mm.math.hermite_renormalized_batch¶
- math.hermite_renormalized_batch(B, C, shape)¶
Renormalized multidimensional Hermite polynomial given by the “exponential” Taylor series of \(exp(C + Bx + 1/2*Ax^2)\) at zero, where the series has \(sqrt(n!)\) at the denominator rather than \(n!\). It computes all the amplitudes within the tensor of given shape in case of B is a batched vector with a batched diemnsion on the last index.
- Parameters:
A (
ndarray[Tuple[int,...],Union[TypeVar(R,float16,float32,float64),TypeVar(C,complex64,complex128),TypeVar(Z,int16,int32,int64),TypeVar(N,uint16,uint32,uint64)]]) – The A matrix.B (
ndarray[Tuple[int,...],Union[TypeVar(R,float16,float32,float64),TypeVar(C,complex64,complex128),TypeVar(Z,int16,int32,int64),TypeVar(N,uint16,uint32,uint64)]]) – The batched B vector with its batch dimension on the last index.C (
ndarray[Tuple[int,...],Union[TypeVar(R,float16,float32,float64),TypeVar(C,complex64,complex128),TypeVar(Z,int16,int32,int64),TypeVar(N,uint16,uint32,uint64)]]) – The C scalar.shape (
Tuple[int]) – The shape of the final tensor.
- Return type:
ndarray[Tuple[int,...],Union[TypeVar(R,float16,float32,float64),TypeVar(C,complex64,complex128),TypeVar(Z,int16,int32,int64),TypeVar(N,uint16,uint32,uint64)]]- Returns:
The batched Hermite polynomial of given shape.