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arXiv 2205.02168cs.CC
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证明复杂性与 TFNP 中的分离

Separations in Proof Complexity and TFNP

Mika Göös, Alexandros Hollender, Siddhartha Jain, Gilbert Maystre, William Pires, Robert Robere, Ran Tao

AI总结:

本文证明一元系数 SA 无法高效模拟 Resolution、NS 无法模拟 Reversible Resolution,并据此刻画多个 TFNP 类,给出经典 TFNP 类间黑盒关系的完整图景。

摘要:

众所周知,Resolution 证明可以由 Sherali-Adams(SA)证明高效模拟。然而,我们证明任何此类模拟都必须利用巨大的系数:当系数以一元形式书写时,Resolution 无法被 SA 高效模拟。我们还证明,Reversible Resolution(MaxSAT Resolution 的一个变体)无法被 Nullstellensatz(NS)高效模拟。这些结果对全 NP 搜索问题产生了影响。首先,我们分别通过 unary-SA、unary-NS 和 Reversible Resolution 刻画类 PPADS、PPAD、SOPL。其次,我们证明,相对于一个预言机,PLS 不包含于 PPP,SOPL 不包含于 PPA,且 EOPL 不包含于 UEOPL。特别地,结合先前工作,这给出了 1990 年代引入的所有经典 TFNP 类之间黑盒关系的完整图景。

英文摘要:

It is well-known that Resolution proofs can be efficiently simulated by Sherali-Adams (SA) proofs. We show, however, that any such simulation needs to exploit huge coefficients: Resolution cannot be efficiently simulated by SA when the coefficients are written in unary. We also show that Reversible Resolution (a variant of MaxSAT Resolution) cannot be efficiently simulated by Nullstellensatz (NS). These results have consequences for total NP search problems. First, we characterise the classes PPADS, PPAD, SOPL by unary-SA, unary-NS, and Reversible Resolution, respectively. Second, we show that, relative to an oracle, PLS $\not\subseteq$ PPP, SOPL $\not\subseteq$ PPA, and EOPL $\not\subseteq$ UEOPL. In particular, together with prior work, this gives a complete picture of the black-box relationships between all classical TFNP classes introduced in the 1990s.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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