| Name: | Alankar Dutta |
| Affiliation: | Indian Institute of Science |
| Conference ID : | ASI2024_656 |
| Title : | Demystifying the multiphase circumgalactic medium |
| Authors : | Alankar Dutta, Prateek Sharma, Ritali Ghosh, Mukesh Singh Bisht, Biman B. Nath, Manami Roy, Dylan Nelson |
| Authors Affiliation: | Alankar Dutta, Prateek Sharma, Ritali Ghosh (Indian Institute of Science)
Mukesh Singh Bisht, Biman B. Nath, Manami Roy (Raman Research Institute)
Dylan Nelson (Heidelberg University) |
| Mode of Presentation: | Oral |
| Abstract Category : | Galaxies and Cosmology |
| Abstract : | The circumgalactic medium (CGM) is the multiphase gaseous medium surrounding galaxies, playing an important role in galaxy evolution. My proposal aims to build a comprehensive understanding of the multiphase CGM through idealized numerical simulations, building models, generating observables and analyzing CGM data from Illustris TNG cosmological simulation.
I will talk about our idealized simulations of galactic outflows with expansion and radiative cooling. Using this, I seek to investigate the crucial role that outflows play in galaxy feedback, quenching and enriching the CGM with metals across large scales. By considering the formation/survival of cold gas, my simulations seek to investigate the condition for the formation of clumpy multiphase outflows observed to be harboring fast moving cold gas (say for example in M82). In this context, I'll also talk about our model of radiative boundary layers that are ubiquitous in these astrophysical systems.
Moreover, we are in an era when optical/FUV line emission maps of CGM are becoming abundant. So will be X-ray observations with high spectral resolution and radio FRB dispersion measures mapping the Milky Way CGM. Considering this, I will talk about our recent work on probabilistic CGM models along with a suite of multiwavelength synthetic observables. I will highlight why such modeling is timely and how it sets the groundwork that would enable benchmarking models against recent and upcoming observations and develop strategies for future models and simulations. |
