State Space Modelling for detecting and characterising Gravitational Waves afterglows
Daniele d'Antonio, Martin Ellis Bell, James John Brown, Clara Grazian

TL;DR
This paper introduces the application of State Space Models to improve detection and characterization of radio transients and variables in astrophysics, including potential gravitational wave afterglows, offering more detailed analysis than traditional methods.
Contribution
It demonstrates the effectiveness of State Space Models in classifying and detecting astrophysical transients and variables, a novel approach in this field.
Findings
State Space Models outperform traditional methods in variability detection.
The approach can distinguish different types of variability.
Potential to identify gravitational wave afterglows.
Abstract
We propose the usage of an innovative method for selecting transients and variables. These sources are detected at different wavelengths across the electromagnetic spectrum spanning from radio waves to gamma-rays. We focus on radio signals and use State Space Models, which are also referred to as Dynamic Linear Models. State Space Models (and more generally parametric autoregressive models) have been the mainstay of economic modelling for some years, but rarely they have been used in Astrophysics. The statistics currently used to identify radio variables and transients are not sophisticated enough to distinguish different types of variability. These methods simply report the overall modulation and significance of the variability, and the ordering of the data in time is insignificant. State Space Models are much more advanced and can encode not only the amount and significance of the…
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