Laboratoire d'informatique de l'École polytechnique

Talk by Riccardo Gozzi: « Analog characterization of complexity classee »

Speaker: Riccardo Gozzi
Location: Room Philippe Flajolet
Date: Tue, 21 Jun 2022, 11:00-12:00

For a new seminar of the proofs and algorithms pole of LIX, we are happy to welcome Riccardo Gozzi, invited by the AlCo team.

Abstract: In the first part of the presentation I will introduce the concept of analog computation in relation with integrator devices used in the 1940’s to compute simple operations, called differntial analyzers. A description of the theoretical model behind the behaviors of those machine was first provided by Shannon, with his GPAC model which stands for Generable Purpose Analog Computation model. I will describe some of the main modifications that have been later applied in litterature to the model in order to simplify its formulation and improve its computational power. Following this guideline, I will then explain how these modifications led to an equivalence between this model and the setting of computable analysis, meaning that every function that can be computed within the computable analysis framework can also be computed by the GPAC model, and viceversa. During the course of this first, introductory, part of the talk, the motivations at the core of this research will be discussed as well. In the second part of the presentation I will illustrate how, with the correct improvements to the notion of computation of the GPAC model, this particular equivalence can be extended to the case of polynomial time complexity, leading to an equivalence between the well known complexity calss P and a certain class of systems of ODEs. To obtain this result it is required a way to encode and reproduce the behavior of the transiction function of a Turing machine in a continuous setting, keeping bounded the error introduced during this simulation.This second part of the talk will be more quantitative than the first, including more technical details. Finally, in the last part of the presentation, I will briefly mention how the results previuosly showed can be applied to further characterize higher complexity classes, such as EXPTIME or PSPACE, with similar dynamical system.

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