A novel framework for semi-Bayesian radial velocities through template matching

Context. The ability to detect and characterise an increasing variety of exoplanets has been made possible by the continuous development stable, high-resolution spectrographs Doppler radial velocity (RV) method. cross-correlation function (CCF) method is one traditional approaches used derive RVs. More recently, template matching introduced as advantageous alternative for M-dwarf stars. Aims. We describe a new implementation technique stellar RV estimation within semi-Bayesian framework, providing more statistically principled characterisation measurements associated uncertainties. This methodology, named Semi-Bayesian Approach RVs with Template matching, S-BART, can currently be applied HARPS ESPRESSO data. first validate its performance respect other pipelines using then apply S-BART observations, comparing scatter uncertainty derived time series those obtained CCF leave full analysis planetary activity signals present in considered datasets future work. Methods. In context common shift assumed difference between each spectral order given spectrum built from available observations. Posterior probability distributions are relative Laplace approximation, after marginalization continuum. also implemented, validation purposes, approach, where estimated individually final estimate calculated weighted average individual orders. Results. application our template-based methods archival observations Barnard’s star allowed us against methods. Although we find similar results, standard deviation smaller than that HARPS-TERRA SERVAL pipelines. believe this due differences construction handling telluric features. After validating it 33 GTO targets, evaluating implemented ESO’s official pipeline. decrease median ~10 ~4% M- K-type stars, respectively. Our framework yields precise estimates method, particular case M-type stars achieves ~15 cm s −1 over 309 16 targets. Further, same data nightly zero point (NZP) instrument, finding NZP below ~0.7 m . Given includes variability, photon noise, potential signals, should taken upper limit on precision attainable