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On the Computational Complexity of Positive Linear Functionals on \(\mathcal{C}[0;1]\)

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Mathematical Aspects of Computer and Information Sciences (MACIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9582))

Abstract

The Lebesgue integration has been related to polynomial counting complexity in several ways, even when restricted to smooth functions. We prove analogue results for the integration operator associated with the Cantor measure as well as a more general second-order \({{\mathbf {\mathsf{{\#P}}}}} \)-hardness criterion for such operators. We also give a simple criterion for relative polynomial time complexity and obtain a better understanding of the complexity of integration operators using the Lebesgue decomposition theorem.

Supported in part by the Marie Curie International Research Staff Exchange Scheme Fellowship 294962 within the 7th European Community Framework Programme and by the German Research Foundation (DFG) with project Zi 1009/4-1. A SHORT version of this work was presented at CCA 2015.

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Correspondence to Martin Ziegler .

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Férée, H., Ziegler, M. (2016). On the Computational Complexity of Positive Linear Functionals on \(\mathcal{C}[0;1]\) . In: Kotsireas, I., Rump, S., Yap, C. (eds) Mathematical Aspects of Computer and Information Sciences. MACIS 2015. Lecture Notes in Computer Science(), vol 9582. Springer, Cham. https://doi.org/10.1007/978-3-319-32859-1_42

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  • DOI: https://doi.org/10.1007/978-3-319-32859-1_42

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