Accurately constraining velocity information from spectral imaging observations using machine learning techniques

@article{MacBride2020AccuratelyCV,
  title={Accurately constraining velocity information from spectral imaging observations using machine learning techniques},
  author={C. D. MacBride and D. Jess and S. Grant and E. Khomenko and P. Keys and M. Stangalini},
  journal={Philosophical Transactions of the Royal Society A},
  year={2020},
  volume={379}
}
Determining accurate plasma Doppler (line-of-sight) velocities from spectroscopic measurements is a challenging endeavour, especially when weak chromospheric absorption lines are often rapidly evolving and, hence, contain multiple spectral components in their constituent line profiles. Here, we present a novel method that employs machine learning techniques to identify the underlying components present within observed spectral lines, before subsequently constraining the constituent profiles… Expand

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