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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
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Source code and simulation results: Computing eigenfrequency sensitivities near exceptional points

Authors: Binkowski, Felix; Kullig, Julius; Betz, Fridtjof; Zschiedrich, Lin; Walther, Andrea; Wiersig, Jan; Burger, Sven;

Source code and simulation results: Computing eigenfrequency sensitivities near exceptional points

Abstract

Summary This publication supplements the article "Computing eigenfrequency sensitivities near exceptional points" with tabulated data as well as matlab and python code that enables reproducing the results. The article presents a semi-analytical solution for a simple system that is used to validate a numerical framework. Structure The scripts refer to the figures in the paper as indicated by their names. They reproduce the figures based on data in corresponding files. If the files with numerical results are removed, the matlab scripts reproduce them. With the python script the semi-analytical results can be generated. Requirements JCMsuite (we used version 6.0.10) MATLAB (tested with version R2019b) In order to run the simulations with JCMsuite you must replace corresponding place holders with a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of JCMwave.

Keywords

Sensitivities, Exceptional points, Photonics, Algorithmitc differentiation, Contour integral methods

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citations
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!
0
Average
Average
Average