Automatically distinguishing Rubin transients from AGN using variability metrics

arXiv (Cornell University)

Abstract

Stochastic variability of active galactic nuclei (AGN) can produce contaminants in the search for explosive extragalactic transients (such as supernovae and tidal disruption events). In the new era of the Rubin Observatory's Legacy Survey of Space and Time (LSST), previously uncatalogued AGN, especially those with luminosity near the survey detection limits, are expected to produce a flood of detections that have the potential to contaminate surveys targeting other transients, leading to inefficient use of spectroscopic follow-up time. For surveys aiming to statistically characterise transient demographics, it is advantageous to use easily modelled and reproducible selection criteria to distinguish AGN from other transients, rather than machine learning. We test enacting cuts based on simple data-driven photometric variability parameters to distinguish non-AGN extragalactic transients from standard AGN variability on both Zwicky Transient Facility photometry and simulated LSST photometry from the MALLORN data set. We also investigate the impact of light curve history availability, redshift range and filter selection on selection efficiency. We find that a two-dimensional cut incorporating the ratio of detection flux and pre-detection standard deviation and the ratio of detection flux to pre-detection mean flux is the most effective cut. This approach is easily scalable as these values are included in the LSST alert packets. We provide estimates of the completeness and purity of the sample produced by enacting this cut, and gauge the AGN contamination avoided. The parameters utilised in this approach could also be implemented as features for identifying AGN in a photometric classifier.

Authors 10

1. Dylan K. J. Magill

   Queen's University Belfast

   Affiliation as printed

   Astrophysics Research Centre , School of Mathematics and Physics , Queen's University Belfast , Belfast BT7 1NN , UK

2. M. Nicholl

   Queen's University Belfast

   Affiliation as printed

   Astrophysics Research Centre , School of Mathematics and Physics , Queen's University Belfast , Belfast BT7 1NN , UK

3. Philip Wiseman

   University of Southampton

   Affiliation as printed

   School of Physics and Astronomy , University of Southampton , Southampton SO17 1BJ , UK

4. C. R. Angus

   Queen's University Belfast

   Affiliation as printed

   Astrophysics Research Centre , School of Mathematics and Physics , Queen's University Belfast , Belfast BT7 1NN , UK

5. P. Ramsden

   University of Birmingham

   Affiliation as printed

   School of Physics and Astronomy , University of Birmingham , Birmingham B15 2TT , UK

6. C. Frohmaier

   University of Portsmouth

   Affiliation as printed

   Institute of Cosmology and Gravitation , University of Portsmouth , Portsmouth , PO13FX , UK

7. Sjoert van Velzen Aachen Leiden Observatory

   Leiden University · Leiden Observatory

   Affiliation as printed

   Leiden Observatory , Leiden University , Postbus 9513 , NL-2300 RA Leiden , the Netherlands

8. Vysakh Anilkumar Aachen Leiden Observatory

   Leiden University · Leiden Observatory

   Affiliation as printed

   Leiden Observatory , Leiden University , Postbus 9513 , NL-2300 RA Leiden , the Netherlands

9. Jaimee Greenwood

   University of Manchester

   Affiliation as printed

   Jodrell Bank Centre for Astrophysics , School of Physics & Astronomy , University of Manchester , Oxford Rd. , Manchester M13 9PL , UK

10. Joshua G. Weston

    Queen's University Belfast

    Affiliation as printed

    Astrophysics Research Centre , School of Mathematics and Physics , Queen's University Belfast , Belfast BT7 1NN , UK