Dr. Ashley R. Bemis
Leiden Observatory Research Associate
The main goal of my research is to better-understand the process of star formation, its connection to dense gas, and its dependence on environment within nearby (z~0) galaxies. I work extensively with observations in the radio regime using data from the Atacama Large Millimeter and sub-millimeter Array, the James Clerk Maxwell Telescope, the Sub-Millimeter Array, and others.
My PhD thesis work (completed October 2020) focused on the relationship between dense gas (primarily as traced by HCN) and star formation (as traced by IR and radio continuum emission) in more-extreme environments than those found in the disks of normal galaxies (mergers, Ultra-Luminous Infrared Galaxies, and galaxy centers). The data were compared to the predictions of theoretical models of star formation (cf. Krumholz & McKee 2005, Padoan & Nordlund 2011, Hennebelle & Chabrier 2011, Federrath & Klessen 2012, Burkhart 2018), in addition to emissivities modeled using the radiative transfer code RADEX (van der Tak et al. 2007).
The following projects are being completed outside of my PhD and incorporate the modeling of my thesis work:
- A comparison of HCN and HCO+ emission across the galaxies studied in my thesis using archival ALMA data. Preliminary results were presented at The Laws of Star Formation Conference, Cambdridge, UK in 2018 without modeling incorporated. Initial results with modeling incorporated (excluding HCO+) were presented in an invited talk at the AAS Summer 2020 meeting.
- A comparison of molecular emission, including multi-J emission of dense gas tracers HCN & HCO+, to independent gas mass tracers (i.e. dust) in Milky Way clouds. This will make use of archival data from the Herschel Gould Belt Survey.
During my postdoctoral studies, I plan to:
- Image cloud-scale CN emission across the Antennae Galaxies, and compare cloud-scale CO and CN emission across this system with star formation rate tracers.
- A multi-J anlaysis of HCN and HCO+ emission at selected sightlines across the Antennae using SMA data (PI project SMA 2018B-S022).