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We present LinApart2, a major update to the LinApart algorithm for univariate partial fraction decomposition. Unlike its predecessor, LinApart2 can handle denominators of arbitrary polynomial degree without explicit factorization, while…

Symbolic Computation · Computer Science 2025-11-21 Levente Fekésházy , Oliver Schnetz

We present a package to perform partial fraction decompositions of multivariate rational functions. The algorithm allows to systematically avoid spurious denominator factors and is capable of producing unique results also when being applied…

Symbolic Computation · Computer Science 2022-01-05 Matthias Heller , Andreas von Manteuffel

We investigate the possibilities to calculate vector partition functions by means of iterated partial fraction decomposition, as suggested by Beck (2004). Particularly, for an important type of families of rational functions, we describe an…

Combinatorics · Mathematics 2009-12-08 Thomas Bliem

We obtain two new algorithms for partial fraction decompositions; the first is over algebraically closed fields, and the second is over general fields. These algorithms takes $O(M^2)$ time, where $M$ is the degree of the denominator of the…

Combinatorics · Mathematics 2007-05-23 Guoce Xin

These notes describe Leinartas's algorithm for multivariate partial fraction decompositions and employ an implementation thereof in Sage.

Commutative Algebra · Mathematics 2012-06-26 Alexander Raichev

We have generalized the \textsc{Mathematica} function \texttt{Apart} from 1 to $N$ dimension, the generalized function \texttt{\$Apart} can decompose any linear dependent elements in $\mathcal{V}_{x}^*$ to irreducible ones. The elements in…

High Energy Physics - Phenomenology · Physics 2012-08-21 Feng Feng

Fractional calculus has become widely studied and applied to physical problems in recent years. As a result, many methods for the numerical computation of fractional derivatives and integrals have been defined. However, these algorithms are…

Mathematical Software · Computer Science 2019-12-12 Matthew Adams

We develop a decomposition method based on the augmented Lagrangian framework to solve a broad family of semidefinite programming problems, possibly with nonlinear objective functions, nonsmooth regularization, and general linear…

Optimization and Control · Mathematics 2023-03-08 Yifei Wang , Kangkang Deng , Haoyang Liu , Zaiwen Wen

In this paper, we give a detailed account of the algorithm outlined in [1] for Feynman integral reduction and $\varepsilon$-factorised differential equations. The algorithm consists of two steps. In the first step, we use a new geometric…

In this article, we deal with the efficient computation of the Wright function in the cases of interest for the expression of solutions of some fractional differential equations. The proposed algorithm is based on the inversion of the…

Numerical Analysis · Mathematics 2024-09-16 Lidia Aceto , Fabio Durastante

We present two new algorithms for the computation of the q-integer linear decomposition of a multivariate polynomial. Such a decomposition is essential for the treatment of q-hypergeometric symbolic summation via creative telescoping and…

Symbolic Computation · Computer Science 2021-02-15 Mark Giesbrecht , Hui Huang , George Labahn , Eugene Zima

In this paper we show how we can compute in a deterministic way the decomposition of a multivariate rational function with a recombination strategy. The key point of our recombination strategy is the used of Darboux polynomials. We study…

Symbolic Computation · Computer Science 2014-02-26 Guillaume Chèze

We review the Laporta algorithm for the reduction of scalar integrals to the master integrals and the differential equations technique for their evaluation. We discuss the use of the basis of harmonic polylogarithms for the analytical…

High Energy Physics - Phenomenology · Physics 2007-05-23 R. Bonciani

Factorization of polynomials is one of the foundations of symbolic computation. Its applications arise in numerous branches of mathematics and other sciences. However, the present advanced programming languages such as C++ and J++, do not…

Algebraic Geometry · Mathematics 2010-08-24 Yong Feng , Wenyuan Wu , Jingzhong Zhang

We propose a new numerical algorithm for computing the tensor rank decomposition or canonical polyadic decomposition of higher-order tensors subject to a rank and genericity constraint. Reformulating this computational problem as a system…

Numerical Analysis · Mathematics 2024-07-02 Simon Telen , Nick Vannieuwenhoven

We present an efficient method to shorten the analytic integration-by-parts (IBP) reduction coefficients of multi-loop Feynman integrals. For our approach, we develop an improved version of Leinartas' multivariate partial fraction…

High Energy Physics - Phenomenology · Physics 2020-12-30 Janko Boehm , Marcel Wittmann , Zihao Wu , Yingxuan Xu , Yang Zhang

A primary interest in dynamic inverse problems is to identify the underlying temporal behaviour of the system from outside measurements. In this work we consider the case, where the target can be represented by a decomposition of spatial…

Numerical Analysis · Mathematics 2020-06-09 Simon Arridge , Pascal Fernsel , Andreas Hauptmann

An algorithm is designed which decomposes a tropical univariate rational function into a composition of tropical binomials and trinomials. When a function is monotone, the composition consists just of binomials. Similar algorithms are…

Algebraic Geometry · Mathematics 2019-03-04 Dima Grigoriev

We present FaRe, a package for Mathematica that implements the decomposition of a generic tensor Feynman integral, with arbitrary loop number, into scalar integrals in higher dimension. In order for FaRe to work, the package FeynCalc is…

High Energy Physics - Phenomenology · Physics 2016-03-23 Michele Re Fiorentin

We propose a novel parallel algorithm for decomposing hard CircuitSAT instances. The technique employs specialized constraints to partition an original SAT instance into a family of weakened formulas. Our approach is implemented as a…

Artificial Intelligence · Computer Science 2026-02-20 Victor Kondratiev , Irina Gribanova , Alexander Semenov
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