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astro-ph.GA2026
Search for quasar pairs with Gaia astrometric data. II. Photometric redshift prediction with machine learning for the MGQPC catalogue
Xingyu Zhu, Qihang Chen, Liang Jing +4
The identification of physically associated kiloparsec-scale quasar pairs is important for understanding galaxy evolution, the growth of supermassive black holes, and their co-evol…
astro-ph.GA2026
Photometric Redshift PDFs via Neural Network Classification for DESI Legacy Imaging Surveys and Pan-STARRS
Da-Chuan Tian, Zhong-Lue Wen, Jun-Qing Xia
We present a neural network classification (NNC) method for photometric redshift estimation that produces well-calibrated redshift probability density functions (PDFs). The method…
astro-ph.GA2026
A Quasar Pair Sample Compiled from DESI DR1
Liang Jing, Qihang Chen, Zhuojun Deng +4
Interacting quasar pairs (QPs, either dual or binary) provide crucial insights into galaxy mergers, black hole growth, and large-scale structure formation. The current literature r…