Developing a Fully Bayesian Search for the Cosmological Stochastic Gravitational-Wave Background in the Presence of Astrophysical Foregrounds

About This Grant

This award supports research in relativity and relativistic astrophysics, and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. Gravitational waves are ripples in the fabric of spacetime caused by the violent acceleration of extremely compact objects, like black holes and neutron stars smashing together billions of light-years away, or exotic processes in the very early universe. Detecting the primordial stochastic gravitational-wave background is one of the most ambitious goals of gravitational-wave astronomy. This persistent signal that permeates all space encodes information about even earlier moments in the Universe’s history than those we can currently probe with traditional electromagnetic telescopes. The primordial background is likely too weak to be detected with the current LIGO-Virgo-KAGRA instruments that routinely observe gravitational waves from black hole and neutron star mergers, but it could lie within the reach of proposed next-generation detectors. However, even with improved data, existing analysis methods are insufficient for disentangling the contributions of the weak background from the much louder foreground of gravitational waves from compact-object mergers. This project focuses on developing a novel method for detecting the primordial background in the presence of the foreground from merger signals. This award also provides training in data analysis and science communication to the students involved, and to the broader local community via the Gravitational-Wave Open Data Workshops that the PI will host at their institution. This award will lay the groundwork for the data analysis strategies needed for the source-rich data expected for next-generation gravitational-wave detectors, facilitating the detection of the primordial background that would uniquely provide us with a glimpse into the moments immediately after the Big Bang when our Universe burst into existence. This work will be conducted at Princeton University by the PI and a graduate student funded by the award, who will gain experience with statistical data analysis techniques and a deep understanding of the physical concepts underlying the stochastic gravitational-wave background, in addition to opportunities for mentorship, networking, leadership, and career development. The fully Bayesian method for the simultaneous detection and characterization of the primordial stochastic background in the presence of astrophysical foregrounds that will be developed under this award hinges on modeling the statistical differences between the foreground—composed of individual and largely unresolved compact-object mergers—and the persistent, Gaussian, primordial background. Expanding upon the PI’s previous proof-of-concept, this project will specifically 1) investigate the effects on the inference of the primordial background properties of systematic errors introduced by uncertainties in the waveform approximations typically used in Bayesian inference of the gravitational-wave signal from individual binary black holes, 2) incorporate the simultaneous inference of the population properties of these binary black hole mergers along with their merger rate and the primordial background properties, and 3) begin to adapt the method to accommodate the foreground of binary neutron star mergers, whose statistical properties differ from those of the binary black hole foreground as the signals overlap in the frequency band of ground-based detectors due to their longer duration. By incorporating simultaneous inference of population properties, we will be able to learn about the high-redshift population of compact-object binaries at current detector sensitivities without detecting any of these events individually, probing the astrophysical processes governing their formation and evolution, which remain largely unknown. The simultaneous Bayesian search will also optimally enable the continued placement of upper limits on the Gaussian background at current detector sensitivities before it becomes detectable, to constrain cosmological sources of gravitational waves such as cosmic strings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.