Science and Exploration

An Astronomer’s Guide to Machine Learning

By Keith Cowing
Status Report
April 4, 2023
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An Astronomer’s Guide to Machine Learning
Example of real time processed candidate images, taken from a past operational run of DWF. Each panel is a small, 121 × 121 pixel image that corresponds to ∼ 30 × 30 arcsec on the sky centred on the candidate. The left panel is the (deeper) template image taken at a time previous to the DWF observations, the central panel is the current science image of the sky taken minutes earlier, and the subtraction image is the digital subtraction of the two images. All constant flux is subtracted, and any flux difference, e.g. from a transient source, will remain in the subtracted image. — astro-ph.IM

With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work.

This proceeding aims to give an overview of what machine learning is and delve into the many different types of learning algorithms and examine two astronomical use cases. Machine learning has opened a world of possibilities for us astronomers working with large amounts of data, however if not careful, users can trip into common pitfalls.

Here we’ll focus on solving problems related to time-series light curve data and optical imaging data mainly from the Deeper, Wider, Faster Program (DWF). Alongside the written examples, online notebooks will be provided to demonstrate these different techniques. This guide aims to help you build a small toolkit of knowledge and tools to take back with you for use on your own future machine learning projects.

Sara A. Webb, Simon R. Goode

Comments: 12 pages, 5 Figures, International Astronomical Union Proceedings Series 368
Subjects: Instrumentation and Methods for Astrophysics (astro-ph.IM)
Cite as: arXiv:2304.00512 [astro-ph.IM] (or arXiv:2304.00512v1 [astro-ph.IM] for this version)
Submission history
From: Sara Webb
[v1] Sun, 2 Apr 2023 11:03:48 UTC (2,339 KB)

SpaceRef co-founder, Explorers Club Fellow, ex-NASA, Away Teams, Journalist, Space & Astrobiology, Lapsed climber.