TelescopeML. II. Convolutional Neural Networks for Predicting Brown Dwarf Atmospheric Parameters

TelescopeML. II. Convolutional Neural Networks for Predicting Brown Dwarf Atmospheric Parameters

Accurately and swiftly predicting the parameters of brown dwarf atmospheres from observational spectra is crucial for understanding their atmospheric composition and guiding future follow-up observations. Here, we utilized convolutional neural networks (CNNs) as a high-performance deep learning algo...

Full description

Saved in:
Bibliographic Details
Main Authors: Ehsan (Sam) Gharib-Nezhad, Hamed Valizadegan, Natasha E. Batalha, Miguel J. S. Martinho, Ben W.P. Lew
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal
Subjects:
Brown dwarfs
Convolutional neural networks
T dwarfs
Atmospheric composition
Online Access:https://doi.org/10.3847/1538-4357/ada1d2
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items