Uncovering the assembly history of galaxies through population-orbit superposition modelling of IFU data

Modern integral field unit spectrographs offer the ability to map the spatial distribution of the motions, ages, and chemical abundances of stars in galaxies. This unprecedented detailed view of galaxies offered by the data demands equally revolutionary analysis and modelling tools. Rather than simple integrated quantities within a given projected spatial region, the population-orbital superposition method developed in our group allows for the recovery of the intrinsic distributions of ages, chemical abundances and kinematics of separate structures within a galaxy.
I will present applications of our method to a large sample of CALIFA galaxies across the Hubble sequence and to galaxies in the Fornax cluster observed with the VLT/MUSE IFU that have led to several interesting results, including: (1) robust orbit-based bulge-disk decompositions and age inferences of each component in present-day galaxies across the Hubble sequence, (2) quantification of environmental effects on cold-disk formation in Fornax cluster galaxies, and (3) first-ever recovery of ancient massive mergers in two galaxies outside the Local Group based on a chemo-dynamical decomposed ‘hot inner stellar halo’ as relics of these merger events.  Our population-orbit superposition method, when applied to extended deep IFU data and in combination with cosmological galaxy simulations, can quantitatively unravel the assembly history of a large number of nearby galaxies.

Speaker: 
Ling Zhu (SHAO)
Place: 
KIAA-auditorium
Host: 
Jing Wang
Time: 
Thursday, April 25, 2024 - 3:30PM to Thursday, April 25, 2024 - 4:30PM
Biography: 
I am a researcher in Shanghai Astronomical Observatory since 09/2018. Before joining SHAO, I was a postdoc researcher at the Max Planck Institute for Astronomy, Heidelberg, Germany from 2013-2018. I got my Ph.D. degree at the Center for Astrophysics, Tsinghua University in 2013. My research focus on galactic structure and dynamics.