def METHOD_NAME(self):
    """Tests if the observables are properly evaluated at each timestep."""
    initial_state = zero(1)
    time_ev = 10.0
    hamiltonian = SparsePauliOp("X")
    observables = {"Energy": SparsePauliOp("X"), "Z": SparsePauliOp("Z")}
    evolution_problem = TimeEvolutionProblem(
        hamiltonian, time_ev, initial_state, aux_operators=observables
    )
    classic_evolver = SciPyRealEvolver(num_timesteps=10)
    result = classic_evolver.evolve(evolution_problem)
    z_mean, z_std = result.observables["Z"]
    timesteps = z_mean.shape[0]
    time_vector = np.linspace(0, time_ev, timesteps)
    expected_z = 1 - 2 * (np.sin(time_vector)) ** 2
    expected_z_std = np.zeros_like(expected_z)
    np.testing.assert_allclose(z_mean, expected_z, atol=1e-10, rtol=0)
    np.testing.assert_allclose(z_std, expected_z_std, atol=1e-10, rtol=0)
    np.testing.assert_equal(time_vector, result.times)