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Probing Late-Stage Stellar Evolution Through Robotic Follow-Up of Nearby Supernovae
Many of the remaining uncertainties in stellar evolution can be addressed through immediate and long-term photometry and spectroscopy of supernovae. The early light curves of thermonuclear supernovae can contain information about the nature of the binary companion to the exploding white dwarf. Spectra of core-collapse supernovae can reveal material lost by massive stars in their final months to years. Thanks to a revolution in technology—robotic telescopes, high-speed internet, machine learning—we can now routinely discover supernovae within days of explosion and obtain well-sampled follow-up data for months and years. Here I present three major results from the Global Supernova Project at Las Cumbres Observatory that take advantage of these technological advances. (1) SN 2017cbv is a Type Ia supernova discovered within a day of explosion. Early photometry shows a bump in the U-band relative to previously observed Type Ia light curves, possibly indicating the presence of a nondegenerate binary companion. (2) SN 2016bkv is a low-luminosity Type IIP supernova also caught very young. Narrow emission lines in the earliest spectra indicate interaction between the ejecta and a dense shell of circumstellar material, previously observed only in the brightest Type IIP supernovae. (3) Type Ibn supernovae are a rare class that interact with hydrogen-free circumstellar material. An analysis of the largest-yet sample of this class has found that their light curves are much more homogeneous and faster-evolving than their hydrogen-rich counterparts, Type IIn supernovae, but that their maximum-light spectra are more diverse
Photometrically-Classified Superluminous Supernovae from the Pan-STARRS1 Medium Deep Survey: A Case Study for Science with Machine Learning-Based Classification
With the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time
(LSST), it is expected that only of all transients will be
classified spectroscopically. To conduct studies of rare transients, such as
Type I superluminous supernovae (SLSNe), we must instead rely on photometric
classification. In this vein, here we carry out a pilot study of SLSNe from the
Pan-STARRS1 Medium-Deep Survey (PS1-MDS) classified photometrically with our
SuperRAENN and Superphot algorithms. We first construct a sub-sample of the
photometric sample using a list of simple selection metrics designed to
minimize contamination and ensure sufficient data quality for modeling. We then
fit the multi-band light curves with a magnetar spin-down model using the
Modular Open-Source Fitter for Transients (MOSFiT). Comparing the magnetar
engine and ejecta parameter distributions of the photometric sample to those of
the PS1-MDS spectroscopic sample and a larger literature spectroscopic sample,
we find that these samples are overall consistent, but that the photometric
sample extends to slower spins and lower ejecta masses, which correspond to
lower luminosity events, as expected for photometric selection. While our
PS1-MDS photometric sample is still smaller than the overall SLSN spectroscopic
sample, our methodology paves the way to an orders-of-magnitude increase in the
SLSN sample in the LSST era through photometric selection and study.Comment: 13 pages, 6 figures, submitted to Ap
Luminous Supernovae: Unveiling a Population Between Superluminous and Normal Core-collapse Supernovae
Stripped-envelope core-collapse supernovae can be divided into two broad
classes: the common Type Ib/c supernovae (SNe Ib/c), powered by the radioactive
decay of Ni, and the rare superluminous supernovae (SLSNe), most likely
powered by the spin-down of a magnetar central engine. Up to now, the
intermediate regime between these two populations has remained mostly
unexplored. Here, we present a comprehensive study of 40 \textit{luminous
supernovae} (LSNe), SNe with peak magnitudes of to mag, bound
by SLSNe on the bright end and by SNe Ib/c on the dim end. Spectroscopically,
LSNe appear to form a continuum between Type Ic SNe and SLSNe. Given their
intermediate nature, we model the light curves of all LSNe using a combined
magnetar plus radioactive decay model and find that they are indeed
intermediate, not only in terms of their peak luminosity and spectra, but also
in their rise times, power sources, and physical parameters. We sub-classify
LSNe into distinct groups that are either as fast-evolving as SNe Ib/c or as
slow-evolving as SLSNe, and appear to be either radioactively or magnetar
powered, respectively. Our findings indicate that LSNe are powered by either an
over-abundant production of Ni or by weak magnetar engines, and may
serve as the missing link between the two populations.Comment: 39 pages, 16 figures, submitted to Ap
SN 2016iet: The Pulsational or Pair Instability Explosion of a Low Metallicity Massive CO Core Embedded in a Dense Hydrogen-Poor Circumstellar Medium
We present optical photometry and spectroscopy of SN 2016iet, an
unprecedented Type I supernova (SN) at with no obvious analog in the
existing literature. The peculiar light curve has two roughly equal brightness
peaks ( mag) separated by 100 days, and a subsequent slow decline
by 5 mag in 650 rest-frame days. The spectra are dominated by emission lines of
calcium and oxygen, with a width of only km s, superposed on a
strong blue continuum in the first year, and with a large ratio of at late times. There is no clear evidence
for hydrogen or helium associated with the SN at any phase. We model the light
curves with several potential energy sources: radioactive decay, central
engine, and circumstellar medium (CSM) interaction. Regardless of the model,
the inferred progenitor mass near the end of its life (i.e., CO core mass) is
M and up to M, placing the event in the
regime of pulsational pair instability supernovae (PPISNe) or pair instability
supernovae (PISNe). The models of CSM interaction provide the most consistent
explanation for the light curves and spectra, and require a CSM mass of
M ejected in the final decade before explosion. We further
find that SN 2016iet is located at an unusually large offset ( kpc) from
its low metallicity dwarf host galaxy ( Z, M), supporting the PPISN/PISN interpretation. In the final
spectrum, we detect narrow H emission at the SN location, likely due to
a dim underlying galaxy host or an H II region. Despite the overall consistency
of the SN and its unusual environment with PPISNe and PISNe, we find that the
inferred properties of SN\,2016iet challenge existing models of such events.Comment: 26 Pages, 17 Figures, Submitted to Ap
The Luminous and Double-Peaked Type Ic Supernova 2019stc: Evidence for Multiple Energy Sources
We present optical photometry and spectroscopy of SN\,2019stc
(=ZTF19acbonaa), an unusual Type Ic supernova (SN Ic) at a redshift of
. SN\,2019stc exhibits a broad double-peaked light curve, with the
first peak having an absolute magnitude of mag, and the second
peak, about 80 rest-frame days later, mag. The total radiated
energy is large, erg. Despite its large
luminosity, approaching those of Type I superluminous supernovae (SLSNe),
SN\,2019stc exhibits a typical SN Ic spectrum, bridging the gap between SLSNe
and SNe Ic. The spectra indicate the presence of Fe-peak elements, but modeling
of the first light curve peak with radioactive heating alone leads to an
unusually high nickel mass fraction of ( M). Instead, if we model the first peak with a combined
magnetar spin-down and radioactive heating model we find a better match with
M, a magnetar spin period of ms and magnetic field of G, and (consistent with SNe Ic). The prominent second peak cannot be naturally
accommodated with radioactive heating or magnetar spin-down, but instead can be
explained as circumstellar interaction with of
hydrogen-free material located AU from the progenitor. Including
the remnant mass leads to a CO core mass prior to explosion of
M. The host galaxy has a metallicity of Z, low
for SNe Ic but consistent with SLSNe. Overall, we find that SN\,2019stc is a
transition object between normal SNe Ic and SLSNe.Comment: 14 pages, 13 figures, Accepted to Ap
Nebular-Phase Spectra of Nearby Type Ia Supernovae
We present late-time spectra of eight Type Ia supernovae (SNe Ia) obtained at
days after peak brightness using the Gemini South and Keck telescopes.
All of the SNe Ia in our sample were nearby, well separated from their host
galaxy's light, and have early-time photometry and spectroscopy from the Las
Cumbres Observatory (LCO). Parameters are derived from the light curves and
spectra such as peak brightness, decline rate, photospheric velocity, and the
widths and velocities of the forbidden nebular emission lines. We discuss the
physical interpretations of these parameters for the individual SNe Ia and the
sample in general, including comparisons to well-observed SNe Ia from the
literature. There are possible correlations between early-time and late-time
spectral features that may indicate an asymmetric explosion, so we discuss our
sample of SNe within the context of models for an offset ignition and/or white
dwarf collisions. A subset of our late-time spectra are uncontaminated by host
emission, and we statistically evaluate our nondetections of H emission
to limit the amount of hydrogen in these systems. Finally, we consider the
late-time evolution of the iron emission lines, finding that not all of our SNe
follow the established trend of a redward migration at days after
maximum brightness.Comment: 20 pages, 8 figures, 9 tables; accepted to MNRA
Type Ibn Supernovae Show Photometric Homogeneity and Spectral Diversity at Maximum Light
Type Ibn supernovae (SNe) are a small yet intriguing class of explosions whose spectra are characterized by low-velocity helium emission lines with little to no evidence for hydrogen. The prevailing theory has been that these are the core-collapse explosions of very massive stars embedded in helium-rich circumstellar material (CSM). We report optical observations of six new SNe Ibn: PTF11rfh, PTF12ldy, iPTF14aki, iPTF15ul, SN 2015G, and iPTF15akq. This brings the sample size of such objects in the literature to 22. We also report new data, including a near-infrared spectrum, on the Type Ibn SN 2015U. In order to characterize the class as a whole, we analyze the photometric and spectroscopic properties of the full Type Ibn sample. We find that, despite the expectation that CSM interaction would generate a heterogeneous set of light curves, as seen in SNe IIn, most Type Ibn light curves are quite similar in shape, declining at rates around 0.1 mag day^(−1) during the first month after maximum light, with a few significant exceptions. Early spectra of SNe Ibn come in at least two varieties, one that shows narrow P Cygni lines and another dominated by broader emission lines, both around maximum light, which may be an indication of differences in the state of the progenitor system at the time of explosion. Alternatively, the spectral diversity could arise from viewing-angle effects or merely from a lack of early spectroscopic coverage. Together, the relative light curve homogeneity and narrow spectral features suggest that the CSM consists of a spatially confined shell of helium surrounded by a less dense extended wind
FLEET: A Redshift-Agnostic Machine Learning Pipeline to Rapidly Identify Hydrogen-Poor Superluminous Supernovae
Over the past decade wide-field optical time-domain surveys have increased
the discovery rate of transients to the point that are being
spectroscopically classified. Despite this, these surveys have enabled the
discovery of new and rare types of transients, most notably the class of
hydrogen-poor superluminous supernovae (SLSN-I), with about 150 events
confirmed to date. Here we present a machine-learning classification algorithm
targeted at rapid identification of a pure sample of SLSN-I to enable
spectroscopic and multi-wavelength follow-up. This algorithm is part of the
FLEET (Finding Luminous and Exotic Extragalactic Transients) observational
strategy. It utilizes both light curve and contextual information, but without
the need for a redshift, to assign each newly-discovered transient a
probability of being a SLSN-I. This classifier can achieve a maximum purity of
about 85\% (with 20\% completeness) when observing a selection of SLSN-I
candidates. Additionally, we present two alternative classifiers that use
either redshifts or complete light curves and can achieve an even higher purity
and completeness. At the current discovery rate, the FLEET algorithm can
provide about SLSN-I candidates per year for spectroscopic follow-up with
85\% purity; with the Legacy Survey of Space and Time we anticipate this will
rise to more than events per year.Comment: 17 pages, 12 figures, submitted to Ap
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