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