jax.scipy.special.hyp1f1#
- jax.scipy.special.hyp1f1 = <jax._src.custom_derivatives.custom_jvp object>[source]#
Confluent hypergeometric function 1F1.
LAX-backend implementation of
scipy.special.hyp1f1().The JAX version only accepts positive and real inputs. Values of a, b and x leading to high values of 1F1 might be erroneous, considering enabling double precision. Convention for a = b = 0 is 1, unlike in scipy’s implementation.
Original docstring below.
The confluent hypergeometric function is defined by the series
\[{}_1F_1(a; b; x) = \sum_{k = 0}^\infty \frac{(a)_k}{(b)_k k!} x^k.\]See [dlmf] for more details. Here \((\cdot)_k\) is the Pochhammer symbol; see poch.
- Parameters:
a (array_like) – Real parameters
b (array_like) – Real parameters
x (array_like) – Real or complex argument
- Returns:
Values of the confluent hypergeometric function
- Return type:
scalar or ndarray
References
[dlmf]NIST Digital Library of Mathematical Functions https://dlmf.nist.gov/13.2#E2