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The application of methods of computational algebra has recently introduced new tools for the study of Hilbert schemes. The key idea is to define flat families of ideals endowed with a scheme structure whose defining equations can be…

Algebraic Geometry · Mathematics 2016-03-15 Paolo Lella , Margherita Roggero

The paper presents a new generalized integer orthogonal transformation which consists of a well known orthogonal transform followed by stretching the basis vectors maintaining the asymptotic behavior of the number of integer solutions for…

Number Theory · Mathematics 2017-04-10 Victor Volfson

Computing the critical points of a polynomial function $q\in\mathbb Q[X_1,\ldots,X_n]$ restricted to the vanishing locus $V\subset\mathbb R^n$ of polynomials $f_1,\ldots, f_p\in\mathbb Q[X_1,\ldots, X_n]$ is of first importance in several…

Symbolic Computation · Computer Science 2014-05-26 Pierre-Jean Spaenlehauer

In this work, we explore the use of operator splitting algorithms for solving regularized structural topology optimization problems. The context is the classical structural design problems (e.g., compliance minimization and compliant…

Optimization and Control · Mathematics 2013-07-22 Cameron Talischi , Glaucio H. Paulino

Let $(f\_1,\dots, f\_s) \in \mathbb{Q}\_p [X\_1,\dots, X\_n]^s$ be a sequence of homogeneous polynomials with $p$-adic coefficients. Such system may happen, for example, in arithmetic geometry. Yet, since $\mathbb{Q}\_p$ is not an effective…

Symbolic Computation · Computer Science 2015-09-28 Tristan Vaccon

Computationally efficient numerical methods for high-order approximations of convolution integrals involving weakly singular kernels find many practical applications including those in the development of fast quadrature methods for…

Numerical Analysis · Mathematics 2018-10-10 Akash Anand , Awanish Kumar Tiwari

We consider the linear time-dependent Schr\"odinger equation with a time-dependent smooth potential on an unbounded domain. A Galerkin spectral method with a tensor-product Hermite basis is used as a discretization in space. Discretizing…

Numerical Analysis · Mathematics 2015-05-14 Bernd Brumm

$L^1$ based optimization is widely used in image denoising, machine learning and related applications. One of the main features of such approach is that it naturally provide a sparse structure in the numerical solutions. In this paper, we…

Numerical Analysis · Mathematics 2023-02-13 Weifeng Qiu , Jin Ren , Ke Shi , Yuesheng Xu

In this paper, we develop a new type of accelerated algorithms to solve some classes of maximally monotone equations as well as monotone inclusions. Instead of using Nesterov's accelerating approach, our methods rely on a so-called…

Optimization and Control · Mathematics 2021-12-08 Quoc Tran-Dinh , Yang Luo

In the papers dealing with derivation and applications of operational matrices of Bernstein polynomials, a basis transformation, commonly a transformation to power basis, is used. The main disadvantage of this method is that the…

Numerical Analysis · Mathematics 2016-11-02 M. Jani , E. Babolian , S. Javadi , D. Bhatta

A theorem of Gekeler compares the number of non-isomorphic automorphic representations associated with the space of cusp forms of weight $k$ on $\Gamma_0(N)$ to a simpler function of $k$ and $N$, showing that the two are equal whenever $N$…

Number Theory · Mathematics 2018-06-25 Miao Gu , Greg Martin

The Difference-of-Gaussian (DoG) is a widely used operator across applications, including image processing (feature and edge detection), quantum machine learning, and finite-difference methods (approximations of the Laplacian-of-Gaussian).…

Quantum Physics · Physics 2026-04-13 Jishnu Mahmud , John Winship , Tom Lash , James Ostrowski , Rebekah Herrman

Sparse polynomial interpolation, sparse linear system solving or modular rational reconstruction are fundamental problems in Computer Algebra. They come down to computing linear recurrence relations of a sequence with the Berlekamp-Massey…

Symbolic Computation · Computer Science 2021-07-07 Jérémy Berthomieu , Jean-Charles Faugère

Joint diagonalization, the process of finding a shared set of approximate eigenvectors for a collection of matrices, arises in diverse applications such as multidimensional harmonic analysis or quantum information theory. This task is…

Optimization and Control · Mathematics 2025-02-12 Erik Troedsson , Marcus Carlsson , Herwig Wendt

In this paper we present an algorithm for construction of minimal involutive polynomial bases which are Groebner bases of the special form. The most general involutive algorithms are based on the concept of involutive monomial division…

Commutative Algebra · Mathematics 2025-10-20 Vladimir P. Gerdt , Yuri A. Blinkov

In the current paper the authors linked two methods in order to evaluate general n-th order tridiagonal determinants. A breakdown free numerical algorithm is developed for computing the inverse of any nxn general nonsingular tridiagonal…

Numerical Analysis · Mathematics 2022-08-30 Moawwad El-Mikkawy , Abdelrahman Karawia

The objective of this paper is to apply the well-known exact operational matrices (EOMs) idea for solving the Emden-Fowler equations, illustrating the superiority of EOMs versus ordinary operational matrices (OOMs). Up to now, a few studies…

Numerical Analysis · Computer Science 2014-01-03 K. Parand , Sayyed A. Hossayni , J. A. Rad

We describe a recursive algorithm that decomposes an algebraic set into locally closed equidimensional sets, i.e. sets which each have irreducible components of the same dimension. At the core of this algorithm, we combine ideas from the…

Symbolic Computation · Computer Science 2023-06-12 Christian Eder , Pierre Lairez , Rafael Mohr , Mohab Safey El Din

The definition for the Slater-type orbitals is generalized. Transformation between an orthonormal basis function and the Slater-type orbital with non-integer principal quantum numbers is investigated. Analytical expressions for the linear…

Chemical Physics · Physics 2022-10-11 A. Bağcı , P. E. Hoggan

We introduce an algorithm to solve linear inverse problems regularized with the total (gradient) variation in a gridless manner. Contrary to most existing methods, that produce an approximate solution which is piecewise constant on a fixed…

Signal Processing · Electrical Eng. & Systems 2025-07-08 Yohann de Castro , Vincent Duval , Romain Petit
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