunes

We compute the Hilbert polynomial and the Poincare function counting the number of fixed jet-order differential invariants of conformal metric structures modulo local diffeomorphisms, and we describe the field of rational differential…

Differential Geometry · Mathematics 2017-03-08 Boris Kruglikov

In this article, we develop new methods for counting integral orbits having bounded invariants that lie inside the cusps of fundamental domains for coregular representations. We illustrate these methods for a representation of cardinal…

Number Theory · Mathematics 2025-05-21 Arul Shankar , Artane Siad , Ashvin Swaminathan , Ila Varma

Based on the quaternionic approach developed by one of us [Z.D. Zhang, Phil. Mag. 87 (2007) 5309.] for the three-dimensional (3D) Ising model, we study in this work conformal invariance in three dimensions. We develop a procedure for…

Statistical Mechanics · Physics 2012-12-06 Zhidong Zhang , Norman H. March

We compute approximate solutions to inverse problems for determining parameters in differential equation models with stochastic data on output quantities. The formulation of the problem and modeling framework define a solution as a…

Numerical Analysis · Mathematics 2014-07-16 Troy Butler , Don Estep , Simon Tavener , Timothy Wildey , Clint Dawson , Lindley Graham

A high-order quadrature algorithm is presented for computing integrals over curved surfaces and volumes whose geometry is implicitly defined by the level sets of (one or more) multivariate polynomials. The algorithm recasts the implicitly…

Numerical Analysis · Mathematics 2021-11-24 Robert I. Saye

The implications of restricted conformal invariance under conformal transformations preserving a plane boundary are discussed for general dimensions $d$. Calculations of the universal function of a conformal invariant $\xi$ which appears in…

Condensed Matter · Physics 2009-10-28 D. M. McAvity , H. Osborn

The conjugate function method is an algorithm for numerical computation of conformal mappings for simply and doubly connected domains. In this paper the conjugate function method is generalized for multiply connected domains. The key…

Numerical Analysis · Mathematics 2017-07-06 Harri Hakula , Tri Quach , Antti Rasila

Space filling designs are central to studying complex systems in various areas of science. They are used for obtaining an overall understanding of the behaviour of the response over the input space, model construction and uncertainty…

Methodology · Statistics 2016-08-10 Shirin Golchi , Jason L. Loeppky

We describe a framework in which is possible to develop and implement algorithms for the approximation of invariant measures of dynamical systems with a given bound on the error of the approximation. Our approach is based on a general…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli

A numerical scheme for computing arc-length parametrized curves of low bending energy that are confined to convex domains is devised. The convergence of the discrete formulations to a continuous model and the unconditional stability of an…

Numerical Analysis · Mathematics 2022-03-18 Sören Bartels , Pascal Weyer

In this paper, we investigate the geometric invariant properties of a normal curve on a smooth immersed surface under conformal transformation. We obtain an invariant-sufficient condition for the conformal image of a normal curve. We also…

General Mathematics · Mathematics 2019-08-12 Mohamd Saleem Lone

We consider the problem of reconstruction of planar domains from their moments. Specifically, we consider domains with boundary which can be represented by a union of a finite number of pieces whose graphs are solutions of a linear…

Classical Analysis and ODEs · Mathematics 2013-06-06 Dmitry Batenkov , Vladimir Golubyatnikov , Yosef Yomdin

Homology has long been accepted as an important computable tool for quantifying complex structures. In many applications, these structures arise as nodal domains of real-valued functions and are therefore amenable only to a numerical study…

Probability · Mathematics 2020-05-29 Konstantin Mischaikow , Thomas Wanner

In this paper, we present a geometric approach for computing controlled invariant sets for hybrid control systems. While the problem is well studied in the ellipsoidal case, this family is quite conservative for constrained or switched…

Optimization and Control · Mathematics 2021-12-08 Benoît Legat , Raphaël M. Jungers

Conformal prediction provides a distribution-free framework for uncertainty quantification via prediction sets with exact finite-sample coverage. In low dimensions these sets are easy to interpret, but in high-dimensional or structured…

Machine Learning · Statistics 2026-05-08 Trevor Harris
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