{"paper":{"title":"A systematic bias in template-based RV extraction algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","astro-ph.SR"],"primary_cat":"astro-ph.EP","authors_text":"A. Castro-Gonz\\'alez, Andr\\'e M. Silva, A. R. Costa Silva, A. Sozzetti, A. Su\\'arez Mascare\\~no, B. Lavie, B. Wehbe, C. J. A. P. Martins, D. F. M. Folha, \\'E. Artigau, E. A. S. Cristo, E. Palle, F. Pepe, H. M. Tabernero, J. H. C. Martins, J. I. Gonz\\'alez Hern\\'andez, J. Lillo-Box, J. P. Faria, J. Rodrigues, K. Al Moulla, N. C. Santos, N. J. Nunes, O. D. S. Demangeon, P. Di Marcantonio, P. Figueira, P. T. P. Viana, S. Cristiani, S. G. Sousa, T. Azevedo Silva, T. L. Campante, T. Schmidt, X. Delfosse, X. Dumusque","submitted_at":"2025-06-29T14:34:48Z","abstract_excerpt":"In this paper we identify and explore a previously unidentified, multi meter-per-second, systematic correlation between time and RVs inferred through TM and LBL methods. We evaluate the influence of the data-driven stellar template in the RV bias and hypothesize on the possible sources of this effect. We first use the s-BART pipeline to extract RVs from three different datasets gathered over four nights of ESPRESSO and HARPS observations. Then, we demonstrate that the effect can be recovered on a larger sample of 19 targets, totaling 4124 ESPRESSO observations spread throughout 38 nights. We a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.23261","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/2506.23261/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"}