Hypercontractivity, Sum-of-Squares Proofs, and their Applications
Boaz Barak, Fernando G.S.L. Brand\~ao, Aram W. Harrow, Jonathan A., Kelner, David Steurer, Yuan Zhou

TL;DR
This paper explores the computational complexity of approximating the 2->q norm of linear operators, revealing connections to quantum information, the Unique Games Conjecture, and providing new bounds and algorithms for related problems.
Contribution
It establishes new links between 2->q norm approximation, graph expansion, and quantum information, and improves bounds for the Sum of Squares hierarchy and related computational problems.
Findings
Approximation of 2->q norm can refute the Small-Set Expansion Conjecture.
Sum of Squares hierarchy certifies bounds on 2->4 norm and separates it from weaker hierarchies.
Computing the 2->4 norm is NP-hard and related to quantum information problems.
Abstract
We study the computational complexity of approximating the 2->q norm of linear operators (defined as ||A||_{2->q} = sup_v ||Av||_q/||v||_2), as well as connections between this question and issues arising in quantum information theory and the study of Khot's Unique Games Conjecture (UGC). We show the following: 1. For any constant even integer q>=4, a graph is a "small-set expander" if and only if the projector into the span of the top eigenvectors of G's adjacency matrix has bounded 2->q norm. As a corollary, a good approximation to the 2->q norm will refute the Small-Set Expansion Conjecture--a close variant of the UGC. We also show that such a good approximation can be obtained in exp(n^(2/q)) time, thus obtaining a different proof of the known subexponential algorithm for Small Set Expansion. 2. Constant rounds of the "Sum of Squares" semidefinite programing hierarchy…
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