The SPHERE infrared survey for exoplanets (SHINE)

IV. Complete observations, data reduction and analysis, detection performances, and final results^★

¹ LESIA, Observatoire de Paris, Université PSL, CNRS, Université Paris Cité, Sorbonne Université, 5 place Jules Janssen, 92195 Meudon, France
² Univ. Grenoble Alpes, CNRS-INSU, Institut de Planetologie et d’Astrophysique de Grenoble (IPAG) UMR 5274, Grenoble 38041, France
³ INAF – Osservatorio Astronomico di Padova, Vicolo della Osservatorio 5, 35122 Padova, Italy
⁴ CRAL, CNRS, Université Lyon 1,Université de Lyon, ENS, 9 avenue Charles Andre, 69561 Saint Genis Laval, France
⁵ Université Côte d’Azur, OCA, CNRS, Lagrange, 96 Bd de l’Observatoire, 06300 Nice, France
⁶ Aix Marseille Univ, CNRS, CNES, LAM, Marseille, France
⁷ Instituto de Estudios Astrofísicos, Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército Libertador 441, Santiago, Chile
⁸ Millennium Nucleus on Young Exoplanets and their Moons (YEMS), Santiago, Chile
⁹ Center for Space and Habitability, University of Bern, 3012 Bern, Switzerland
¹⁰ Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA
¹¹ Institute for Particle Physics and Astrophysics, ETH Zurich, Wolfgang-Pauli-Strasse 27, 8093 Zurich, Switzerland
¹² Institute for Astronomy, University of Edinburgh, Edinburgh EH9 3HJ, UK
¹³ Max Planck Institute for Astronomy, Königstuhl 17, 69117 Heidelberg, Germany
¹⁴ Fakultät für Physik, Universität Duisburg-Essen, Lotharstraße 1, 47057 Duisburg, Germany
¹⁵ Department of Astronomy, Stockholm University, 10691 Stockholm, Sweden
¹⁶ INAF – Catania Astrophysical Observatory, via S. Sofia 78, 95123 Catania, Italy
¹⁷ Univ. de Toulouse, CNRS, IRAP, 14 avenue Belin, 31400 Toulouse, France
¹⁸ ONERA (Office National dEtudes et de Recherches Arospatiales), B.P. 72, 92322 Chatillon, France
¹⁹ European Southern Observatory (ESO), Karl-Schwarzschild-Str. 2, 85748 Garching, Germany
²⁰ Geneva Observatory, University of Geneva, Chemin des Mailettes 51, 1290 Versoix, Switzerland
²¹ Anton Pannekoek Institute for Astronomy, Science Park 9, 1098 XH Amsterdam, The Netherlands
²² Leiden Observatory, Leiden University, PO Box 9513, 2300 RA Leiden, The Netherlands
²³ INAF – Osservatorio Astronomico di Capodimonte, Salita Moiariello 16, 80131 Napoli, Italy
²⁴ European Southern Observatory, Alonso de Còrdova 3107, Vitacura, Casilla 19001, Santiago, Chile
²⁵ Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA Instituto de Física y Astronomía, Facultad de Ciencias, Universidad de Valparaíso, Av. Gran Bretaña 1111, Valparaíso, Chile
²⁶ NOVA/UVA, Northern Virginia, USA
²⁷ Université Grenoble Alpes, CNRS, Observatoire des Sciences de l’Univers de Grenoble (OSUG), Grenoble, France
²⁸ School of Natural Sciences, Center for Astronomy, University of Galway, Galway H91 CF50, Ireland

^★★ Corresponding author: antoine.chomez@obspm.fr

Received: 1 August 2024
Accepted: 13 January 2025

Abstract

Context. Over the past decade, large surveys with state-of-the-art planet-finder instruments such as Spectro-Polarimetric High-contrast Exoplanet REsearch on board Very Large Telescope (SPHERE@VLT), coupled with coronagraphic devices and extreme adaptive optics (AO) systems, have unveiled around 20 planetary mass companions at a semi-major axis greater than 10 astronomical units (au). Since direct imaging is the only detection technique with the ability to probe this outer region of planetary systems, the SPHERE infrared survey for exoplanets (SHINE) was designed and conducted from 2015 to 2021 to study the demographics of such young gas giant planets around 400 young nearby solar-type stars. The analysis of the first part of the survey focused on 150 stars (SHINE F150) was already published in a series of papers in 2021. An additional filler campaign called snapSHINE was conducted to acquire second epoch data, using shallow observations.

Aims. In this paper, we present the observing strategy, data quality, and point source analysis of the full SHINE statistical sample as well as snapSHINE.

Methods. Both surveys used the SPHERE@VLT instrument with the IRDIS dual band imager in conjunction with the integral field spectrograph (IFS) and the angular differential imaging observing technique. All SHINE data (650 datasets), corresponding to 400 stars, including the targets of the F150 survey, are processed in a uniform manner, with an advanced post-processing algorithm called PACO ASDI. An emphasis is put on the classification and identification of the most promising candidate companions.

Results. Compared to the previous early analysis SHINE F150, the use of advanced post-processing techniques significantly improved the contrast detection limits by one or two magnitudes (x3-x6), which will allow us to put even tighter constraints on the radial distribution of young gas giants. This increased sensitivity directly sets SHINE apart as the largest and deepest direct imaging survey ever conducted. We detected and classified more than 3500 physical sources. One additional substellar companion was confirmed during the second phase of the survey (HIP 74865 B) and several new promising candidate companions are awaiting follow-up epoch confirmations.