Vector field divergence of predictive model output as indication of phase transitions

Schäfer, Frank and Lörch, Niels. (2019) Vector field divergence of predictive model output as indication of phase transitions. Physical review E, 99 (6). 062107.

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Official URL: https://edoc.unibas.ch/74546/

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We introduce an alternative method to identify phase boundaries in physical systems. It is based on training a predictive model such as a neural network to infer a physical system`s parameters from its state. The deviation of the inferred parameters from the underlying correct parameters will be most susceptible and diverge maximally in the vicinity of phase boundaries. Therefore, peaks in the vector field divergence of the model`s predictions are used as indication of phase transitions. Our method is applicable for phase diagrams of arbitrary parameter dimension and without prior information about the phases. Application to both the two-dimensional Ising model and the dissipative Kuramoto-Hopf model show promising results.
Faculties and Departments:05 Faculty of Science > Departement Physik > Physik > Theoretische Physik (Bruder)
UniBasel Contributors:Lörch, Niels and Schäfer, Frank
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:American Physical Society
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:16 Apr 2020 13:48
Deposited On:16 Apr 2020 13:48

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