Methods and Algorithms for Scientific Computing

Deflation Techniques for Finding Distinct Solutions of Nonlinear Partial Differential Equations

Abstract

Nonlinear systems of partial differential equations (PDEs) may permit several distinct solutions. The typical current approach to finding distinct solutions is to start Newton's method with many different initial guesses, hoping to find starting points that lie in different basins of attraction. In this paper, we present an infinite-dimensional deflation algorithm for systematically modifying the residual of a nonlinear PDE problem to eliminate known solutions from consideration. This enables the Newton--Kantorovitch iteration to converge to several different solutions, even starting from the same initial guess. The deflated Jacobian is dense, but an efficient preconditioning strategy is devised, and the number of Krylov iterations is observed not to grow as solutions are deflated. The power of the approach is demonstrated on several problems from special functions, phase separation, differential geometry, and fluid mechanics that permit distinct solutions.

Keywords

  1. deflation
  2. Newton's method
  3. distinct solutions
  4. continuation

MSC codes

  1. 65N30
  2. 65N35
  3. 65H99
  4. 35B32

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Published In

cover image SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Pages: A2026 - A2045
ISSN (online): 1095-7197

History

Submitted: 2 September 2014
Accepted: 27 May 2015
Published online: 13 August 2015

Keywords

  1. deflation
  2. Newton's method
  3. distinct solutions
  4. continuation

MSC codes

  1. 65N30
  2. 65N35
  3. 65H99
  4. 35B32

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