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Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Delgado-Mena, E.'

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[ascl:2002.005] ODUSSEAS: Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes
Antoniadis-Karnavas, A.; Sousa, S. G.; Delgado-Mena, E.; Santos, N. C.; Teixeira, G. D. C.; Neves, V.

ODUSSEAS (Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes) uses machine learning to derive the Teff and [Fe/H] of M dwarf stars by using their optical spectra obtained by different spectrographs with different resolutions. The software uses the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and the machine learning Python package scikit-learn (https://scikit-learn.org/stable/) to predict the stellar parameters.

[ascl:2506.004] TESS-cont: TESS contamination tool
Castro-González, A.; Lillo-Box, J.; Armstrong, D. J.; Acuña, L.; Aguichine, A.; Bourrier, V.; Gandhi, S.; Sousa, S. G.; Delgado-Mena, E.; Moya, A.; Adibekyan, V.; Correia, A. C. M.; Barrado, D.; Damasso, M.; Winn, J. N.; Santos, N. C.; Barkaoui, K.; Barros, S. C. C.; Benkhaldoun, Z.; Bouchy, F.; Briceño, C.; Caldwell, D. A.; Collins, K. A.; Essack, Z.; Ghachoui, M.; Gillon, M.; Hounsell, R.; Jehin, E.; Jenkins, J. M.; Keniger, M. A. F.; Law, N.; Mann, A. W.; Nielsen, L. D.; Pozuelos, F. J.; Schanche, N.; Seager, S.; Tan, T. -G.; Timmermans, M.; Villaseñor, J.; Watkins, C. N.; Ziegler, C.

TESS-cont quantifies the flux fraction coming from nearby stars in the TESS photometric aperture of any observed target. The package identifies the main contaminant Gaia DR2/DR3 sources, quantifies their individual and total flux contributions to the aperture, and determines whether any of these stars could be the origin of the observed transit and variability signals. Written in Python, TESS-cont is based on building the pixel response functions (PRFs) of nearby Gaia sources and computing their flux distributions across the TESS Target Pixel Files (TPFs) or Full Frame Images (FFIs).