Quasars behind the Galactic Plane (GPQs) are important astrometric references and useful probes of Milky Way gas, yet difficult to find. This project aims to select quasar candidates at |b| <= 20 deg with Machine Learning, and identify the candidates with optical telescopes.
1. Candidate selection methods and the GPQ candidate catalog
The paper (Fu et al 2021 ApJS 254 6):
Title: Finding Quasars behind the Galactic Plane. I. Candidate Selections with Transfer Learning.
ADS: https://ui.adsabs.harvard.edu/abs/2021ApJS..254....6F/abstract
DOI: 10.3847/1538-4365/abe85e
arXiv: 2102.09770
Bibcode: 2021ApJS..254….6F
The GPQ candidate catalog:
Description page: https://nadc.china-vo.org/article/20200722160959?id=101051
Download link: http://paperdata.china-vo.org/FuYuming/table-05.fits