Gauss–Laguerre quadrature

In numerical analysis Gauss–Laguerre quadrature (named after Carl Friedrich Gauss and Edmond Laguerre) is an extension of the Gaussian quadrature method for approximating the value of integrals of the following kind: In this case where xi is the i-th root of Laguerre polynomial Ln(x) and the weight wi is given by The following Python code with the SymPy library will allow for calculation of the values of and to 20 digits of precision: from sympy import * def lag_weights_roots(n): x = Symbol("x") roots = Poly(laguerre(n, x)).all_roots() x_i = [rt.evalf(20) for rt in roots] w_i = [(rt / ((n + 1) * laguerre(n + 1, rt)) ** 2).evalf(20) for rt in roots] return x_i, w_i print(lag_weights_roots(5)) To integrate the function we apply the following transformation where . For the last integral one then uses Gauss-Laguerre quadrature. Note, that while this approach works from an analytical perspective, it is not always numerically stable. More generally, one can also consider integrands that have a known power-law singularity at x=0, for some real number , leading to integrals of the form: In this case, the weights are given in terms of the generalized Laguerre polynomials: where are the roots of . This allows one to efficiently evaluate such integrals for polynomial or smooth f(x) even when α is not an integer.