def get_chi0_nk_at_specific_w(g_wk, nw_index=1, nwf=None):
r""" Compute the generalized bare lattice susceptibility
:math:`\chi^{0}_{\bar{a}b\bar{c}d}(i\omega_{n=\mathrm{nw\_index}}, i\nu_n, \mathbf{k})` from the single-particle
Green's function :math:`G_{a\bar{b}}(i\nu_n, \mathbf{k})` 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})`.
nw_index : int,
The bosonic Matsubara frequency index :math:`i\omega_{n=\mathrm{nw\_index}}`
at which :math:`\chi^0` is calculated.
nwf : int,
Number of fermionic frequencies in :math:`\chi^0`.
Returns
-------
chi0_nk : Gf,
Generalized bare lattice susceptibility
:math:`\chi^{0}_{\bar{a}b\bar{c}d}(i\omega_{n=\mathrm{nw\_index}}, i\nu_n, \mathbf{k})`.
"""
fmesh = g_wk.mesh.components[0]
kmesh = g_wk.mesh.components[1]
if nwf is None:
nwf = len(fmesh) // 2
mpi.barrier()
mpi.report('g_wk ' + str(g_wk[Idx(2), Idx(0, 1, 2)][0, 0]))
n = np.sum(g_wk.data) // len(kmesh)
mpi.report('n ' + str(n))
mpi.barrier()
mpi.report('--> g_wr from g_wk')
g_wr = fourier_wk_to_wr(g_wk)
mpi.report('--> chi0_wnr from g_wr')
chi0_nr = chi0_nr_from_gr_PH_at_specific_w(nw_index=nw_index,
nn=nwf,
g_nr=g_wr)
del g_wr
mpi.report('--> chi0_wnk from chi0_wnr')
# Create a 'fake' bosonic mesh to be able to use 'chi0q_from_chi0r'
chi0_wnr = add_fake_bosonic_mesh(chi0_nr)
del chi0_nr
chi0_wnk = chi0q_from_chi0r(chi0_wnr)
del chi0_wnr
chi0_nk = chi0_wnk[Idx(0), :, :]
del chi0_wnk
return chi0_nk
def solve_lattice_bse(parm, momsus=False):
print '--> solve_lattice_bse'
print 'nw =', parm.nw
print 'nwf =', parm.nwf
# ------------------------------------------------------------------
# -- Setup lattice
bl = BravaisLattice([(1, 0, 0), (0, 1, 0)])
bz = BrillouinZone(bl)
bzmesh = MeshBrillouinZone(bz, n_k=1) # only one k-point
e_k = Gf(mesh=bzmesh, target_shape=[1, 1])
e_k *= 0.
# ------------------------------------------------------------------
# -- Lattice single-particle Green's function
mesh = MeshImFreq(beta=parm.beta, S='Fermion', n_max=parm.nwf_gf)
parm.Sigma_iw = parm.G_iw.copy()
G0_iw = parm.G_iw.copy()
G0_iw << inverse(iOmega_n + 0.5 * parm.U)
parm.Sigma_iw << inverse(G0_iw) - inverse(parm.G_iw)
parm.mu = 0.5 * parm.U
g_wk = lattice_dyson_g_wk(mu=parm.mu, e_k=e_k, sigma_w=parm.Sigma_iw)
g_wr = fourier_wk_to_wr(g_wk)
# ------------------------------------------------------------------
# -- Non-interacting generalized lattice susceptibility
chi0_wr = chi0r_from_gr_PH(nw=parm.nw, nnu=parm.nwf, gr=g_wr)
chi0_wk = chi0q_from_chi0r(chi0_wr)
# ------------------------------------------------------------------
# -- Solve lattice BSE
parm.chi_wk = chiq_from_chi0q_and_gamma_PH(chi0_wk, parm.gamma_m)
# ------------------------------------------------------------------
# -- Store results and static results
num = np.squeeze(parm.chi_wk.data.real)
ref = np.squeeze(parm.chi_m.data.real)
diff = np.max(np.abs(num - ref))
print 'diff =', diff
parm.chi_w = chiq_sum_nu_q(parm.chi_wk) # static suscept
return parm
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
def get_chi0_wnk(g_wk, nw=1, nwf=None):
fmesh = g_wk.mesh.components[0]
kmesh = g_wk.mesh.components[1]
if nwf is None:
nwf = len(fmesh) / 2
mpi.barrier()
mpi.report('g_wk ' + str(g_wk[Idx(2), Idx(0, 1, 2)][0, 0]))
n = np.sum(g_wk.data) / len(kmesh)
mpi.report('n ' + str(n))
mpi.barrier()
mpi.report('--> g_wr from g_wk')
g_wr = fourier_wk_to_wr(g_wk)
mpi.barrier()
mpi.report('g_wr ' + str(g_wr[Idx(2), Idx(0, 1, 2)][0, 0]))
n_r = np.sum(g_wr.data, axis=0)[0]
mpi.report('n_r=0 ' + str(n_r[0, 0]))
mpi.barrier()
mpi.report('--> chi0_wnr from g_wr')
chi0_wnr = chi0r_from_gr_PH(nw=nw, nnu=nwf, gr=g_wr)
#mpi.report('--> chi0_wnr from g_wr (nompi)')
#chi0_wnr_nompi = chi0r_from_gr_PH_nompi(nw=nw, nnu=nwf, gr=g_wr)
del g_wr
#abs_diff = np.abs(chi0_wnr.data - chi0_wnr_nompi.data)
#mpi.report('shape = ' + str(abs_diff.shape))
#idx = np.argmax(abs_diff)
#mpi.report('argmax = ' + str(idx))
#diff = np.max(abs_diff)
#mpi.report('diff = %6.6f' % diff)
#del chi0_wnr
#chi0_wnr = chi0_wnr_nompi
#exit()
mpi.barrier()
mpi.report('chi0_wnr ' +
str(chi0_wnr[Idx(0), Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
chi0_r0 = np.sum(chi0_wnr[:, :, Idx(0, 0, 0)].data)
mpi.report('chi0_r0 ' + str(chi0_r0))
mpi.barrier()
mpi.report('--> chi0_wnk from chi0_wnr')
chi0_wnk = chi0q_from_chi0r(chi0_wnr)
del chi0_wnr
mpi.barrier()
mpi.report('chi0_wnk ' +
str(chi0_wnk[Idx(0), Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
chi0 = np.sum(chi0_wnk.data) / len(kmesh)
mpi.report('chi0 = ' + str(chi0))
mpi.barrier()
#if mpi.is_master_node():
if False:
from triqs_tprf.ParameterCollection import ParameterCollection
p = ParameterCollection()
p.g_wk = g_wk
p.g_wr = g_wr
p.chi0_wnr = chi0_wnr
p.chi0_wnk = chi0_wnk
print '--> Writing debug info for BSE'
with HDFArchive('data_debug_bse.h5', 'w') as arch:
arch['p'] = p
mpi.barrier()
return chi0_wnk
def get_chi0_wnk(g_wk, nw=1, nwf=None):
r""" Compute the generalized lattice bubble susceptibility
:math:`\chi^{(0)}_{abcd}(\omega, \nu, \mathbf{k})` from the single-particle
Green's function :math:`G_{ab}(\omega, \mathbf{k})`.
Parameters
----------
g_wk : Single-particle Green's function :math:`G_{ab}(\omega, \mathbf{k})`.
nw : Number of bosonic freqiencies in :math:`\chi`.
nwf : Number of fermionic freqiencies in :math:`\chi`.
Returns
-------
chi0_wnk : Generalized lattice bubble susceptibility
:math:`\chi^{(0)}_{abcd}(\omega, \nu, \mathbf{k})`
"""
fmesh = g_wk.mesh.components[0]
kmesh = g_wk.mesh.components[1]
if nwf is None:
nwf = len(fmesh) / 2
mpi.barrier()
mpi.report('g_wk ' + str(g_wk[Idx(2), Idx(0, 0, 0)][0, 0]))
n = np.sum(g_wk.data) / len(kmesh)
mpi.report('n ' + str(n))
mpi.barrier()
mpi.report('--> g_wr from g_wk')
g_wr = fourier_wk_to_wr(g_wk)
mpi.barrier()
mpi.report('g_wr ' + str(g_wr[Idx(2), Idx(0, 0, 0)][0, 0]))
n_r = np.sum(g_wr.data, axis=0)[0]
mpi.report('n_r=0 ' + str(n_r[0, 0]))
mpi.barrier()
mpi.report('--> chi0_wnr from g_wr')
chi0_wnr = chi0r_from_gr_PH(nw=nw, nn=nwf, g_nr=g_wr)
#mpi.report('--> chi0_wnr from g_wr (nompi)')
#chi0_wnr_nompi = chi0r_from_gr_PH_nompi(nw=nw, nn=nwf, g_wr=g_wr)
del g_wr
#abs_diff = np.abs(chi0_wnr.data - chi0_wnr_nompi.data)
#mpi.report('shape = ' + str(abs_diff.shape))
#idx = np.argmax(abs_diff)
#mpi.report('argmax = ' + str(idx))
#diff = np.max(abs_diff)
#mpi.report('diff = %6.6f' % diff)
#del chi0_wnr
#chi0_wnr = chi0_wnr_nompi
#exit()
mpi.barrier()
mpi.report('chi0_wnr ' +
str(chi0_wnr[Idx(0), Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
chi0_r0 = np.sum(chi0_wnr[:, :, Idx(0, 0, 0)].data)
mpi.report('chi0_r0 ' + str(chi0_r0))
mpi.barrier()
mpi.report('--> chi0_wnk from chi0_wnr')
chi0_wnk = chi0q_from_chi0r(chi0_wnr)
del chi0_wnr
mpi.barrier()
mpi.report('chi0_wnk ' +
str(chi0_wnk[Idx(0), Idx(0), Idx(0, 0, 0)][0, 0, 0, 0]))
chi0 = np.sum(chi0_wnk.data) / len(kmesh)
mpi.report('chi0 = ' + str(chi0))
mpi.barrier()
#if mpi.is_master_node():
if False:
from triqs_tprf.ParameterCollection import ParameterCollection
p = ParameterCollection()
p.g_wk = g_wk
p.g_wr = g_wr
p.chi0_wnr = chi0_wnr
p.chi0_wnk = chi0_wnk
print '--> Writing debug info for BSE'
with HDFArchive('data_debug_bse.h5', 'w') as arch:
arch['p'] = p
mpi.barrier()
return chi0_wnk
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