Theoretical astrophysics makes extensive use of computational methods and resources to model increasingly resolved observations of astronomical objects, phenomena and associated processes, and explore theoretical scenarios that can inform and guide observational campaigns. The detection of gravitational waves resulting from the merger of two black holes provides a recent stunning example of a system where theoretical work, then sophisticated numerical relativity simulations preceded by decades the observational signals which they helped identify.
Within our program, the computational astrophysics track reflects the investment of the department of physics in theoretical astrophysics, and computational physics through the development and optimization of tailor made numerical tools, and/or the adaptation of open source packages to address problems in solar physics, star formation and evolution and astrophysical dynamics (concerned with the formation and evolution of planets, galaxies, galactic nuclei and the supermassive black hole lurking within them).
The track should be of particular interest to students of physics, mathematics and/or computer science who are keen on applications in astronomy and astrophysics. Following a selection of astrophysics electives, a computationally skilled student in the track can engage in the design and optimal deployment of: tools for the solution of systems of partial, ordinary and/or integro-differential equations (all non-linear); Monte Carlo techniques for equilibria of systems with long-range interactions; and, increasingly, machine-learning techniques for sifting through massive observational data sets on one hand, or “replacing” expensive numerical simulations on the other.