Superluminous Supernovae in LSST: Rates, Detection Metrics, and Light Curve Modeling

Abstract

We explore and demonstrate the capabilities of LSST to study Type I superluminous supernovae (SLSNe). We first fit the light curves of 58 known SLSNe at z~0.1-1.6, using an analytical magnetar spin-down model implemented in MOSFiT. We then use the posterior distributions of the magnetar and ejecta parameters to generate thousands of synthetic SLSN light curves, and we inject those into the OpSim to generate realistic ugrizy light curves. We define simple, measurable metrics to quantify the detectability and utility of the light curve, and to measure the efficiency of LSST in returning SLSN light curves satisfying these metrics. We combine the metric efficiencies with the volumetric rate of SLSNe to estimate the overall discovery rate of LSST, and we find that ~10^4 SLSNe per year with >10 data points will be discovered in the WFD survey at z<3.0, while only ~15 SLSNe per year will be discovered in each DDF at z<4.0. To evaluate the information content in the LSST data, we refit representative output light curves with the same model that was used to generate them. We correlate our ability to recover magnetar and ejecta parameters with the simple light curve metrics to evaluate the most important metrics. 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 fifty observations in all bands combined, are most information rich, with ~30% of these light curves having recoverable physical parameters to ~30% accuracy. WFD survey strategies which increase cadence in these bands and minimize seasonal gaps will maximize the number of scientifically useful SLSN light curves. Finally, although the DDFs will provide more densely sampled light curves, we expect only ~50 SLSNe with recoverable parameters in each field in the decade-long survey.

13 pages, 11 figures, submitted to ApJ

References in corpus (17)

• Cosmic Star Formation History
• The magnetar model for Type I superluminous supernovae I: Bayesian analysis of the full multicolour light curve sample with MOSFiT
• SN 2005ap: A Most Brilliant Explosion
• MOSFiT: Modular Open-Source Fitter for Transients
• Spectroscopy of superluminous supernova host galaxies. A preference of hydrogen-poor events for extreme emission line galaxies
• Superluminous supernovae
• Hydrogen-Poor Superluminous Supernovae from the Pan-STARRS1 Medium Deep Survey
• The hydrogen-poor superluminous supernova iPTF13ajg and its host galaxy in absorption and emission
• Superluminous supernova 2015bn in the nebular phase: evidence for the engine-powered explosion of a stripped massive star
• Theoretical Models of Optical Transients. I. A Broad Exploration of the Duration-Luminosity Phase Space
• Super Luminous Supernovae as standardizable candles and high redshift distance probes
• An ultraviolet excess in the superluminous supernova Gaia16apd reveals a powerful central engine
• On the early-time excess emission in hydrogen-poor superluminous supernovae
• DES13S2cmm: The First Superluminous Supernova from the Dark Energy Survey
• A Monte Carlo Approach to Magnetar-powered Transients: I. Hydrogen-deficient Superluminous Supernovae
• Jets in Hydrogen-poor Super-luminous Supernovae: Constraints from a Comprehensive Analysis of Radio Observations
• Far-UV HST Spectroscopy of An Unusual Hydrogen Poor Superluminous Supernova: SN2017egm

Cited by in corpus (37)

• Constraints from gravitational wave detections of binary black hole mergers on the ${}^{12}\mathrm{C}{\left(\alpha ,\gamma \right)}^{16}\mathrm{O}$ rate
• The Explosion of Helium Stars Evolved With Mass Loss
• Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)
• POEMMA's Target of Opportunity Sensitivity to Cosmic Neutrino Transient Sources
• Supernova Photometric Classification Pipelines Trained on Spectroscopically Classified Supernovae from the Pan-STARRS1 Medium-Deep Survey
• From core collapse to superluminous: The rates of massive stellar explosions from the Palomar Transient Factory
• Bumpy Declining Light Curves Are Common in Hydrogen-poor Superluminous Supernovae
• Pre-collapse Properties of Superluminous Supernovae and Long Gamma-Ray Burst Progenitor Models
• A Deep Learning Approach for Active Anomaly Detection of Extragalactic Transients
• Superluminous supernovae: an explosive decade
• The Pre-Explosion Mass Distribution of Hydrogen-Poor Superluminous Supernova Progenitors and New Evidence for a Mass-Spin Correlation
• Luminous Supernovae: Unveiling a Population Between Superluminous and Normal Core-collapse Supernovae
• GHOST: Using Only Host Galaxy Information to Accurately Associate and Distinguish Supernovae
• ParSNIP: Generative Models of Transient Light Curves with Physics-Enabled Deep Learning
• FLEET: A Redshift-Agnostic Machine Learning Pipeline to Rapidly Identify Hydrogen-Poor Superluminous Supernovae
• The Luminous and Double-Peaked Type Ic Supernova 2019stc: Evidence for Multiple Energy Sources
• Four (Super)luminous Supernovae from the First Months of the ZTF Survey
• Identifying Tidal Disruption Events with an Expansion of the FLEET Machine Learning Algorithm
• Towards Nebular Spectral Modeling of Magnetar-Powered Supernovae
• The first Hubble diagram and cosmological constraints using superluminous supernova
• SN 2017gci: a nearby Type I Superluminous Supernova with a bumpy tail
• Evaluating chemically homogeneous evolution in stellar binaries: Electromagnetic implications -- Ionizing photons, SLSN-I, GRB, Ic-BL
• SN2020qlb: A hydrogen-poor superluminous supernova with well-characterized light curve undulations
• A unified accreting magnetar model for long-duration gamma-ray bursts and some stripped-envelope supernovae
• Magnetar Models of Superluminous Supernovae from the Dark Energy Survey: Exploring Redshift Evolution
• Star formation and morphological properties of galaxies in the Pan-STARRS $3\pi$ survey- I. A machine learning approach to galaxy and supernova classification
• Post maximum light and late time optical imaging polarimetry of type I superluminous supernova 2020znr
• Core-collapse Supernovae in the Dark Energy Survey: Luminosity Functions and Host Galaxy Demographics
• Constraints on the rate of supernovae lasting for more than a year from Subaru/Hyper Suprime-Cam
• Close, bright and boxy: the superluminous SN 2018hti
• Dark Matter-admixed Rotating White Dwarfs as Peculiar Compact Objects
• Photometrically-Classified Superluminous Supernovae from the Pan-STARRS1 Medium Deep Survey: A Case Study for Science with Machine Learning-Based Classification
• Galaxy Formation and Symbiotic Evolution with the Inter-Galactic Medium in the Age of ELT-ANDES
• Feeding post core collapse supernova explosion jets with an inflated main sequence companion
• The restframe ultraviolet of superluminous supernovae -- I. Potential as cosmological probes
• Optical Observations and Modeling of the Superluminous Supernova 2018lfe
• Late-Time Hubble Space Telescope Observations of a Hydrogen-Poor Superluminous Supernova Reveal the Power-Law Decline of a Magnetar Central Engine