cuquantum.custatevec.abs2sum_array_batched¶

cuquantum.custatevec.abs2sum_array_batched(intptr_t handle, intptr_t batched_svs, int sv_data_type, uint32_t n_index_bits, uint32_t n_svs, _Index sv_stride, intptr_t abs2sum, _Index abs2sum_stride, bit_ordering, uint32_t bit_ordering_len, mask_bit_string, mask_ordering, uint32_t mask_len)[source]¶

Calculates the batched sum of squared absolute values for a given set of index bits.

Parameters

handle (intptr_t) – The library handle.
batched_svs (intptr_t) – The pointer address (as Python int) to the batched statevectors (on device).
sv_data_type (cuquantum.cudaDataType) – The data type of the statevector.
n_index_bits (uint32_t) – The number of index bits.
n_svs (uint32_t) – The number of batched statevectors.
sv_stride (int64_t) – The stride between each state vector in the batch.
abs2sum (intptr_t) – The pointer address (as Python int) to the array (on either host or device) that would hold the sums.
abs2sum_stride (int64_t) – The stride between each abs2sum array in the batch.
bit_ordering –
A host array of index bit ordering. It can be
- an int as the pointer address to the array
- a Python sequence of index bit ordering
bit_ordering_len (uint32_t) – The length of bit_ordering.
mask_bit_string –
An array for specifying mask values. It can be
- an int as the pointer address to the array (on host or device)
- a Python sequence of mask values on host
mask_ordering –
A host array of mask ordering. It can be
- an int as the pointer address to the array
- a Python sequence of index bit ordering
mask_len (uint32_t) – The length of mask_ordering.