Block sensitivity ($bs(f)$), certificate complexity ($C(f)$) and fractional certificate complexity ($C^*(f)$) are three fundamental combinatorial measures of complexity of a boolean function $f$. It has long been known that $bs(f) \leq C^{\ast}(f) \leq C(f) =O(bs(f)^2)$. We provide an infinite family of examples for which $C(f)$ grows quadratically in $C^{\ast}(f)$ (and also $bs(f)$) giving optimal separations between these measures. Previously the biggest separation known was $C(f)=C^{\ast}(f)^{\log_{4.5}5}$. We also give a family of examples for which $C^{\ast}(f)=Ω(bs(f)^{3/2})$.
These examples are obtained by composing boolean functions in various ways. Here the composition $f \circ g$ of $f$ with $g$ is obtained by substituting for each variable of $f$ a copy of $g$ on disjoint sets of variables. To construct and analyse these examples we systematically investigate the behaviour under function composition of these measures and also the sensitivity measure $s(f)$. The measures $s(f)$, $C(f)$ and $C^{\ast}(f)$ behave nicely under composition: they are submultiplicative (where measure $m$ is submultiplicative if $m(f \circ g) \leq m(f)m(g)$) with equality holding under some fairly general conditions. The measure $bs(f)$ is qualitatively different: it is not submultiplicative. This qualitative difference was not noticed in the previous literature and we correct some errors that appeared in previous papers. We define the composition limit of a measure $m$ at function $f$, $m^{\lim}(f)$ to be the limit as $k$ grows of $m(f^{(k)})^{1/k}$, where $f^{(k)}$ is the iterated composition of $f$ with itself $k$-times. For any function $f$ we show that $bs^{\lim}(f) = (C^*)^{\lim}(f)$ and characterize $s^{\lim}(f), (C^*)^{\lim}(f)$, and $C^{\lim}(f)$ in terms of the largest eigenvalue of a certain set of $2\times 2$ matrices associated with $f$.
Randomized query complexity of sabotaged and composed functions
我们研究了有界错误随机查询复杂度的合成问题：对于所有的布尔函数f和g，R（f o g）= Omega（R（f）R（g））吗？我们表明，插入一个简单的布尔函数h，其查询复杂度只有Theta（log R（g）），在f和g之间允许我们证明R（f o h o g）= Omega（R（f）R（h）R（g））。我们证明了这一点，使用一个新的下界测量随机查询复杂性，我们称之为随机破坏复杂性，RS（f）。随机破坏复杂度具有几个期望的性质，例如完美合成定理，RS（f o g）>= RS（f）RS（g），以及具有随机查询复杂度的合成定理，R（f o g）= Omega（R（f）RS（g））。它也是全函数的二次紧下界，并且可以二次优于分区界，这是随机查询复杂度的最佳已知一般下界。使用这种技术，我们还表明提升定理的影响，通信复杂性。我们证明了零错误随机化协议的一般提升定理隐含了有界错误协议的一般提升定理。
我们证明下界的复杂性措施，如布尔函数的近似程度和布尔矩阵的近似秩，使用量子参数。我们证明了这些下界使用量子查询算法的组合组测试问题。我们证明了对于任何函数f，计算f的n个副本的OR的近似程度是Ω（sqrt{n}）乘以f的近似程度，这是最优的。在我们的工作之前，没有这样的一般结果，甚至AND函数的OR下限也是在2013年才解决的。然后，我们证明了一个类似的结果，在通信复杂性，显示的对数的近似秩（或更准确地说，近似gamma_2范数）的F：X x Y -> {0，1}增长的一个因素Ω ~（sqrt{n}）时，我们采取的或的n个副本的F，这也是本质上最优的。作为推论，我们给出了Razborov著名的Ω（sqrt{n}）下界的量子通信复杂性的不相交性问题的一个新的证明。最后，我们将这两个结果从与OR函数的组合推广到与任意对称函数的组合，在这种情况下也得到了接近最优的下界。
