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# scipy.special.roots_hermitenorm

`scipy.special.``roots_hermitenorm`(n, mu=False)

  Gauss-Hermite (statistician’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, \(He_n(x)\). These sample points and weights correctly integrate polynomials of degree \(2n - 1\) or less over the interval \([-\infty, \infty]\) with weight function \(f(x) = e^{-x^2/2}\).

  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

  See also

  `scipy.integrate.quadrature`, `scipy.integrate.fixed_quad`, `numpy.polynomial.hermite_e.hermegauss`

  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 used which computes nodes and weights in a numerical stable manner. The algorithm has linear runtime making computation for very large n (several thousand or more) feasible.