Searching for codes credited to 'Ribas, I.'
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[ascl:2006.011]
SERVAL: SpEctrum Radial Velocity AnaLyser
Zechmeister, M.;
Reiners, A.;
Amado, P. J.;
Azzaro, M.;
Bauer, F. F.;
Béjar, V. J. S.;
Caballero, J. A.;
Guenther, E. W.;
Hagen, H. -J.;
Jeffers, S. V.;
Kaminski, A.;
Kürster, M.;
Launhardt, R.;
Montes, D.;
Morales, J. C.;
Quirrenbach, A.;
Reffert, S.;
Ribas, I.;
Seifert, W.;
Tal-Or, L. Wolthoff, V.
SERVAL calculates radial velocities (RVs) from stellar spectra. The code uses least-squares fitting algorithms to derive the RVs and additional spectral diagnostics. Forward modeling in pixel space is used to properly weight pixel errors, and the stellar templates are reconstructed from the observations themselves to make optimal use of the RV information inherent in the stellar spectra.
[ascl:2312.034]
pycheops: Light curve analysis for ESA CHEOPS data
Maxted, P. F. L.;
Ehrenreich, D.;
Wilson, T. G.;
Alibert, Y.;
Cameron, A. Collier;
Hoyer, S.;
Sousa, S. G.;
Olofsson, G.;
Bekkelien, A.;
Deline, A.;
Delrez, L.;
Bonfanti, A.;
Borsato, L.;
Alonso, R.;
Anglada Escudé, G.;
Barrado, D.;
Barros, S. C. C.;
Baumjohann, W.;
Beck, M.;
Beck, T.;
Benz, W.;
Billot, N.;
Biondi, F.;
Bonfils, X.;
Brandeker, A.;
Broeg, C.;
Bárczy, T.;
Cabrera, J.;
Charnoz, S.;
Corral Van Damme, C.;
Csizmadia, Sz;
Davies, M. B.;
Deleuil, M.;
Demangeon, O. D. S.;
Demory, B. -O.;
Erikson, A.;
Florén, H. G.;
Fortier, A.;
Fossati, L.;
Fridlund, M.;
Futyan, D.;
Gandolfi, D.;
Gillon, M.;
Guedel, M.;
Guterman, P.;
Heng, K.;
Isaak, K. G.;
Kiss, L.;
Laskar, J.;
Lecavelier des Etangs, A.;
Lendl, M.;
Lovis, C.;
Magrin, D.;
Nascimbeni, V.;
Ottensamer, R.;
Pagano, I.;
Pallé, E.;
Peter, G.;
Piotto, G.;
Pollacco, D.;
Pozuelos, F. J.;
Queloz, D.;
Ragazzoni, R.;
Rando, N.;
Rauer, H.;
Reimers, C.;
Ribas, I.;
Salmon, S.;
Santos, N. C.;
Scandariato, G.;
Simon, A. E.;
Smith, A. M. S.;
Steller, M.;
Swayne, M. I.;
Szabó, Gy M.;
Ségransan, D.;
Thomas, N.;
Udry, S.;
Van Grootel, V.;
Walton, N. A.
pycheops analyzes CHEOPS light curve data. The models in the package can also be applied to other types of data. pycheops includes a "cook book" and examples; in addition, it provides a command-line tool that aids in the preparation of observing requests for CHEOPS observers.