povm_test.py 文件源码

def test_mppovm_embed_expectation(
        nr_sites, local_dim, rank, startsite, width, rgen):
    if hasattr(local_dim, '__iter__'):
        local_dim2 = local_dim
    else:
        local_dim2 = [local_dim] * nr_sites
    local_dim2 = list(zip(local_dim2, local_dim2))

    # Create a local POVM `red_povm`, embed it onto a larger chain
    # (`full_povm`), and go back to the reduced POVM.
    red_povm = mp.chain(
        mp.povm.MPPovm.from_local_povm(mp.povm.pauli_povm(d), 1)
        for d, _ in local_dim2[startsite:startsite + width]
    )
    full_povm = red_povm.embed(nr_sites, startsite, local_dim)
    axes = [(1, 2) if i < startsite or i >= startsite + width else None
            for i in range(nr_sites)]
    red_povm2 = mp.partialtrace(full_povm, axes, mp.MPArray)
    red_povm2 = mp.prune(red_povm2, singletons=True)
    red_povm2 /= np.prod([d for i, (d, _) in enumerate(local_dim2)
                          if i < startsite or i >= startsite + width])
    assert_almost_equal(mp.normdist(red_povm, red_povm2), 0.0)

    # Test with an arbitrary random MPO instead of an MPDO
    mpo = mp.factory.random_mpa(nr_sites, local_dim2, rank, rgen,
                                dtype=np.complex_, normalized=True)
    mpo_red = next(mp.reductions_mpo(mpo, width, startsites=[startsite]))
    ept = mp.prune(full_povm.pmf(mpo, 'mpdo'), singletons=True).to_array()
    ept_red = red_povm.pmf(mpo_red, 'mpdo').to_array()
    assert_array_almost_equal(ept, ept_red)