Sensitivity lower bounds from linear dependencies - Université Paris Cité Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2020

Sensitivity lower bounds from linear dependencies

Sophie Laplante
  • Fonction : Auteur
Anupa Sunny
  • Fonction : Auteur

Résumé

Recently, using the eigenvalue techniques, H. Huang proved that every subgraph of the hypercube of dimension n induced on more than half the vertices has maximum degree at least √ n. Combined with some earlier work, this completed a proof of the sensitivity conjecture. In this work we show how to derive a proof of Huang's result using only linear dependency and independence of vectors associated with the vertices of the hypercube. Our approach leads to several improvements of the result. In particular we prove that in any induced subgraph of H n with more than half the number of vertices, there are two vertices, one of odd parity and the other of even parity, each with at least n vertices at distance at most 2. As an application we show that for any Boolean function f , the polynomial degree of f is bounded above by s 0 (f)s 1 (f), a strictly stronger statement which implies the sensitivity conjecture.
Fichier principal
Vignette du fichier
Sensitivity-06.pdf (318.43 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02429358 , version 1 (06-01-2020)

Identifiants

  • HAL Id : hal-02429358 , version 1

Citer

Sophie Laplante, Reza Naserasr, Anupa Sunny. Sensitivity lower bounds from linear dependencies. 2020. ⟨hal-02429358⟩
195 Consultations
210 Téléchargements

Partager

Gmail Facebook X LinkedIn More