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zbMATH Open
Article . 2011
Data sources: zbMATH Open
https://dx.doi.org/10.48550/ar...
Article . 2011
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2022
Data sources: DBLP
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Effective theories for circuits and automata

Authors: Simon DeDeo;

Effective theories for circuits and automata

Abstract

Abstracting an effective theory from a complicated process is central to the study of complexity. Even when the underlying mechanisms are understood, or at least measurable, the presence of dissipation and irreversibility in biological, computational, and social systems makes the problem harder. Here, we demonstrate the construction of effective theories in the presence of both irreversibility and noise, in a dynamical model with underlying feedback. We use the Krohn-Rhodes theorem to show how the composition of underlying mechanisms can lead to innovations in the emergent effective theory. We show how dissipation and irreversibility fundamentally limit the lifetimes of these emergent structures, even though, on short timescales, the group properties may be enriched compared to their noiseless counterparts.

Related Organizations
Keywords

FOS: Computer and information sciences, Formal Languages and Automata Theory (cs.FL), FOS: Physical sciences, Computer Science - Formal Languages and Automata Theory, Formal languages and automata, Quantitative Biology - Quantitative Methods, Nonlinear Sciences - Adaptation and Self-Organizing Systems, FOS: Biological sciences, Analytic circuit theory, Adaptation and Self-Organizing Systems (nlin.AO), Quantitative Methods (q-bio.QM)

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
7
Average
Average
Average
Green
bronze