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Details of Grant 

EPSRC Reference: EP/I030298/1
Title: Rare Events via Parallel Forward Flux Sampling
Principal Investigator: Allen, Professor RJ
Other Investigators:
Stratford, Dr K Marenduzzo, Professor D
Researcher Co-Investigators:
Project Partners:
Department: Sch of Physics and Astronomy
Organisation: University of Edinburgh
Scheme: Standard Research
Starts: 01 October 2011 Ends: 30 September 2013 Value (£): 245,458
EPSRC Research Topic Classifications:
Fundamentals of Computing Gas & Solution Phase Reactions
High Performance Computing Software Engineering
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 Mar 2011 HPC Software Development 2010-11 Announced
Summary on Grant Application Form
Rare events can have extremely important consequences. A recent example is of course the credit crunch of 2008, a global event of a size not seen since the 1930s. A part of the systematic failure to predict this event has been attributed to the failure of the banks' computer models to account properly for these events which, while having very low probability, are of very high import.From the scientific perspective, such a failure is understandable. Simulating rare events is extremely hard. This is for the simple reason that any given computer simulation will simply not see any rare events in any reasonable time. If you are looking for them, most (if not all) of your computational time and effort will be wasted.In our work, we will attempt to improve the situation. To do this, we will combine a powerful new technique for capturing rare events with the use of large supercomputers. The goal of the work is to provide software which will make it easier for scientists to apply this technique (known as Forward Flux Sampling ) to more difficult problems. As an example, the method can be used to study conformational (shape) changes in proteins; rare mistakes in the folding of proteins is thought to play an important role in neurodegenerative diseases. Our new software will help to make the study of such problems more straightforward. It may even help to predict the next financial crisis!
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