X-SHYNE: X-Shooter spectra of young exoplanet analogs

II. Presentation and analysis of the full library^★

¹ NASA-Goddard Space Flight Center, Greenbelt, MD 20771, USA
² Instituto de Estudios Astrofísicos, Facultad de Ingeniería y Ciencias, Uni. Diego Portales, Av. Ejército 441, Santiago, Chile
³ Millennium Nucleus on Young Exoplanets and their Moons (YEMS), Santiago, Chile
⁴ Univ. Grenoble Alpes, CNRS, IPAG, 38000 Grenoble, France
⁵ Max-Planck-Institut für Astronomie, Königstuhl 17, 69117 Heidelberg, Germany
⁶ Laboratoire Lagrange, Université Cote d’Azur, CNRS, Observatoire de la Cote d’Azur, 06304 Nice, France
⁷ Maison de la Simulation, CEA, CNRS, Univ. Paris-Sud, UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
⁸ Department of Astronomy, University of Texas at Austin, Austin, TX, USA
⁹ LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Univ. Paris Diderot, Sorbonne Paris Cité, 5 place Jules Janssen, 92195 Meudon, France
¹⁰ Department of Astrophysics, American Museum of Natural History, Central Park West at 79th Street, NY 10024, USA
¹¹ Planétarium de Montréal, Espace pour la Vie, 4801 av. Pierre-de Coubertin, Montréal, Québec, Canada
¹² Trottier Institute for Research on Exoplanets, Université de Montréal, Département de Physique, C.P. 6128 Succ. Centre-ville, Montréal, QC H3C 3J7, Canada
¹³ Aix Marseille Univ, CNRS, CNES, LAM, Marseille, France
¹⁴ European Southern Observatory, Karl Schwarzschild-Straße 2, D-85748 Garching bei München, Germany
¹⁵ Institute for Astronomy The University of Edinburgh Royal Observatory Blackford Hill Edinburgh EH9 3HJ UK
¹⁶ Department of Astronomy and Carl Sagan Institute, Cornell University, 122 Sciences Drive, Ithaca, NY 14853, USA
¹⁷ Astrophysics Group, School of Physics and Astronomy, University of Exeter, Exeter EX4 4QL, UK
¹⁸ AURA for the European Space Agency (ESA), ESA Office, Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 USA
¹⁹ Centro de Astrofísica y Tecnologías Afines (CATA), Casilla 36-D, Santiago, Chile
²⁰ Observatoire de Genève, Département d’Astronomie, Université de Genève, Chemin Pegasi 51b, 1290 Versoix, Switzerland
²¹ Institute for Astronomy, University of Hawai’i at Mānoa, 2680 Woodlawn Drive, Honolulu, HI 96822, USA
²² Department of Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA
²³ Division of Space Research and Planetary Sciences, Physics Institute, University of Bern, Gesellschaftsstr. 6, 3012 Bern, Switzerland
²⁴ Center for Space and Habitability, University of Bern, Gesellschaftsstr. 6, 3012 Bern, Switzerland
²⁵ Fakultät für Physik, Universität Duisburg-Essen, Lotharstraße 1, 47057 Duisburg, Germany
²⁶ Departamento de Astronomía, Universidad de Chile, Camino el Observatorio 1515, Las Condes, Santiago, Chile
²⁷ Department of Astronomy & Astrophysics, University of California, Santa Cruz, CA 95064, USA
²⁸ Department of Physics & Astronomy, University of Rochester, Rochester, NY 14627, USA

^★★ Corresponding author: simon.petrus.pro@gmail.com

Received: 1 April 2025
Accepted: 30 May 2025

Abstract

Characterizing exoplanets’ spectra is a crucial step in understanding the chemical and physical processes shaping their atmospheres and constraining their formation and evolutionary history. The X-SHYNE library is a homogeneous sample of 43 medium-resolution (R_λ ~ 8000) infrared (0.3–2.5 μm) spectra of young (<500 Myr), low-mass (<20 M_Jup), and cold (T_eff ~600–2000 K) isolated brown dwarfs and wide-separation companions observed with the VLT/X-Shooter instrument. To characterize our targets, we performed a global comparative analysis. We first applied a semiempirical approach. By refining their age and bolometric luminosity, we derived key atmospheric and physical properties, such as T_eff, mass, surface gravity (g), and radius, using the evolutionary model COND03. These results were then compared with the results from a synthetic analysis based on three self-consistent atmospheric models: the cloudy models Exo-REM and Sonora Diamondback, and the cloudless model ATMO. To compare our spectra with these grids we used the Bayesian inference code ForMoSA. We found similar L_bol estimates between both approaches, but an underestimated T_eff from the cloudy models, likely due to a lack of absorbers that could dominate the J and H bands of early L. We also observed a discrepancy in the log(g) estimates, which are dispersed between 3.5 and 5.5 dex for mid-L objects. We interpret this as a bias caused by a range of rotational velocities leading to cloud migration toward equatorial latitudes, combined with a variety of viewing angles that result in different observed atmospheric properties (cloud column densities, atmospheric pressures, etc.). This interpretation is supported by the correlation of the color anomaly Δ(J–K) of each object with log(g) and the parameter f_sed that drives the sedimentation of the clouds. Finally, while providing robust estimates of [M/H] and C/O for individual objects remains challenging, the X-SHYNE library globally suggests solar values that are consistent with a formation via stellar formation mechanisms. This study highlights the strength of homogeneous datasets in performing comparative analyses, reducing the impact of systematics, and ensuring robust conclusions while avoiding overinterpretation.