A Lanczos method for approximating composite functions

We seek to approximate a composite function h(x)=g(f(x))h(x)=g(f(x)) with a global polynomial. The standard approach chooses points x in the domain of f   and computes h(x)h(x) at each point, which requires an evaluation of f and an evaluation of g. We present a Lanczos-based procedure that implicitly approximates g with a polynomial of f. By constructing a quadrature rule for the density function of f  , we can approximate h(x)h(x) using many fewer evaluations of g. The savings is particularly dramatic when g is much more expensive than f or the dimension of x is large. We demonstrate this procedure with two numerical examples: (i) an exponential function composed with a rational function and (ii) a Navier–Stokes model of fluid flow with a scalar input parameter that depends on multiple physical quantities.