Constraining nearby substellar companion architectures using High Contrast Imaging, Radial Velocity and Astrometry data

Nearby stars offer prime opportunities for exoplanet discovery and characterization through various detection methods. By combining HCI, RV, and astrometry, it is possible to better constrain the presence of substellar companions, as each method probes different regions of their parameter space. A detailed census of planets around nearby stars is essential to guide the selection of targets for future space missions seeking to identify Earth-like planets and potentially habitable worlds. In addition, the detection and characterisation of giant planets and brown dwarfs is crucial for understanding the formation and evolution of planetary systems. We aim to constrain the possible presence of substellar companions for 7 nearby M-dwarf stars using a combination of new SPHERE/H2 HCI and archival RV and astrometric data. We investigate how combining these techniques improves the detection constraints for giant planets and brown dwarfs compared to using each method individually. For each star and each data set, we compute the mass limits as a function of semi-major axis or projected separation using standard techniques. We then use a Monte Carlo approach to assess the completeness of the companion mass / semi-major axis parameter space probed by the combination of the three methods, as well as by the three methods independently. Our combined approach significantly increases the fraction of detectable companions. Although no new companion was detected, we could place stronger constraints on potential substellar companions. The combination of HCI, RV and astrometry provides significant improvements in the detection of substellar companions over a wider parameter space. Applying this approach to larger samples and lower-mass companions will help constraining the search space for future space missions aimed at finding potentially habitable or even inhabited planets.