Sensitivity lower bounds from linear dependencies - Archive ouverte HAL
Preprints, Working Papers, ... Year : 2020

Sensitivity lower bounds from linear dependencies

Sophie Laplante
  • Function : Author
Anupa Sunny
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Abstract

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.
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Dates and versions

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

Identifiers

  • HAL Id : hal-02429358 , version 1

Cite

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

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