Bibliographic Information: Wu, Q., Scialpi, M., Liao, S., Mannucci, F., & Qi, Z. (2024). DULAG: A DUal and Lensed AGN candidate catalog with GMP method. Astronomy & Astrophysics manuscript no. aa.
Research Objective: This paper aims to create a larger, highly reliable catalog of AGN pair candidates using the Gaia Multi-Peak (GMP) method, expanding beyond spectroscopically confirmed AGNs to include candidates from the Gaia quasar candidate catalog.
Methodology: The researchers analyzed astrometric and multi-band color data from Gaia DR3, Milliquas catalog, and other surveys. They compared the properties of spectroscopically confirmed AGN pairs with single AGNs to establish selection criteria for identifying potential pairs among the Gaia quasar candidates. These criteria included specific thresholds for parallax, proper motion, WISE infrared colors (W1-W2), and Gaia optical colors (BP-G and G-RP). Two catalogs were generated: a comprehensive superset with potential contaminants and a highly reliable "Golden" sample with stricter selection criteria.
Key Findings: The study found significant differences in the astrometric and color properties of AGN pairs compared to single AGNs. AGN pairs tend to have larger parallaxes and proper motions, bluer infrared colors, and distinct optical color distributions. Applying the defined selection criteria, the researchers identified 5,286 AGN pair candidates for the superset and 1,867 candidates for the Golden sample.
Main Conclusions: The DULAG catalog, particularly the Golden sample, provides a valuable resource for identifying and studying dual and lensed AGNs. The study demonstrates the effectiveness of the GMP method in identifying AGN pairs with varying separations and highlights the importance of considering astrometric and multi-band color information in candidate selection.
Significance: This research significantly expands the number of potential AGN pair candidates, enabling more comprehensive studies of these systems and their role in galaxy evolution and black hole growth.
Limitations and Future Research: The study acknowledges limitations in the accuracy of photometric redshifts and the potential for contamination in the superset. Future research could focus on obtaining spectroscopic confirmation for the candidates and further refining the selection criteria using machine learning techniques.
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by Qiqi Wu, M. ... at arxiv.org 11-12-2024
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