Hardness Magnification for all Sparse NP Languages
Name
TR19-118.pdf
Description
Accepted version
Size
857.85 KB
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Adobe PDF
Checksum (MD5)
b02e9c41a9dce722b427534e8b205933
Author(s)
Chen, Lijie
Jin, Ce
Williams, R Ryan
Date Issued
2019
Journal
Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Chen, Lijie, Jin, Ce and Williams, R Ryan. 2019. "Hardness Magnification for all Sparse NP Languages." Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS, 2019-November.
Version
Author's final manuscript
Abstract
© 2019 IEEE. In the Minimum Circuit Size Problem (MCSP[s(m)]), we ask if there is a circuit of size s(m) computing a given truth-Table of length n = 2m. Recently, a surprising phenomenon termed as hardness magnification by [Oliveira and Santhanam, FOCS 2018] was discovered for MCSP[s(m)] and the related problem MKtP of computing time-bounded Kolmogorov complexity. In [Oliveira and Santhanam, FOCS 2018], [Oliveira, Pich, and Santhanam, CCC 2019], and [McKay, Murray, and Williams, STOC 2019], it was shown that minor (n{1+eps}-style) lower bounds for MCSP[2o(m)] or MKtP[2o(m)] would imply breakthrough circuit lower bounds such as NP is not in P/poly, NP is not in NC1, or EXP is not in P/poly. We consider the question: What is so special about MCSP and MKtP? Why do they admit this striking phenomenon? One simple property is that all variants of MCSP (and MKtP) considered in prior work are sparse languages. For example, MCSP[s(m)] has 2{O(s(m))} yes-instances of length n=2m, so MCSP[2o(m)] is 2{no(1)}-sparse. We show that there is a hardness magnification phenomenon for all equally-sparse NP languages. Formally, suppose there is an eps > 0 and a language L in NP which is 2{no(1)}-sparse, and L is not in Circuit[n{1+eps}]. Then NP does not have nk-size circuits for all k. We prove analogous theorems for De Morgan formulas, B-2-formulas, branching programs, AC0[6] and TC0 circuits, and more: improving the state of the art in NP lower bounds against any of these models by an eps factor in the exponent would already imply NP lower bounds for all fixed polynomials. In fact, in our proofs it is not necessary to prove a (say) n{1+eps} circuit size lower bound for L: one only has to prove a lower bound against n{1+eps}-Time neps-space deterministic algorithms with neps advice bits. Such lower bounds are well-known for non-sparse problems. Building on our techniques, we also show interesting new hardness magnifications for search-MCSP and search-MKtP (where one must output small circuits or short representations of strings), showing consequences such as Parity-P (or PP, PSPACE, and EXP) is not contained in P/poly (or NC1, AC0[6], or branching programs of polynomial size). For instance, if there is an eps > 0 such that search-MCSP[2{beta m}] does not have De Morgan formulas of size n{3+eps} for all constants beta > 0, then -P ⊄ NC1.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/FOCS.2019.00077
