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Adaptivity vs Postselection

We study the following problem: with the power of postselection (classically or quantumly), what is your ability to answer adaptive queries to certain languages? More specifically, for what kind of computational classes $\mathcal{C}$, we have $\mathsf{P}^{\mathcal{C}}$ belongs to $\mathsf{PostBPP}$ and $\mathsf{PostBQP}$? While a complete answer to the above question seems impossible given the development of present computational complexity theory. We study the analogous question in query complexity, which sheds light on the limitation of {\em relativized} methods (the relativization barrier) to the above question. Informally, we show that, for a partial function $f$, if there is no efficient (In the world of query complexity, being efficient means using $O(\operatorname*{polylog}(n))$ time.) {\em small bounded-error} algorithm for $f$ classically or quantumly, then there is no efficient postselection bounded-error algorithm to answer adaptive queries to $f$ classically or quantumly. Our results imply a new proof for the classical oracle separation $\mathsf{P}^{\mathsf{NP}^{\mathcal{O}}} \not\subset \mathsf{PP}^{\mathcal{O}}$. They also lead to a new oracle separation $\mathsf{P}^{

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AuthorshipTopic signalWAdaptivity vs Postselectionpreprint / 2016ALijie ChenResearcherTComputational Complexity1354 works
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Adaptivity vs Postselection

preprint / 2016

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