Andrew Pontzen (Jacobsohn Memorial Lecturer), University College London
Monday, April 30, 2018 - 4:00pm to 5:00pm
PAA A-102
The next generation of astronomical observatories bring a realistic prospect of paradigm-shifting constraints on the nature of dark matter and dark energy. But to interpret data from these observatories we require numerical simulations of the formation of galaxies and large-scale-structure.
I will discuss the unique computational challenges that such simulations pose. On the one hand we wish to simulate large volumes to gain representative samples of galaxies and to understand the cosmological implications of forthcoming survey data from LSST, Euclid and DESI. On the other, we also want to maintain very high resolution to resolve highly non-linear astrophysical processes and internal kinematics for forthcoming galaxy IFU studies like MaNGA. These two requirements result in a tension on how to best spend limited computer time.
I will argue that a new approach to simulations, in which we use statistical models to tailor cosmological initial conditions for different questions, can help relieve this tension. I will show a range of applications from large scale power spectrum estimation to the astrophysical biases introduced by galaxy formation.
I will discuss the unique computational challenges that such simulations pose. On the one hand we wish to simulate large volumes to gain representative samples of galaxies and to understand the cosmological implications of forthcoming survey data from LSST, Euclid and DESI. On the other, we also want to maintain very high resolution to resolve highly non-linear astrophysical processes and internal kinematics for forthcoming galaxy IFU studies like MaNGA. These two requirements result in a tension on how to best spend limited computer time.
I will argue that a new approach to simulations, in which we use statistical models to tailor cosmological initial conditions for different questions, can help relieve this tension. I will show a range of applications from large scale power spectrum estimation to the astrophysical biases introduced by galaxy formation.
Watch a video of the talk here.