arXiv subjects

Edo Berger

Publications and source records attributed to Edo Berger.

At least 109 records · Page 6Linked to original sources

arXiv2021

Optical Observations and Modeling of the Superluminous Supernova 2018lfe

We present optical imaging and spectroscopy of SN\,2018lfe, which we classify as a Type I superluminous supernova (SLSN-I) at a redshift of $z = 0.3501$ with a peak absolute magnitude of $M_r\approx -22.1$ mag, one of the brightest SLSNe discovered. SN\,2018lfe was identified for follow-up using our FLEET machine learning pipeline. Both the light curve and the spectra of SN\,2018lfe are consistent with the broad population of SLSNe. We fit the light curve with a magnetar central engine model and find an ejecta mass of $M_{\rm ej}\approx 3.8$ M$_\odot$, a magnetar spin period of $P\approx 2.9$ ms and a magnetic field strength of $B_{\perp}\approx 2.8\times 10^{14}$ G. The magnetic field strength is near the top of the distribution for SLSNe, while the spin period and ejecta mass are near the median values of the distribution for SLSNe. From late-time imaging and spectroscopy we find that the host galaxy of SN\,2018lfe has an absolute magnitude of $M_r\approx -17.85$, ($L_B \approx 0.029$ $L^*$), and an inferred metallicity of $Z\approx 0.3$ Z$_\odot$, and star formation rate of $\approx 0.8$ M$_\odot$ yr$^{-1}$.

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arXiv2021

Deep Hubble Space Telescope Observations of GW170817: Complete Light Curves and the Properties of the Galaxy Merger of NGC 4993

We present the complete set of {\it Hubble Space Telescope} imaging of the binary neutron star merger GW170817 and its optical counterpart AT 2017gfo. Including deep template imaging in F814W, F110W, F140W, and F160W at 3.4 years post-merger, we re-analyze the full light curve of AT 2017gfo across 12 bands from 5--1273 rest-frame days after merger. We obtain four new detections of the short $γ$-ray burst (GRB) 170817A afterglow from 109--170 rest-frame days post-merger. These detections are consistent with the previously observed $β=-0.6$ spectral index in the afterglow light curve with no evidence for spectral evolution. We also analyze our limits in the case of novel late-time optical and IR emission signatures, such as a kilonova afterglow or infrared dust echo, but find our limits are not constraining in these contexts. We use the new data to construct deep optical and infrared stacks, reaching limits of $M=-6.3$ to $-4.6$ mag, to analyze the local environment around AT 2017gfo and low surface brightness features in its host galaxy NGC 4993. We rule out the presence of any globular cluster at the position of AT 2017gfo to $2.3 \times 10^{4} L_{\odot}$, including those with the reddest $V-H$ colors. Finally, we analyze the substructure of NGC 4993 in deep residual imaging, and find shell features which extend up to 71.8\arcsec\ (14.2 kpc) from the center of the galaxy. We find that the shells have a cumulative stellar mass of $6.3\times10^{8} M_{\odot}$, roughly 2% the total stellar mass of NGC 4993, and mass-weighted ages of $>$3 Gyr. We conclude that it was unlikely the GW170817 progenitor system formed in the galaxy merger, which based on dynamical signatures and the stellar population in the shells mostly likely occurred 220--685 Myr ago.

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arXiv2021

Detection and Parameter Estimation of Gravitational Waves from Binary Neutron-Star Mergers in Real LIGO Data using Deep Learning

One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filtering and Bayesian inference approaches. In particular, the application of these methods to the full signal parameter space available to the gravitational-wave detectors, and/or real-time parameter estimation is computationally prohibitive. On the other hand, rapid detection and inference are critical for prompt follow-up of the electromagnetic and astro-particle counterparts accompanying important transients, such as binary neutron-star and black-hole neutron-star mergers. Training deep neural networks to identify specific signals and learn a computationally efficient representation of the mapping between gravitational-wave signals and their parameters allows both detection and inference to be done quickly and reliably, with high sensitivity and accuracy. In this work we apply a deep-learning approach to rapidly identify and characterize transient gravitational-wave signals from binary neutron-star mergers in real LIGO data. We show for the first time that artificial neural networks can promptly detect and characterize binary neutron star gravitational-wave signals in real LIGO data, and distinguish them from noise and signals from coalescing black-hole binaries. We illustrate this key result by demonstrating that our deep-learning framework classifies correctly all gravitational-wave events from the Gravitational-Wave Transient Catalog, GWTC-1 [Phys. Rev. X 9 (2019), 031040]. These results emphasize the importance of using realistic gravitational-wave detector data in machine learning approaches, and represent a step towards achieving real-time detection and inference of gravitational waves.

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arXiv2021

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 $z=0.117$. SN\,2019stc exhibits a broad double-peaked light curve, with the first peak having an absolute magnitude of $M_r=-20.0$ mag, and the second peak, about 80 rest-frame days later, $M_r=-19.2$ mag. The total radiated energy is large, $E_{\rm rad}\approx 2.5\times 10^{50}$ 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 $f_{\rm Ni}\approx 31\%$ ($M_{\rm Ni}\approx 3.2$ M$_\odot$). Instead, if we model the first peak with a combined magnetar spin-down and radioactive heating model we find a better match with $M_{\rm ej}\approx 4$ M$_\odot$, a magnetar spin period of $P_{\rm spin}\approx 7.2$ ms and magnetic field of $B\approx 10^{14}$ G, and $f_{\rm Ni}\lesssim 0.2$ (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 $\approx 0.7$ $M_\odot$ of hydrogen-free material located $\approx 400$ AU from the progenitor. Including the remnant mass leads to a CO core mass prior to explosion of $\approx 6.5$ M$_\odot$. The host galaxy has a metallicity of $\approx 0.26$ Z$_\odot$, low for SNe Ic but consistent with SLSNe. Overall, we find that SN\,2019stc is a transition object between normal SNe Ic and SLSNe.

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arXiv2021

A Pilot Radio Search for Magnetic Activity in Directly Imaged Exoplanets

We present the first systematic search for GHz frequency radio emission from directly imaged exoplanets using Very Large Array (VLA) observations of sufficient angular resolution to separate the planets from their host stars. We obtained results for five systems and eight exoplanets located at $\lesssim 50$ pc, through new observations (Ross 458, GU Psc, and 51 Eri) and archival data (GJ 504 and HR 8799). We do not detect radio emission from any of the exoplanets, with $3σ$ luminosity upper limits of $(0.9-23)\times10^{21}$ erg s$^{-1}$. These limits are comparable to the level of radio emission detected in several ultracool dwarfs, including T dwarfs, whose masses are only a factor of two times higher than those of the directly-imaged exoplanets. Despite the lack of detections in this pilot study, we highlight the need for continued GHz frequency radio observations of nearby exoplanets at $μ$Jy-level sensitivity.

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arXiv2021

Late-Time Hubble Space Telescope Observations of a Hydrogen-Poor Superluminous Supernova Reveal the Power-Law Decline of a Magnetar Central Engine

The light curve diversity of hydrogen-poor superluminous supernovae (SLSNe) has kept open the possibility that multiple power sources account for the population. Specifically, pair-instability explosions (PISNe), which produce large masses of $^{56}$Ni, have been argued as the origin of some slowly-evolving SLSNe. Here we present detailed observations of SN 2016inl (=PS16fgt), a slowly-evolving SLSN at $z=0.3057$, whose unusually red spectrum matches PS1-14bj, a SLSN with an exceptionally long rise time consistent with a PISN. Ground-based and Hubble Space Telescope data, spanning about 800 rest-frame days, reveal a significant light curve flattening, similar to that seen in SN 2015bn, and much slower than the decline rate expected from radioactive decay of $^{56}$Co. We therefore conclude that despite its slow evolution, SN 2016inl is inconsistent with a PISN. Instead, the light curve evolution matches the expected power-law spin-down of a magnetar central engine, but with a shallower power law ($L\propto t^{-2.8}$) compared to that in SN 2015bn, indicating a possible difference in the $γ$-ray opacity between the two events. Analytical modeling indicates typical magnetar engine parameters, but one of the highest ejecta masses ($\approx 20$ M$_{\odot}$) inferred for a SLSN. Our results indicate that monitoring the late-time light curve evolution of SLSNe provides a powerful diagnostic of their energy source.

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arXiv2021

GRB 180418A: A possibly-short GRB with a wide-angle outflow in a faint host galaxy

We present X-ray and multi-band optical observations of the afterglow and host galaxy of GRB 180418A, discovered by ${\it Swift}$/BAT and ${\it Fermi}$/GBM. We present a reanalysis of the GBM and BAT data deriving durations of the prompt emission of $T_{90}\approx$2.56s and $\approx$1.90s, respectively. Modeling the ${\it Fermi}$/GBM catalog of 1405 bursts (2008-2014) in the Hardness-$T_{90}$ plane, we obtain a probability of $\approx$60% that GRB 180418A is a short-hard burst. From a combination of ${\it Swift}$/XRT and ${\it Chandra}$ observations, the X-ray afterglow is detected to $\approx$38.5 days after the burst, and exhibits a single power-law decline with $F_{\rm X} \propto t^{-0.98}$. Late-time Gemini observations reveal a faint r$\approx$25.69 mag host galaxy at an angular offset of $\approx$0.16''. At the likely redshift range of z$\approx$1-2.25, we find that the X-ray afterglow luminosity of GRB 180418A is intermediate between short and long GRBs at all epochs during which there is contemporaneous data, and that GRB 180418A lies closer to the $E_{γ,{\rm peak}}-E_{γ,{\rm iso}}$ correlation for short GRBs. Modeling the multi-wavelength afterglow with the standard synchrotron model, we derive the burst explosion properties and find a jet opening angle of $θ_{\rm j} \gtrsim 9-14^{\circ}$. If GRB 180418A is a short GRB that originated from a neutron star merger, it has one of the brightest and longest-lived afterglows along with an extremely faint host galaxy. If instead the event is a long GRB that originated from a massive star collapse, it has among the lowest luminosity afterglows, and lies in a peculiar space in terms of the Hardness-$T_{90}$ and $E_{γ,{\rm peak}}-E_{γ,{\rm iso}}$ planes.

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arXiv2021

A Deep Learning Approach for Active Anomaly Detection of Extragalactic Transients

There is a shortage of multi-wavelength and spectroscopic followup capabilities given the number of transient and variable astrophysical events discovered through wide-field, optical surveys such as the upcoming Vera C. Rubin Observatory. From the haystack of potential science targets, astronomers must allocate scarce resources to study a selection of needles in real time. Here we present a variational recurrent autoencoder neural network to encode simulated Rubin Observatory extragalactic transient events using 1% of the PLAsTiCC dataset to train the autoencoder. Our unsupervised method uniquely works with unlabeled, real time, multivariate and aperiodic data. We rank 1,129,184 events based on an anomaly score estimated using an isolation forest. We find that our pipeline successfully ranks rarer classes of transients as more anomalous. Using simple cuts in anomaly score and uncertainty, we identify a pure (~95% pure) sample of rare transients (i.e., transients other than Type Ia, Type II and Type Ibc supernovae) including superluminous and pair-instability supernovae. Finally, our algorithm is able to identify these transients as anomalous well before peak, enabling real-time follow up studies in the era of the Rubin Observatory.

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arXiv2021

Late-time Observations of Calcium-Rich Transient SN 2019ehk Reveal a Pure Radioactive Decay Power Source

We present $\textit{Hubble Space Telescope}$ imaging of the Calcium-rich supernova (SN) 2019ehk at 276 - 389 days after explosion. These observations represent the latest photometric measurements of a Calcium-rich transient to date and allows for the first opportunity to analyze the late-time evolution of an object in this observational SN class. We find that the late-time bolometric light curve of SN 2019ehk can be described predominantly through the radioactive decay of ${}^{56}\textrm{Co}$ for which we derive a mass of $M({}^{56}\textrm{Co}) = (2.8 \pm 0.1) \times 10^{-2}$$\rm{M}_\odot$. Furthermore, the rate of decline in bolometric luminosity requires the leakage of $γ$-rays on timescale $t_γ = 53.9 \pm 1.30$ days, but we find no statistical evidence for incomplete positron trapping in the SN ejecta. While our observations cannot constrain the exact masses of other radioactive isotopes synthesized in SN 2019ehk, we estimate a mass ratio limit of $M({}^{57}\textrm{Co}) / M({}^{56}\textrm{Co}) \leq 0.030$. This limit is consistent with the explosive nucleosynthesis produced in the merger of low-mass white dwarfs, which is one of the favored progenitor scenarios in early-time studies of SN 2019ehk.

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arXiv2021

A Program for Multi-Messenger Standard Siren Cosmology in the Era of LIGO A+, Rubin Observatory, and Beyond

The most promising variation of the standard siren technique combines gravitational-wave (GW) data for binary neutron star (BNS) mergers with redshift measurements enabled by their electromagnetic (EM) counterparts, to constrain cosmological parameters such as $H_0$, $Ω_m$, and $w_0$. Here we evaluate the near- and long-term prospects of multi-messenger cosmology in the era of future GW observatories: Advanced LIGO Plus (A+, 2025), Voyager-like detectors (2030s), and Cosmic Explorer-like detectors (CE, 2035 and beyond). We show that the BNS horizon distance of $\approx 700$ Mpc for A+ is well-matched to the sensitivity of the Vera C. Rubin Observatory (VRO) for kilonova detections. We find that one year of joint A+ and VRO observations will constrain the value of $H_0$ to percent-level precision, given a small investment of VRO time dedicated to target-of-opportunity GW follow-up. In the Voyager era, the BNS-kilonova observations begin to constrain $Ω_m$ with an investment of a few percent of VRO time. With the larger BNS horizon distance in the Cosmic Explorer era, on-axis short gamma-ray bursts (SGRBs) and their afterglows (though accompanying only some of the GW-detected mergers) supplant kilonovae as the most promising counterparts for redshift identification. We show that five years of joint observations with Cosmic Explorer-like facilities and a next-generation gamma-ray satellite with localization capabilities similar to that presently possible with Swift could constrain both $Ω_m$ and $w_0$ to $15-20\%$. We therefore advocate for a robust target-of-opportunity (ToO) program with VRO, and a wide-field gamma-ray satellite with improved sensitivity in the 2030s, to enable standard siren cosmology with next-generation gravitational wave facilities.

astro-ph.CO↗

arXiv2020

Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot

The classification of supernovae (SNe) and its impact on our understanding of the explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming wide-field time-domain surveys have increased the transient discovery rate far beyond our capacity to obtain even a single spectrum of each new event. We must therefore rely heavily on photometric classification, connecting SN light curves back to their spectroscopically defined classes. Here we present Superphot, an open-source Python implementation of the machine-learning classification algorithm of Villar et al., and apply it to 2315 previously unclassified transients from the Pan-STARRS1 Medium Deep Survey for which we obtained spectroscopic host-galaxy redshifts. Our classifier achieves an overall accuracy of 82%, with completenesses and purities of >80% for the best classes (SNe Ia and superluminous SNe). For the worst performing SN class (SNe Ibc), the completeness and purity fall to 37% and 21%, respectively. Our classifier provides 1257 newly classified SNe Ia, 521 SNe II, 298 SNe Ibc, 181 SNe IIn, and 58 SLSNe. These are among the largest uniformly observed samples of SNe available in the literature and will enable a wide range of statistical studies of each class.

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arXiv2020

The distant, galaxy cluster environment of the short GRB 161104A at $z\sim 0.8$ and a comparison to the short GRB host population

We present optical observations of the Swift short-duration gamma-ray burst (GRB) GRB 161104A and its host galaxy at $z=0.793 \pm 0.003$. We model the multiband photometry and spectroscopy with the stellar population inference code Prospector, and explore the posterior using nested sampling. We find that the mass-weighted age $t_m = 2.12^{+0.23}_{-0.21}$~Gyr, stellar mass $\log{(M/M_\odot)} = 10.21 \pm 0.04$, metallicity $\log{(Z/Z_\odot)} = 0.08^{+0.05}_{-0.06}$, dust extinction $A_V = 0.08^{+0.08}_{-0.05}$ mag, and the star formation rate $\text{SFR} = 9.9 \times 10^{-2} M_\odot$~yr$^{-1}$. These properties, along with a prominent 4000 Angstrom break and optical absorption lines classify this host as an early-type, quiescent galaxy. Using Dark Energy Survey galaxy catalogues, we demonstrate that the host of GRB 161104A resides on the outskirts of a galaxy cluster at $z\approx 0.8$, situated $\approx 1$ Mpc from the likely brightest cluster galaxy. We also present new modeling for 20 additional short GRB hosts ($\approx33\%$ of which are early-type galaxies), finding population medians of $\log(M/M_\odot) = 9.94^{+0.88}_{-0.98}$ and $t_m = 1.07^{+1.98}_{-0.67}$~Gyr ($68\%$ confidence). We further find that the host of GRB 161104A is more distant, less massive, and younger than the four other short GRB hosts known to be associated with galaxy clusters. Cluster short GRBs have faint afterglows, in the lower $\approx 11\%$ ($\approx 30\%$) of observed X-ray (optical) luminosities. We place a lower limit on the fraction of short GRBs in galaxy clusters versus those in the field of $\approx 5-13\%$, consistent with the fraction of stellar mass $\approx 10-20\%$ in galaxy clusters at redshifts $0.1 \leq z \leq 0.8$.

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arXiv2020

Radio Monitoring of the Tidal Disruption Event Swift J164449.3+573451. IV. Continued Fading and Non-Relativistic Expansion

We present continued radio and X-ray observations of the previously relativistic tidal disruption event (TDE) Swift J164449.3+573451 (\sw) extending to about 9.4 years post disruption, as part of ongoing campaigns with the Jansky Very Large Array (VLA) and the \textit{Chandra} X-ray observatory. We find that the X-ray emission has faded below detectable levels, with an upper limit of $\lesssim 3.5\times 10^{-15}$ erg cm$^{-2}$ s$^{-1}$ in a 100 ks observation, while the radio emission continues to be detected and steadily fade. Both are consistent with forward shock emission from a non-relativistic outflow, although we find that the radio spectral energy distribution is better fit at these late times with an electron power law index of $p\approx 3$ (as opposed to $p\approx 2.5$ at earlier times). With the revised spectral index we find $ε_B\approx 0.01$ using the radio and X-ray data, and a density of $\approx 0.04$ cm$^{3}$ at a radius of $R\approx 0.65$ pc ($R_{\rm sch}\approx 2\times 10^6$ R$_\odot$) from the black hole. The energy scale of the blastwave is $\approx 10^{52}$ erg. We also report detections of \sw\ at 3 GHz from the first two epochs of the VLA Sky Survey (VLASS), and find that $\sim 10^2$ off-axis \sw-like events to $z\sim 0.5$ may be present in the VLASS data. Finally, we find that \sw\ itself will remain detectable for decades at radio frequencies, although observations at sub-GHz frequencies will become increasingly important to characterize its dynamical evolution.

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arXiv2020

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 $\lesssim 10\%$ 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 $20$ 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 $\sim 10^3$ events per year.

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arXiv2020

A Late-time Radio Survey of Short GRBs at $z<0.5$: New Constraints on the Remnants of Neutron Star Mergers

Massive, rapidly-spinning magnetar remnants produced as a result of binary neutron star (BNS) mergers may deposit a fraction of their energy into the surrounding kilonova ejecta, powering a synchrotron radio signal from the interaction of the ejecta with the circumburst medium. We present 6.0 GHz Very Large Array (VLA) observations of nine, low-redshift short gamma-ray bursts (SGRBs; $z<0.5$) on rest-frame timescales of $\approx2.4-13.9$ yr following the bursts. We place $3σ$ limits on radio continuum emission of $F_ν\lesssim6-20\,μ$Jy at the burst positions, or $L_ν\lesssim(0.6-8.3)\times10^{28}$erg s$^{-1}$Hz$^{-1}$. Comparing these limits with new light curve modeling which properly incorporates relativistic effects, we obtain limits on the energy deposited into the ejecta of $E_{ej}\lesssim(0.6-6.7)\times 10^{52}$erg ($E_{ej}\lesssim(1.8-17.6)\times10^{52}$erg) for an ejecta mass of $0.03\,M_{\odot}$ ($0.1\,M_{\odot}$). We present a uniform re-analysis of 27 SGRBs with $5.5-6.0$ GHz observations, and find that $\gtrsim50\%$ of SGRBs did not form stable magnetar remnants in their mergers. Assuming SGRBs are produced by BNS mergers drawn from the Galactic BNS population plus an additional component of high-mass GW194025-like mergers in a fraction $f_{GW190425}$ of cases, we place constraints on the maximum mass of a non-rotating neutron star (NS) ($M_{TOV}$), finding $M_{TOV}\lesssim2.23\,M_{\odot}$ for $f_{GW190425}=0.4$; this limit increases for larger values of $f_{GW190425}$. The detection (or lack thereof) of radio remnants in untargeted surveys such as the VLA Sky Survey (VLASS) could provide more stringent constraints on the fraction of mergers that produce stable remnants. If $\gtrsim30-300$ radio remnants are discovered in VLASS, this suggests that SGRBs are a biased population of BNS mergers in terms of the stability of the remnants they produce.

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arXiv2020

The Tidal Disruption Event AT 2018hyz II: Light Curve Modeling of a Partially Disrupted Star

AT 2018hyz (=ASASSN-18zj) is a tidal disruption event (TDE) located in the nucleus of a quiescent E+A galaxy at a redshift of $z = 0.04573$, first detected by the All-Sky Automated Survey for Supernovae (ASAS-SN). We present optical+UV photometry of the transient, as well as an X-ray spectrum and radio upper limits. The bolometric light curve of AT 2018hyz is comparable to other known TDEs and declines at a rate consistent with a $t^{-5/3}$ at early times, emitting a total radiated energy of $E = 9\times10^{50}$ erg. An excess bump appears in the UV light curve about 50 days after bolometric peak, followed by a flattening beyond 250 days. The light curve shows an excess bump in the UV about 50 days after bolometric peak lasting for at least 100 days, which may be related to an outflow. We detect a constant X-ray source present for at least 86 days. The X-ray spectrum shows a total unabsorbed flux of $\sim 4\times10^{-14}$ erg cm$^{-2}$ s$^{-1}$ and is best fit by a blackbody plus power-law model with a photon index of $Γ= 0.8$. A thermal X-ray model is unable to account for photons $> 1$ keV, while the radio non-detection favors inverse-Compton scattering rather than a jet for the non-thermal component. We model the optical and UV light curves using the Modular Open-Source Fitter for Transients (MOSFiT) and find a best fit for a black hole of $5.2\times10^6$ M$_\odot$ partially disrupting a $0.1$ M$_\odot$ star (stripping a mass of $\sim 0.01$ M$_\odot$ for the inferred impact parameter, $β=0.6$). The low optical depth implied by the small debris mass may explain how we are able to see hydrogen emission with disk-like line profiles in the spectra of AT 2018hyz (see our companion paper, Short et al.~2020).

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arXiv2020

SuperRAENN: A Semi-supervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium Deep Survey Supernovae

Automated classification of supernovae (SNe) based on optical photometric light curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multi-wavelength follow-up, as well as archival population studies. Here we present the complete sample of 5,243 "SN-like" light curves (in griz) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters and depth, making this a useful training set for the community. Using this dataset, we train a novel semi-supervised machine learning algorithm to photometrically classify 2,315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of a random forest supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I). We find the highest accuracy rates for Type Ia SNe and SLSNe and the lowest for Type Ibc SNe. Our complete spectroscopically- and photometrically-classified samples break down into: 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects). Finally, we discuss how this algorithm can be modified for online LSST data streams.

astro-ph.HE↗

arXiv2020

Does GW190425 require an alternative formation pathway than a fast-merging channel?

The LIGO/Virgo Scientific Collaboration (LVC) recently announced the detection of a compact object binary merger, GW190425, with a total mass of $3.4^{+0.3}_{-0.1}$ M$_{\odot}$, and individual component masses in the range of about 1.1 to 2.5 $M_{\odot}$. If the constituent compact objects are neutron stars, then the total mass is five standard deviations higher than the mean of $2.66\pm 0.12$ M$_{\odot}$ for Galactic binary neutron stars (BNSs). LVC suggests such massive BNS systems are born from a fast-merging channel, and therefore, their non-detection in the Galaxy to be due to a selection effect. However, we are unable to reconcile the inferred formation efficiency from the reported merger rate, $\mathcal{R}_{\rm GW190425}=460^{+1050}_{-390}$ yr$^{-1}$ Gpc$^{-3}$, with predictions from our own study for fast-merging BNS systems. Moreover, the comparable merger rates of GW190425, and GW170817 are possibly in tension with our results for two reasons: (i) more massive systems are expected to have a lower formation rate, and (ii) fast merging channels should constitute $\lesssim 10\%$ of the total BNS systems if case BB unstable mass transfer is permitted to take place as a formation pathway. We argue that to account for the high merger rate of GW190425 as a BNS system requires: (i) revisiting our understanding of NS formation in supernova explosions, or (ii): that more massive NSs need to be preferentially born with either very weak or very high magnetic fields so that they would be undetectable in the radio surveys. Perhaps massive NSs detected in NS-white dwarf binaries are our clues to the formation path of GW190425 systems.

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