Probabilistic Complexity Classes through Semantics

Thomas Seiller

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arXiv · 2002.00009

Probabilistic Complexity Classes through Semantics

Thomas Seiller

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Abstract

In a recent paper, the author has shown how Interaction Graphs models for linear logic can be used to obtain implicit characterisations of non-deterministic complexity classes. In this paper, we show how this semantic approach to Implicit Complexity Theory (ICC) can be used to characterise deterministic and probabilistic models of computation. In doing so, we obtain correspondences between group actions and both deterministic and probabilistic hierarchies of complexity classes. As a particular case, we provide the first implicit characterisations of the classes PLogspace (un-bounded error probabilistic logarithmic space) and PPtime (unbounded error probabilistic polynomial time)

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BibTeX RIS

Thomas Seiller. 2020-01-31. Probabilistic Complexity Classes through Semantics. https://arxiv.org/abs/2002.00009

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