What is it about?
We use the output of a physical model of galaxy formation to learn the connection between the intrinsic properties of a galaxy, such as its stellar mass, and its observable properties, for example, the brightness or magnitude in different filters used to image the galaxy.
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Why is it important?
We establish the connection using a technique called symbolic regression -- this results in a simple equation that explains how the observable quantities can be used to predict the number of stars in a galaxy.
Perspectives
This is explainable AI. A more general symbolic regression can be counter productive, with many "possible" terms returned giving unweidly equations.
Professor Carlton M. Baugh
Durham University
Read the Original
This page is a summary of: The PAU Survey: Uncovering the connection between intrinsic and observed galaxy properties using symbolic regression, Monthly Notices of the Royal Astronomical Society, July 2026, Oxford University Press (OUP),
DOI: 10.1093/mnras/stag1332.
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