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Improved Quantum Query Complexity on Easier Inputs
Noel T. Anderson (Middlebury College), Jay-U Chung (Middlebury College), Shelby Kimmel (Middlebury College), Da-Yeon Koh (Williams College), Xiaohan Ye (Middlebury College, Brown University)
Abstract: Quantum span program algorithms for function evaluation sometimes have reduced query complexity when promised that the input has a certain structure. We design a modified span program algorithm to show these improvements persist even without a promise ahead of time, and we extend this approach to the more general problem of state conversion. As an application, we prove exponential and superpolynomial quantum advantages in average query complexity for several search problems, generalizing Montanaro's Search with Advice [Montanaro, TQC 2010].