Development and applications of high performance computing
Development and applications of high performance computing
In this thesis we demonstrate the application of high performance computing techniques to three scientific problems. The first uses the Maximum Entropy method to determine structure in players' choices of numbers in the UK National Lottery. The resulting equations are solved using an efficient parallel algorithm. We find that players preferentially pick numbers in the centre of the ticket. The second is a model for cooperation in groups, in which the parameter space of the model is explored using task farming. We demonstrate, using a simple model, that it is possible to sustain cooperation in large groups when there is repeated interaction, recognition of the identity of individual participants, and memory of the outcomes of previous encounters. In larger groups, players with longer memories are favoured, supporting the conjecture that the selection pressures leading to large primate groups resulted in an increased neocortex size. Thirdly we have constructed a theoretical model for the electro-optic properties of polymer dispersed liquid crystal systems and provided a full numerical solution for the governing equations. This yields a detailed description of the optical response of the system to an applied field.
University of Southampton
Cox, Simon J
d9440aae-d6b0-4da5-b430-0a20452aff1c
1998
Cox, Simon J
d9440aae-d6b0-4da5-b430-0a20452aff1c
Cox, Simon J
(1998)
Development and applications of high performance computing.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
In this thesis we demonstrate the application of high performance computing techniques to three scientific problems. The first uses the Maximum Entropy method to determine structure in players' choices of numbers in the UK National Lottery. The resulting equations are solved using an efficient parallel algorithm. We find that players preferentially pick numbers in the centre of the ticket. The second is a model for cooperation in groups, in which the parameter space of the model is explored using task farming. We demonstrate, using a simple model, that it is possible to sustain cooperation in large groups when there is repeated interaction, recognition of the identity of individual participants, and memory of the outcomes of previous encounters. In larger groups, players with longer memories are favoured, supporting the conjecture that the selection pressures leading to large primate groups resulted in an increased neocortex size. Thirdly we have constructed a theoretical model for the electro-optic properties of polymer dispersed liquid crystal systems and provided a full numerical solution for the governing equations. This yields a detailed description of the optical response of the system to an applied field.
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Published date: 1998
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Local EPrints ID: 463159
URI: http://eprints.soton.ac.uk/id/eprint/463159
PURE UUID: 42ee5e50-a991-4c1a-b2a1-14e2e7ace6df
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Date deposited: 04 Jul 2022 20:46
Last modified: 04 Jul 2022 20:46
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Author:
Simon J Cox
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