Data for "Exploration of the parameter space of quasisymmetric stellarator vacuum fields through adjoint optimisation"

Nies, Richard ; Paul, Elizabeth ; Panici, Dario ; Hudson, Stuart ; Bhattacharjee, Amitava
Issue date: 2024
Rights:
 Creative Commons Attribution 4.0 International (CC BY)
Cite as:
Nies, Richard, Paul, Elizabeth, Panici, Dario, Hudson, Stuart, & Bhattacharjee, Amitava. (2024). Data for "Exploration of the parameter space of quasisymmetric stellarator vacuum fields through adjoint optimisation" [Data set]. Princeton Plasma Physics Laboratory, Princeton University. https://doi.org/10.34770/rt5a-sy08
@electronic{nies_richard_2024,
  author      = {Nies, Richard and
                Paul, Elizabeth and
                Panici, Dario and
                Hudson, Stuart and
                Bhattacharjee, Amitava},
  title       = {{Data for "Exploration of the parameter s
                pace of quasisymmetric stellarator vacuu
                m fields through adjoint optimisation"}},
  publisher   = {{Princeton Plasma Physics Laboratory, Pri
                nceton University}},
  year        = 2024,
  url         = {https://doi.org/10.34770/rt5a-sy08}
}
Description:

This dataset contains the DESC input files with the boundary coefficients of the optimised stellarator configurations presented in the accompanying paper 'Exploration of the parameter space of quasisymmetric stellarator vacuum fields through adjoint optimisation’.

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More about this record
Authors Nies, Richard (Princeton Plasma Physics Laboratory)
Paul, Elizabeth (Princeton Plasma Physics Laboratory)
Panici, Dario (Princeton University)
Hudson, Stuart (Princeton Plasma Physics Laboratory)
Bhattacharjee, Amitava (Princeton Plasma Physics Laboratory)
Domains Natural Sciences
Communities Princeton Plasma Physics Laboratory
Subcommunities Theory
Issue date 2024
Date Created 2024-01-01
Date Modified 2024-03-28
URI https://doi.org/10.34770/rt5a-sy08
URI http://arks.princeton.edu/ark:/88435/dsp01m326m505b
Publisher Princeton Plasma Physics Laboratory, Princeton University
Type Dataset
Funders United States Department of Energy, DE-AC02-09CH11466
United States Department of Energy, DE-SC0016072
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