cuquantum.custatevec.apply_generalized_permutation_matrix¶

cuquantum.custatevec.apply_generalized_permutation_matrix(intptr_t handle, intptr_t sv, int sv_data_type, uint32_t n_index_bits, permutation, intptr_t diagonals, int diagonals_data_type, int32_t adjoint, targets, uint32_t n_targets, controls, control_bit_values, uint32_t n_controls, intptr_t extra_workspace, size_t extra_workspace_size_in_bytes)[source]¶

Apply generalized permutation matrix.

Parameters

handle (intptr_t) – the handle to the cuStateVec library.
sv (intptr_t) – state vector.
sv_data_type (int) – data type of the state vector.
n_index_bits (uint32_t) – the number of index bits of the state vector.
permutation (object) –
host or device pointer to a permutation table. It can be:
- an int as the pointer address to the array, or
- a Python sequence of custatevecIndex_t.
diagonals (intptr_t) – host or device pointer to diagonal elements.
diagonals_data_type (int) – data type of diagonals.
adjoint (int32_t) – apply adjoint of generalized permutation matrix.
targets (object) –
pointer to a host array of target bits. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
n_targets (uint32_t) – the number of target bits.
controls (object) –
pointer to a host array of control bits. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
control_bit_values (object) –
pointer to a host array of control bit values. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
n_controls (uint32_t) – the number of control bits.
extra_workspace (intptr_t) – extra workspace.
extra_workspace_size_in_bytes (size_t) – extra workspace size.