abs2sum_array_batched#

cuquantum.bindings.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.

See also

custatevecAbs2SumArrayBatched()