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arXiv quant-ph/0501057quant-ph
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量子对抗方法与经典公式大小下界

The quantum adversary method and classical formula size lower bounds

Sophie Laplante, Troy Lee, Mario Szegedy

摘要:

我们引入了布尔函数的两个新的复杂性度量,或者更一般地,对于f:S->T形式的函数。我们称这些度量为sumPI和maxPI。数量sumPI已经通过所谓的量子对抗方法[Amb 02,Amb 03,BSS 03,Zha 04,LM 04]对量子查询复杂度下限的一系列研究而出现,最终在[SS 04]中实现了这些不同的公式实际上是等价的。鉴于sumPI原来是这样一个强大的不变量的功能,我们开始研究这个数量本身,并看到它也有应用到经典的复杂性理论。作为一个令人惊讶的应用,我们证明了sumPI^2(f)是公式大小的下界,甚至在常数乘法因子下,是f的概率公式大小的下界。我们证明了文献中的几个公式大小下界,特别是Khrapchenko及其扩展[Khr 71,Kou 93],包括[Has 98]的一个关键引理,实际上是我们方法的特例。我们引入的第二个量maxPI(f)总是至少和sumPI(f)一样大,并且是从sumPI导出的,使得maxPI^2(f)仍然是公式大小的下限。虽然sumPI(f)始终是f的量子查询复杂度的下限,但对于maxPI(f)通常情况并非如此。sumPI(f)的一个强大优势是它具有原始和对偶特征,因此相对容易给出函数的sumPI复杂度的上下界。为了证明这一点,我们看几个具体的例子,三个函数:递归多数三,由Ambainis定义的函数,和碰撞问题。

英文摘要:

We introduce two new complexity measures for Boolean functions, or more generally for functions of the form f:S->T. We call these measures sumPI and maxPI. The quantity sumPI has been emerging through a line of research on quantum query complexity lower bounds via the so-called quantum adversary method [Amb02, Amb03, BSS03, Zha04, LM04], culminating in [SS04] with the realization that these many different formulations are in fact equivalent. Given that sumPI turns out to be such a robust invariant of a function, we begin to investigate this quantity in its own right and see that it also has applications to classical complexity theory. As a surprising application we show that sumPI^2(f) is a lower bound on the formula size, and even, up to a constant multiplicative factor, the probabilistic formula size of f. We show that several formula size lower bounds in the literature, specifically Khrapchenko and its extensions [Khr71, Kou93], including a key lemma of [Has98], are in fact special cases of our method. The second quantity we introduce, maxPI(f), is always at least as large as sumPI(f), and is derived from sumPI in such a way that maxPI^2(f) remains a lower bound on formula size. While sumPI(f) is always a lower bound on the quantum query complexity of f, this is not the case in general for maxPI(f). A strong advantage of sumPI(f) is that it has both primal and dual characterizations, and thus it is relatively easy to give both upper and lower bounds on the sumPI complexity of functions. To demonstrate this, we look at a few concrete examples, for three functions: recursive majority of three, a function defined by Ambainis, and the collision problem.

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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