Preparation for an unsupervised massive analysis of SPHERE high-contrast data with PACO

We aim at searching for exoplanets on the whole ESO/VLT-SPHERE archive with improved and unsupervised data analysis algorithm that could allow to detect massive giant planets 5 au. To prepare, test optimize our approach, we gathered a sample of twenty four solar-type stars observed SPHERE using angular spectral differential imaging modes. use PACO, new generation recently developed, has been shown outperform classical methods. also improve pre-reduction pipeline, outputs PACO enhance detection performance. develop custom built prior libraries capability ASDI mode both IRDIS IFS. Compared previous works conducted more algorithms than contrast limits derived are reliable significantly better, especially short separations where gain by factor ten is obtained between 0.2 0.5 arcsec. Under good observing conditions, down MJup, orbiting au be detected around within 60 parsec. identified two exoplanet candidates require follow-up common proper motion. In this work, demonstrated small benefits in terms achievable control confidence levels. Besides, have developed tools take full quantity total error budget estimated astrometry photometry. This work paves way towards an end-to-end, homogeneous, re-reduction archival direct surveys quest exoJupiters.