SIMBAD references

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.