High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games
Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett

TL;DR
This paper develops a spectral and combinatorial framework for high dimensional expanders, leading to new structural theorems, improved algorithms for unique games, and insights into hardness of approximation.
Contribution
It introduces a combinatorial spectral characterization of HD-walks on two-sided local-spectral expanders, and applies this to improve algorithms for unique games and explore hardness of approximation.
Findings
Spectral structure of HD-walks is tightly concentrated in structured strips.
New $ ext{l}_2$-characterization of edge-expansion on HDX.
Polynomial-time algorithms for certain unique games instances.
Abstract
Higher order random walks (HD-walks) on high dimensional expanders (HDX) have seen an incredible amount of study and application since their introduction by Kaufman and Mass [KM16], yet their broader combinatorial and spectral properties remain poorly understood. We develop a combinatorial characterization of the spectral structure of HD-walks on two-sided local-spectral expanders [DK17], which offer a broad generalization of the well-studied Johnson and Grassmann graphs. Our characterization, which shows that the spectra of HD-walks lie tightly concentrated in a few combinatorially structured strips, leads to novel structural theorems such as a tight -characterization of edge-expansion, as well as to a new understanding of local-to-global algorithms on HDX. Towards the latter, we introduce a spectral complexity measure called Stripped Threshold Rank, and show how it can…
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Topological and Geometric Data Analysis · Theoretical and Computational Physics
