A Smart and Colorful Cadence for the LSST Wide Fast Deep Survey: Maximizing TDE Science. (arXiv:1812.07036v1 [astro-ph.IM])

A Smart and Colorful Cadence for the LSST Wide Fast Deep Survey: Maximizing TDE Science. (arXiv:1812.07036v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Gezari_S/0/1/0/all/0/1">Suvi Gezari</a> (UMD), <a href="http://arxiv.org/find/astro-ph/1/au:+Velzen_S/0/1/0/all/0/1">Sjoert van Velzen</a> (UMD, NYU), <a href="http://arxiv.org/find/astro-ph/1/au:+Hung_T/0/1/0/all/0/1">Tiara Hung</a> (UCSC), <a href="http://arxiv.org/find/astro-ph/1/au:+Cenko_B/0/1/0/all/0/1">Brad Cenko</a> (NASA/Goddard), <a href="http://arxiv.org/find/astro-ph/1/au:+Arcavi_I/0/1/0/all/0/1">Iair Arcavi</a> (Tel Aviv University)

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.

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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