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Reading Rational Univariate Representations on lexicographic Groebner bases

2 Pith papers cite this work. Polarity classification is still indexing.

2 Pith papers citing it
abstract

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 certifying a separating linear form and, once certified, calculating the RUR that comes from it, without any condition on the ideal else than being zero-dimensional. Our key result is that the RUR can be read (closed formula) from lexicographic Groebner bases of bivariate elimination ideals, even in the case where the original ideal that is not in shape position, so that one can use the same core as the well known FGLM method to propose a simple algorithm. Our first experiments, either with a very short code (300 lines) written in Maple or with a Julia code using straightforward implementations performing only classical Gaussian reductions in addition to Groebner bases for the degree reverse lexicographic ordering, show that this new method is already competitive with sophisticated state of the art implementations which do not certify the parameterizations.

fields

cs.SC 2

years

2026 2

representative citing papers

Groebner.jl: Fast Gr\"obner Tracing in Julia

cs.SC · 2026-07-07 · conditional · novelty 4.0

A Julia F4 package with a reusable learn/apply tracing interface speeds up repeated Gröbner-basis computations, with 1.5–6.6x measured gains in solving and identifiability benchmarks.

citing papers explorer

Showing 2 of 2 citing papers.

  • Fast Rational Univariate Representation via Gaussian Elimination cs.SC · 2026-07-07 · accept · none · ref 1 · internal anchor

    Dense Gaussian elimination yields a practical, certified Julia solver for rational univariate representations of zero-dimensional ideals with thousands of solutions in seconds.

  • Groebner.jl: Fast Gr\"obner Tracing in Julia cs.SC · 2026-07-07 · conditional · none · ref 6 · internal anchor

    A Julia F4 package with a reusable learn/apply tracing interface speeds up repeated Gröbner-basis computations, with 1.5–6.6x measured gains in solving and identifiability benchmarks.