Certificate for Orthogonal Equivalence of Real Polynomials by Polynomial-Weighted Principal Component Analysis

TL;DR

The paper introduces Polynomial-Weighted Principal Component Analysis (PW-PCA) as a scalable method to determine orthogonal transformations that relate two real polynomials, providing a certificate of their orthogonal equivalence.

Contribution

It proposes PW-PCA as an efficient alternative to nonlinear systems for identifying orthogonal symmetries between polynomials.

Findings

PW-PCA can be effectively computed for high-dimensional polynomials.

The method provides a certificate of orthogonal equivalence between polynomials.

PW-PCA reduces computational complexity compared to traditional approaches.

Abstract

Suppose that $f(x) \in \mathbb{R}[x_1,\dots, x_n]$ and $g(x) \in \mathbb{R}[x_1,\dots, x_n]$ are two real polynomials of degree $d$ in $n$ variables. If the polynomials $f$ and $g$ are the same up to orthogonal symmetry a natural question is then what element of the orthogonal group induces the orthogonal symmetry; i.e. to find the element $R\in O(n)$ such that $f(Rx)=g(x)$. One may directly solve this problem by constructing a nonlinear system of equations induced by the relation $f(Rx)=g(x)$ along with the identities of the orthogonal group however this approach becomes quite computationally expensive for larger values of $n$ and $d$. To give an alternative and significantly more scalable solution to this problem, we introduce the concept of Polynomial-Weighted Principal Component Analysis (PW-PCA). We in particular show how PW-PCA can be effectively computed and how these techniques can be used to obtain a certificate of orthogonal equivalence, that is we find the $R\in O(n)$ such that $f(Rx)=g(x)$.