DocumentCode
2653311
Title
Gaussian Noise Sensitivity and Fourier Tails
Author
Kindler, Guy ; O´Donnell, Ryan
Author_Institution
Sch. of Comput. Sci. & Eng., Hebrew Univ. of Jerusalem, Jerusalem, Israel
fYear
2012
fDate
26-29 June 2012
Firstpage
137
Lastpage
147
Abstract
We study the problem of matrix isomorphism of matrix Lie algebras (MatIsoLie). Lie algebras arise centrally in areas as diverse as differential equations, particle physics, group theory, and the Mulmuley -- Sohoni Geometric Complexity Theory program. A matrix Lie algebra is a set L of matrices that is closed under linear combinations and the operation [A, B] = AB - BA. Two matrix Lie algebras L, L´ are matrix isomorphic if there is an invertible matrix M such that conjugating every matrix in L by M yields the set L´. We show that certain cases of MatIsoLie -- for the wide and widely studied classes of semi simple and abelian Lie algebras -- are equivalent to graph isomorphism and linear code equivalence, respectively. On the other hand, we give polynomial-time algorithms for other cases of MatIsoLie, which allow us to mostly derandomize a recent result of Kayal on affine equivalence of polynomials.
Keywords
Boolean functions; Gaussian processes; computational complexity; set theory; theorem proving; Boolean function; Borell isoperimetric inequality; Bourgain proof; Fourier tail bound; Gaussian isoperimetric inequality; Gaussian noise sensitivity; Hermite tail bound; UG-hardness; invariance principle; max-cut; subadditivity property; volume sets; Approximation methods; Educational institutions; Noise; Noise measurement; Polynomials; Sensitivity; Standards;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Complexity (CCC), 2012 IEEE 27th Annual Conference on
Conference_Location
Porto
ISSN
1093-0159
Print_ISBN
978-1-4673-1663-7
Type
conf
DOI
10.1109/CCC.2012.35
Filename
6243390
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