Rapid identification of the optical counterparts of neutron star (NS) merger events discovered by gravitational wave detectors may require observing a large error region and sifting through a large number of transients to identify the object of interest. Given the expense of spectroscopic observations, a question arises: How can we utilize photometric observations for candidate prioritization, and what kinds of photometric observations are needed to achieve this goal? NS merger kilonova exhibits low ejecta mass (∼5 × 10−2 M⊙) and a rapidly evolving photospheric radius (with a velocity ∼0.2c). As a consequence, these sources display rapid optical-flux evolution. Indeed, selection based on fast flux variations is commonly used for young supernovae and NS mergers. In this study, we leverage the best currently available flux-limited transient survey – the Zwicky Transient Facility Bright Transient Survey – to extend and quantify this approach. We focus on selecting transients detected in a 3-day cadence survey and observed at a one-day cadence. We explore their distribution in the phase space defined by g–r, $\dot{g}$, and $\dot{r}$. Our analysis demonstrates that for a significant portion of the time during the first week, the kilonova AT 2017gfo stands out in this phase space. It is important to note that this investigation is subject to various biases and challenges; nevertheless, it suggests that certain photometric observations can be leveraged to identify transients with the highest probability of being fast-evolving events. We also find that a large fraction (≈75 per cent) of the transient candidates with $\vert\dot{g}\vert>0.7$ mag d−1, are cataclysmic variables or active galactic nuclei with radio counterparts.
We present our follow-up observations with GRANDMA of transient sources revealed by the Zwicky Transient Facility (ZTF). Over a period of six months, all ZTF alerts were examined in real time by a dedicated science module implemented in the Fink broker, which will be used in filtering of transients discovered by the Vera C. Rubin Observatory. In this article, we present three selection methods to identify kilonova candidates. Out of more than 35 million alerts, a hundred sources have passed our selection criteria. Six were then followed-up by GRANDMA (by both professional and amateur astronomers). The majority were finally classified either as asteroids or as supernovae events. We mobilized 37 telescopes, bringing together a large sample of images, taken under various conditions and quality. To complement the orphan kilonova candidates, we included three additional supernovae alerts to conduct further observations during summer 2021. We demonstrate the importance of the amateur astronomer community that contributed images for scientific analyses of new sources discovered in a magnitude range r′ = 17 − 19 mag. We based our rapid kilonova classification on the decay rate of the optical source that should exceed 0.3 mag d−1. GRANDMA’s follow-up determined the fading rate within 1.5 ± 1.2 d post-discovery, without waiting for further observations from ZTF. No confirmed kilonovae were discovered during our observing campaign. This work will be continued in the coming months in the view of preparing for kilonova searches in the next gravitational-wave observing run O4.
more » « less- NSF-PAR ID:
- 10370001
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 515
- Issue:
- 4
- ISSN:
- 0035-8711
- Page Range / eLocation ID:
- p. 6007-6022
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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While optical surveys regularly discover slow transients like supernovae on their own, the most common way to discover extragalactic fast transients, fading away in a few nights, is via follow-up observations of gamma-ray burst and gravitational-wave triggers. However, wide-field surveys have the potential to also identify rapidly fading transients independently of such external triggers. The volumetric survey speed of the Zwicky Transient Facility (ZTF) makes it sensitive to faint and fast-fading objects as kilonovae, the optical counterparts to binary neutron stars and neutron star-black hole mergers, out to almost 200Mpc. We introduce an open-source software infrastructure, the ZTF REaltime Search and Triggering, ZTFReST, designed to identify kilonovae and fast optical transients in ZTF data. Using the ZTF alert stream combined with forced photometry, we have implemented automated candidate ranking based on their photometric evolution and fitting to kilonova models. Automated triggering of follow-up systems, such as Las Cumbres Observatory, has also been implemented. In 13 months of science validation, we found several extragalactic fast transients independent of any external trigger (though some counterparts were identified later), including at least one supernova with post-shock cooling emission, two known afterglows with an associated gamma-ray burst, two known afterglows without any known gamma-ray counterpart, and three new fast-declining sources (ZTF20abtxwfx, ZTF20acozryr, and ZTF21aagwbjr) that are likely associated with GRB200817A, GRB201103B, and GRB210204A. However, we have not found any objects which appear to be kilonovae; therefore, we constrain the rate of GW170817-like kilonovae to R<900Gpc−3yr−1. A framework such as ZTFReST could become a prime tool for kilonova and fast transient discovery with the Vera C. Rubin Observatory.more » « less
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Context. With a rapidly rising number of transients detected in astronomy, classification methods based on machine learning are increasingly being employed. Their goals are typically to obtain a definitive classification of transients, and for good performance they usually require the presence of a large set of observations. However, well-designed, targeted models can reach their classification goals with fewer computing resources. Aims. The aim of this study is to assist in the observational astronomy task of deciding whether a newly detected transient warrants follow-up observations. Methods. This paper presents SNGuess, a model designed to find young extragalactic nearby transients with high purity. SNGuess works with a set of features that can be efficiently calculated from astronomical alert data. Some of these features are static and associated with the alert metadata, while others must be calculated from the photometric observations contained in the alert. Most of the features are simple enough to be obtained or to be calculated already at the early stages in the lifetime of a transient after its detection. We calculate these features for a set of labeled public alert data obtained over a time span of 15 months from the Zwicky Transient Facility (ZTF). The core model of SNGuess consists of an ensemble of decision trees, which are trained via gradient boosting. Results. Approximately 88% of the candidates suggested by SNGuess from a set of alerts from ZTF spanning from April 2020 to August 2021 were found to be true relevant supernovae (SNe). For alerts with bright detections, this number ranges between 92% and 98%. Since April 2020, transients identified by SNGuess as potential young SNe in the ZTF alert stream are being published to the Transient Name Server (TNS) under the AMPEL_ZTF_NEW group identifier. SNGuess scores for any transient observed by ZTF can be accessed via a web service https://ampel.zeuthen.desy.de/api/live/docs . The source code of SNGuess is publicly available https://github.com/nmiranda/SNGuess . Conclusions. SNGuess is a lightweight, portable, and easily re-trainable model that can effectively suggest transients for follow-up. These properties make it a useful tool for optimizing follow-up observation strategies and for assisting humans in the process of selecting candidate transients.more » « less
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