RUI: Supporting LIGO Calibration, Detector Characterization, and Data Analysis in O4

The fourth observing run (O4) for ground-based gravitational-wave detectors LIGO, Virgo, and KAGRA is scheduled to begin in the spring of 2023. O4 promises to bring the largest network of ground-based gravitational-wave detectors and the best detector sensitivity seen to date. This award supports the Kenyon College LIGO Scientific Collaboration (LSC) group, consisting of PI L. Wade and co-PI M. Wade, and between four and six undergraduate research students, in their research pursuits in the field of gravitational-wave physics. The Kenyon College LSC group will contribute to the operation of the LIGO calibration pipeline and implementation of a novel LIGO calibration monitor, the construction of new machine learning algorithms for predicting the presence of noise artifacts in gravitational-wave strain data using information from detector auxiliary channels, and the development of more robust and sophisticated ways of measuring the neutron-star equation of state. This award also supports two established, impactful astronomy and physics research groups that engage a diverse population of high school and undergraduate students: The Kenyon College Radio and Optical Astronomy Research (ROAR) group and the Mount Vernon High School (MVHS) astronomy club. ROAR is a no-barrier to entry research group that targets recruitment at first- and second-year potential physics majors at Kenyon College. Students in ROAR engage in discussions about current astronomy and gravitational physics research topics, do independent investigations into topics of interest, engage in hands-on astronomy and physics related activities, and contribute to outreach efforts in physics and astronomy. The MVHS astronomy club is run out of the local high school near Kenyon College and regularly engages 10-20 high school students in hands-on activities and research topics in astronomy and gravitational physics. This award has three main research focusses: calibration, data quality, and neutron-star equation of state (EOS) parameter estimation. This award will contribute to the operation of the LIGO calibration pipeline used to produce the final calibrated strain data, which is an effort lead by co-PI M. Wade, development and implementation of a monitoring tool for the low-latency calibrated data stream, and exploration of methods for producing a low-latency calibration systematic error estimate. The second focus area in this award is related to inferring the neutron star EOS from binary neutron star gravitational-wave events. PI L. Wade proposes to improve the flexibility of the parameterized models used to measure the neutron star EOS, develop inference software to marginalize over parameters measured in other contexts, and build software to allow the data to inform the number of parameters to use in the EOS models. Additionally, PI L. Wade will contribute to EOS inference efforts on any binary neutron star signals found in O4. The final set of research activities involve exploring improvements to the low-latency data quality identification system known as iDQ. iDQ uses machine learning algorithms (MLAs) to predict the presence of loud transient noise events, known as glitches, in the strain data using only auxiliary information. PI L. Wade and co-PI M. Wade propose to build hierarchical MLAs that will account for the variability in different auxiliary subsystems and the variability in glitch morphologies, aiming to improve the efficiency with which glitches can be identified in low-latency data, thereby improving the data quality information available to low-latency astrophysical analyses. The final research focus area will be in searching for a newly theorized signal known as a gravitational glint which is produced by perturbers along the line-of-sight from a compact binary event to an observer. If no such signals are found in archival LIGO/Virgo data then upper bounds could be set on the density of perturbers in the universe. 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.