SciPy

scipy.special.roots_hermite

scipy.special.roots_hermite(n, mu=False)[source]

Gauss-Hermite (physicst’s) quadrature.

Computes the sample points and weights for Gauss-Hermite quadrature. The sample points are the roots of the n-th degree Hermite polynomial, \(H_n(x)\). These sample points and weights correctly integrate polynomials of degree \(2n - 1\) or less over the interval \([-\infty, \infty]\) with weight function \(f(x) = e^{-x^2}\).

Parameters:
n : int

quadrature order

mu : bool, optional

If True, return the sum of the weights, optional.

Returns:
x : ndarray

Sample points

w : ndarray

Weights

mu : float

Sum of the weights

Notes

For small n up to 150 a modified version of the Golub-Welsch algorithm is used. Nodes are computed from the eigenvalue problem and improved by one step of a Newton iteration. The weights are computed from the well-known analytical formula.

For n larger than 150 an optimal asymptotic algorithm is applied which computes nodes and weights in a numerically stable manner. The algorithm has linear runtime making computation for very large n (several thousand or more) feasible.

References

[townsend.trogdon.olver-2014]Townsend, A. and Trogdon, T. and Olver, S. (2014) Fast computation of Gauss quadrature nodes and weights on the whole real line. arXiv:1410.5286.
[townsend.trogdon.olver-2015]Townsend, A. and Trogdon, T. and Olver, S. (2015) Fast computation of Gauss quadrature nodes and weights on the whole real line. IMA Journal of Numerical Analysis DOI:10.1093/imanum/drv002.

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