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https://dx.doi.org/10.48550/ar...
Article . 2016
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Conference object . 2019
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Physical Computation, P/poly and P/log*

Authors: Richard Whyman;

Physical Computation, P/poly and P/log*

Abstract

In this paper we give a framework for describing how abstract systems can be used to compute if no randomness or error is involved. Using this we describe a class of classical "physical" computation systems whose computational capabilities in polynomial time are equivalent to P/poly. We then extend our framework to describe how measurement and transformation times may vary depending on their input. Finally we describe two classes of classical "physical" computation systems in this new framework whose computational capabilities in polynomial time are equivalent to P/poly and P/log*.

In Proceedings PC 2016, arXiv:1606.06513

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Keywords

FOS: Computer and information sciences, Computer Science - Computational Complexity, Electronic computers. Computer science, QA1-939, QA75.5-76.95, Computational Complexity (cs.CC), Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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gold