def test_lanczos_evolve(n, N_cache, tol=5.e-15):
# generate Hermitian test array
leg = gen_random_legcharge(ch, n)
H = npc.Array.from_func_square(rmat.GUE, leg) - npc.diag(1., leg)
H_flat = H.to_ndarray()
H_Op = H # use `matvec` of the array
qtotal = leg.to_qflat()[0]
psi_init = npc.Array.from_func(np.random.random, [leg], qtotal=qtotal)
psi_init /= npc.norm(psi_init)
psi_init_flat = psi_init.to_ndarray()
lanc = lanczos.LanczosEvolution(H_Op, psi_init, {
'verbose': 1,
'N_cache': N_cache
})
for delta in [-0.1j, 0.1j, 1.j]: #, 0.1, 1.]:
psi_final_flat = expm(H_flat * delta).dot(psi_init_flat)
psi_final, N = lanc.run(delta)
ov = np.inner(psi_final.to_ndarray().conj(), psi_final_flat)
ov /= np.linalg.norm(psi_final_flat)
print("<psi1|psi1_flat>/norm=", ov)
assert (abs(1. - abs(ov)) < tol)
def test_lanczos_evolve(n, N_cache, tol=5.e-14):
# generate Hermitian test array
leg = gen_random_legcharge(ch, n)
H = npc.Array.from_func_square(rmat.GUE, leg) - npc.diag(1., leg)
H_flat = H.to_ndarray()
H_Op = H # use `matvec` of the array
qtotal = leg.to_qflat()[0]
psi_init = npc.Array.from_func(np.random.random, [leg], qtotal=qtotal)
#psi_init /= npc.norm(psi_init) # not necessary
psi_init_flat = psi_init.to_ndarray()
lanc = lanczos.LanczosEvolution(H_Op, psi_init, {'N_cache': N_cache})
for delta in [-0.1j, 0.1j, 1.j, 0.1, 1.]:
psi_final_flat = expm(H_flat * delta).dot(psi_init_flat)
norm = np.linalg.norm(psi_final_flat)
psi_final, N = lanc.run(delta, normalize=False)
diff = np.linalg.norm(psi_final.to_ndarray() - psi_final_flat)
print("norm(|psi_final> - |psi_final_flat>)/norm = ",
diff / norm) # should be 1.
assert diff / norm < tol
psi_final2, N = lanc.run(delta, normalize=True)
assert npc.norm(psi_final / norm - psi_final2) < tol