Pseudorandom Generators for Read-Once Branching Programs, in any Order
Michael A. Forbes, Zander Kelley

TL;DR
This paper develops an improved explicit pseudorandom generator with near-optimal seed-length for fooling polynomial-size read-once branching programs reading variables in any unknown order, advancing derandomization efforts.
Contribution
It introduces a new analysis using the 'bounded independence plus noise' paradigm to construct PRGs with $O( ext{log}^3 n)$ seed-length for general roBPs in unknown order, and $ ilde{O}( ext{log}^2 n)$ for constant width.
Findings
Achieved explicit PRG with $O( ext{log}^3 n)$ seed-length for general polynomial-size roBPs.
Improved seed-length to $ ilde{O}( ext{log}^2 n)$ for constant-width roBPs.
Extended the understanding of fooling roBPs in unknown variable order settings.
Abstract
A central question in derandomization is whether randomized logspace (RL) equals deterministic logspace (L). To show that RL=L, it suffices to construct explicit pseudorandom generators (PRGs) that fool polynomial-size read-once (oblivious) branching programs (roBPs). Starting with the work of Nisan, pseudorandom generators with seed-length were constructed. Unfortunately, improving on this seed-length in general has proven challenging and seems to require new ideas. A recent line of inquiry has suggested focusing on a particular limitation of the existing PRGs, which is that they only fool roBPs when the variables are read in a particular known order, such as . In comparison, existentially one can obtain logarithmic seed-length for fooling the set of polynomial-size roBPs that read the variables under any fixed unknown permutation…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Cryptography and Data Security · Optimization and Search Problems
