TY - JOUR
T1 - Automatic Deformation of Riemann-Hilbert Problems with Applications to the Painlevé II Transcendents
AU - Wechslberger, Georg
AU - Bornemann, Folkmar
N1 - Funding Information:
This research was supported by the DFG-Collaborative Research Center, TRR 109, “Discretization in Geometry and Dynamics.”
PY - 2014/2
Y1 - 2014/2
N2 - The stability and convergence rate of Olver's collocation method for the numerical solution of Riemann-Hilbert problems (RHPs) are known to depend very sensitively on the particular choice of contours used as data of the RHP. By manually performing contour deformations that proved to be successful in the asymptotic analysis of RHPs, such as the method of nonlinear steepest descent, the numerical method can basically be preconditioned, making it asymptotically stable. In this paper, however, we will show that most of these preconditioning deformations, including lensing, can be addressed in an automatic, completely algorithmic fashion that would turn the numerical method into a black-box solver. To this end, the preconditioning of RHPs is recast as a discrete, graph-based optimization problem: the deformed contours are obtained as a system of shortest paths within a planar graph weighted by the relative strength of the jump matrices. The algorithm is illustrated for the RHP representing the Painlevé II transcendents.
AB - The stability and convergence rate of Olver's collocation method for the numerical solution of Riemann-Hilbert problems (RHPs) are known to depend very sensitively on the particular choice of contours used as data of the RHP. By manually performing contour deformations that proved to be successful in the asymptotic analysis of RHPs, such as the method of nonlinear steepest descent, the numerical method can basically be preconditioned, making it asymptotically stable. In this paper, however, we will show that most of these preconditioning deformations, including lensing, can be addressed in an automatic, completely algorithmic fashion that would turn the numerical method into a black-box solver. To this end, the preconditioning of RHPs is recast as a discrete, graph-based optimization problem: the deformed contours are obtained as a system of shortest paths within a planar graph weighted by the relative strength of the jump matrices. The algorithm is illustrated for the RHP representing the Painlevé II transcendents.
KW - Contour deformation
KW - Discrete optimization
KW - Greedy algorithm
KW - Painlevé II
KW - Preconditioning
KW - Riemann-Hilbert problems
UR - http://www.scopus.com/inward/record.url?scp=84891004443&partnerID=8YFLogxK
U2 - 10.1007/s00365-013-9199-x
DO - 10.1007/s00365-013-9199-x
M3 - Article
AN - SCOPUS:84891004443
SN - 0176-4276
VL - 39
SP - 151
EP - 171
JO - Constructive Approximation
JF - Constructive Approximation
IS - 1
ER -