A Symbolic Homotopy Algorithm for Solving Composable Polynomial Systems
Thi Xuan Vu

TL;DR
This paper introduces a symbolic homotopy algorithm that leverages composable polynomial structures to efficiently compute isolated regular solutions of polynomial systems, with applications to invariant theory.
Contribution
It presents a probabilistic algorithm exploiting composable structures to solve polynomial systems more efficiently than traditional methods.
Findings
Algorithm has polynomial complexity in input size and solutions
Applicable to systems with algebraically independent polynomials
Effective for invariant polynomial systems under reflection groups
Abstract
We study the problem of computing the isolated regular solutions of a system \((f_1,\ldots,f_n)\) of \(n\) polynomial equations in \(n\) variables \((X_1, \dots, X_n)\) over a field of characteristic zero \(k\). We focus on systems with a \emph{composable structure}, where each polynomial \(f_i\) can be expressed as a composition \( f_i = h_i(g_1,\dots,g_n)\). Exploiting this structure allows us to reduce the original system to one in the \(g_j\) variables, thereby significantly improving the efficiency of symbolic solution algorithms. We present a probabilistic algorithm that computes all isolated regular solutions, with arithmetic complexity being polynomial in the input size and in the number of solutions. A first important application is when \(f_1, \dots, f_n\) belong to the subring \(k[g_1, \dots, g_n]\), where \(g_1, \dots, g_n\) are algebraically independent polynomials in…
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