Searching for Quasi-periodic Oscillations in Astrophysical Transients Using Gaussian Processes

Abstract Analyses of quasi-periodic oscillations (QPOs) are important to understanding the dynamic behavior in many astrophysical objects during transient events like gamma-ray bursts, solar flares, magnetar and fast radio bursts. Astrophysicists often search for QPOs with frequency-domain methods such as (Lomb–Scargle) periodograms, which generally assume power-law models plus some excess around QPO frequency. Time-series data can alternatively be investigated directly time domain using Gaussian process (GP) regression. While GP regression is computationally expensive general case, properties allow likelihood strategies. Heteroscedasticity nonstationarity have been shown cause bias periodogram-based analyses. GPs take account these properties. Using GPs, we model a stochastic on top deterministic flare shape. Bayesian inference, demonstrate how infer hyperparameters assign them physical meaning, We also perform selection between alternative red noise show that this used reliably find QPOs. This method easily applicable variety different sets. use range short transients: burst, flare, giant simulated data.