cuquantum.custatevec.abs2sum_array_batched¶

cuquantum.custatevec.abs2sum_array_batched(intptr_t handle, intptr_t batched_sv, int sv_data_type, uint32_t n_index_bits, uint32_t n_svs, int64_t sv_stride, intptr_t abs2sum_arrays, int64_t abs2sum_array_stride, bit_ordering, uint32_t bit_ordering_len, mask_bit_strings, mask_ordering, uint32_t mask_len)[source]¶

Calculate batched abs2sum array for a given set of index bits.

Parameters

handle (intptr_t) – the handle to the cuStateVec library.
batched_sv (intptr_t) – batch of state vectors.
sv_data_type (int) – data type of state vector.
n_index_bits (uint32_t) – the number of index bits.
n_svs (uint32_t) – the number of state vectors in a batch.
sv_stride (int64_t) – the stride of state vector.
abs2sum_arrays (intptr_t) – pointer to a host or device array of sums of squared absolute values.
abs2sum_array_stride (int64_t) – the distance between consequence abs2sum_arrays.
bit_ordering (object) –
pointer to a host array of index bit ordering. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
bit_ordering_len (uint32_t) – the length of bit_ordering.
mask_bit_strings (object) –
pointer to a host or device array of mask bit strings. It can be:
- an int as the pointer address to the array, or
- a Python sequence of custatevecIndex_t.
mask_ordering (object) –
pointer to a host array for the mask ordering. It can be:
- an int as the pointer address to the array, or
- a Python sequence of int32_t.
mask_len (uint32_t) – the length of mask.