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Nondeterministic Separations

  • Lance FortnowEmail author
Conference paper
  • 558 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9076)

Abstract

We survey recent research on the power of nondeterministic computation and how to use nondeterminism to get new separations of complexity classes. Results include separating \(\mathsf{NEXP}\) from \(\mathsf{NP}\) with limited advice, a new proof of the nondeterministic time hierarchy and a surprising relativized world where \(\mathsf{NP}\) is as powerful as \(\mathsf{NEXP}\) infinitely often.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Georgia Institute of TechnologyAtlantaUSA

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