Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499367
Title: Hybrid Monte Carlo methods for linear algebraic problems
Author: Branford, Simon
Awarding Body: Reading University
Current Institution: University of Reading
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Abstract:
Forsythe and Leibler presented the first research, in 1950, showing how a matrix could be inverted using Monte Carlo (MC) methods. West and Sobol extended this research by presenting MC algorithms to give statistical estimates for the elements of the inverse matrix, or for the components of the solution vector of a system of linear algebraic equations (SLAE). This algorithm uses a Markov chain MC method to generate a rough approximation to the inverse matrix and then rapidly improves the accuracy of the rough inverse using an iterative refinement scheme. Further results are presented comparing the performance of the sparse hybrid MC algorithm with other methods for producing inverse matrices.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.499367  DOI: Not available
Share: