Rotating Stars and Revolving Planets: Bayesian Exploration of the Pulsating Sky

TL;DR

This paper develops Bayesian methods to detect and analyze periodic signals from pulsars and exoplanets, improving the accuracy and efficiency of astronomical data interpretation.

Contribution

It introduces novel Bayesian techniques tailored for pulsar signal detection and exoplanet orbit estimation, including adaptive observation scheduling.

Findings

Effective detection of pulsar signals in photon arrival data

Accurate estimation of exoplanet orbital parameters

Optimized observation strategies for astronomical surveys

Abstract

I describe ongoing work on development of Bayesian methods for exploring periodically varying phenomena in astronomy, addressing two classes of sources: pulsars, and extrasolar planets (exoplanets). For pulsars, the methods aim to detect and measure periodically varying signals in data consisting of photon arrival times, modeled as non-homogeneous Poisson point processes. For exoplanets, the methods address detection and estimation of planetary orbits using observations of the reflex motion "wobble" of a host star, including adaptive scheduling of observations to optimize inferences.