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Seminar
3/28/2018 11:00 am
CoRE 301

Hitting Sets with Near-Optimal Error for Read-Once Branching Programs

Sumegha Garg, Princeton University

Organizer(s): Pranjal Awasthi and Shubhangi Saraf

Abstract

Nisan [Nis92] constructed a pseudorandom generator for length n, width n read-once branching programs (ROBPs) with error ε and seed length O(log^2(n) + log(n) · log(1/ε)). A major goal in complexity theory is to reduce the seed length, hopefully, to the optimal O(log(n) + log(1/ε)), or to construct improved hitting sets, as these would yield stronger derandomization of BPL and RL, respectively. In this talk, we make the first improvement by constructing a hitting set with seed length ~O����(log^2(n) + log(1/ε)). That is, we decouple ε and n, and obtain near-optimal dependence on the former. The regime of parameters in which our construction strictly improves upon prior works, namely, log(1/ε) ≫ log n, is well- motivated by the work of Saks and Zhou [SZ99] who use pseudorandom generators with error ε = 2^{−log^2(n)} in their proof for BPL ⊆ L^{3/2}.

Joint work with Mark Braverman and Gil Cohen.

Bio

I am a third year PhD student in the Department of Computer Science at Princeton University. I am extremely fortunate to be advised by Mark Braverman. Before coming here, I finished my undergraduate studies in the Department of Computer Science and Engineering at Indian Institute of Technology, Delhi.

I am interested in Theoretical Computer Science, particularly in information theory, complexity theory and quantum computing. CV