Numerical Studies of the Circumgalactic Medium

The circumgalactic medium (CGM) is the gas surrounding a galaxy. Because it is generally quite tenuous, detecting its emission is difficult; however, it is readily seen in absorption when it falls in the line of sight of a bright background quasar. Numerous recent observational studies have begun to correlate the strength of different atomic absorption lines with their apparent distance to different types of galaxies. Since each atomic absorption line occurs in a small density, temperature, and metallicity regime of gas, we are slowly reaching a point where we can describe how the state of the CGM changes with distance to a galaxy.

In order to better understand the nature of the CGM and its implications for star formation and stellar feedback, theorists are attempting to make mock obserservations of the simulated CGM around some galaxies found in our cosmological hydrodynamic simulations. I recently wrote a paper describing one such study, where I use a grid-based hydrodynamics code, Enzo, to simulate a large chunk of the Universe from z = 100 to present, following the evolution of a single Milky-Way-massed galaxy at high-resolution. I then created mock observations of the galaxy to determine the concentration of various atomic absorption species throughout its CGM to compare against the observational studies. I ran several such simulations of the same galaxy, where I only varied the stellar feedback prescription, that is, how much energy gets released when stars turn into supernovae, to see which galaxy's mock observations would best fit the observational data. Our results indicate that none of the models do a perfect job of matching the observational data, but there are some partial matches. This suggests that theorists still lack methods for prescribing how feedback returns supernovae energy to the surrounding gas.

I have included here a tarball containing tab-delimited textfiles with the resulting data from these models. These files are the data used to produce Figures 2, 3, 4, and 5 of Hummels et al. 2013, and I include them so that other scientists who want to compare against this work are able to do so easily. If there are any questions or comments on this data (or the study in general), please do not hesitate to contact me.

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