Polynomial Time Algorithms in Invariant Theory for Torus Actions

Open Access
Authors
  • P. Bürgisser
  • M.L. Doğan
  • V. Makam
  • M. Walter
  • A. Wigderson
Publication date 07-2021
Host editors
  • V. Kabanets
Book title 36th Computational Complexity Conference
Book subtitle CCC2021, July 20-23, 2021, Toronto Canada (Virtual Conference)
ISBN (electronic)
  • 9783959771931
Series Leibniz International Proceedings in Informatics
Event 36th Computational Complexity Conference
Article number 32
Number of pages 30
Publisher Saarbrücken/Wadern: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Organisations
  • Faculty of Science (FNWI) - Institute of Physics (IoP) - Institute for Theoretical Physics Amsterdam (ITFA)
  • Faculty of Science (FNWI) - Korteweg-de Vries Institute for Mathematics (KdVI)
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
An action of a group on a vector space partitions the latter into a set of orbits. We consider three natural and useful algorithmic "isomorphism" or "classification" problems, namely, orbit equality, orbit closure intersection, and orbit closure containment. These capture and relate to a variety of problems within mathematics, physics and computer science, optimization and statistics. These orbit problems extend the more basic null cone problem, whose algorithmic complexity has seen significant progress in recent years.
In this paper, we initiate a study of these problems by focusing on the actions of commutative groups (namely, tori). We explain how this setting is motivated from questions in algebraic complexity, and is still rich enough to capture interesting combinatorial algorithmic problems. While the structural theory of commutative actions is well understood, no general efficient algorithms were known for the aforementioned problems. Our main results are polynomial time algorithms for all three problems. We also show how to efficiently find separating invariants for orbits, and how to compute systems of generating rational invariants for these actions (in contrast, for polynomial invariants the latter is known to be hard). Our techniques are based on a combination of fundamental results in invariant theory, linear programming, and algorithmic lattice theory.
Document type Conference contribution
Note Longer version available on ArXiv.org
Language English
Published at https://doi.org/10.4230/LIPIcs.CCC.2021.32
Published at https://arxiv.org/abs/2102.07727
Downloads
Polynomial Time Algorithms (Final published version)
2102.07727 (Other version)
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