Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, Kanpur 208016, India
Proc Natl Acad Sci U S A. 2019 Apr 23;116(17):8107-8118. doi: 10.1073/pnas.1901272116. Epub 2019 Apr 11.
We show that for the blackbox polynomial identity testing (PIT) problem it suffices to study circuits that depend only on the first extremely few variables. One needs only to consider size-s degree-s circuits that depend on the first [Formula: see text] variables (where c is a constant and composes a logarithm with itself c times). Thus, the hitting-set generator (hsg) manifests a bootstrapping behavior-a partial hsg against very few variables can be efficiently grown to a complete hsg. A Boolean analog, or a pseudorandom generator property of this type, is unheard of. Our idea is to use the partial hsg and its annihilator polynomial to efficiently bootstrap the hsg exponentially w.r.t. variables. This is repeated c times in an efficient way. Pushing the envelope further we show that () a quadratic-time blackbox PIT for 6,913-variate degree-s size-s polynomials will lead to a "near"-complete derandomization of PIT and () a blackbox PIT for n-variate degree-s size-s circuits in [Formula: see text] time, for [Formula: see text], will lead to a near-complete derandomization of PIT (in contrast, [Formula: see text] time is trivial). Our second idea is to study depth-4 circuits that depend on constantly many variables. We show that a polynomial-time computable, [Formula: see text]-degree hsg for trivariate depth-4 circuits bootstraps to a quasipolynomial time hsg for general polydegree circuits and implies a lower bound that is a bit stronger than that of Kabanets and Impagliazzo [Kabanets V, Impagliazzo R (2003) ].
我们证明,对于黑盒多项式恒等测试(PIT)问题,只需要研究仅依赖于前极少数变量的电路。只需要考虑大小为 s 度为 s 的电路,这些电路依赖于前 [公式:见文本] 个变量(其中 c 是一个常数,它自身构成 c 次对数)。因此,命中集生成器(hsg)表现出自举行为——针对极少数变量的部分 hsg 可以有效地生长为完整的 hsg。这种类型的布尔模拟或伪随机生成器属性是前所未闻的。我们的想法是使用部分 hsg 和其消去多项式来有效地针对变量进行 hsg 的指数级自举。这在高效的方式中重复 c 次。更进一步,我们表明 () 对于 6913 变量度为 s 大小为 s 的多项式的二次时间黑盒 PIT 将导致 PIT 的近乎完全去随机化,并且 () 对于 [公式:见文本] 时间的 n 变量度为 s 大小为 s 的电路的黑盒 PIT,将导致 PIT 的近乎完全去随机化(相比之下,[公式:见文本] 时间是微不足道的)。我们的第二个想法是研究依赖于常数多个变量的深度为 4 的电路。我们表明,对于三变量深度为 4 的电路,多项式时间可计算的 [公式:见文本] 度 hsg 可以自举到一般多项式度电路的准多项式时间 hsg,并暗示了一个比 Kabanets 和 Impagliazzo [Kabanets V, Impagliazzo R (2003)] 的下限稍微强一些的下限。