@article{DinevaVermaGonzalezManriqueetal.2020,
  author    = {Dineva, Ekaterina Ivanova and Verma, Meetu and Gonzalez Manrique, Sergio Javier and Schwartz, Pavol and Denker, Carsten},
  title     = {Cloud model inversions of strong chromospheric absorption lines using principal component analysis},
  series = {Astronomische Nachrichten = Astronomical notes},
  volume    = {341},
  journal   = {Astronomische Nachrichten = Astronomical notes},
  number    = {1},
  publisher = {Wiley-VCH Verl.},
  address   = {Berlin},
  issn      = {0004-6337},
  doi       = {10.1002/asna.202013652},
  pages     = {64 -- 78},
  year      = {2020},
  abstract  = {High-resolution spectroscopy of strong chromospheric absorption lines delivers nowadays several millions of spectra per observing day, when using fast scanning devices to cover large regions on the solar surface. Therefore, fast and robust inversion schemes are needed to explore the large data volume. Cloud model (CM) inversions of the chromospheric H alpha line are commonly employed to investigate various solar features including filaments, prominences, surges, jets, mottles, and (macro-) spicules. The choice of the CM was governed by its intuitive description of complex chromospheric structures as clouds suspended above the solar surface by magnetic fields. This study is based on observations of active region NOAA 11126 in H alpha, which were obtained November 18-23, 2010 with the echelle spectrograph of the vacuum tower telescope at the Observatorio del Teide, Spain. Principal component analysis reduces the dimensionality of spectra and conditions noise-stripped spectra for CM inversions. Modeled H alpha intensity and contrast profiles as well as CM parameters are collected in a database, which facilitates efficient processing of the observed spectra. Physical maps are computed representing the line-core and continuum intensity, absolute contrast, equivalent width, and Doppler velocities, among others. Noise-free spectra expedite the analysis of bisectors. The data processing is evaluated in the context of "big data," in particular with respect to automatic classification of spectra.},
  language  = {en}
}
@article{IlinPoppenhaegerAlvaradoGomez2022,
  author    = {Ilin, Ekaterina and Poppenh{\"a}ger, Katja and Alvarado-G{\´o}mez, Juli{\´a}n David},
  title     = {Localizing flares to understand stellar magnetic fields and space weather in exo-systems},
  series = {Astronomische Nachrichten = Astronomical notes},
  volume    = {343},
  journal   = {Astronomische Nachrichten = Astronomical notes},
  number    = {4},
  publisher = {Berlin},
  address   = {Wiley-VCH},
  issn      = {1521-3994},
  doi       = {10.1002/asna.20210111},
  pages     = {7},
  year      = {2022},
  abstract  = {Stars are uniform spheres, but only to first order. The way in which stellar rotation and magnetism break this symmetry places important observational constraints on stellar magnetic fields, and factors in the assessment of the impact of stellar activity on exoplanet atmospheres. The spatial distribution of flares on the solar surface is well known to be nonuniform, but elusive on other stars. We briefly review the techniques available to recover the loci of stellar flares, and highlight a new method that enables systematic flare localization directly from optical light curves. We provide an estimate of the number of flares we may be able to localize with the Transiting Exoplanet Survey Satellite, and show that it is consistent with the results obtained from the first full sky scan of the mission. We suggest that nonuniform flare latitude distributions need to be taken into account in accurate assessments of exoplanet habitability.},
  language  = {en}
}