In the Spotlight: Clara Pennock

Dr Clara Marie Pennock is a Postdoctoral Research Associate at the University of Edinburgh. The focus of her research is multi-wavelength population studies of active galactic nuclei (AGN) and how they evolve with their host galaxies across cosmic time. This includes a current focus on AGN as seen in the X-ray and radio, as well as implementing machine learning to locate and characterise AGN.

 Tell us a bit about your work in LSST:UK.

My most recent research showed that there is a complex relationship between the radio (from jets) and X-ray (from the accretion disk and a corona) emission produced by AGN, especially for the brightest (and rarest) sources. The data provided by the LSST will cover half the sky, which can be cross-matched with ongoing X-ray (e.g. eROSITA) and radio (e.g. MeerKAT, ASKAP) surveys to further study this relationship.

Furthermore, LSST will provide variability information, which, in the optical, can be linked to changes in the accretion disk; seeing how these match up (or not) with X-ray and radio measurements could provide some insight on how the different structures of an AGN affect/interact with each other. Lastly, such a large dataset cannot be explored by humans alone, so I aim to use machine learning to find both the mundane and the rare.

What excites you most about the Rubin LSST?

The large area coverage, the depth and variability. AGN make up a small fraction of all galaxies, and not all of these are detected in the X-ray and/or radio, and not all X-ray/radio detected AGN are detected in the optical (e.g. due to being too faint and/or obscured). The depth of this survey will allow us to find faintest/most obscured AGN while the large coverage will allow us to build a population of the brightest and rarest sources – the comparison of these two populations could provide insight onto how AGN evolve across cosmic time.

AGN are also known to be variable sources, the faintest of which tend to be the most variable, so the many repeated observations LSST will provide over the next 10 years will allow us to discover extreme variability events, as well as long term variability, which could indicate changes in accretion.

What motivates/inspires you to do the work you do?

AGN are some of the most powerful objects in the Universe, yet they originate from such a small space at the centre of a galaxy. They remain mostly unresolved at all wavelengths, so we have to infer their structure using non-direct methods (e.g. reverberation mapping), making it an ever-changing field as we try to discover how AGN actually work. Discovering new aspects of AGN that no one else has come across is most certainly motivating.

What do you predict will be the most challenging thing about working with the LSST data?

The sheer amount of data to work with. I work on population studies of AGN across multiple wavelengths so I'm used to working with large data sets, but this will be on an entirely different level!

How did you end up doing what you do?

My Dad is an amateur astronomer – that was definitely the start of my inspiration. One of my earliest memories is of watching the total solar eclipse in 1999 while sitting on my Dad’s shoulders. I did an undergraduate at the University of Nottingham in Physics with Astronomy and one of the modules was on extreme astrophysics, among which were AGN. From there I was fascinated by these super powerful objects capable of producing large relativistic jets and affecting the evolution of their host galaxies.

Next, I took a PhD at Keele University with Dr. Jacco van Loon to use machine learning to find and characterise AGN behind the Magellanic Clouds using multi-wavelength surveys. Now I find myself a postdoc at the University Edinburgh, looking at the X-ray and radio properties of AGN and how they relate to each other, as well as finding new ways to implement machine learning to help with my research. 

 What's your favourite thing about working in astronomy?

There's always something new to learn.

What do you enjoy doing outside of work?

Reading, baking, drawing, gaming, walking and photographing (including what I bake/draw, things I see on my walks).

If you weren't working in this field what would your dream job be?

Something more artistic, perhaps? Maybe a video game artist, bringing stories to life through art – perhaps with an astronomy theme.

What's your advice for anyone aspiring to do the kind of work you do?

Never stop being curious. And don't be afraid of not knowing the answer to something: it might be that no one truly knows the answer and maybe you'll be the one to discover it.