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    Quadratically Tight Relations for Randomized Query Complexity

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    Let f:{0,1}n→{0,1}f:\{0,1\}^n \rightarrow \{0,1\} be a Boolean function. The certificate complexity C(f)C(f) is a complexity measure that is quadratically tight for the zero-error randomized query complexity R0(f)R_0(f): C(f)≤R0(f)≤C(f)2C(f) \leq R_0(f) \leq C(f)^2. In this paper we study a new complexity measure that we call expectational certificate complexity EC(f)EC(f), which is also a quadratically tight bound on R0(f)R_0(f): EC(f)≤R0(f)=O(EC(f)2)EC(f) \leq R_0(f) = O(EC(f)^2). We prove that EC(f)≤C(f)≤EC(f)2EC(f) \leq C(f) \leq EC(f)^2 and show that there is a quadratic separation between the two, thus EC(f)EC(f) gives a tighter upper bound for R0(f)R_0(f). The measure is also related to the fractional certificate complexity FC(f)FC(f) as follows: FC(f)≤EC(f)=O(FC(f)3/2)FC(f) \leq EC(f) = O(FC(f)^{3/2}). This also connects to an open question by Aaronson whether FC(f)FC(f) is a quadratically tight bound for R0(f)R_0(f), as EC(f)EC(f) is in fact a relaxation of FC(f)FC(f). In the second part of the work, we upper bound the distributed query complexity Dϵμ(f)D^\mu_\epsilon(f) for product distributions μ\mu by the square of the query corruption bound (corrϵ(f)\mathrm{corr}_\epsilon(f)) which improves upon a result of Harsha, Jain and Radhakrishnan [2015]. A similar statement for communication complexity is open.Comment: 14 page
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