Abstract
A sampling procedure for a distribution P over {0, 1}ℓ is a function C : {0, 1}n → {0, 1}ℓ such that the distribution C(Un) (obtained by applying C on the uniform distribution Un) is the "desired distribution" P. Let n > r ≥ ℓ = nΩ(1). An ∈-nb-PRG (defined by Dubrov and Ishai [2006]) is a function G : {0, 1}r → {0, 1}n such that for every C : {0, 1}n → {0, 1}ℓ in some class of "interesting sampling procedures," C′(Ur) = C(G(Ur)) is ∈-close to C(Un) in statistical distance. We construct poly-time computable nb-PRGs with r = O(ℓ) for poly-size circuits relying on the assumption that there exists β > 0 and a problem L in E = DTIME(2O(n)) such that for every large enough n, nondeterministic circuits of size 2βn that have NP-gates cannot solve L on inputs of length n. This assumption is a scaled nonuniform analog of (the widely believed) EXP ≠ ΣP2, and similar assumptions appear in various contexts in derandomization. Previous nb-PRGs of Dubrov and Ishai have r = Ω(ℓ2) and are based on very strong cryptographic assumptions or, alternatively, on nonstandard assumptions regarding incompressibility of functions on random inputs. When restricting to poly-size circuits C : {0, 1}n → {0, 1}ℓ with Shannon entropy H(C(Un)) ≤ k, for ℓ > k = nΩ(1), our nb-PRGs have r = O(k). The nb-PRGs of Dubrov and Ishai use seed length r = Ω(k2) and require that the probability distribution of C(Un) is efficiently computable. Our nb-PRGs follow from a notion of "conditional PRGs," which may be of independent interest. These are PRGs where G(Ur) remains pseudorandom even when conditioned on a "large" event {A(G(Ur)) = 1}, for an arbitrary poly-size circuit A. A related notion was considered by Shaltiel and Umans [2005] in a different setting, and our proofs use ideas from that paper, as well as ideas of Dubrov and Ishai. We also give an unconditional construction of poly-time computable nb-PRGs for poly(n)-size, depth d circuits C : {0, 1}n → {0, 1}ℓ with r = O(ℓ · logd+O(1)n). This improves upon the previous work of Dubrov and Ishai that has r ≥ ℓ2. This result follows by adapting a recent PRG construction of Trevisan and Xue [2013] to the case of nb-PRGs. We also show that this PRG can be implemented by a uniform family of constant-depth circuits with slightly increased seed length.
| Original language | English |
|---|---|
| Article number | 6 |
| Journal | ACM Transactions on Computation Theory |
| Volume | 9 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2017 |
Bibliographical note
Publisher Copyright:© 2017 ACM.
Keywords
- Hardness versus randomness
- Pseudorandom generators
- Pseudorandomness
- Randomness complexity of sampling
ASJC Scopus subject areas
- Theoretical Computer Science
- Computational Theory and Mathematics
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Pseudorandom generators with optimal seed length for non-boolean poly-size circuits
Artemenko, S. & Shaltiel, R., 2014, STOC 2014 - Proceedings of the 2014 ACM Symposium on Theory of Computing. Association for Computing Machinery, p. 99-108 10 p. (Proceedings of the Annual ACM Symposium on Theory of Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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