Probabilistic computation of Jacobson form from a diagonal form

Let RR be a simple Euclidean domain and let MM be a square matrix in diagonal form

M=Diag(m1,,mr).M=\operatorname{Diag}(m_1,\ldots,m_r).

The quantity deg(mi)\sum\deg(m_i) is an invariant of the module Rr×r/MR^{r\times r}/M. Choose polynomials pip_i of degree at most deg(mi)1\deg(m_i)-1 with random coefficients in AA, and let cRc\in R generate the left annihilator ideal of the vector [p1,,pr]T[p_1,\ldots,p_r]^T in Rr×r/MR^{r\times r}/M. Jacobson-form computation conjecture. If deg(c)=deg(mi)\deg(c)=\sum\deg(m_i), then Diag(1,,1,c)\operatorname{Diag}(1,\dots,1,c) is a Jacobson form of MM; otherwise, repeating the procedure with another random set of polynomials eventually computes the Jacobson form. This gives the invariant degree sum as a certificate for a probabilistic approach. The conjecture proposes a practical method for computing Jacobson form from a diagonal form over simple Euclidean domains; the supplied text gives no resolution or evidence establishing termination of the repeated random procedure.

Sources & referencesView supporting material

Primary source

Viktor Levandovskyy and Kristina Schindelar, “Computing diagonal form and Jacobson normal form of a matrix using Gröbner bases”, arXiv:1003.3785 (2010).

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