Affiliation:
1. University of California, San Diego
2. University of California, Los Angeles
3. University of Texas at Austin
Abstract
One powerful theme in complexity theory and pseudorandomness in the past few decades has been the use of lower bounds to give pseudorandom generators (PRGs). However, the general results using this hardness vs. randomness paradigm suffer from a quantitative loss in parameters, and hence do not give nontrivial implications for models where we don’t know super-polynomial lower bounds but do know lower bounds of a fixed polynomial. We show that when such lower bounds are proved using random restrictions, we can construct PRGs which are essentially best possible without in turn improving the lower bounds.
More specifically, say that a circuit family has shrinkage exponent Γ if a random restriction leaving a
p
fraction of variables unset shrinks the size of any circuit in the family by a factor of
p
Γ +
o
(1)
. Our PRG uses a seed of length
s
1/(Γ + 1) +
o
(1)
to fool circuits in the family of size
s
. By using this generic construction, we get PRGs with polynomially small error for the following classes of circuits of size
s
and with the following seed lengths:
(1) For de Morgan formulas, seed length
s
1/3+
o
(1)
;
(2) For formulas over an arbitrary basis, seed length
s
1/2+
o
(1)
;
(3) For read-once de Morgan formulas, seed length
s
.234...
;
(4) For branching programs of size
s
, seed length
s
1/2+
o
(1)
.
The previous best PRGs known for these classes used seeds of length bigger than
n
/2 to output
n
bits, and worked only for size
s
=
O
(
n
) [8].
Funder
Institute for Advanced Study
Simons Foundation
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software
Reference37 articles.
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3. N. Alon and J. H. Spencer. 2011. The Probabilistic Method. Wiley. N. Alon and J. H. Spencer. 2011. The Probabilistic Method. Wiley.
4. On a method for obtaining more than quadratic effective lower bounds for the complexity of π-schemes;Andreev A. E.;Moscow Univ. Math. Bull.,1987
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