{"paper":{"title":"The CARMENES search for exoplanets around M dwarfs -- A deep learning approach to determine fundamental parameters of target stars","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.SR","authors_text":"A. Bello-Garc\\'ia, A. Gonz\\'alez-Marcos, A. Kaminski, A.P. Hatzes, A. Quirrenbach, A. Reiners, A. Schweitzer, D. Montes, E. Marfil, E. Nagel, E. Solano, F.F. Bauer, H.M. Tabernero, I. Ribas, J.A. Caballero, J.C. Morales, J. Ordieres-Mer\\'e, L.M. Sarro, M. Azzaro, M. Cort\\'es-Contreras, M. K\\\"urster, M. Lafarga, M. Zechmeister, P.J. Amado, S. Dreizler, S.V. Jeffers, Th. Henning, V.J.S. B\\'ejar, V.M. Passegger","submitted_at":"2020-08-03T20:53:17Z","abstract_excerpt":"Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity. With this study, we firstly demonstrate the capability of deep neural networks to precisely recover stellar parameters from a synthetic training set. Secondly, we analyze the application of this method to observed spectra and the impact of the synthet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.01186","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2008.01186/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}