Identifying merging galaxies in MaNGA using H-α and Hi observations

• Main Authors: Danial Ahmad Ariffin Lee, Zamri Zainal Abidin, Abdul Kadir Md Jwel, Mohd Shaiful Rizal Hassan
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2022
• Online Access: http://journalarticle.ukm.my/20247/1/20.pdf; http://journalarticle.ukm.my/20247/; https://www.ukm.my/jsm/malay_journals/jilid51bil7_2022/KandunganJilid51Bil7_2022.html
• Institution: Universiti Kebangsaan Malaysia

Reliable methods that could recognise and distinguish galactic mergers are important for better understanding of galaxy evolution. This paper explores the feasibility of using observations on Hα and HI as a method to identify mergers. Sixty sample galaxies were carefully selected from the MaNGA DR15 database and cross-checked with the MaNGA Deep Learning DR15 Morphology to determine the merger signature. The chosen galaxies were divided into two groups, where galaxies with P M E RG < 0.5 were selected as non-merging galaxies and galaxies with P M E RG > 0.8 were selected as mergers. The Hα emission line plot and Hα velocity maps were obtained from the MaNGA DR15 database while HI data comes from HI-MaNGA DR1 catalogue for all 60 galaxies. Seventeen of the 30 merging galaxies have more than Hα blobs (28.3% of the 60 galaxies) compared to 14 of the 30 non-merging galaxies (23.3%). Fourteen of the mergers (23.3% of 60 galaxies) have asymmetric Hα velocity plots compared to 8 of the non-mergers. Thirteen of the mergers have a well-defined HI peak (21.7%) versus 11 of the non-merging galaxies (18.3%). These parameters were found to be a feasible new method in determining merging galaxies in the universe.