2020
DOI: 10.48550/arxiv.2011.04658
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High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games

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(7 citation statements)
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“…Fourier Analysis on HDX: High dimensional expanders (HDX) are a class of robustly connected complexes that have seen an incredible amount of development and application throughout theoretical computer science in the past few years, most famously in coding theory [DEL + 21, EKZ20, JST21, KO21, KT21b, DDHRZ20, JQST20, DHK + 19] and approximate sampling [ALOV19, AL20, ALO20, CLV20, CLV21, CGŠV21, FGYZ21, JPV21, Liu21, BCC + 21], but also in agreement testing [DK17, DD19, KM20], CSPapproximation [AJT19,BHKL20], and (implicitly) hardness of approximation [KMMS18,KMS18]. In this work, we study a central notion of high dimensional expansion called two-sided local-spectral expansion, originally developed by Dinur and Kaufman [DK17] to build sparse agreement testers.…”
Section: Contributionsmentioning
confidence: 99%
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“…Fourier Analysis on HDX: High dimensional expanders (HDX) are a class of robustly connected complexes that have seen an incredible amount of development and application throughout theoretical computer science in the past few years, most famously in coding theory [DEL + 21, EKZ20, JST21, KO21, KT21b, DDHRZ20, JQST20, DHK + 19] and approximate sampling [ALOV19, AL20, ALO20, CLV20, CLV21, CGŠV21, FGYZ21, JPV21, Liu21, BCC + 21], but also in agreement testing [DK17, DD19, KM20], CSPapproximation [AJT19,BHKL20], and (implicitly) hardness of approximation [KMMS18,KMS18]. In this work, we study a central notion of high dimensional expansion called two-sided local-spectral expansion, originally developed by Dinur and Kaufman [DK17] to build sparse agreement testers.…”
Section: Contributionsmentioning
confidence: 99%
“…2 Traditionally proved via hypercontractivity, a variant of this result on the Grassmannian recently led to the resolution of the 2-2 Games Conjecture [KMS18]. On the other hand, Bafna, Hopkins, Kaufman, and Lovett [BHKL20] showed that second moment methods cannot recover such a result. While they are able to recover some sort of characterization with these techniques, it necessarily decays as the dimension grows to infinity, becoming trivial in the regime useful for hardness of approximation-if we want to do better, it appears we need a theory of hypercontractivity.…”
Section: Contributionsmentioning
confidence: 99%
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