What’s the Difference? The Potential for Convolutional Neural Networks for Transient Detection without Template Subtraction

What’s the Difference? The Potential for Convolutional Neural Networks for Transient Detection without Template Subtraction

We present a study of the potential for convolutional neural networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as “real–bogus” classification, without requiring a template-subtracted (or difference) image, which requires a computationally expensive p...

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Bibliographic Details
Main Authors: Tatiana Acero-Cuellar, Federica Bianco, Gregory Dobler, Masao Sako, Helen Qu, The LSST Dark Energy Science Collaboration
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:The Astronomical Journal
Subjects:
Astronomical methods
Convolutional neural networks
Transient detection
Online Access:https://doi.org/10.3847/1538-3881/ace9d8

Internet

https://doi.org/10.3847/1538-3881/ace9d8

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