[ont.events] UW Num. Anal. Seminar, Dr. Liniger on "Fast Finite Difference Algorithms for Solving Poisson's Equation on General Two-Dimensional Regions"

mwang@watmath.UUCP (mwang) (04/03/84)

          DEPARTMENT OF COMPUTER SCIENCE
          UNIVERSITY OF WATERLOO
          SEMINAR ACTIVITIES

          NUMERICAL ANALYSIS SEMINAR
                                     - Thursday, April 12, 1984.

          Dr. W. Liniger of IBM Thomas J. Watson Research  Center
          will  speak  on ``Fast Finite Difference Algorithms for
          Solving Poisson's Equation on  General  Two-Dimensional
          Regions.''

          TIME:                3:30 PM

          ROOM:              MC 6091A

          ABSTRACT

          Fast finite  difference  algorithms  are  proposed  for
          solving  Poisson's  equation on general two-dimensional
          regions.  These algorithms are based on  a  variant  of
          the  marching  method  but  are intrinsically much more
          stable than the latter and thus can be applied on rela-
          tively large grids without resorting to multiple shoot-
          ing.   The  algorithms  are  associated  with  a   one-
          parameter   family  of  factored  second-order  complex
          discretizations of the Laplace operator and the gain in
          stability  is due to solving initial value problems for
          two first-order difference equations, rather  than  one
          second-order  equation  as in the conventional marching
          method.  These initial value problems  represent  back-
          solves in a sparse Choleski decomposition.  The stabil-
          ity and accuracy of the  method  can  be  further  con-
          trolled  by  the  choice  of the parameter on which the
          discretization depends.   The  factored  discretization
          lends  itself  well  to  an iterative implementation by
          means of the preconditioned conjugate gradient  method,
          as well as for a direct implementation.  The algorithms
          were tested successfully on  regions  with  complicated
          geometries, including multiply connected ones.