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3D image processing constitutes nowadays a challenging topic in many scientific fields such as medicine, computational physics and informatics. Therefore, development of suitable tools that guaranty a best treatment is a necessity.…

Numerical Analysis · Computer Science 2018-05-22 Malika Jallouli , Wafa Bel Hadj Khalifa , Anouar Ben Mabrouk , Mohamed Ali Mahjoub

This work presents a novel framework for spherical mesh parameterization. An efficient angle-preserving spherical parameterization algorithm is introduced, which is based on dynamic Yamabe flow and the conformal welding method with solid…

Graphics · Computer Science 2018-10-23 Saad Nadeem , Zhengyu Su , Wei Zeng , Arie Kaufman , Xianfeng Gu

Spherical regression explores relationships between variables on spherical domains. We develop a nonparametric model that uses a diffeomorphic map from a sphere to itself. The restriction of this mapping to diffeomorphisms is natural in…

Other Statistics · Statistics 2017-02-06 Michael Rosenthal , Wei Wu , Eric Klassen , Anuj Srivastava

Computing spherical harmonic decompositions is a ubiquitous technique that arises in a wide variety of disciplines and a large number of scientific codes. Because spherical harmonics are defined by integrals over spheres, however, one must…

General Relativity and Quantum Cosmology · Physics 2015-06-25 David R. Fiske

For the representation of spin-$s$ band-limited functions on the sphere, we propose a sampling scheme with optimal number of samples equal to the number of degrees of freedom of the function in harmonic space. In comparison to the existing…

Instrumentation and Methods for Astrophysics · Physics 2018-09-06 Usama Elahi , Zubair Khalid , Rodney A. Kennedy , Jason D. McEwen

The mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report gives an in-depth introduction to the theoretical foundation…

Machine Learning · Computer Science 2023-07-10 Janis Keuper

A spherical $t$-design is a set of points on the sphere that are nodes of a positive equal weight quadrature rule having algebraic accuracy $t$ for all spherical polynomials with degrees $\le t$. Spherical $t$-designs have many…

Numerical Analysis · Mathematics 2015-02-13 Yang Zhou , Xiaojun Chen

The authors present SHarmonic, a new implementation of the spherical harmonics targeted for electronic-structure calculations. Their approach is to use explicit formulas for the harmonics written in terms of normalized Cartesian…

Computational Physics · Physics 2025-10-08 Xavier Andrade , Jacopo Simoni , Yuan Ping , Tadashi Ogitsu , Alfredo A. Correa

This paper demonstrates that the space of piecewise smooth functions can be well approximated by the space of functions defined by a set of simple (non-linear) operations on smooth uniform splines. The examples include bivariate functions…

Numerical Analysis · Mathematics 2024-05-13 David Levin

We construct spherical wavelets based on approximate identities that are directional, i.e. not rotation-invariant, and have an adaptive angular selectivity. The problem of how to find a proper representation of distinct kinds of details of…

Classical Analysis and ODEs · Mathematics 2018-04-10 Ilona Iglewska-Nowak

Based on a quantitative version of the inverse function theorem and an appropriate saddle-point formulation we derive a quasi-optimal error estimate for the finite element approximation of harmonic maps into spheres with a nodal…

Numerical Analysis · Mathematics 2022-09-27 Sören Bartels , Christian Palus , Zhangxian Wang

Functions of one or more variables are usually approximated with a basis: a complete, linearly-independent system of functions that spans a suitable function space. The topic of this paper is the numerical approximation of functions using…

Numerical Analysis · Mathematics 2018-11-07 Ben Adcock , Daan Huybrechs

Series representations consisting of spherical harmonics are obtained for characteristic exponents and probability density functions of multivariate stable distributions under various conditions. A esult potentially applicable in a…

Probability · Mathematics 2021-10-18 Zhiyi Chi

In this paper, we discuss the problem of minimizing the sum of two convex functions: a smooth function plus a non-smooth function. Further, the smooth part can be expressed by the average of a large number of smooth component functions, and…

Machine Learning · Computer Science 2016-11-17 Luo Luo , Zihao Chen , Zhihua Zhang , Wu-Jun Li

A convolution of the all-sky survey data with a smoothing function is crucial in calculating the smooth surface brightness of the sky survey data. The convolution is usually performed using a spherical version of the convolution theorem.…

Astrophysics · Physics 2007-05-23 Kwang-Il Seon

The aim of this work is to develop a fast algorithm for approximating the matrix function $f(A)$ of a square matrix $A$ that is symmetric and has hierarchically semiseparable (HSS) structure. Appearing in a wide variety of applications,…

Numerical Analysis · Mathematics 2024-02-28 Angelo A. Casulli , Daniel Kressner , Leonardo Robol

Surface parameterizations are widely applied in computer graphics, medical imaging and transformation optics. In this paper, we rigorously derive the gradient vector and Hessian matrix of the discrete conformal energy for spherical…

Numerical Analysis · Mathematics 2023-12-01 Zhong-Heng Tan , Tiexiang Li , Wen-Wei Lin , Shing-Tung Yau

A fully implementable filtered polynomial approximation on spherical shells is considered. The method proposed is a quadrature-based version of a filtered polynomial approximation. The radial direction and the angular direction of the…

Numerical Analysis · Mathematics 2017-12-27 Yoshihito Kazashi

We use some fundamental ideas from complex analysis to create symmetric images and animations. Using a domain coloring algorithm, we generate mappings to the entire complex plane or the hyperbolic upper half-plane. The resulting designs can…

Metric Geometry · Mathematics 2020-08-27 Emily J. Gullerud , James S. Walker

In this work, we consider convex optimization problems with smooth objective function and nonsmooth functional constraints. We propose a new stochastic gradient algorithm, called Stochastic Halfspace Approximation Method (SHAM), to solve…

Optimization and Control · Mathematics 2024-12-04 Nitesh Kumar Singh , Ion Necoara