Abstract
Abstract We explore and demonstrate the capabilities of the upcoming Large Synoptic Survey Telescope (LSST) to study Type I superluminous supernovae (SLSNe). We fit the light curves of 58 known SLSNe at z ≈ 0.1–1.6, using a magnetar spin-down model. We use the posterior distributions of the magnetar and ejecta parameters to generate synthetic SLSN light curves, and we inject those into the LSST Operations Simulator to generate ugrizy light curves. We define metrics to quantify the detectability and utility of the light curve. We combine the metric efficiencies with the SLSN volumetric rate to estimate the discovery rate of LSST and find that ≈104 SLSNe per year with >10 data points will be discovered in the Wide-Fast-Deep (WFD) survey at z ≲ 3.0, while only ≈15 SLSNe per year will be discovered in each Deep Drilling Field at z ≲ 4.0. To evaluate the information content in the LSST data, we refit representative output light curves. We find that we can recover physical parameters to within 30% of their true values from ≈18% of WFD light curves. Light curves with measurements of both the rise and decline in gri-bands, and those with at least 50 observations in all bands combined, are most information rich. WFD survey strategies, which increase cadence in these bands and minimize seasonal gaps, will maximize the number of scientifically useful SLSNe. Finally, although the Deep Drilling Fields will provide more densely sampled light curves, we expect only ≈50 SLSNe with recoverable parameters in each field in the decade-long survey.
Highlights
Type I Superluminous supernovae (SLSNe) are an observationally classified class of transients that typically reach a peak absolute magnitude of −20 mag and display unique early time spectra with O II absorption superposed on a hydrogenfree blue continuum (Chomiuk et al 2011; Quimby et al 2011; Gal-Yam 2012)
We constructed a realistic distribution of magnetar and explosion parameters from an existing sample of 58 superluminous supernovae (SLSNe) spanning z = 0.1–1.6 and used this to simulate thousands of SLSNe at z = 0–6 in the Large Synoptic Survey Telescope (LSST) Operations Simulator
We define a number of measurable light-curve metrics, which we use to define a “detection.” For our loosest definition of a detection, we find that the detection efficiency of the WFD survey quickly declines from ≈50% at z = 1 to ≈10% at z = 3, while for the Deep Drilling fields (DDFs), the efficiency declines from ≈100% at z = 0.5 to ≈50% at z = 3 and 10% at z = 5
Summary
Type I Superluminous supernovae (SLSNe) are an observationally classified class of transients that typically reach a peak absolute magnitude of −20 mag and display unique early time spectra with O II absorption superposed on a hydrogenfree blue continuum (Chomiuk et al 2011; Quimby et al 2011; Gal-Yam 2012) These events typically exhibit long durations, with a time to rise and decline by one magnitude of tdur 50 days, allowing them to radiate ≈1051 erg in the optical/UV, comparable to the kinetic energies of normal corecollapse SNe. These events typically exhibit long durations, with a time to rise and decline by one magnitude of tdur 50 days, allowing them to radiate ≈1051 erg in the optical/UV, comparable to the kinetic energies of normal corecollapse SNe Despite their high luminosities and long durations, SLSNe are a relatively recent discovery due to the advent of untargeted wide-field time-domain surveys. Due to limited spectroscopic resources, it is essential to explore what information can be obtained about these large samples from light curves alone; namely, their diverse observational properties (Nicholl et al 2015b), progenitor populations (Lunnan et al 2014), host. 0s.t3an0d7a, rdandcoWsmL o=log0y.6,91wi(tPhlaHnc0k= Co6l7l.a7bkomratsio−n1 et al 2016)
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