LSTM-MDNz: Estimating Quasar Photometric Redshifts with an LSTM-augmented Mixture Density Network

Quasar photometric redshifts are essential for studying cosmology and large-scale structures. However, their complex spectral energy distributions cause significant redshift–color degeneracy, limiting the accuracy of traditional methods. To overcome this, we introduce long short-term memory (LSTM)-M...

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書誌詳細

主要な著者:	Jianzhen Chen, Zhijian Luo, Liping Fu, Zhu Chen, Hubing Xiao, Shaohua Zhang, Chenggang Shu
フォーマット:	Artigo
言語:	Inglês
出版事項:	IOP Publishing 2026-01-01
シリーズ:	The Astrophysical Journal Supplement Series
主題:	Astrostatistics Astronomy data analysis Photometry Sky surveys Redshift surveys Computational astronomy
オンライン･アクセス:	https://doi.org/10.3847/1538-4365/ae2eb2
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