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Generalize number of time orderings #25

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@ksunden

#TODO: generalize nTimeOrderings
cuda.memcpy_htod(int(pointer) + 8, np.array([6], dtype=np.int32))

Currently assumes 6, which is 3!, the number of orderings in a 3 beam experiment, but other experiments may have different values.
It's possible this should always be the factorial, but we may need to discuss this

This assumption is only made for transferring a Hamiltonian to a CUDA device

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