2019/09/30 by Kirill Grishin, Grishin, Kirill A., Igor Chilingarian +5
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Fluorescence Microscopy Techniques #Advanced Optical Sensing Technologies #Astronomy and Astrophysical Research #Astrophysics of Galaxies (astro-ph.GA) #Data Visualization and Analytics #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Instrumentation and Methods for Astrophysics (astro-ph.IM)
paper · pdf · doi:10.48550/arxiv.1909.13460
openalex publication_date 2019/09/30 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28
Observational studies of ultra-diffuse galaxies (UDGs) represent a\nsignificant challenge because of their very low surface brightnesses. A\nfeasible approach is to identify "future" UDGs when their stars are still\nyoung. Using data mining, we found 12 such low-mass spatially extended\nquiescent galaxies in the Coma and Abell 2147 clusters in the SDSS legacy\ngalaxy sample and followed them up using a new high-throughput Binospec\nspectrograph at the 6.5m MMT. Several of them exhibit signs of the recently\nfinished ram pressure stripping. Here we describe our data analysis approach\nthat uses spectroscopic and photometric measurements with a dedicated set of\nstellar population models, which include realistic chemical enrichment and star\nformation histories. From our analysis we can precisely estimate stellar\nmass-to-light ratios and dark matter content of UDGs.\n