Literature DB >> 14995857

Computational irreducibility and the predictability of complex physical systems.

Navot Israeli1, Nigel Goldenfeld.   

Abstract

Using elementary cellular automata (CA) as an example, we show how to coarse grain CA in all classes of Wolfram's classification. We find that computationally irreducible physical processes can be predictable and even computationally reducible at a coarse-grained level of description. The resulting coarse-grained CA which we construct emulate the large-scale behavior of the original systems without accounting for small-scale details. At least one of the CA that can be coarse grained is irreducible and known to be a universal Turing machine.

Year:  2004        PMID: 14995857     DOI: 10.1103/PhysRevLett.92.074105

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  4 in total

1.  Generalized logistic growth modeling of the COVID-19 outbreak: comparing the dynamics in the 29 provinces in China and in the rest of the world.

Authors:  Ke Wu; Didier Darcet; Qian Wang; Didier Sornette
Journal:  Nonlinear Dyn       Date:  2020-08-19       Impact factor: 5.022

2.  Interpreting, analysing and modelling COVID-19 mortality data.

Authors:  Didier Sornette; Euan Mearns; Michael Schatz; Ke Wu; Didier Darcet
Journal:  Nonlinear Dyn       Date:  2020-10-01       Impact factor: 5.022

3.  Predicting financial market crashes using ghost singularities.

Authors:  Damian Smug; Peter Ashwin; Didier Sornette
Journal:  PLoS One       Date:  2018-03-29       Impact factor: 3.240

4.  Social distancing mediated generalized model to predict epidemic spread of COVID-19.

Authors:  Kashif Ammar Yasir; Wu-Ming Liu
Journal:  Nonlinear Dyn       Date:  2021-04-11       Impact factor: 5.022

  4 in total

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