Prediction and Understanding of Soft-proton Contamination in XMM-Newton: A Machine Learning Approach

@article{id2667,
  author = {Kronberg, Elena A. and Gastaldello, Fabio and Haaland, Stein and Smirnov, Artem and Berrendorf, Max and Ghizzardi, Simona and Kuntz, K. D. and Sivadas, Nithin and Allen, Robert C. and Tiengo, Andrea and Ilie, Raluca and Huang, Yu and Kistler, Lynn},
  doi = {10.3847/1538-4357/abbb8f},
  eid = {89},
  journal = {Astrophysical Journal},
  language = {en},
  note = {Provided by the SAO/NASA Astrophysics Data System},
  number = {2},
  pages = {89},
  title = {Prediction and Understanding of Soft-proton Contamination in XMM-Newton: A Machine Learning Approach},
  url = {https://ui.adsabs.harvard.edu/abs/2020ApJ...903...89K},
  volume = {903},
  year = {2020},
}

%O Journal Article
%A Kronberg, Elena A.
%A Gastaldello, Fabio
%A Haaland, Stein
%A Smirnov, Artem
%A Berrendorf, Max
%A Ghizzardi, Simona
%A Kuntz, K. D.
%A Sivadas, Nithin
%A Allen, Robert C.
%A Tiengo, Andrea
%A Ilie, Raluca
%A Huang, Yu
%A Kistler, Lynn
%R 10.3847/1538-4357/abbb8f
%1 89
%J Astrophysical Journal
%G en
%O Provided by the SAO/NASA Astrophysics Data System
%N 2
%P 89
%T Prediction and Understanding of Soft-proton Contamination in XMM-Newton: A Machine Learning Approach
%U https://ui.adsabs.harvard.edu/abs/2020ApJ...903...89K
%V 903
%D 2020