In this case study, we hear from Alix Freckelton, a PhD student in Physics and Astronomy, who is exploring transit timing variations (TTVs).
My research focuses on transit timing variations (TTVs): these are tiny irregularities in the times that we see exoplanets transiting their host stars. TTVs are caused in multi-planet systems by the planets gravitationally pulling on each other.
In order to determine the properties of the planets, I compare the observed transit times with thousands of possible dynamical models generated with TTVFast. Each of these models integrates the planetary orbits and predicts when transits will occur. From this, I can infer the masses and orbital properties of the planets that are most consistent with our observations.
This is hugely computationally expensive – one single fit requires hundreds of thousands of TTVFast runs across a massive parameter space, inside Markov Chain Monte Carlo sampling. Running this on my laptop would be slow and impractical; BlueBEAR allows me to submit multiple jobs, test alternative assumptions, and quickly obtain solutions that would take years on a standard machine.
The results will determine how planet interactions shape our observations, and place strong constraints on the properties of the planets I’m characterising. BlueBEAR has been essential, allowing me to transform a handful of individual transit time measurements into a vast dynamical picture of an exoplanetary system.
We were so pleased to hear how Alix was able to make use of what is on offer from Advanced Research Computing. If you have any examples of how it has helped your research, then do get in contact with us at bearinfo@contacts.bham.ac.uk.
We are always looking for good examples of the use of High Performance Computing to nominate for HPC Wire Awards – see our recent winner for more details.