This content will become publicly available on June 1, 2024
The modern study of astrophysical transients has been transformed by an exponentially growing volume of data. Within the last decade, the transient discovery rate has increased by a factor of ∼20, with associated survey data, archival data, and metadata also increasing with the number of discoveries. To manage the data at this increased rate, we require new tools. Here we present
- NSF-PAR ID:
- 10491550
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Publications of the Astronomical Society of the Pacific
- Date Published:
- Journal Name:
- Publications of the Astronomical Society of the Pacific
- Volume:
- 135
- Issue:
- 1048
- ISSN:
- 0004-6280
- Page Range / eLocation ID:
- 064501
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract SkyPortal is an open-source software package designed to discover interesting transients efficiently, manage follow-up, perform characterization, and visualize the results. By enabling fast access to archival and catalog data, crossmatching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, aSkyPortal -based platform has been operating at scale for >2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. WhileSkyPortal emphasizes rich user experiences across common front-end workflows, recognizing that scientific inquiry is increasingly performed programmatically,SkyPortal also surfaces an extensive and well-documented application programming interface system. From back-end and front-end software to data science analysis tools and visualization frameworks, theSkyPortal design emphasizes the reuse and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance,SkyPortal now leverages ChatGPT large language models to generate and surface source-level human-readable summaries automatically. With the imminent restart of the next generation of gravitational-wave detectors,SkyPortal now also includes dedicated multimessenger features addressing the requirements of rapid multimessenger follow-up: multitelescope management, team/group organizing interfaces, and crossmatching of multimessenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for newcomers to the field. This paper focuses on the detailed implementations, capabilities, and early science results that establishSkyPortal as a community software package ready to take on the data science challenges and opportunities presented by this next chapter in the multimessenger era. -
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
-
Abstract We analyze a sample of 45 Type II supernovae from the Zwicky Transient Facility public survey using a grid of hydrodynamical models in order to assess whether theoretically driven forecasts can intelligently guide follow-up observations supporting all-sky survey alert streams. We estimate several progenitor properties and explosion physics parameters, including zero-age main-sequence (ZAMS) mass, mass-loss rate, kinetic energy, 56 Ni mass synthesized, host extinction, and the time of the explosion. Using complete light curves we obtain confident characterizations for 34 events in our sample, with the inferences of the remaining 11 events limited either by poorly constraining data or the boundaries of our model grid. We also simulate real-time characterization of alert stream data by comparing our model grid to various stages of incomplete light curves (Δ t < 25 days, Δ t < 50 days, all data), and find that some parameters are more reliable indicators of true values at early epochs than others. Specifically, ZAMS mass, time of the explosion, steepness parameter β , and host extinction are reasonably constrained with incomplete light-curve data, whereas mass-loss rate, kinetic energy, and 56 Ni mass estimates generally require complete light curves spanning >100 days. We conclude that real-time modeling of transients, supported by multi-band synthetic light curves tailored to survey passbands, can be used as a powerful tool to identify critical epochs of follow-up observations. Our findings are relevant to identifying, prioritizing, and coordinating efficient follow-up of transients discovered by the Vera C. Rubin Observatory.more » « less
-
Abstract We present
nimbus : a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on nondetections. This framework makes use of GW 3D distance information and electromagnetic upper limits from multiple surveys for multiple events and self-consistently accounts for the finite sky coverage and probability of astrophysical origin. The framework is agnostic to the brightness evolution assumed and can account for multiple electromagnetic passbands simultaneously. Our analyses highlight the importance of accounting for model selection effects, especially in the context of nondetections. We show our methodology using a simple, two-parameter linear brightness model, taking the follow-up of GW190425 with the Zwicky Transient Facility as a single-event test case for two different prior choices of model parameters: (i) uniform/uninformative priors and (ii) astrophysical priors based on surrogate models of Monte Carlo radiative-transfer simulations of KNe. We present results under the assumption that the KN is within the searched region to demonstrate functionality and the importance of prior choice. Our results show consistency withsimsurvey —an astronomical survey simulation tool used previously in the literature to constrain the population of KNe. While our results based on uniform priors strongly constrain the parameter space, those based on astrophysical priors are largely uninformative, highlighting the need for deeper constraints. Future studies with multiple events having electromagnetic follow-up from multiple surveys should make it possible to constrain the KN population further. -
Over the past decade wide-field optical time-domain surveys have increased the discovery rate of transients to the point that ≲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 multiwavelength follow-up. This algorithm is part of the Finding Luminous and Exotic Extragalactic Transients (FLEET) 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.more » « less