eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2023-07-05
39:1
39:20
10.4230/LIPIcs.ICALP.2023.39
article
New PRGs for Unbounded-Width/Adaptive-Order Read-Once Branching Programs
Chen, Lijie
1
https://orcid.org/0000-0002-6084-4729
Lyu, Xin
2
Tal, Avishay
2
Wu, Hongxun
2
Miller Institute for Basic Research in Science at University of California at Berkeley, CA, USA
University of California at Berkeley, CA, USA
We give the first pseudorandom generators with sub-linear seed length for the following variants of read-once branching programs (roBPs):
1) First, we show there is an explicit PRG of seed length O(log²(n/ε)log(n)) fooling unbounded-width unordered permutation branching programs with a single accept state, where n is the length of the program. Previously, [Lee-Pyne-Vadhan RANDOM 2022] gave a PRG with seed length Ω(n) for this class. For the ordered case, [Hoza-Pyne-Vadhan ITCS 2021] gave a PRG with seed length Õ(log n ⋅ log 1/ε).
2) Second, we show there is an explicit PRG fooling unbounded-width unordered regular branching programs with a single accept state with seed length Õ(√{n ⋅ log 1/ε} + log 1/ε). Previously, no non-trivial PRG (with seed length less than n) was known for this class (even in the ordered setting). For the ordered case, [Bogdanov-Hoza-Prakriya-Pyne CCC 2022] gave an HSG with seed length Õ(log n ⋅ log 1/ε).
3) Third, we show there is an explicit PRG fooling width w adaptive branching programs with seed length O(log n ⋅ log² (nw/ε)). Here, the branching program can choose an input bit to read depending on its current state, while it is guaranteed that on any input x ∈ {0,1}ⁿ, the branching program reads each input bit exactly once. Previously, no PRG with a non-trivial seed length is known for this class.
We remark that there are some functions computable by constant-width adaptive branching programs but not by sub-exponential-width unordered branching programs.
In terms of techniques, we indeed show that the Forbes-Kelly PRG (with the right parameters) from [Forbes-Kelly FOCS 2018] already fools all variants of roBPs above. Our proof adds several new ideas to the original analysis of Forbes-Kelly, and we believe it further demonstrates the versatility of the Forbes-Kelly PRG.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol261-icalp2023/LIPIcs.ICALP.2023.39/LIPIcs.ICALP.2023.39.pdf
pseudorandom generators
derandomization
read-once branching programs