Erratum: Gaia Early Data Release 3: Summary of the contents and survey properties (Astronomy and Astrophysics DOI: 10.1051/0004-6361/202039657)

This is a corrigendum for Gaia Collaboration (2021). It corrects errors in Sects. 6.3.2 and 7.2 and Appendix A, which erroneously state that the correction to theG-band fluxes and magnitudes presented in Riello et al. (2021) (their Table 5) should be applied to sources in Gaia EDR3 with six-parameter astrometric solutions. In fact, the corrections should be applied to sources with twoparameter or six-parameter astrometric solutions. The corrected Astronomical Data Query Language (ADQL) query and Python source code from Appendix A are presented in the new version of Appendix A below. Following the discovery of the above error, a more detailed investigation was done for the sources with two-parameter (2-p) astrometric solutions. Out of the 344 million 2-p sources present in Gaia EDR3, about 20 million have an astrometric solution in which the actual source colour was used instead of a default colour. This means that for these 20 million 2-p sources the Gband correction should actually not be applied. These sources are mostly faint, with 96% at magnitudes G > 20, and for 75% of these 20 million sources the correction that is (wrongly) applied amounts to less than 4 milli-magnitudes. It was thus decided not to make a special effort to exclude these sources from the correction. Should a user of the Gaia EDR3 data wish to undo the wrong correction for one or more of these 20 million sources, the list of source IDs and applied corrections can be provided on request. Appendix A: G-band corrections for sources with two-parameter or six-parameter astrometric solutions Figure A.1 shows how to formulate an ADQL query, to be executed in the Gaia EDR3 archive, that contains an on-the-fly calculation of the corrected G-band fluxes or magnitudes. These queries are somewhat complex and create a performance overhead. Hence downloading the requisite Gaia EDR3 fields and calculating the corrections a posteriori may be more efficient. Example Python code to do this is included in Fig. A.2. The Python code is also available as a Jupyter notebook1. Appendix A: G-band corrections for sources with two-parameter or six-parameter astrometric solutions Figure A.1 shows how to formulate an ADQL query, to be executed in the Gaia EDR3 archive, that contains an on-the-fly calculation of the corrected G-band fluxes or magnitudes. These queries are somewhat complex and create a performance overhead. Hence downloading the requisite Gaia EDR3 fields and calculating the corrections a posteriori may be more efficient. Example Python code to do this is included in Fig. A.2. The Python code is also available as a Jupyter notebook.