Cataloguing astronomical ground-based images of asteroids and TNOs

 

In our field of work, a wide variety of large databases are being generated from data obtained by different instruments, in different formats, on similar objects at different times or thousands of different objects over a number of years. In recent years only, catalogues of CCD optical observations from ground-based telescopes are published. Well known examples are the catalogues of moving objects from SLOAN, Gaia-DR2, K2 and several others.

In this paper we present a set of software tools that can process images from any telescope, any filter and any FITS header content. The source code of the tools is open to the scientific community using a public repository.

Those tools (OM, M2 and HENOSIS) are executed locally (no internet access required), does not include any dependence with traditional software packages (IDL, Python), store the results in a database and has been designed in Scala programming language, allowing to run them in computation clusters (with Spark Hadoop and Yarn) for massive data processing and also enabling the use of latest machine learning algorithms.

The OM tool, automatically detects relevant information of an image (telescope, filter, observing date, etc.), including the image type (i.e. science, bias, flat-field, dark). Then it performs the calibration of science images using the master flat, bias and dark previously generated. Finally, it solves the images astrometry using the Gaia-EDR3 catalogue.

The M2 tool has a set of capabilities using as input the calibrated images generated by OM:

1) Astrometry
a) It fits the image WCS to increase the accuracy
b) Manages an astrometry database with 100K images calibrated by OM

2) Photometry
a) Calculates the absolute and relative photometry of an asteroid/TNO
b) Calculates the light curve and rotational phase of an asteroid/TNO
c) Locates all Gaia-EDR3 sources present in an image and calculates its absolute and relative
photometry
d) Locates all images that contains a specific asteroid/TNO, by request
e) Locates all known asteroids/TNOs in a sequence of images
f) Using an input sequence of images, locates the groups of them with the biggest common field
of view

Finally, the HENOSIS tool, allows to cross match different catalogues (Gaia-DR2 MOC, SDSS MOC,MPC...) including the database generated by M2, obtaining as result a unique extended catalogue merging all disperse data.

Note that with point 2.c) of M2, for the Gaia stars, the G, Bp and Rp magnitudes are extracted and with them it is possible to calculate the V and R magnitudes. We then calculate and fit to a cubic polynomial and obtain the parameters from which we can obtain the asteroid/TNO magnitude in V and R filters. In this way, data from different telescopes, in different filters and with years of difference, can be compared, assuming a known V-R color for the object.

We have tested the system on images from our database of observations over 21 years, at different telescopes and observing filters and present the first results in the poster "Absolute photometry of the transneptunian dwarf planets in a long time span" done by Nicolas Morales at this same meeting.