Amanda Cook

Title: K-contact distance for noisy nonhomogenous spatial point data and application to repeating fast

Date: Thursday, May 28th 2026
Time: 1:30PM (PDT)
Location: AQ 5037

Abstract: In this talk, I’ll introduce an approach to analyze nonhomogeneous Poisson processes (NHPP) observed with noise which focuses on previously unstudied second-order characteristics of the noisy process. Utilizing a hierarchical Bayesian model with noisy data, we first estimate hyperparameters governing a physically motivated NHPP intensity. Leveraging the posterior distribution, we then infer the probability of detecting a certain number of events within a given radius, the k-contact distance. This methodology is demonstrated by its motivating application: observations of fast radio bursts (FRBs) detected by the Canadian Hydrogen Intensity Mapping Experiment's FRB Project (CHIME/FRB). The approach allows us to identify repeating FRB sources by computing the probability of observing k physically independent sources within some radius in the detection domain, or the probability of coincidence (P_C). Applied, the new methodology improves the repeater detection P_c, in 86% of cases when applied to the largest sample of previously classified observations, with a median improvement factor (existing metric over P_C from our methodology) of ~ 3000. Throughout the talk, I will provide the necessary astrophysical context to motivate the application and highlight some of the other active statistical problems in FRB science.