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

MacBride, Conor D.; Jess, David B.; Grant, Samuel D. T.; Khomenko, Elena; Keys, Peter H.; Stangalini, Marco
Bibliographical reference

Philosophical Transactions of the Royal Society of London Series A

Advertised on:
2
2021
Number of authors
6
IAC number of authors
1
Citations
10
Refereed citations
8
Description
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 through single or multiple Voigt fits. Our method allows active and quiescent components present in spectra to be identified and isolated for subsequent study. Lastly, we employ a Ca II 8542 Å spectral imaging dataset as a proof-of-concept study to benchmark the suitability of our code for extracting two-component atmospheric profiles that are commonly present in sunspot chromospheres. Minimisation tests are employed to validate the reliability of the results, achieving median reduced χ2 values equal to 1.03 between the observed and synthesised umbral line profiles
Related projects
Solar Eruption
Numerical Simulation of Astrophysical Processes

Numerical simulation through complex computer codes has been a fundamental tool in physics and technology research for decades. The rapid growth of computing capabilities, coupled with significant advances in numerical mathematics, has made this branch of research accessible to medium-sized research centers, bridging the gap between theoretical and

Daniel Elías
Nóbrega Siverio
Project Image
Solar and Stellar Magnetism

Magnetic fields are at the base of star formation and stellar structure and evolution. When stars are born, magnetic fields brake the rotation during the collapse of the mollecular cloud. In the end of the life of a star, magnetic fields can play a key role in the form of the strong winds that lead to the last stages of stellar evolution. During

Tobías
Felipe García