create_elementary_operator#

cuquantum.bindings.cudensitymat.create_elementary_operator( intptr_t handle, int32_t num_space_modes, space_mode_extents, int sparsity, int32_t num_diagonals, diagonal_offsets, int data_type, intptr_t tensor_data, tensor_callback, tensor_gradient_callback, ) → intptr_t[source]#

Creates an elementary tensor operator acting on a given number of quantum state modes (aka space modes).

Parameters:

handle (intptr_t) – Library handle.
num_space_modes (int32_t) – Number of the (state) space modes acted on.
space_mode_extents (object) –
Extents of the (state) space modes acted on. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int64_t.
sparsity (ElementaryOperatorSparsity) – Tensor operator sparsity defining the storage scheme.
num_diagonals (int32_t) – For multi-diagonal tensor operator matrices, specifies the total number of non-zero diagonals (>= 1), otherwise ignored.
diagonal_offsets (object) –
For multi-diagonal tensor operator matrices, these are the offsets of the non-zero diagonals (for example, the main diagonal has offset 0, the diagonal right above the main diagonal has offset +1, the diagonal right below the main diagonal has offset -1, and so on). It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
data_type (int) – Tensor operator data type.
tensor_data (intptr_t) – GPU-accessible pointer to the tensor operator elements storage.
tensor_callback (object) – Optional user-defined tensor callback function which can be called later to fill in the tensor elements in the provided storage, or NULL.
tensor_gradient_callback (object) – Optional user-defined tensor gradient callback function which can be called later to compute the Vector-Jacobian Product (VJP) for the tensor operator, to produce gradients with respect to the user-defined real parameters, or NULL.

Returns:

Elementary tensor operator.

Return type:

intptr_t