0000000000482019

AUTHOR

Seiichiro Tani

showing 3 related works from this author

Average/Worst-Case Gap of Quantum Query Complexities by On-Set Size

2009

This paper considers the query complexity of the functions in the family F_{N,M} of N-variable Boolean functions with onset size M, i.e., the number of inputs for which the function value is 1, where 1<= M <= 2^{N}/2 is assumed without loss of generality because of the symmetry of function values, 0 and 1. Our main results are as follows: (1) There is a super-linear gap between the average-case and worst-case quantum query complexities over F_{N,M} for a certain range of M. (2) There is no super-linear gap between the average-case and worst-case randomized query complexities over F_{N,M} for every M. (3) For every M bounded by a polynomial in N, any function in F_{N,M} has quantum que…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityFOS: Physical sciencesComputational Complexity (cs.CC)Quantum Physics (quant-ph)
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Quantum Query Complexity of Boolean Functions with Small On-Sets

2008

The main objective of this paper is to show that the quantum query complexity Q(f) of an N-bit Boolean function f is bounded by a function of a simple and natural parameter, i.e., M = |{x|f(x) = 1}| or the size of f's on-set. We prove that: (i) For $poly(N)\le M\le 2^{N^d}$ for some constant 0 < d < 1, the upper bound of Q(f) is $O(\sqrt{N\log M / \log N})$. This bound is tight, namely there is a Boolean function f such that $Q(f) = \Omega(\sqrt{N\log M / \log N})$. (ii) For the same range of M, the (also tight) lower bound of Q(f) is $\Omega(\sqrt{N})$. (iii) The average value of Q(f) is bounded from above and below by $Q(f) = O(\log M +\sqrt{N})$ and $Q(f) = \Omega (\log M/\log N+ \sqrt{N…

CombinatoricsDiscrete mathematicsComplexity indexKarp–Lipton theoremBounded functionCircuit minimization for Boolean functionsCircuit complexityUpper and lower boundsPlanarity testingBoolean conjunctive queryMathematics
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The quantum query complexity of certification

2009

We study the quantum query complexity of finding a certificate for a d-regular, k-level balanced NAND formula. Up to logarithmic factors, we show that the query complexity is Theta(d^{(k+1)/2}) for 0-certificates, and Theta(d^{k/2}) for 1-certificates. In particular, this shows that the zero-error quantum query complexity of evaluating such formulas is O(d^{(k+1)/2}) (again neglecting a logarithmic factor). Our lower bound relies on the fact that the quantum adversary method obeys a direct sum theorem.

FOS: Computer and information sciencesDiscrete mathematicsQuantum Physics0209 industrial biotechnologyNuclear and High Energy PhysicsQuantum queryComputer scienceDirect sumFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear Physics0102 computer and information sciences02 engineering and technologyCertificationComputational Complexity (cs.CC)Certificate01 natural sciencesTheoretical Computer ScienceComputer Science - Computational Complexity020901 industrial engineering & automationComputational Theory and Mathematics010201 computation theory & mathematicsQuantum Physics (quant-ph)QuantumMathematical PhysicsQuantum Information and Computation
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