Toward next-generation time-domain surveys: VST monitoring of the LSST Deep Drilling Fields

SUMMARY: The TIMEDOMES project aims at producing a legacy dataset of images, catalogs and lightcurves over 4 of the LSST Deep Drilling Fields using the VST telescope, doubling the temporal baseline that will be covered by the Vera Rubin observatory over the next decade and down to similar single-epoch depths in at least 2 bands.

Background:

The Vera Rubin Observatory Legacy Survey of Space and Time (LSST), plans to monitor the sky with day to week cadence for 10 years in the u,g,r,i,y,z bands. Variability, in combination with optical colors, will be one of the main methods envisioned to select AGN and to study their properties and demographics, as well as the coevolution with their host galaxies. 

In the last decade the VST telescope conducted several surveys designed to probe the time domain. The SUDARE survey was designed to acquire images every 3-10 days in r,g,i bands, in 4 sq.deg in the CDFS region over timescales of months. A parallel effort targeted 1 sq.deg in the COSMOS field but over a longer baseline of 3 years. These campaigns provided a broad scientific return, allowing to conduct studies ranging from the census and evolution of SNe to the detection and characterisation of AGN populations. VST has thus targeted some of the extragalactic fields with the best available multi-wavelength coverage, in order to assess the efficiency and contamination of variability-selected samples w.r.t. other selection approaches, such as optical/IR colors, spectroscopy, and X-rays. As a result it has been possible to identiy hundreds of AGN demonstrating that variability selection yields high-purity (~90%) AGN samples, easily distinguished from e.g. SNe and stars, even at faint magnitudes. 

The VST surveys are crucial in probing the observational parameter space (depth, cadence, bands) in close resemblance to what LSST will ultimately offer, and represent a pioneer homogeneous, wide-field investigation, probing down to r>24 mag (comparable to the planned LSST depth per single epoch, see Brandt+2018). 

The project: 

The TIMEDOMES program intends to extend the VST coverage in space and time in order to create deep image templates, reference catalogs of variable sources and light curves with extended temporal baseline, with the aim of improving the efficiency of LSST in the DDF from the very beginning of the survey. To this end the team started to collect and homogenise all archival VST observations; in parallel it obtained GO and GTO VST time to target pre-exhisting (COSMOS, CDF-S) and new (ELAIS-S1, XMM-LSS) DDFs. This effort benefitted from time allocated within other ongoing surveys (e.g. VEGAS, VSTxSKA), as well as on dedicated time allocated by INAF once VST became an entirely italian facility (late 2022). 

Since 2023 the TIMEDOMES project became an italian in-kind contribution to the LSST community and as such its data will be released within the LSST collaboration following the in-kind policies. A short presentation of the project can be found at the end of this page.

Goals:

The TIMEDOMES aims at: 

1. anticipating the performance expected by the future LSST survey over the whole Southern sky, extending the VST monitoring campaign to the same final temporal baseline, in some of the regions of the sky with the best multiwavelength ancillary coverage; 

2. studying the effectiveness of AGN variability selection, in order to verify what fraction of X-ray/IR/spectroscopically selected AGN will be discovered by LSST, and compute the corresponding selection corrections;

3. improving the identification of low-luminosity and Type-2 AGN, which are affected by a lower selection efficiency, and understand if this is due to intrinsic properties of these source and if it can be improved by longer baselines and the use of Machine Learning methods; 

4. better probing the faint end of the AGN LF (r>22 mag) where the lower contrast of the AGN w.r.t. the host-galaxy requires the larger variability expected on longer timescales for a robust detection;

5. identifying rare/peculiar AGN candidates that are not selected by complementary methods and study their properties through archival data and dedicated follow-ups;

6. studying the much-debated link between variability and intrinsic AGN properties (BH mass, accretion rate) which requires long baselines to be properly measured. 

Clearly these data will also produce additional non-AGN science, e.g. studies of SN rates, variable stars, galaxy populations, as demonstrated by the publication record of the collaboration, and serve as a training datasets for machine learning classification of AGN.