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Nondeterministic Separations

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Theory and Applications of Models of Computation (TAMC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9076))

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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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Notes

  1. 1.

    We assume that if \(M_i\) needs only \(r < |y|\) bits of advice, then only the first \(r\) bits of \(y\) are used.

References

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Author information

Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, USA

    Lance Fortnow

Authors
  1. Lance Fortnow
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Correspondence to Lance Fortnow .

Editor information

Editors and Affiliations

  1. National University of Singapore, Singapore, Singapore

    Rahul Jain

  2. National University of Singapore, Singapore, Singapore

    Sanjay Jain

  3. National University of Singapore, Singapore, Singapore

    Frank Stephan

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Fortnow, L. (2015). Nondeterministic Separations. In: Jain, R., Jain, S., Stephan, F. (eds) Theory and Applications of Models of Computation. TAMC 2015. Lecture Notes in Computer Science(), vol 9076. Springer, Cham. https://doi.org/10.1007/978-3-319-17142-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-17142-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17141-8

  • Online ISBN: 978-3-319-17142-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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