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A widely used method for solving SOS (Sum Of Squares) decomposition problem is to reduce it to the problem of semi-definite programs (SDPs) which can be efficiently solved in theory. In practice, although many SDP solvers can work out some…

Symbolic Computation · Computer Science 2018-01-31 Haokun Li , Bican Xia

Regular chains and triangular decompositions are fundamental and well-developed tools for describing the complex solutions of polynomial systems. This paper proposes adaptations of these tools focusing on solutions of the real analogue:…

Symbolic Computation · Computer Science 2010-05-17 Changbo Chen , James H. Davenport , John P. May , Marc Moreno Maza , Bican Xia , Rong Xiao

We propose new algorithms for computing triangular decompositions of polynomial systems incrementally. With respect to previous works, our improvements are based on a {\em weakened} notion of a polynomial GCD modulo a regular chain, which…

Symbolic Computation · Computer Science 2011-04-06 Changbo Chen , Marc Moreno Maza

Existing algorithms for isolating real solutions of zero-dimensional polynomial systems do not compute the multiplicities of the solutions. In this paper, we define in a natural way the multiplicity of solutions of zero-dimensional…

Symbolic Computation · Computer Science 2009-06-18 Zhihai Zhang , Tian Fang , Bican Xia

A new concept, decomposition-unstable (DU) variety of a parametric polynomial system, is introduced in this paper and the stabilities of several triangular decomposition methods, such as characteristic set decomposition, relatively…

Symbolic Computation · Computer Science 2012-08-31 Xiaoxian Tang , Bican Xia

This paper presents a novel algorithm for constructing a sum-of-squares (SOS) decomposition for positive semi-definite polynomials with rational coefficients. Unlike previous methods that typically yield SOS decompositions with…

Symbolic Computation · Computer Science 2025-10-06 Zhenbing Zeng , Yong Huang , Lu Yang , Yongsheng Rao

Efficient characteristic set methods for computing solutions of polynomial equation systems in a finite field are proposed. The concept of proper triangular sets is introduced and an explicit formula for the number of solutions of a proper…

Symbolic Computation · Computer Science 2010-12-01 Xiao-Shan Gao , Zhenyu Huang

In this paper, we are concerned with the problem of counting the multiplicities of a zero-dimensional regular set's zeros. We generalize the squarefree decomposition of univariate polynomials to the so-called pseudo squarefree decomposition…

Symbolic Computation · Computer Science 2021-03-08 Xiaoliang Li , Wei Niu

We focus on two central themes in this dissertation. The first one is on decomposing polytopes and polynomials in ways that allow us to perform nonlinear optimization. We start off by explaining important results on decomposing a polytope…

Combinatorics · Mathematics 2016-05-18 Brandon Dutra

We introduce a new approach to isolate the real roots of a square-free polynomial $F=\sum_{i=0}^n A_i x^i$ with real coefficients. It is assumed that each coefficient of $F$ can be approximated to any specified error bound. The presented…

Data Structures and Algorithms · Computer Science 2015-03-17 Michael Sagraloff

This paper is concerned with linear algebra based methods for solving exactly polynomial systems through so-called Gr\"obner bases, which allow one to compute modulo the polynomial ideal generated by the input equations. This is a topical…

Symbolic Computation · Computer Science 2023-07-28 Jérémy Berthomieu , Christian Eder , Mohab Safey El Din

We present an effective method for computing parametric primary decomposition via comprehensive Gr\"obner systems. In general, it is very difficult to compute a parametric primary decomposition of a given ideal in the polynomial ring with…

Symbolic Computation · Computer Science 2024-08-29 Yuki Ishihara , Kazuhiro Yokoyama

In this note, we show that the decomposition group $Dec(I)$ of a zero-dimensional radical ideal $I$ in ${\bf K}[x_1,\ldots,x_n]$ can be represented as the direct sum of several symmetric groups of polynomials based upon using Gr\"{o}bner…

Commutative Algebra · Mathematics 2016-01-26 Yongbin Li

Sum of squares (SOS) optimization is a powerful technique for solving problems where the positivity of a polynomials must be enforced. The common approach to solve an SOS problem is by relaxation to a Semidefinite Program (SDP). The main…

Optimization and Control · Mathematics 2024-10-29 Daniel Keren , Margarita Osadchy , Roi Poranne

Chordal and factor-width decomposition methods for semidefinite programming and polynomial optimization have recently enabled the analysis and control of large-scale linear systems and medium-scale nonlinear systems. Chordal decomposition…

Optimization and Control · Mathematics 2021-11-23 Yang Zheng , Giovanni Fantuzzi , Antonis Papachristodoulou

The computation of triangular decompositions are based on two fundamental operations: polynomial GCDs modulo regular chains and regularity test modulo saturated ideals. We propose new algorithms for these core operations relying on modular…

Symbolic Computation · Computer Science 2009-07-25 Xin Li , Marc Moreno Maza , Wei Pan

Let $f$ be a polynomial system consisting of $n$ polynomials $f_1,\cdots, f_n$ in $n$ variables $x_1,\cdots, x_n$, with coefficients in $\mathbb{Q}$ and let $\langle f\rangle$ be the ideal generated by $f$. Such a polynomial system, which…

Commutative Algebra · Mathematics 2018-07-31 Jean-Paul Cardinal

The real radical ideal of a system of polynomials with finitely many complex roots is generated by a system of real polynomials having only real roots and free of multiplicities. It is a central object in computational real algebraic…

Optimization and Control · Mathematics 2015-04-07 Greg Reid , Fei Wang , Henry Wolkowicz , Wenyuan Wu

In this paper, we develop a new deflation technique for refining or verifying the isolated singular zeros of polynomial systems. Starting from a polynomial system with an isolated singular zero, by computing the derivatives of the input…

Symbolic Computation · Computer Science 2019-01-01 Jin-San Cheng , Xiaojie Dou , Junyi Wen

Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and…

Data Structures and Algorithms · Computer Science 2014-01-21 Aditya Bhaskara , Moses Charikar , Ankur Moitra , Aravindan Vijayaraghavan
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