Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation

We present Mantis Shrimp , a multisurvey deep learning model for photometric redshift estimation that fuses ultraviolet (Galaxy Evolution Explorer), optical (PanSTARRS), and infrared (UnWISE) imagery. Machine learning is now an established approach for photometric redshift estimation, with generally...

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Bibliographic Details
Published in:	The Astrophysical journal Vol. 991; no. 2; pp. 124 - 149
Main Authors:	Engel, Andrew W., Byler, Nell, Tsou, Adam, Narayan, Gautham, Bonilla, Emmanuel, Smith, Ian
Format:	Journal Article
Language:	English
Published:	Philadelphia The American Astronomical Society 01.10.2025 IOP Publishing
Subjects:	Artificial neural networks Astronomy data analysis Computer vision Deep learning Density Estimates Galactic evolution Galaxies Galaxy distribution Infrared imagery Infrared photometry Machine learning Neural networks Photometry Red shift Redshift surveys Resampling Shellfish Shrimps
ISSN:	0004-637X, 1538-4357
Online Access:	Get full text
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