Recent Advances in Debordering Methods

Fuente: arXiv
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Main Authors: Dutta, Pranjal, Lysikov, Vladimir
Format: Preprint
Published: 2025
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author Dutta, Pranjal
Lysikov, Vladimir
author_facet Dutta, Pranjal
Lysikov, Vladimir
contents Border complexity captures functions that can be approximated by low-complexity ones. Debordering is the task of proving an upper bound on some non-border complexity measure in terms of a border complexity measure, thus getting rid of limits. Debordering lies at the heart of foundational complexity theory questions relating Valiant's determinant versus permanent conjecture (1979) and its geometric complexity theory (GCT) variant proposed by Mulmuley and Sohoni (2001). The debordering of matrix multiplication tensors by Bini (1980) played a pivotal role in the development of efficient matrix multiplication algorithms. Consequently, debordering finds applications in both establishing computational complexity lower bounds and facilitating algorithm design. Recent years have seen notable progress in debordering various restricted border complexity measures. In this survey, we highlight these advances and discuss techniques underlying them.
format Preprint
id arxiv_https___arxiv_org_abs_2510_13049
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Recent Advances in Debordering Methods
Dutta, Pranjal
Lysikov, Vladimir
Computational Complexity
Symbolic Computation
Algebraic Geometry
68Q17, 68Q15, 14L30
Border complexity captures functions that can be approximated by low-complexity ones. Debordering is the task of proving an upper bound on some non-border complexity measure in terms of a border complexity measure, thus getting rid of limits. Debordering lies at the heart of foundational complexity theory questions relating Valiant's determinant versus permanent conjecture (1979) and its geometric complexity theory (GCT) variant proposed by Mulmuley and Sohoni (2001). The debordering of matrix multiplication tensors by Bini (1980) played a pivotal role in the development of efficient matrix multiplication algorithms. Consequently, debordering finds applications in both establishing computational complexity lower bounds and facilitating algorithm design. Recent years have seen notable progress in debordering various restricted border complexity measures. In this survey, we highlight these advances and discuss techniques underlying them.
title Recent Advances in Debordering Methods
topic Computational Complexity
Symbolic Computation
Algebraic Geometry
68Q17, 68Q15, 14L30
url https://arxiv.org/abs/2510.13049