Bayesian multimessenger search method for common sources of gravitational waves and high-energy neutrinos

• Multimessenger astrophysics is undergoing a transition towards low-latency searches based on signals that could not individually be established as discoveries. The rapid identification of signals is important in order to initiate timely follow-up observations of transient emission that is only detectable for short time periods. Joint searches for gravitational waves and high-energy neutrinos represent a prime motivation for this strategy. Both gravitational waves and high-energy neutrinos are typically emitted over a short time frame of seconds to minutes during the formation or evolution of compact objects. In addition, detectors searching for both messengers observe the whole sky continuously, making observational information on potential transient sources rapidly available to guide follow-up electromagnetic surveys. The direction of high-energy neutrinos can be reconstructed to subdegree precision, making a joint detection much better localized than a typical gravitational-wave signal. Here we present a search strategy for joint gravitational-wave and high-energy neutrino events that allows the incorporation of astrophysical priors and detector characteristics following a Bayesian approach. We aim to determine whether a multimessenger correlated signal is a real event, a chance coincidence of two background events, or the chance coincidence of an astrophysical signal and a background event. We use an astrophysical prior that is model agnostic and takes into account mostly geometric factors. Our detector characterization in the search is mainly empirical, enabling detailed realistic accounting for the sensitivity of the detector that can depend on the source properties. By this means, we can calculate the false alarm rate for each multimessenger event which is required for initiating electromagnetic follow-up campaigns.

Subject headings

NATURVETENSKAP  -- Fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences (hsv//eng)

Publication and Content Type

ref (subject category)

art (subject category)