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  1. Abstract In recent years, there have been significant advances in multimessenger astronomy due to the discovery of the first, and so far only confirmed, gravitational wave event with a simultaneous electromagnetic (EM) counterpart, as well as improvements in numerical simulations, gravitational wave (GW) detectors, and transient astronomy. This has led to the exciting possibility of performing joint analyses of the GW and EM data, providing additional constraints on fundamental properties of the binary progenitor and merger remnant. Here, we present a new Bayesian framework that allows inference of these properties, while taking into account the systematic modeling uncertainties that arisemore »when mapping from GW binary progenitor properties to photometric light curves. We extend the relative binning method presented in Zackay et al. to include extrinsic GW parameters for fast analysis of the GW signal. The focus of our EM framework is on light curves arising from r -process nucleosynthesis in the ejected material during and after merger, the so-called kilonova, and particularly on black hole−neutron star systems. As a case study, we examine the recent detection of GW190425, where the primary object is consistent with being either a black hole or a neutron star. We show quantitatively how improved mapping between binary progenitor and outflow properties, and/or an increase in EM data quantity and quality are required in order to break degeneracies in the fundamental source parameters.« less
    Free, publicly-accessible full text available December 1, 2022
  2. Free, publicly-accessible full text available January 1, 2023
  3. null (Ed.)
    ABSTRACT Searches for gravitational-wave counterparts have been going in earnest since GW170817 and the discovery of AT2017gfo. Since then, the lack of detection of other optical counterparts connected to binary neutron star or black hole–neutron star candidates has highlighted the need for a better discrimination criterion to support this effort. At the moment, low-latency gravitational-wave alerts contain preliminary information about binary properties and hence whether a detected binary might have an electromagnetic counterpart. The current alert method is a classifier that estimates the probability that there is a debris disc outside the black hole created during the merger as wellmore »as the probability of a signal being a binary neutron star, a black hole–neutron star, a binary black hole, or of terrestrial origin. In this work, we expand upon this approach to both predict the ejecta properties and provide contours of potential light curves for these events, in order to improve the follow-up observation strategy. The various sources of uncertainty are discussed, and we conclude that our ignorance about the ejecta composition and the insufficient constraint of the binary parameters by low-latency pipelines represent the main limitations. To validate the method, we test our approach on real events from the second and third Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO)–Virgo observing runs.« less
  4. Abstract The discovery of the electromagnetic counterpart to the binary neutron star (NS) merger GW170817 has opened the era of gravitational-wave multimessenger astronomy. Rapid identification of the optical/infrared kilonova enabled a precise localization of the source, which paved the way to deep multiwavelength follow-up and its myriad of related science results. Fully exploiting this new territory of exploration requires the acquisition of electromagnetic data from samples of NS mergers and other gravitational-wave sources. After GW170817, the frontier is now to map the diversity of kilonova properties and provide more stringent constraints on the Hubble constant, and enable new tests ofmore »fundamental physics. The Vera C. Rubin Observatory’s Legacy Survey of Space and Time can play a key role in this field in the 2020s, when an improved network of gravitational-wave detectors is expected to reach a sensitivity that will enable the discovery of a high rate of merger events involving NSs (∼tens per year) out to distances of several hundred megaparsecs. We design comprehensive target-of-opportunity observing strategies for follow-up of gravitational-wave triggers that will make the Rubin Observatory the premier instrument for discovery and early characterization of NS and other compact-object mergers, and yet unknown classes of gravitational-wave events.« less
    Free, publicly-accessible full text available May 1, 2023
  5. We present the goals, strategy and first results of the high-cadence Galactic plane survey using the Zwicky Transient Facility (ZTF). The goal of the survey is to unveil the Galactic population of short-period variable stars, including short period binaries and stellar pulsators with periods less than a few hours. Between June 2018 and January 2019, we observed 64 ZTF fields resulting in 2990 deg2 of high stellar density in ZTF-r band along the Galactic Plane. Each field was observed continuously for 1.5 to 6 hrs with a cadence of 40 sec. Most fields have between 200 and 400 observations obtainedmore »over 2-3 continuous nights. As part of this survey we extract a total of ≈230 million individual objects with at least 80 epochs obtained during the high-cadence Galactic Plane survey reaching an average depth of ZTF-r ≈20.5 mag. For four selected fields with 2 million to 10 million individual objects per field we calculate different variability statistics and find that ≈1-2% of the objects are astrophysically variable over the observed period. We present a progress report on recent discoveries, including a new class of compact pulsators, the first members of a new class of Roche Lobe filling hot subdwarf binaries as well as new ultracompact double white dwarfs and flaring stars. Finally we present a sample of 12 new single-mode hot subdwarf B-star pulsators with pulsation amplitudes between ZTF-r = 20-76 mmag and pulsation periods between P = 5.8-16 min with a strong cluster of systems with periods ≈ 6 min. All of the data have now been released in either ZTF Data Release 3 or data release 4.« less
  6. We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R ∼100) data. The goal of SNIascore is fully automated classification of SNe Ia with a very low false-positive rate (FPR) so that human intervention can be greatly reduced in large-scale SN classification efforts, such as that undertaken by the public Zwicky Transient Facility (ZTF) Bright Transient Survey (BTS). We utilize a recurrent neural network (RNN) architecture with a combination of bidirectional long short-term memory and gated recurrent unit layers. SNIascore achieves a <0.6% FPR while classifying up to 90% ofmore »the low-resolution SN Ia spectra obtained by the BTS. SNIascore simultaneously performs binary classification and predicts the redshifts of secure SNe Ia via regression (with a typical uncertainty of <0.005 in the range from z=0.01 to z=0.12). For the magnitude-limited ZTF BTS survey (≈70% SNe Ia), deploying SNIascore reduces the amount of spectra in need of human classification or confirmation by ≈60%. Furthermore, SNIascore allows SN Ia classifications to be automatically announced in real-time to the public immediately following a finished observation during the night.« less