K-contact Distance for Noisy Nonhomogeneous Spatial Point Data and Application to Repeating Fast Radio Burst Sources
Amanda M. Cook · Oct 10, 2025
Date: 2025-10-10
Time: 15:30-16:30 (Montreal time)
Location: In person, Burnside 1104
https://mcgill.zoom.us/j/81986712072
Meeting ID: 819 8671 2072
Passcode: None
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.