Galactic winds are huge flows of matter driven out of the discs of galaxies by feedback from star formation and black hole accretion. Winds play a decisive role in shaping galaxy evolution; without them, our Milky Way would be much more massive than we actually observe, and would likely have already exhausted its supply of gas and transformed into a “red and dead” passive galaxy. While we now have many direct observations of outflows, and we have general ideas from models how much mass those outflows should carry, turning our observations into quantitative estimates of outflow mass fluxes that can be compared to theoretical predictions has proven difficult. Outflows have complex, three-dimensional structures that we can observe only in projection, and the mass can be carried by a range of different gas phases that are best probed in different parts of the electromagnetic spectrum. As a result of this complexity, estimates of outflow mass fluxes are often rely on extreme simplifying assumptions (e.g., spherical symmetry), and are uncertain by orders of magnitude.

The goal of this project is to build on a combination of simulations and improved theoretical understanding to develop improved mass flux estimation techniques for galactic winds, and to apply these techniques to observations of nearby galaxies where the data are best. A pilot study on M82, perhaps the best-studied galactic outflow (see figure), demonstrates that these new methods can reduce the uncertainties on the mass fluxes in at least some phases from orders of magnitude to tens of percent, for the first time making the measurement quality high enough that it is possible to begin testing theoretical models. This PhD will involve applying similar techniques to other galaxies with high-quality galactic wind data, and improving the robustness of the methods so that they can be used reliably for more distant systems where the data quality is lower.

Relevant papers: 

https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.4084Y/abstract

https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.4061K/abstract