Research reports

Sparse adaptive approximation of high dimensional parametric initial value problems

by M. Hansen and Ch. Schwab

(Report number 2011-64)

Abstract
We consider nonlinear systems of ordinary differential equations (ODEs) on a state space \(S\). We consider the general setting when \(S\) is a Banach space over \(IR\) or \(IC\). We assume the right hand side depends affinely linear on a vector \(y = (y_j)_{j\ge 1}\) of possibly countably many parameters, normalized such that \(|y_i | \le 1\). Under suitable analyticity assumptions on the ODEs, we prove that the parametric solution \({X (t; y) : 0 \le t \le T } \subset S\) of the corresponding IVP depends holomorphically on the parameter vector \(y\), as a mapping from the infinite-dimensional parameter domain \(U = (-1,1)^IN\) into a suitable function space on \([0, T] \times S\). Such affine parameter dependence of the ODE arises, among others, in mass action models in computational biology (see, e.g. [18]) and in stochiometry with uncertain reaction rate constants. Using our analytic regularity result, we prove summability theorems for coefficient sequences of generalized polynomial chaos (gpc) expansions of the parametric solutions \({X (\cdot; y)}_{y\in U}\) with respect to tensor product orthogonal polynomial bases of \(L^2(U)\). We give sufficient conditions on the ODEs for \(N\) -term truncations of these expansions to converge on the entire parameter space with efficiency (i.e. accuracy versus complexity) being independent of the number of parameters viz. the dimension of the parameter space \(U\).

Keywords: Ordinary differential equations, initial value problem, parametric dependence, analyticity in infinite dimensional spaces, Taylor series, N-term approximation.

BibTeX
@Techreport{HS11_114,
  author = {M. Hansen and Ch. Schwab},
  title = {Sparse adaptive approximation of high dimensional parametric initial value problems },
  institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich},
  number = {2011-64},
  address = {Switzerland},
  url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2011/2011-64.pdf },
  year = {2011}
}

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