Weak lower bounds on resource-bounded compression imply strong separations of complexity classes

The Minimum Circuit Size Problem (MCSP) asks to determine the minimum size of a circuit computing a given truth table. MCSP is a natural and powerful string compression problem using bounded-size circuits. Recently, Oliveira and Santhanam [FOCS 2018] and Oliveira, Pich, and Santhanam [ECCC 2018] demonstrated a “hardness magnification” phenomenon for MCSP in restricted settings. Letting MCSP[s(n)] be the problem of deciding if a truth table of length 2n has circuit complexity at most s(n), they proved that small (fixed-polynomial) average case circuit/formula lower bounds for MCSP[2√n], or lower bounds for approximating MCSP[2o(n)], would imply major separations such as NP ⊄BPP and NP ⊄P/poly. We strengthen their results in several directions, obtaining magnification results from worst-case lower bounds on exactly computing the search version of generalizations of MCSP[s(n)], which also extend to time-bounded Kolmogorov complexity. In particular, we show that search-MCSP[s(n)] (where we must output a s(n)-size circuit when it exists) admits extremely efficient AC0 circuits and streaming algorithms using Σ3 SAT oracle gates of small fan-in (related to the size s(n) we want to test). For A : {0,1}⋆ → {0,1}, let search-oracleMCSPA[s(n)] be the problem: Given a truth table T of size N=2n, output a Boolean circuit for T of size at most s(n) with AND, OR, NOT, and A-oracle gates (or report that no such circuit exists). Some consequences of our results are: (1) For reasonable s(n) ≥ n and A ∈ PH, if search-MCSPA[s(n)] does not have a 1-pass deterministic poly(s(n))-space streaming algorithm with poly(s(n)) update time, then P ≠ NP. For example, proving that it is impossible to synthesize SAT-oracle circuits of size 2n/log⋆ n with a streaming algorithm on truth tables of length N=2n using Nε update time and Nε space on length-N inputs (for some ε > 0) would already separate P and NP. Note that some extremely simple functions, such as EQUALITY of two strings, already satisfy such lower bounds. (2) If search-MCSP[nc] lacks Õ(N)-size, Õ(1)-depth circuits for a c ≥ 1, then NP ⊄P/poly. (3) If search-MCSP[s(n)] does not have N · poly(s(n))-size, O(logN)-depth circuits, then NP ⊄NC1. Note it is known that MCSP[2√n] does not have formulas of N1.99 size [Hirahara and Santhanam, CCC 2017]. (4) If there is an ε > 0 such that for all c ≥ 1, search-MCSP[2n/c] does not have N1+ε-size O(1/ε)-depth ACC0 circuits, then NP ⊄ACC0. Thus the amplification results of Allender and Koucký [JACM 2010] can extend to problems in NP and beyond. Furthermore, if we substitute ⊕ P, PP, PSPACE, or EXP-complete problems for the oracle A, we obtain separations for those corresponding complexity classes instead of NP. Analogues of the above results hold for time-bounded Kolmogorov complexity as well.

[1]  Richard J. Lipton,et al.  Time-space lower bounds for satisfiability , 2005, JACM.

[2]  Sanjeev Arora,et al.  Computational Complexity: A Modern Approach , 2009 .

[3]  Moritz Müller,et al.  Feasibly constructive proofs of succinct weak circuit lower bounds , 2020, Electron. Colloquium Comput. Complex..

[4]  Avi Wigderson,et al.  Algebrization: A New Barrier in Complexity Theory , 2009, TOCT.

[5]  Boris A. Trakhtenbrot,et al.  A Survey of Russian Approaches to Perebor (Brute-Force Searches) Algorithms , 1984, Annals of the History of Computing.

[6]  Alexander A. Razborov,et al.  Natural Proofs , 1997, J. Comput. Syst. Sci..

[7]  Miklós Ajtai,et al.  A non-linear time lower bound for Boolean branching programs , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[8]  Eric Allender,et al.  Amplifying Lower Bounds by Means of Self-Reducibility , 2008, 2008 23rd Annual IEEE Conference on Computational Complexity.

[9]  Rahul Santhanam,et al.  On the Average-Case Complexity of MCSP and Its Variants , 2017, CCC.

[10]  Richard J. Lipton,et al.  Amplifying circuit lower bounds against polynomial time, with applications , 2013, 2012 IEEE 27th Conference on Computational Complexity.

[11]  Igor Carboni Oliveira,et al.  Hardness magnification near state-of-the-art lower bounds , 2019, Electron. Colloquium Comput. Complex..

[12]  Eric Allender,et al.  The Minimum Oracle Circuit Size Problem , 2016, computational complexity.

[13]  Leonid A. Levin,et al.  Randomness Conservation Inequalities; Information and Independence in Mathematical Theories , 1984, Inf. Control..

[14]  Igor Carboni Oliveira,et al.  Hardness Magnification for Natural Problems , 2018, 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS).

[15]  Aravind Srinivasan,et al.  On the approximability of clique and related maximization problems , 2003, J. Comput. Syst. Sci..

[16]  Miklós Ajtai,et al.  Determinism versus Nondeterminism for Linear Time RAMs with Memory Restrictions , 2002, J. Comput. Syst. Sci..

[17]  Samuel R. Buss,et al.  Limits on Alternation Trading Proofs for Time–Space Lower Bounds , 2012, computational complexity.

[18]  Jin-Yi Cai,et al.  Circuit minimization problem , 2000, STOC '00.

[19]  John M. Hitchcock,et al.  On the NP-Completeness of the Minimum Circuit Size Problem , 2015, FSTTCS.

[20]  Eric Allender,et al.  Power from Random Strings , 2006, SIAM J. Comput..

[21]  Eric Allender,et al.  When Worlds Collide: Derandomization, Lower Bounds, and Kolmogorov Complexity , 2001, FSTTCS.

[22]  Osamu Watanabe,et al.  Limits of Minimum Circuit Size Problem as Oracle , 2016, CCC.

[23]  Michael E. Saks,et al.  Time-Space Tradeoffs for Branching Programs , 2001, J. Comput. Syst. Sci..

[24]  Cody Murray,et al.  On the (Non) NP-Hardness of Computing Circuit Complexity , 2015, Theory Comput..

[25]  Michael E. Saks,et al.  Time-space trade-off lower bounds for randomized computation of decision problems , 2003, JACM.

[26]  Timothy Y. Chow Almost-natural proofs , 2011, J. Comput. Syst. Sci..

[27]  John Gill,et al.  Relativizations of the P =? NP Question , 1975, SIAM J. Comput..

[28]  Igor Carboni Oliveira,et al.  NP-hardness of Minimum Circuit Size Problem for OR-AND-MOD Circuits , 2018, Electron. Colloquium Comput. Complex..

[29]  R. Solovay,et al.  Relativizations of the $\mathcal{P} = ?\mathcal{NP}$ Question , 1975 .

[30]  Ilya Volkovich,et al.  The Power of Natural Properties as Oracles , 2018, Electron. Colloquium Comput. Complex..

[31]  Richard Ryan Williams,et al.  Time-Space Tradeoffs for Counting NP Solutions Modulo Integers , 2007, Twenty-Second Annual IEEE Conference on Computational Complexity (CCC'07).

[32]  Shuichi Hirahara,et al.  Non-Black-Box Worst-Case to Average-Case Reductions within NP , 2018, 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS).

[33]  Eric Allender,et al.  New Insights on the (Non-)Hardness of Circuit Minimization and Related Problems , 2019, MFCS.