Oracles are subtle but not malicious

S. Aaronson
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引用次数: 34

Abstract

Theoretical computer scientists have been debating the role of oracles since the 1970's. This paper illustrates both that oracles can give us nontrivial insights about the barrier problems in circuit complexity, and that they need not prevent us from trying to solve those problems. First, we give an oracle relative to which PP has linear-sized circuits, by proving a new lower bound for perceptrons and low-degree threshold polynomials. This oracle settles a longstanding open question, and generalizes earlier results due to Beigel and to Buhrman, Fortnow, and Thierauf. More importantly, it implies the first provably nonrelativizing separation of "traditional" complexity classes, as opposed to interactive proof classes such as MIP and MAEXP. For Vinodchandran showed, by a nonrelativizing argument, that PP does not have circuits of size nk for any fixed k. We present an alternative proof of this fact, which shows that PP does not even have quantum circuits of size nk with quantum advice. To our knowledge, this is the first nontrivial lower bound on quantum circuit size. Second, we study a beautiful algorithm of Bshouty et al. for learning Boolean circuits in ZPPNP. We show that the NP queries in this algorithm cannot be parallelized by any relativizing technique, by giving an oracle relative to which ZPPNP par and even BPPNP par have linear-size circuits. On the other hand, we also show that the NP queries could be parallelized if P = NP. Thus, classes such as ZPPNP par inhabit a "twilight zone", where we need to distinguish between relativizing and black-box techniques. Our results on this subject have implications for computational learning theory as well as for the circuit minimization problem
神谕是微妙的,但不是恶意的
自20世纪70年代以来,理论计算机科学家一直在争论预言机的作用。这篇论文说明了神谕可以给我们提供关于电路复杂性中的障碍问题的重要见解,并且它们不需要阻止我们尝试解决这些问题。首先,我们通过证明感知器和低次阈值多项式的新下界,给出了一个相对于PP具有线性大小电路的预测。这个预言解决了一个长期悬而未决的问题,并概括了Beigel和Buhrman, Fortnow和Thierauf的早期结果。更重要的是,它意味着“传统”复杂性类的第一个可证明的非相对分离,而不是交互式证明类,如MIP和MAEXP。因为Vinodchandran通过一个非相对化的论证表明,对于任何固定的k, PP都没有大小为nk的电路。我们提出了另一个证明这一事实的证明,表明PP甚至没有大小为nk的量子电路。据我们所知,这是量子电路尺寸的第一个非平凡下界。其次,我们研究了Bshouty等人在ZPPNP中学习布尔电路的优美算法。我们通过给出ZPPNP参数甚至BPPNP参数具有线性大小电路的一个oracle,证明了该算法中的NP查询不能被任何相对化技术并行化。另一方面,我们也证明了NP查询可以并行化,如果P = NP。因此,像ZPPNP这样的类通常处于“模糊地带”,在这里我们需要区分相对化和黑盒技术。我们在这个问题上的研究结果对计算学习理论和电路最小化问题都有启示
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