Gaia Early Data Release 3

Modelling and calibration of Gaia’s point and line spread functions

¹ Institute for Astronomy, School of Physics and Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh, EH9 3HJ, UK
e-mail: nr@roe.ac.uk
² Lund Observatory, Department of Astronomy and Theoretical Physics, Lund University, Box 43, 22100 Lund, Sweden
³ Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
⁴ DAPCOM for Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona IEEC-UB), Martí Franquès 1, 08028 Barcelona, Spain
⁵ Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona (IEEC-UB), Martí Franquès 1, 08028 Barcelona, Spain
⁶ Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstraße 14, 69120 Heidelberg, Germany
⁷ ESA, European Space Astronomy Centre, Camino Bajo del Castillo s/n, 28691 Villanueva de la Cañada, Spain
⁸ HE Space Operations BV for ESA/ESAC, Camino Bajo del Castillo s/n, 28691 Villanueva de la Cañada, Spain
⁹ Gaia Project Office for DPAC/ESA, Camino Bajo del Castillo s/n, 28691 Villanueva de la Cañada, Spain
¹⁰ Aurora Technology for ESA/ESAC, Camino Bajo del Castillo s/n, 28691 Villanueva de la Cañada, Spain
¹¹ Istituto Nazionale di Astrofisica, Osservatorio Astrofisico di Torino, Via Osservatorio 20, Pino Torinese, Torino 10025, Italy
¹² Leiden Observatory, Leiden University, Niels Bohrweg 2, 2333 CA Leiden, The Netherlands

Received: 16 September 2020
Accepted: 30 November 2020

Abstract

Context. The unprecedented astrometric precision of the Gaia mission relies on accurate estimates of the locations of sources in the Gaia data stream. This is ultimately performed by point spread function (PSF) fitting, which in turn requires an accurate reconstruction of the PSF, including calibrations of all the major dependences. These include a strong colour dependence due to Gaia’s broad G band and a strong time dependence due to the evolving contamination levels and instrument focus. Accurate PSF reconstruction is also important for photometry. Gaia Early Data Release 3 (EDR3) will, for the first time, use a PSF calibration that models several of the strongest dependences, leading to signficantly reduced systematic errors.

Aims. We describe the PSF model and calibration pipeline implemented for Gaia EDR3, including an analysis of the calibration results over the 34 months of data. We include a discussion of the limitations of the current pipeline and directions for future releases. This will be of use both to users of Gaia data and as a reference for other precision astrometry missions.

Methods. We develop models of the 1D line spread function (LSF) and 2D PSF profiles based on a linear combination of basis components. These are designed for flexibility and performance, as well as to meet several mathematical criteria such as normalisation. We fit the models to selected primary sources in independent time ranges, using simple parameterisations for the colour and other dependences. Variation in time is smoothed by merging the independent calibrations in a square root information filter, with resets at certain mission events that induce a discontinuous change in the PSF.

Results. The PSF calibration shows strong time and colour dependences that accurately reproduce the varying state of the Gaia astrometric instrument. Analysis of the residuals reveals both the performance and the limitations of the current models and calibration pipeline, and indicates the directions for future development.

Conclusions. The PSF modelling and calibration carried out for Gaia EDR3 represents a major step forwards in the data processing and will lead to reduced systematic errors in the core mission data products. Further significant improvements are expected in the future data releases.