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A Smart and Colorful Cadence for the LSST Wide Fast Deep Survey: Maximizing TDE Science

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 نشر من قبل Suvi Gezari
 تاريخ النشر 2018
  مجال البحث فيزياء
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 تأليف Suvi Gezari




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Tidal disruption events (TDEs) are rare, 10^(-7)/yr/Mpc^3 (Hung et al. 2018), yet the large survey volume of LSST implies a very large detection rate of 200/yr/(1000 deg^2) (van Velzen et al. 2011), a factor of 250 increase in the detection capability of the current generation of optical synoptic surveys, e.g. ZTF, ASAS-SN, Pan-STARRS, and ATLAS. The goal of this LSST cadence white paper is to determine which survey strategy will ensure the efficient selection and characterization of TDEs in the LSST Wide-Fast-Deep Survey transient alert stream. We conclude that the baseline cadence design fails to 1) measure the u-r color and color evolution of transients, a critical parameter for distinguishing TDEs from SNe, and to 2) catch the pre-peak light curves of transients, an essential measurement for probing their rise times, which are in turn a probe of black hole mass in TDEs. If we do not harvest the fruits of the LSST transient alert stream with photometric classification and early detections, both TDE and SN science will be greatly limited. Hence, we propose for a smart and colorful rolling cadence in the Wide-Fast Deep (WFD) Survey, that allows for efficient photometric transient classification from well sampled multi-band light curves, with the 20,000 deg^2 survey divided into eight 2500 deg^2 strips each observed for one year in Years 2-9, with the full WFD area observed in Years 1 & 10. This will yield a legacy sample of 200 TDEs per year with early detections in u, g, and r bands for efficient classification and full light curve characterization.



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