Gibbs Manifolds
Section 3 features a symbolic implicitization algorithm for the Gibbs variety of a given LSSM defined over \(\mathbb{Q}\). We implemented this algorithm in Julia using the Oscar computer algebra package. Our code can be downloaded here: GibbsCode.zip
. An implementation of the algorithm can be found in symbolic_implicitization.jl
inside this archive.
Example 3.4 illustrates how numerical methods can be used to implicitize Gibbs varieties that are infeasible for symbolic computation: the defining equation is found numerically for the Gibbs variety of the following LSSM of Hankel matrices:
Julia code for this example can be downloaded here: numerical_implicitization.jl
(this file is also part of GibbsCode.zip
). The resulting equation has 853 terms and can be found here: hankel4.txt
.
Project page created: 25/11/2022.
Project contributors: Dmitrii Pavlov, Bernd Sturmfels, Simon Telen.
Corresponding author of this page: Dmitrii Pavlov, pavlov@mis.mpg.de.
Software used: Julia (Version 1.8.3), Oscar (Version 0.11.0).
System setup used: MacBook Pro with macOS Monterey 12.6, Processor 2,8 GHz Intel Core i7, Memory 16 GB 2133 MHz LPDDR3, Graphics Intel HD Graphics 630 1536 MB.
Last updated 29/11/22.