Visualising the input space of a Galaxy Formation Simulation Seminar
- Date:
- 10 November 2011
- Venue:
- Building 54 Room 10037
For more information regarding this seminar, please email Mrs Jane Revell at j.revell@southampton.ac.uk .
Event details
Building 54 Room 10037
Abstract
The question of whether there exists large quantities of Dark Matter in our Universe is one of the most important problems in modern cosmology. This project deals with a complex model of the Universe known as Galform, developed by the ICC group, at Durham University. This model simulates the creation and evolution of approximately 1 million galaxies from the beginning of the Universe until the current day, a process which is very sensitive to the presence of Dark Matter. A major problem that the cosmologists face is that Galform requires the specification of a large number of input parameters in order to run. The outputs of Galform can be compared to available observational data, and the general goal of the project is to identify which input parameter specifications will give rise to acceptable matches between model output and observed data, given the many types of uncertainty present in such a situation. As the model is slow to run, and the input space large, this is a very difficult task. We have solved this problem using general techniques related to the Bayesian treatment of uncertainty for computer models. These techniques are centred around the use of emulators: fast stochastic approximations to the full Galform model. These emulators are used to perform an iterative strategy known as history matching, which identifies regions of the input space of interest. Visualising the results of such an analysis is a non-trivial task. The acceptable region of input space is a complex shape in high dimension. Although the emulators are fast to evaluate, they still cannot give detailed coverage of the full volume. We have therefore developed fast emulation techniques specifically targeted at producing lower dimensional visualisations of higher dimensional objects, leading to novel, dynamic 2- and 3-dimensional projections of the acceptable input region. These visualisation techniques allow full exploitation of the emulators, and provide the cosmologists with vital physical insight into the behaviour of the Galform model. This talk will report on much of the work as featured in "Galaxy Formation: A Bayesian Uncertainty Analysis", I Vernon, M Goldstein and R G Bower (2010), Bayesian Analysis 05(04): 619--670 (with discussion), which was awarded the 2010 Mitchell Prize for best applied Bayesian analysis paper.
Speaker information
Dr Ian Vernon , Durham University. Lecturer in the Department of Mathematical Sciences