Physica D: Nonlinear Phenomena
Source Normalized Impact per Paper (SNIP): 1.115
Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 0.929
SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 1.807 (2019)
Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 1.687 (2019)
Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volume 14
Issues: 14 issues
ISSN: 01672789
Editor-in-Chief: Pérez García
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Description
Physica D (Nonlinear Phenomena) publishes research and review articles reporting on theoretical and experimental work, techniques, and ideas that advance the understanding of nonlinear phenomena.
The scope of the journal encompasses mathematical methods for nonlinear systems including: wave motion, pattern formation and collective phenomena in physical, chemical and biological systems; hydrodynamics and turbulence; integrable and Hamiltonian systems; and data-driven dynamical systems. The journal encourages submissions in established and emerging application domains, for example applications of nonlinear science to artificial intelligence, robotics, control theory, complex networks, and social and economic dynamics.