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Measure on small complexity classes, with applications for BPP
Conference paper   Open access

Measure on small complexity classes, with applications for BPP

Eric Allender and Martin Strauss
Annual Symposium on Foundations of Computer Science, 35 (Santa Fe, NM, 11/20/1994–11/22/1994)
10/19/2004

Abstract

Computational complexity
We present a notion of resource-bounded measure for P and other subexponential-time classes. This generalization is based on Lutz's notion of measure, but overcomes the limitations that cause Lutz's definitions to apply only to classes at least as large as E. We present many of the basic properties of this measure, and use it to explore the class of sets that are hard for BPP. Bennett and Gill showed that almost all sets are hard for BPP; Lutz improved this from Lebesgue measure to measure on ESPACE. We use our measure to improve this still further, showing that for all epsilon > 0, almost every set in E_epsilon is hard for BPP, where E_epsilon = U_delta DTIME(2^n^delta) ; which is the best that can be achieved without showing that BPP is properly contained in E. A number of related results are also obtained in this way.
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https://doi.org/10.1109/SFCS.1994.365713View
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