Gaia Data Release 2: processing of the photometric data
Journal
Date Issued
2018
Author(s)
Riello, M.
•
De Angeli, F.
•
Evans, D. W.
•
Busso, G.
•
Hambly, N. C.
•
Davidson, M.
•
Burgess, P. W.
•
•
Osborne,P. J.
•
Kewley,A.
•
Carrasco, J. M.
•
Fabricius, C.
•
Jordi, C.
•
Cacciari, C.
•
van Leeuwen, F.
•
Holland, G.
Abstract
The second Gaia data release is based on 22 months of mission data with an
average of 0.9 billion individual CCD observations per day. A data volume of
this size and granularity requires a robust and reliable but still flexible
system to achieve the demanding accuracy and precision constraints that Gaia is
capable of delivering. The internal Gaia photometric system was initialised
using an iterative process that is solely based on Gaia data. A set of
calibrations was derived for the entire Gaia DR2 baseline and then used to
produce the final mean source photometry. The photometric catalogue contains
2.5 billion sources comprised of three different grades depending on the
availability of colour information and the procedure used to calibrate them:
1.5 billion gold, 144 million silver, and 0.9 billion bronze. These figures
reflect the results of the photometric processing; the content of the data
release will be different due to the validation and data quality filters
applied during the catalogue preparation. The photometric processing pipeline,
PhotPipe, implements all the processing and calibration workflows in terms of
Map/Reduce jobs based on the Hadoop platform. This is the first example of a
processing system for a large astrophysical survey project to make use of these
technologies. The improvements in the generation of the integrated G-band
fluxes, in the attitude modelling, in the cross-matching, and and in the
identification of spurious detections led to a much cleaner input stream for
the photometric processing. This, combined with the improvements in the
definition of the internal photometric system and calibration flow, produced
high-quality photometry. Hadoop proved to be an excellent platform choice for
the implementation of PhotPipe in terms of overall performance, scalability,
downtime, and manpower required for operations and maintenance.
Volume
616
Start page
A3
Issn Identifier
0004-6361
Rights
open.access
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