skip to main content

Search for: All records

Creators/Authors contains: "Coughlin, Michael"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. The recent application of neural network algorithms to problems in gravitational-wave physics invites the study of how best to build production-ready applications on top of them. By viewing neural networks not as standalone models, but as components or functions in larger data processing pipelines, we can apply lessons learned from both traditional software development practices as well as successful deep learning applications from the private sector. This paper highlights challenges presented by straightforward but naïve deployment strategies for deep learning models, and identifies solutions to them gleaned from these sources. It then presents HERMES, a library of tools for implementingmore »these solutions, and describes how HERMES is being used to develop a particular deep learning application which will be deployed during the next data collection run of the International Gravitational-Wave Observatories.« less
    Free, publicly-accessible full text available June 27, 2023
  2. Free, publicly-accessible full text available May 1, 2023
  3. Abstract The limiting temporal resolution of a time-domain survey in detecting transient behavior is set by the time between observations of the same sky area. We analyze the distribution of visit separations for a range of Vera C. Rubin Observatory cadence simulations. Simulations from families v1.5–v1.7.1 are strongly peaked at the 22 minute visit pair separation and provide effectively no constraint on temporal evolution within the night. This choice will necessarily prevent Rubin from discovering a wide range of astrophysical phenomena in time to trigger rapid follow-up. We present a science-agnostic metric to supplement detailed simulations of fast-evolving transients andmore »variables and suggest potential approaches for improving the range of timescales explored.« less
    Free, publicly-accessible full text available January 1, 2023
  4. 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
  5. 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,more »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 with simsurvey —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.« less
    Free, publicly-accessible full text available January 1, 2023
  6. Free, publicly-accessible full text available May 5, 2023
  7. 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
  8. Free, publicly-accessible full text available January 1, 2023