Volume 609, January 2018
|Number of page(s)||13|
|Section||Numerical methods and codes|
|Published online||05 January 2018|
RoboTAP: Target priorities for robotic microlensing observations
1 Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg (ZAH), 69120 Heidelberg, Germany
2 Las Cumbres Observatory Global Telescope Network, 6740 Cortona Drive, suite 102, Goleta, CA 93117, USA
3 SUPA, School of Physics & Astronomy, University of St Andrews, North Haugh, St Andrews KY16 9SS, UK
4 Dipartimento di Fisica “E. R. Caianiello”, Università di Salerno, via Giovanni Paolo II 132, 84084 Fisciano (SA), Italy
5 Istituto Nazionale di Fisica Nucleare, Sezione di Napoli, via Cintia, 80126 Napoli, Italy
6 Sorbonne Universités, UPMC Univ. Paris 6 et CNRS, UMR 7095, Institut d’Astrophysique de Paris, 98 bis bd Arago, 75014 Paris, France
7 INAF–Observatory of Capodimonte, Salita Moiariello, 16, 80131 Naples, Italy
8 European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching bei München, Germany
9 Space Telescope Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
10 NASA Postdoctoral Program Fellow, NASA Goddard Space Flight Center, Mail Code 661, Greenbelt, MD 20771, USA
11 Planetary and Space Sciences, School of Physical Sciences, The Open University, Milton Keynes, MK7 6AA, UK
12 Astrophysics Research Institute, Liverpool John Moores University, Liverpool CH41 1LD, UK
13 National Astronomical Observatories, Chinese Academy of Sciences, 100012 Beijing, PR China
14 Department of Astronomy, Yale University, 52 Hillhouse Avenue, New Haven, CT 06511, USA
15 South African Astronomical Observatory, PO Box 9, Observatory 7935, South Africa
16 School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel
17 Jet Propulsion Laboratory, M/S 169-506, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
18 New York University Abu Dhabi, PO Box 129188, Saadiyat Island, Abu Dhabi, UAE
Received: 24 February 2017
Accepted: 28 September 2017
Context. The ability to automatically select scientifically-important transient events from an alert stream of many such events, and to conduct follow-up observations in response, will become increasingly important in astronomy. With wide-angle time domain surveys pushing to fainter limiting magnitudes, the capability to follow-up on transient alerts far exceeds our follow-up telescope resources, and effective target prioritization becomes essential. The RoboNet-II microlensing program is a pathfinder project, which has developed an automated target selection process (RoboTAP) for gravitational microlensing events, which are observed in real time using the Las Cumbres Observatory telescope network.
Aims. Follow-up telescopes typically have a much smaller field of view compared to surveys, therefore the most promising microlensing events must be automatically selected at any given time from an annual sample exceeding 2000 events. The main challenge is to select between events with a high planet detection sensitivity, with the aim of detecting many planets and characterizing planetary anomalies.
Methods. Our target selection algorithm is a hybrid system based on estimates of the planet detection zones around a microlens. It follows automatic anomaly alerts and respects the expected survey coverage of specific events.
Results. We introduce the RoboTAP algorithm, whose purpose is to select and prioritize microlensing events with high sensitivity to planetary companions. In this work, we determine the planet sensitivity of the RoboNet follow-up program and provide a working example of how a broker can be designed for a real-life transient science program conducting follow-up observations in response to alerts; we explore the issues that will confront similar programs being developed for the Large Synoptic Survey Telescope (LSST) and other time domain surveys.
Key words: gravitational lensing: micro / methods: observational / methods: statistical
© ESO, 2018
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