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Sara Ellison

Sara  Ellison
Position
Professor
Physics and Astronomy
Contact
Office: Elliott 208
Area of expertise

Multi-wavelength studies of galaxies and AGN, QSO absorption lines

Astronomy Research

My main research interests can be divided into two basic categories: quasar absorption lines and galaxy evolution as a function of environment. The underlying theme of this research is to understand galaxy evolution through cosmic time, with a particular focus on chemical enrichment of the interstellar and intergalactic media. The work is built on three pillars which span the main tools we use to study galaxy evolution: observations, simulations and machine learning.

My research has been funded by NSERC Discovery grants ($821,695, from 2007-2023), a $120,000 NSERC Discovery Accelerator grant (2007-2010) and half a million dollars in infrastructure from CFI (2003-2012).

A list of past and current students and postdocs in my  and a full list of  is available..

Observational studies

My group has made extensive use of large observational datasets to tackle a broad range of questions in the field of galaxy evolution. We are perhaps most well known for our work on galaxy mergers, where we have used the SDSS to extensively characterize the effect of interactions at low redshift with superlative statistics. This work has been complemented by both public and PI multi-wavelength observations spanning the X-ray to the radio, in order to study  and . Most recently, we have been extending this work to study spatial variations of merger-induced star formation and chemistry using the MaNGA IFU survey.

Other recent observational projects have tackled the physical processes responsible for , the gas content and , searching for (and finding!) , galaxy morphologies, compact groups and  and using .

Finally, I continue to work actively in the field of QSO absorption line spectroscopy. Most significant recent projects in this domain include the  large program (on which I was co-PI) and the . Within the XQ-100 project, I led the DLA science working group, which has contributed to the census of both  and  at high redshift.

Simulation studies

To complement the observational work in my group, I maintain close ties with theoretical colleagues, and support galaxy simulation research in my group. Again, this work has had a significant focus on galaxy mergers, using a range of cosmological, zoom-in and binary galaxy simulations. Recent work includes the study of the impact of , the use of  and tracing the . I also work closely with the group of Hugo Martel to simulate the . All of the above projects aim to make direct comparisons with simulations and data, or even directly merge the two by producing . 

Machine learning

The availability of massive public galaxy surveys, such as the SDSS, has revolutionized the power of archival research in extra-galacic astronomy. Multi-wavelength complements, over large fractions of the sky, leverage incredible diagnostic power, at energies ranging from the UV (e.g. GALEX) to the mid-IR (e.g. WISE) all the way to the radio (e.g. ALFALFA). This revolution is set to continue in the coming decades with even more massive datasets from projects such as Euclid and LSST. My group has been at the leading edge of using machine learning techniques in astronomy, publishing on topics that range from predictions of  and , to analysing the likely physical mechanisms that .

In recognition of the enormous scope of machine learning applications in extra-galactic astronomy, I lead the GalNet collaboration, one branch of UVic's ARCNet research centre.