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Separations in query complexity using cheat sheets

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abstract

We show a power 2.5 separation between bounded-error randomized and quantum query complexity for a total Boolean function, refuting the widely believed conjecture that the best such separation could only be quadratic (from Grover's algorithm). We also present a total function with a power 4 separation between quantum query complexity and approximate polynomial degree, showing severe limitations on the power of the polynomial method. Finally, we exhibit a total function with a quadratic gap between quantum query complexity and certificate complexity, which is optimal (up to log factors). These separations are shown using a new, general technique that we call the cheat sheet technique. The technique is based on a generic transformation that converts any (possibly partial) function into a new total function with desirable properties for showing separations. The framework also allows many known separations, including some recent breakthrough results of Ambainis et al., to be shown in a unified manner.

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quant-ph 1

years

2019 1

verdicts

ACCEPT 1

representative citing papers

Span Programs and Quantum Space Complexity

quant-ph · 2019-08-12 · accept · novelty 7.0

Unitary quantum space complexity is lower bounded by log approximate span program size, and an explicit function requires (log n)^(2-o(1)) space for monotone phase estimation algorithms.

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  • Span Programs and Quantum Space Complexity quant-ph · 2019-08-12 · accept · none · ref 2 · internal anchor

    Unitary quantum space complexity is lower bounded by log approximate span program size, and an explicit function requires (log n)^(2-o(1)) space for monotone phase estimation algorithms.