def create_eliashberg_ingredients(p):
H = create_model_for_tests(**p)
kmesh = H.get_kmesh(n_k=[p.nk] * p.dim + [1] * (3 - p.dim))
e_k = H.fourier(kmesh)
wmesh = MeshImFreq(beta=p.beta, S="Fermion", n_max=p.nw)
g0_wk = lattice_dyson_g0_wk(mu=p.mu, e_k=e_k, mesh=wmesh)
chi0_wk = imtime_bubble_chi0_wk(g0_wk, nw=p.nw)
U_d, U_m = kanamori_charge_and_spin_quartic_interaction_tensors(
p.norb, p.U, p.Up, p.J, p.Jp)
chi_d = solve_rpa_PH(chi0_wk, U_d)
chi_m = solve_rpa_PH(chi0_wk,
-U_m) # Minus for correct charge rpa equation
phi_d_wk = construct_phi_wk(chi_d, U_d)
phi_m_wk = construct_phi_wk(chi_m, U_m)
gamma = construct_gamma_singlet_rpa(U_d, U_m, phi_d_wk, phi_m_wk)
eliashberg_ingredients = ParameterCollection(
g0_wk=g0_wk,
gamma=gamma,
U_m=U_m,
U_d=U_d,
chi_m=chi_m,
chi_d=chi_d,
)
return eliashberg_ingredients
def test_square_lattice_chi00():
# ------------------------------------------------------------------
# -- Discretizations
n_k = (2, 2, 1)
nw_g = 500
nnu = 400
nw = 1
# ------------------------------------------------------------------
# -- tight binding parameters
beta = 20.0
mu = 0.0
t = 1.0
h_loc = np.array([
[-0.3, -0.5],
[-0.5, .4],
])
T = -t * np.array([
[1., 0.23],
[0.23, 0.5],
])
# ------------------------------------------------------------------
# -- tight binding
print '--> tight binding model'
t_r = TBLattice(
units=[(1, 0, 0), (0, 1, 0)],
hopping={
# nearest neighbour hopping -t
(0, 0): h_loc,
(0, +1): T,
(0, -1): T,
(+1, 0): T,
(-1, 0): T,
},
orbital_positions=[(0, 0, 0)] * 2,
orbital_names=['up_0', 'do_0'],
)
e_k = t_r.on_mesh_brillouin_zone(n_k)
kmesh = e_k.mesh
wmesh = MeshImFreq(beta=beta, S='Fermion', n_max=nw_g)
print '--> g0_wk'
g0_wk = lattice_dyson_g0_wk(mu=mu, e_k=e_k, mesh=wmesh)
print '--> g0_wr'
g0_wr = fourier_wk_to_wr(g0_wk)
print '--> g0_tr'
g0_tr = fourier_wr_to_tr(g0_wr)
# ------------------------------------------------------------------
# -- anaytic chi00
print '--> chi00_wk analytic'
chi00_wk_analytic = lindhard_chi00_wk(e_k=e_k, nw=nw, beta=beta, mu=mu)
print '--> chi00_wr analytic'
chi00_wr_analytic = chi_wr_from_chi_wk(chi00_wk_analytic)
# ------------------------------------------------------------------
# -- imtime chi00
print '--> chi0_tr_from_grt_PH'
chi00_tr = chi0_tr_from_grt_PH(g0_tr)
print '--> chi_wr_from_chi_tr'
chi00_wr = chi_wr_from_chi_tr(chi00_tr, nw=1)
print '--> chi_w0r_from_chi_tr'
chi00_wr_ref = chi_w0r_from_chi_tr(chi00_tr)
print '--> chi0_w0r_from_grt_PH'
chi00_wr_opt = chi0_w0r_from_grt_PH(g0_tr)
print 'dchi00_wr =', np.max(
np.abs(chi00_wr_analytic.data - chi00_wr.data))
print 'dchi00_wr_ref =', np.max(
np.abs(chi00_wr_analytic.data - chi00_wr_ref.data))
print 'dchi00_wr_opt =', np.max(
np.abs(chi00_wr_analytic.data - chi00_wr_opt.data))
np.testing.assert_array_almost_equal(chi00_wr_analytic.data,
chi00_wr.data,
decimal=8)
np.testing.assert_array_almost_equal(chi00_wr_analytic.data,
chi00_wr_ref.data,
decimal=4)
np.testing.assert_array_almost_equal(chi00_wr_analytic.data,
chi00_wr_opt.data,
decimal=4)
print '--> chi_wk_from_chi_wr'
chi00_wk_imtime = chi_wk_from_chi_wr(chi00_wr)
# ------------------------------------------------------------------
# -- imtime chi00 helper function
chi00_wk_imtime_2 = imtime_bubble_chi0_wk(g0_wk, nw=1)
# ------------------------------------------------------------------
# -- imfreq chi00
print '--> chi00_wnr'
chi00_wnr = chi0r_from_gr_PH(nw=1, nnu=nnu, gr=g0_wr)
print '--> chi00_wnk'
chi00_wnk = chi0q_from_chi0r(chi00_wnr)
# -- Test per k and w calculator for chi0_wnk
print '--> chi00_wnk_ref'
from triqs_tprf.lattice import chi0q_from_g_wk_PH
chi00_wnk_ref = chi0q_from_g_wk_PH(nw=1, nnu=nnu, g_wk=g0_wk)
diff = np.max(np.abs(chi00_wnk.data - chi00_wnk_ref.data))
print 'chi00_wnk diff =', diff
np.testing.assert_array_almost_equal(chi00_wnk.data, chi00_wnk_ref.data)
print '--> chi00_wk_imfreq'
chi00_wk_imfreq = chi0q_sum_nu(chi00_wnk)
print '--> chi00_wk_imfreq_tail_corr'
chi00_wk_imfreq_tail_corr = chi0q_sum_nu_tail_corr_PH(chi00_wnk)
# ------------------------------------------------------------------
# -- Compare results
def cf_chi_w0(chi1, chi2, decimal=9):
chi1, chi2 = chi1[Idx(0), :].data, chi2[Idx(0), :].data
diff = np.linalg.norm(chi1 - chi2)
print '|dchi| =', diff
np.testing.assert_array_almost_equal(chi1, chi2, decimal=decimal)
print '--> Cf analytic with imtime'
cf_chi_w0(chi00_wk_analytic, chi00_wk_imtime, decimal=7)
print '--> Cf analytic with imtime 2'
cf_chi_w0(chi00_wk_analytic, chi00_wk_imtime_2, decimal=4)
print '--> Cf analytic with imfreq'
cf_chi_w0(chi00_wk_analytic, chi00_wk_imfreq, decimal=2)
print '--> Cf analytic with imfreq (tail corr)'
cf_chi_w0(chi00_wk_analytic, chi00_wk_imfreq_tail_corr, decimal=5)
def make_calc():
# ------------------------------------------------------------------
# -- Read precomputed ED data
filename = "data_pomerol.tar.gz"
p = read_TarGZ_HDFArchive(filename)
# ------------------------------------------------------------------
# -- RPA tensor
from triqs_tprf.rpa_tensor import get_rpa_tensor
from triqs_tprf.rpa_tensor import fundamental_operators_from_gf_struct
fundamental_operators = fundamental_operators_from_gf_struct(p.gf_struct)
p.U_abcd = get_rpa_tensor(p.H_int, fundamental_operators)
# ------------------------------------------------------------------
# -- Generalized PH susceptibility
loc_bse = ParameterCollection()
loc_bse.chi_wnn = chi_from_gg2_PH(p.G_iw, p.G2_iw_ph)
loc_bse.chi0_wnn = chi0_from_gg2_PH(p.G_iw, p.G2_iw_ph)
loc_bse.gamma_wnn = inverse_PH(loc_bse.chi0_wnn) - inverse_PH(
loc_bse.chi_wnn)
loc_bse.chi_wnn_ref = inverse_PH(
inverse_PH(loc_bse.chi0_wnn) - loc_bse.gamma_wnn)
np.testing.assert_array_almost_equal(loc_bse.chi_wnn.data,
loc_bse.chi_wnn_ref.data)
loc_bse.chi0_w = trace_nn(loc_bse.chi0_wnn)
loc_bse.chi_w = trace_nn(loc_bse.chi_wnn)
# ------------------------------------------------------------------
# -- RPA, using BSE inverses and constant Gamma
loc_rpa = ParameterCollection()
loc_rpa.U_abcd = p.U_abcd
# -- Build constant gamma
loc_rpa.gamma_wnn = loc_bse.gamma_wnn.copy()
loc_rpa.gamma_wnn.data[:] = loc_rpa.U_abcd[None, None, None, ...]
# Nb! In the three frequency form $\Gamma \propto U/\beta^2$
loc_rpa.gamma_wnn.data[:] /= p.beta**2
loc_rpa.chi0_wnn = loc_bse.chi0_wnn
loc_rpa.chi0_w = loc_bse.chi0_w
# -- Solve RPA
loc_rpa.chi_wnn = inverse_PH(
inverse_PH(loc_rpa.chi0_wnn) - loc_rpa.gamma_wnn)
loc_rpa.chi_w = trace_nn(loc_rpa.chi_wnn)
# ------------------------------------------------------------------
# -- Bubble RPA on lattice
lat_rpa = ParameterCollection()
# -- Setup dummy lattice Green's function equal to local Green's function
bz = BrillouinZone(
BravaisLattice(units=np.eye(3), orbital_positions=[(0, 0, 0)]))
periodization_matrix = np.diag(np.array(list([1] * 3), dtype=np.int32))
kmesh = MeshBrillouinZone(bz, periodization_matrix)
wmesh = MeshImFreq(beta=p.beta, S='Fermion', n_max=p.nwf_gf)
lat_rpa.g_wk = Gf(mesh=MeshProduct(wmesh, kmesh),
target_shape=p.G_iw.target_shape)
lat_rpa.g_wk[:, Idx(0, 0, 0)] = p.G_iw
# -- chi0_wk bubble and chi_wk_rpa bubble RPA
from triqs_tprf.lattice_utils import imtime_bubble_chi0_wk
lat_rpa.chi0_wk = imtime_bubble_chi0_wk(lat_rpa.g_wk, nw=1)
from triqs_tprf.lattice import solve_rpa_PH
lat_rpa.chi_wk = solve_rpa_PH(lat_rpa.chi0_wk, p.U_abcd)
lat_rpa.chi0_w = lat_rpa.chi0_wk[:, Idx(0, 0, 0)]
lat_rpa.chi_w = lat_rpa.chi_wk[:, Idx(0, 0, 0)]
print '--> cf Tr[chi0] and chi0_wk'
print loc_rpa.chi0_w.data.reshape((4, 4)).real
print lat_rpa.chi0_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(loc_rpa.chi0_w.data,
lat_rpa.chi0_w.data,
decimal=2)
print 'ok!'
print '--> cf Tr[chi_rpa] and chi_wk_rpa'
print loc_rpa.chi_w.data.reshape((4, 4)).real
print lat_rpa.chi_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(loc_rpa.chi_w.data,
lat_rpa.chi_w.data,
decimal=2)
print 'ok!'
# ------------------------------------------------------------------
# -- Lattice BSE
lat_bse = ParameterCollection()
lat_bse.g_wk = lat_rpa.g_wk
from triqs_tprf.lattice import fourier_wk_to_wr
lat_bse.g_wr = fourier_wk_to_wr(lat_bse.g_wk)
from triqs_tprf.lattice import chi0r_from_gr_PH
lat_bse.chi0_wnr = chi0r_from_gr_PH(nw=1, nnu=p.nwf, gr=lat_bse.g_wr)
from triqs_tprf.lattice import chi0q_from_chi0r
lat_bse.chi0_wnk = chi0q_from_chi0r(lat_bse.chi0_wnr)
# -- Lattice BSE calc
from triqs_tprf.lattice import chiq_from_chi0q_and_gamma_PH
lat_bse.chi_kwnn = chiq_from_chi0q_and_gamma_PH(lat_bse.chi0_wnk,
loc_bse.gamma_wnn)
# -- Trace results
from triqs_tprf.lattice import chi0q_sum_nu_tail_corr_PH
from triqs_tprf.lattice import chi0q_sum_nu
lat_bse.chi0_wk_tail_corr = chi0q_sum_nu_tail_corr_PH(lat_bse.chi0_wnk)
lat_bse.chi0_wk = chi0q_sum_nu(lat_bse.chi0_wnk)
from triqs_tprf.lattice import chiq_sum_nu, chiq_sum_nu_q
lat_bse.chi_kw = chiq_sum_nu(lat_bse.chi_kwnn)
lat_bse.chi0_w_tail_corr = lat_bse.chi0_wk_tail_corr[:, Idx(0, 0, 0)]
lat_bse.chi0_w = lat_bse.chi0_wk[:, Idx(0, 0, 0)]
lat_bse.chi_w = lat_bse.chi_kw[Idx(0, 0, 0), :]
print '--> cf Tr[chi0_wnk] and chi0_wk'
print lat_bse.chi0_w_tail_corr.data.reshape((4, 4)).real
print lat_bse.chi0_w.data.reshape((4, 4)).real
print lat_rpa.chi0_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(lat_bse.chi0_w_tail_corr.data,
lat_rpa.chi0_w.data)
np.testing.assert_array_almost_equal(lat_bse.chi0_w.data,
lat_rpa.chi0_w.data,
decimal=2)
print 'ok!'
print '--> cf Tr[chi_kwnn] and chi_wk'
print lat_bse.chi_w.data.reshape((4, 4)).real
print loc_bse.chi_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(lat_bse.chi_w.data,
loc_bse.chi_w.data)
print 'ok!'
# ------------------------------------------------------------------
# -- Store to hdf5
filename = 'data_bse_rpa.h5'
with HDFArchive(filename, 'w') as res:
res['p'] = p
n = rho[0, 0] + rho[1, 1]
m = 0.5 * (rho[0, 0] - rho[1, 1])
print('n, m =', n, m)
E_tot = E_kin - U * (n**2 / 4 - m**2)
print('E_tot =', E_tot)
np.testing.assert_almost_equal(E_tot_ref, E_tot, decimal=6)
# ------------------------------------------------------------------
# -- Lattice chi0
print('--> chi00_wk')
chi00_wk = imtime_bubble_chi0_wk(g0_wk, nw=1)
print('chi0_q0 =\n', chi00_wk[Idx(0), Idx(0, 0, 0)].real.reshape((4, 4)))
print('--> lindhard_chi00_wk')
chi00_wk_analytic = lindhard_chi00_wk(e_k=e_k, nw=1, beta=beta, mu=mu)
print('chi0_q0_analytic =\n', chi00_wk_analytic[Idx(0),
Idx(0, 0, 0)].real.reshape(
(4, 4)))
np.testing.assert_almost_equal(chi00_wk.data,
chi00_wk_analytic.data,
decimal=5)
chi0_q0_ref = chi0_q0_integral(t, beta)
print('chi0_q0 =', chi00_wk[Idx(0), Idx(0, 0, 0)][0, 0, 0, 0].real)
def make_calc():
# ------------------------------------------------------------------
# -- Read precomputed ED data
filename = "bse_and_rpa_loc_vs_latt.tar.gz"
p = read_TarGZ_HDFArchive(filename)['p']
# ------------------------------------------------------------------
# -- RPA tensor
from triqs_tprf.rpa_tensor import get_rpa_tensor
from triqs_tprf.rpa_tensor import fundamental_operators_from_gf_struct
fundamental_operators = fundamental_operators_from_gf_struct(p.gf_struct)
p.U_abcd = get_rpa_tensor(p.H_int, fundamental_operators)
# ------------------------------------------------------------------
# -- Generalized PH susceptibility
loc_bse = ParameterCollection()
loc_bse.chi_wnn = chi_from_gg2_PH(p.G_iw, p.G2_iw_ph)
loc_bse.chi0_wnn = chi0_from_gg2_PH(p.G_iw, p.G2_iw_ph)
loc_bse.gamma_wnn = inverse_PH(loc_bse.chi0_wnn) - inverse_PH(
loc_bse.chi_wnn)
loc_bse.chi_wnn_ref = inverse_PH(
inverse_PH(loc_bse.chi0_wnn) - loc_bse.gamma_wnn)
np.testing.assert_array_almost_equal(loc_bse.chi_wnn.data,
loc_bse.chi_wnn_ref.data)
from triqs_tprf.bse import solve_local_bse
loc_bse.gamma_wnn_ref = solve_local_bse(loc_bse.chi0_wnn, loc_bse.chi_wnn)
np.testing.assert_array_almost_equal(loc_bse.gamma_wnn.data,
loc_bse.gamma_wnn_ref.data)
loc_bse.chi0_w = trace_nn(loc_bse.chi0_wnn)
loc_bse.chi_w = trace_nn(loc_bse.chi_wnn)
# ------------------------------------------------------------------
# -- RPA, using BSE inverses and constant Gamma
loc_rpa = ParameterCollection()
loc_rpa.chi0_wnn = loc_bse.chi0_wnn
loc_rpa.chi0_w = loc_bse.chi0_w
loc_rpa.U_abcd = p.U_abcd
# -- Build constant gamma
from triqs_tprf.rpa_tensor import get_gamma_rpa
loc_rpa.gamma_wnn = get_gamma_rpa(loc_rpa.chi0_wnn, loc_rpa.U_abcd)
# -- Solve RPA
loc_rpa.chi_wnn = inverse_PH(
inverse_PH(loc_rpa.chi0_wnn) - loc_rpa.gamma_wnn)
loc_rpa.chi_w = trace_nn(loc_rpa.chi_wnn)
# ------------------------------------------------------------------
# -- Bubble RPA on lattice
lat_rpa = ParameterCollection()
# -- Setup dummy lattice Green's function equal to local Green's function
bz = BrillouinZone(
BravaisLattice(units=np.eye(3), orbital_positions=[(0, 0, 0)]))
periodization_matrix = np.diag(np.array(list([1] * 3), dtype=np.int32))
kmesh = MeshBrillouinZone(bz, periodization_matrix)
wmesh = MeshImFreq(beta=p.beta, S='Fermion', n_max=p.nwf_gf)
lat_rpa.g_wk = Gf(mesh=MeshProduct(wmesh, kmesh),
target_shape=p.G_iw.target_shape)
lat_rpa.g_wk[:, Idx(0, 0, 0)] = p.G_iw
# -- chi0_wk bubble and chi_wk_rpa bubble RPA
from triqs_tprf.lattice_utils import imtime_bubble_chi0_wk
lat_rpa.chi0_wk = imtime_bubble_chi0_wk(lat_rpa.g_wk, nw=1)
from triqs_tprf.lattice import solve_rpa_PH
lat_rpa.chi_wk = solve_rpa_PH(lat_rpa.chi0_wk, p.U_abcd)
lat_rpa.chi0_w = lat_rpa.chi0_wk[:, Idx(0, 0, 0)]
lat_rpa.chi_w = lat_rpa.chi_wk[:, Idx(0, 0, 0)]
print '--> cf Tr[chi0] and chi0_wk'
print loc_rpa.chi0_w.data.reshape((4, 4)).real
print lat_rpa.chi0_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(loc_rpa.chi0_w.data,
lat_rpa.chi0_w.data,
decimal=2)
print 'ok!'
print '--> cf Tr[chi_rpa] and chi_wk_rpa'
print loc_rpa.chi_w.data.reshape((4, 4)).real
print lat_rpa.chi_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(loc_rpa.chi_w.data,
lat_rpa.chi_w.data,
decimal=2)
print 'ok!'
# ------------------------------------------------------------------
# -- Lattice BSE
lat_bse = ParameterCollection()
lat_bse.g_wk = lat_rpa.g_wk
lat_bse.mu = p.mu
lat_bse.e_k = Gf(mesh=kmesh, target_shape=p.G_iw.target_shape)
lat_bse.e_k[Idx(0, 0, 0)] = np.eye(2)
lat_bse.sigma_w = p.G_iw.copy()
lat_bse.sigma_w << iOmega_n + lat_bse.mu * np.eye(2) - lat_bse.e_k[Idx(
0, 0, 0)] - inverse(p.G_iw)
lat_bse.g_wk_ref = lat_bse.g_wk.copy()
lat_bse.g_wk_ref[:, Idx(0, 0, 0)] << inverse(iOmega_n +
lat_bse.mu * np.eye(2) -
lat_bse.e_k[Idx(0, 0, 0)] -
lat_bse.sigma_w)
np.testing.assert_array_almost_equal(lat_bse.g_wk.data,
lat_bse.g_wk_ref.data)
#for w in lat_bse.g_wk.mesh.components[0]:
# print w, lat_bse.g_wk[w, Idx(0,0,0)][0, 0]
from triqs_tprf.lattice import fourier_wk_to_wr
lat_bse.g_wr = fourier_wk_to_wr(lat_bse.g_wk)
from triqs_tprf.lattice import chi0r_from_gr_PH
lat_bse.chi0_wnr = chi0r_from_gr_PH(nw=1, nn=p.nwf, g_nr=lat_bse.g_wr)
from triqs_tprf.lattice import chi0q_from_chi0r
lat_bse.chi0_wnk = chi0q_from_chi0r(lat_bse.chi0_wnr)
#for n in lat_bse.chi0_wnk.mesh.components[1]:
# print n.value, lat_bse.chi0_wnk[Idx(0), n, Idx(0,0,0)][0,0,0,0]
# -- Lattice BSE calc
from triqs_tprf.lattice import chiq_from_chi0q_and_gamma_PH
lat_bse.chi_kwnn = chiq_from_chi0q_and_gamma_PH(lat_bse.chi0_wnk,
loc_bse.gamma_wnn)
# -- Lattice BSE calc with built in trace
from triqs_tprf.lattice import chiq_sum_nu_from_chi0q_and_gamma_PH
lat_bse.chi_kw_ref = chiq_sum_nu_from_chi0q_and_gamma_PH(
lat_bse.chi0_wnk, loc_bse.gamma_wnn)
# -- Lattice BSE calc with built in trace using g_wk
from triqs_tprf.lattice import chiq_sum_nu_from_g_wk_and_gamma_PH
lat_bse.chi_kw_tail_corr_ref = chiq_sum_nu_from_g_wk_and_gamma_PH(
lat_bse.g_wk, loc_bse.gamma_wnn)
# -- Trace results
from triqs_tprf.lattice import chi0q_sum_nu_tail_corr_PH
from triqs_tprf.lattice import chi0q_sum_nu
lat_bse.chi0_wk_tail_corr = chi0q_sum_nu_tail_corr_PH(lat_bse.chi0_wnk)
lat_bse.chi0_wk = chi0q_sum_nu(lat_bse.chi0_wnk)
from triqs_tprf.lattice import chiq_sum_nu, chiq_sum_nu_q
lat_bse.chi_kw = chiq_sum_nu(lat_bse.chi_kwnn)
np.testing.assert_array_almost_equal(lat_bse.chi_kw.data,
lat_bse.chi_kw_ref.data)
from triqs_tprf.bse import solve_lattice_bse
lat_bse.chi_kw_tail_corr, tmp = solve_lattice_bse(lat_bse.g_wk,
loc_bse.gamma_wnn)
from triqs_tprf.bse import solve_lattice_bse_e_k_sigma_w
lat_bse.chi_kw_tail_corr_new = solve_lattice_bse_e_k_sigma_w(
lat_bse.mu, lat_bse.e_k, lat_bse.sigma_w, loc_bse.gamma_wnn)
np.testing.assert_array_almost_equal(lat_bse.chi_kw_tail_corr.data,
lat_bse.chi_kw_tail_corr_ref.data)
np.testing.assert_array_almost_equal(lat_bse.chi_kw_tail_corr.data,
lat_bse.chi_kw_tail_corr_new.data)
np.testing.assert_array_almost_equal(lat_bse.chi_kw_tail_corr_ref.data,
lat_bse.chi_kw_tail_corr_new.data)
lat_bse.chi0_w_tail_corr = lat_bse.chi0_wk_tail_corr[:, Idx(0, 0, 0)]
lat_bse.chi0_w = lat_bse.chi0_wk[:, Idx(0, 0, 0)]
lat_bse.chi_w_tail_corr = lat_bse.chi_kw_tail_corr[Idx(0, 0, 0), :]
lat_bse.chi_w = lat_bse.chi_kw[Idx(0, 0, 0), :]
print '--> cf Tr[chi0_wnk] and chi0_wk'
print lat_bse.chi0_w_tail_corr.data.reshape((4, 4)).real
print lat_bse.chi0_w.data.reshape((4, 4)).real
print lat_rpa.chi0_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(lat_bse.chi0_w_tail_corr.data,
lat_rpa.chi0_w.data)
np.testing.assert_array_almost_equal(lat_bse.chi0_w.data,
lat_rpa.chi0_w.data,
decimal=2)
print 'ok!'
print '--> cf Tr[chi_kwnn] and chi_wk (without chi0 tail corr)'
print lat_bse.chi_w.data.reshape((4, 4)).real
print loc_bse.chi_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(lat_bse.chi_w.data,
loc_bse.chi_w.data)
print 'ok!'
# ------------------------------------------------------------------
# -- Use chi0 tail corrected trace to correct chi_rpa cf bubble
dchi_wk = lat_bse.chi0_wk_tail_corr - lat_bse.chi0_wk
dchi_w = dchi_wk[:, Idx(0, 0, 0)]
loc_rpa.chi_w_tail_corr = loc_rpa.chi_w + dchi_w
# -- this will be the same, but it will be close to the real physical value
lat_bse.chi_w_tail_corr_ref = lat_bse.chi_w + dchi_w
loc_bse.chi_w_tail_corr_ref = loc_bse.chi_w + dchi_w
print '--> cf Tr[chi_rpa] and chi_wk_rpa'
print loc_rpa.chi_w.data.reshape((4, 4)).real
print loc_rpa.chi_w_tail_corr.data.reshape((4, 4)).real
print lat_rpa.chi_w.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(loc_rpa.chi_w_tail_corr.data,
lat_rpa.chi_w.data,
decimal=3)
print '--> cf Tr[chi_kwnn] with tail corr (from chi0_wnk)'
print lat_bse.chi_w_tail_corr.data.reshape((4, 4)).real
print lat_bse.chi_w_tail_corr_ref.data.reshape((4, 4)).real
np.testing.assert_array_almost_equal(lat_bse.chi_w_tail_corr.data,
lat_bse.chi_w_tail_corr_ref.data)
print 'ok!'
# ------------------------------------------------------------------
# -- Store to hdf5
filename = 'data_bse_rpa.h5'
with HDFArchive(filename, 'w') as res:
res['p'] = p
hopping = {hop : t for hop in non_diagonal_hoppings},
orbital_positions = [(0,0,0)]*p.norbs,
)
e_k = H.on_mesh_brillouin_zone(n_k=[p.nk]*p.dim + [1]*(3-p.dim))
# A bigger w-mesh is needed to construct a Gamma with a twice as big w-mesh than GF
big_factor = 2.0
wmesh = MeshImFreq(beta=p.beta, S='Fermion', n_max=p.nw)
wmesh_big = MeshImFreq(beta=p.beta, S='Fermion', n_max=int(big_factor*p.nw))
g0_wk = lattice_dyson_g0_wk(mu=p.mu, e_k=e_k, mesh=wmesh)
g0_wk_big = lattice_dyson_g0_wk(mu=p.mu, e_k=e_k, mesh=wmesh_big)
chi0_wk_big = imtime_bubble_chi0_wk(g0_wk_big, nw=int(big_factor*p.nw)+1)
U_c, U_s = kanamori_charge_and_spin_quartic_interaction_tensors(p.norbs, p.U, 0, 0, 0)
chi_s_big = solve_rpa_PH(chi0_wk_big, U_s)
chi_c_big = solve_rpa_PH(chi0_wk_big, -U_c) # Minus for correct charge rpa equation
gamma_big = gamma_PP_singlet(chi_c_big, chi_s_big, U_c, U_s)
# -- Preprocess gamma for the FFT implementation
gamma_dyn_wk, gamma_const_k = split_into_dynamic_wk_and_constant_k(gamma_big)
gamma_dyn_tr, gamma_const_r = dynamic_and_constant_to_tr(gamma_dyn_wk, gamma_const_k)
# -- Test the Eliashberg equation
def test_chi0_wk_save_memory(g0_wk, p):
chi0_wk = imtime_bubble_chi0_wk(g0_wk, nw=p.nw_chi, save_memory=False)
chi0_wk_save_memory = imtime_bubble_chi0_wk(g0_wk, nw=p.nw_chi, save_memory=True)
assert np.allclose(chi0_wk.data, chi0_wk_save_memory.data)
def solve_lattice_bse_at_specific_w(g_wk, gamma_wnn, nw_index):
r""" Compute the generalized lattice susceptibility
:math:`\chi_{\bar{a}b\bar{c}d}(i\omega_{n=\mathrm{nw\_index}}, \mathbf{k})` using the Bethe-Salpeter
equation (BSE) for a specific :math:`i\omega_{n=\mathrm{nw\_index}}`.
Parameters
----------
g_wk : Gf,
Single-particle Green's function :math:`G_{a\bar{b}}(i\nu_n, \mathbf{k})`.
gamma_wnn : Gf,
Local particle-hole vertex function
:math:`\Gamma_{a\bar{b}c\bar{d}}(i\omega_n, i\nu_n, i\nu_n')`.
nw_index : int,
The bosonic Matsubara frequency index :math:`i\omega_{n=\mathrm{nw\_index}}`
at which the BSE is solved.
Returns
-------
chi_k : Gf,
Generalized lattice susceptibility
:math:`\chi_{\bar{a}b\bar{c}d}(i\omega_{n=\mathrm{nw\_index}}, \mathbf{k})`.
chi0_k : Gf,
Generalized bare lattice susceptibility
:math:`\chi^0_{\bar{a}b\bar{c}d}(i\omega_{n=\mathrm{nw\_index}}, \mathbf{k})`.
"""
# Only use \Gamma at the specific \omega
gamma_nn = gamma_wnn[Idx(nw_index), :, :]
# Keep fake bosonic mesh for usability with other functions
gamma_wnn = add_fake_bosonic_mesh(gamma_nn)
fmesh_g = g_wk.mesh.components[0]
kmesh = g_wk.mesh.components[1]
bmesh = gamma_wnn.mesh.components[0]
fmesh = gamma_wnn.mesh.components[1]
nk = len(kmesh)
nwf = len(fmesh) // 2
nwf_g = len(fmesh_g) // 2
if mpi.is_master_node():
print(tprf_banner(), "\n")
print(
'Lattcie BSE with local vertex approximation at specific \omega.\n'
)
print('nk =', nk)
print('nw_index =', nw_index)
print('nwf =', nwf)
print('nwf_g =', nwf_g)
print()
mpi.report('--> chi0_wk_tail_corr')
# Calculate chi0_wk up to the specific \omega
chi0_wk_tail_corr = imtime_bubble_chi0_wk(g_wk,
nw=np.abs(nw_index) + 1,
save_memory=True)
# Only use specific \omega, but put back on fake bosonic mesh
chi0_k_tail_corr = chi0_wk_tail_corr[Idx(nw_index), :]
chi0_wk_tail_corr = add_fake_bosonic_mesh(chi0_k_tail_corr,
beta=bmesh.beta)
chi0_nk = get_chi0_nk_at_specific_w(g_wk, nw_index=nw_index, nwf=nwf)
# Keep fake bosonic mesh for usability with other functions
chi0_wnk = add_fake_bosonic_mesh(chi0_nk)
mpi.report('--> trace chi0_wnk')
chi0_wk = chi0q_sum_nu(chi0_wnk)
dchi_wk = chi0_wk_tail_corr - chi0_wk
chi0_kw = Gf(mesh=MeshProduct(kmesh, bmesh),
target_shape=chi0_wk_tail_corr.target_shape)
chi0_kw.data[:] = chi0_wk_tail_corr.data.swapaxes(0, 1)
del chi0_wk
del chi0_wk_tail_corr
assert (chi0_wnk.mesh.components[0] == bmesh)
assert (chi0_wnk.mesh.components[1] == fmesh)
assert (chi0_wnk.mesh.components[2] == kmesh)
# -- Lattice BSE calc with built in trace
mpi.report('--> chi_kw from BSE')
#mpi.report('DEBUG BSE INACTIVE'*72)
chi_kw = chiq_sum_nu_from_chi0q_and_gamma_PH(chi0_wnk, gamma_wnn)
#chi_kw = chi0_kw.copy()
mpi.barrier()
mpi.report('--> chi_kw from BSE (done)')
del chi0_wnk
mpi.report('--> chi_kw tail corrected (using chi0_wnk)')
for k in kmesh:
chi_kw[
k, :] += dchi_wk[:,
k] # -- account for high freq of chi_0 (better than nothing)
del dchi_wk
mpi.report('--> solve_lattice_bse, done.')
chi_k = chi_kw[:, Idx(0)]
del chi_kw
chi0_k = chi0_kw[:, Idx(0)]
del chi0_kw
return chi_k, chi0_k
def solve_lattice_bse(g_wk, gamma_wnn):
r""" Compute the generalized lattice susceptibility
:math:`\chi_{\bar{a}b\bar{c}d}(\mathbf{k}, \omega_n)` using the Bethe-Salpeter
equation (BSE).
Parameters
----------
g_wk : Gf,
Single-particle Green's function :math:`G_{a\bar{b}}(i\nu_n, \mathbf{k})`.
gamma_wnn : Gf,
Local particle-hole vertex function
:math:`\Gamma_{a\bar{b}c\bar{d}}(i\omega_n, i\nu_n, i\nu_n')`.
Returns
-------
chi_kw : Gf,
Generalized lattice susceptibility
:math:`\chi_{\bar{a}b\bar{c}d}(\mathbf{k}, i\omega_n)`.
chi0_kw : Gf,
Generalized bare lattice susceptibility
:math:`\chi^0_{\bar{a}b\bar{c}d}(\mathbf{k}, i\omega_n)`.
"""
fmesh_g = g_wk.mesh.components[0]
kmesh = g_wk.mesh.components[1]
bmesh = gamma_wnn.mesh.components[0]
fmesh = gamma_wnn.mesh.components[1]
nk = len(kmesh)
nw = (len(bmesh) + 1) // 2
nwf = len(fmesh) // 2
nwf_g = len(fmesh_g) // 2
if mpi.is_master_node():
print(tprf_banner(), "\n")
print('Lattcie BSE with local vertex approximation.\n')
print('nk =', nk)
print('nw =', nw)
print('nwf =', nwf)
print('nwf_g =', nwf_g)
print()
mpi.report('--> chi0_wk_tail_corr')
chi0_wk_tail_corr = imtime_bubble_chi0_wk(g_wk, nw=nw)
mpi.barrier()
mpi.report('B1 ' +
str(chi0_wk_tail_corr[Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
mpi.barrier()
chi0_wnk = get_chi0_wnk(g_wk, nw=nw, nwf=nwf)
mpi.barrier()
mpi.report('C ' + str(chi0_wnk[Idx(0), Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
mpi.barrier()
mpi.report('--> trace chi0_wnk')
chi0_wk = chi0q_sum_nu(chi0_wnk)
mpi.barrier()
mpi.report('D ' + str(chi0_wk[Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
mpi.barrier()
dchi_wk = chi0_wk_tail_corr - chi0_wk
chi0_kw = Gf(mesh=MeshProduct(kmesh, bmesh),
target_shape=chi0_wk_tail_corr.target_shape)
chi0_kw.data[:] = chi0_wk_tail_corr.data.swapaxes(0, 1)
del chi0_wk
del chi0_wk_tail_corr
assert (chi0_wnk.mesh.components[0] == bmesh)
assert (chi0_wnk.mesh.components[1] == fmesh)
assert (chi0_wnk.mesh.components[2] == kmesh)
# -- Lattice BSE calc with built in trace
mpi.report('--> chi_kw from BSE')
#mpi.report('DEBUG BSE INACTIVE'*72)
chi_kw = chiq_sum_nu_from_chi0q_and_gamma_PH(chi0_wnk, gamma_wnn)
#chi_kw = chi0_kw.copy()
mpi.barrier()
mpi.report('--> chi_kw from BSE (done)')
del chi0_wnk
mpi.report('--> chi_kw tail corrected (using chi0_wnk)')
for k in kmesh:
chi_kw[
k, :] += dchi_wk[:,
k] # -- account for high freq of chi_0 (better than nothing)
del dchi_wk
mpi.report('--> solve_lattice_bse, done.')
return chi_kw, chi0_kw
