Integrals with a large parameter. Several nearly coincident saddle points

Author:

Ursell F.

Abstract

AbstractIn the contour integralthe functions g( ) and f( ) are analytic functions of their arguments, and N is a large positive parameter. When N tends to ∞, asymptotic expansions can usually be found by the method of steepest descents, which shows that the principal contributions arise from the saddle-points, i.e. the values of z at which ∂f/∂z = 0. The position of the saddle-points varies with the l parameters, denoted by α = (α12,…,αl), and it may happen that two or more saddle-points coincide at a certain value of α. The asymptotic expansions given by the ordinary method of steepest descents are then non-uniform. The case of a single parameter and two nearly coincident saddle- points was studied earlier and leads to Airy functions. Here we are concerned with the case of l parameters and of m saddle-points which are nearly coincident when α is near 0. It is then known that f(z,α) can be transformed locally into a polynomial of degree m + 1, and accordingly we here restrict f(z,α) to be such a polynomial. The form of the resulting asymptotic expansion had already been conjectured (correctly as we now see), and involves certain special functions of m–1 variables. To establish the validity of the expansion we must show that the remainder after any number of terms is of smaller magnitude than the last term retained in the expansion. In other words, we must establish an inequality between integrals which is to hold for sufficiently small α and sufficiently large N, and which involves 1 parameters and m nearly coincident saddle-points.

Publisher

Cambridge University Press (CUP)

Subject

General Mathematics

Reference5 articles.

1. Integrals with a large parameter. The continuation of uniformly asymptotic expansions;Ubsell;Proc. Cambridge Philos. Soc.,1965

2. Uniform asymptotic expansions of integrals with many nearby stationary points and algebraic singularities;Bleistein;J. Math. and Mech.,1967

3. An extension of the method of steepest descents

4. Transformation of an analytic function of several variables to a canonical form

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