Information-Based Complexity of Integration in the Randomized and Quantum Computation Model

Author:

Gao Wen Hua1,Duan Li Qin2,Zhou Wei1,Ye Pei Xin3

Affiliation:

1. Beijing Normal University Zhuhai

2. Hangzhou Dianzi University

3. Nankai University

Abstract

In this paper, we investigate the integration of the Hölder-Nikolskii classes in the randomized and quantum computation model. We develop randomized and quantum algorithms for integration of functions from this class and analyze their convergence rates. Comparing our result with the convergence rates in the deterministic setting, we see that quantum computing can reach an exponential speedup over deterministic classical computation and a quadratic speedup over randomized classical computation.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference9 articles.

1. Bakhvalov N. S., On a rate of convergence of indeterministic integration processes within the functional classes , Theory. Probab. Appl., 7(1962), 227.

2. Dubinin V. V., On optimal quadrature formulae for classes of functions with bounded mixed difference, Mat. Zametki, 49(1991), 149-151.

3. Heinrich S., Random approximation in numerical analysis, In K.D. Bierstedt, et al., editor, Functional Analysis: Proceedings of the Essen Conference, Volume 150 of Lect. Notes in pure and appl. Math., (1994), 123-171.

4. S. Heinrich, Quantum integration in Sobolev classes,J. Complexity 19(2003)19-42.

5. S. Heinrich, Quantum summation with an application to integration, J. Complexity 18(2002)1-50.

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