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Solving polynomial systems arising from applications is frequently made easier by the structure of the systems. Weighted homogeneity (or quasi-homogeneity) is one example of such a structure: given a system of weights…

Symbolic Computation · Computer Science 2015-12-22 Jean-Charles Faugère , Mohab Safey El Din , Thibaut Verron

The aim of this article is to introduce standard bases of ideals in polynomial rings with respect to a class of orderings which are not necessarily semigroup orderings. Our approach generalises the concept of standard bases with respect to…

Algebraic Geometry · Mathematics 2007-05-23 Stephan Endrass

One of the main contributions which Volker Weispfenning made to mathematics is related to Groebner bases theory. In this paper we present an algorithm for computing all algebraic intermediate subfields in a separably generated unirational…

Symbolic Computation · Computer Science 2008-05-15 Jaime Gutierrez , David Sevilla

The extended cyclic reduction algorithm developed by Swarztrauber in 1974 was used to solve the block-tridiagonal linear system. The paper fills in the gap of theoretical results concerning the zeros of matrix polynomial $B_{i}^{(r)}$ with…

Numerical Analysis · Mathematics 2022-04-06 Xuhao Diao , Jun Hu , Suna Ma

A strong link between information geometry and algebraic statistics is made by investigating statistical manifolds which are algebraic varieties. In particular it it shown how first and second order efficient estimators can be constructed,…

Statistics Theory · Mathematics 2014-01-13 Kei Kobayashi , Henry P. Wynn

Let $K$ be a field equipped with a valuation. Tropical varieties over $K$ can be defined with a theory of Gr\"obner bases taking into account the valuation of $K$. Because of the use of the valuation, this theory is promising for stable…

Symbolic Computation · Computer Science 2015-09-30 Tristan Vaccon

A preconditioning theory is presented which establishes sufficient conditions for multiplicative and additive Schwarz algorithms to yield self-adjoint positive definite preconditioners. It allows for the analysis and use of non-variational…

Numerical Analysis · Mathematics 2010-01-12 Michael Holst , Stefan Vandewalle

Over the last two decades, significant advances have been made in the design and analysis of fixed-parameter algorithms for a wide variety of graph-theoretic problems. This has resulted in an algorithmic toolbox that is by now…

Data Structures and Algorithms · Computer Science 2021-01-01 Faisal Abu-Khzam , Sebastian Lamm , Matthias Mnich , Alexander Noe , Christian Schulz , Darren Strash

We present a formalization of Gr\"obner basis theory in Lean 4, built on top of Mathlib's infrastructure for multivariate polynomials and monomial orders. Our development covers the core foundations of Gr\"obner basis theory, including…

Commutative Algebra · Mathematics 2026-04-21 Junyu Guo , Hao Shen , Junqi Liu , Lihong Zhi

Predict and optimize is an increasingly popular decision-making paradigm that employs machine learning to predict unknown parameters of optimization problems. Instead of minimizing the prediction error of the parameters, it trains…

Machine Learning · Computer Science 2024-02-05 Grigorii Veviurko , Wendelin Böhmer , Mathijs de Weerdt

It is known that for binary codes one can use Gr\"obner bases to obtain a subset of codewords of minimal support that can be used to determine the second generalized Hamming weight of the code. In this paper we establish conditions on a…

Commutative Algebra · Mathematics 2025-10-14 Hernán de Alba , Cecilia Martínez-Reyes

With the advent of high-throughput profiling methods, interest in reverse engineering the structure and dynamics of biochemical networks is high. Recently an algorithm for reverse engineering of biochemical networks was developed by…

Quantitative Methods · Quantitative Biology 2010-01-18 Edgar Delgado-Eckert

In this paper we state and explain techniques useful for the computation of strong Gr\"obner and standard bases over Euclidean domains: First we investigate several strategies for creating the pair set using an idea by Lichtblau. Then we…

Commutative Algebra · Mathematics 2018-11-15 Christian Eder , Gerhard Pfister , Adrian Popescu

This paper introduces a rectified and renormalized Fisher-Bingham model for compositional data with zeros, motivated in part by the presence of zeros in microbiota studies. The approach represents compositions through a square-root…

Methodology · Statistics 2026-04-29 Eugene Han , Marahi Perez-Tamayo , Hannah D. Holscher , Ruoqing Zhu

This paper describes and analyzes a method for computing border bases of a zero-dimensional ideal $I$. The criterion used in the computation involves specific commutation polynomials and leads to an algorithm and an implementation extending…

Symbolic Computation · Computer Science 2008-12-02 Bernard Mourrain , Philippe Trébuchet

Fisher zeros play a central role in the theoretical understanding of phase transitions. However, their computation requires knowledge of the density of states, which limits their practical applicability. Alternative approaches based on the…

Computational Physics · Physics 2026-05-22 R. G. M. Rodrigues

In the field of algebraic systems biology, the number of minimal polynomial models constructed using discretized data from an underlying system is related to the number of distinct reduced Gr\"obner bases for the ideal of the data points.…

Algebraic Geometry · Mathematics 2024-11-19 Anyu Zhang , Brandilyn Stigler

In this contribution, we consider a zero-dimensional polynomial system in $n$ variables defined over a field $\mathbb{K}$. In the context of computing a Rational Univariate Representation (RUR) of its solutions, we address the problem of…

Symbolic Computation · Computer Science 2025-05-26 Alexander Demin , Fabrice Rouillier , Joao Ruiz

In this paper we present an algorithm for computing Groebner bases of linear ideals in a difference polynomial ring over a ground difference field. The input difference polynomials generating the ideal are also assumed to be linear. The…

Mathematical Physics · Physics 2009-11-11 Vladimir P. Gerdt

A scalable Bayesian machine learning framework is introduced for estimating scalar properties of an unknown quantum state from measurement data, which bypasses full density matrix reconstruction. This work is the first to integrate the…

Quantum Physics · Physics 2025-12-08 Hyunho Cha , Wonjung Kim , Jungwoo Lee