def full_fill_Gweiss_iw(Gweiss_iw, G_ij_iw, Sigma_imp_iw):
if mpi.is_master_node(): print "full_fill_Gweiss_iw"
for name,g in Gweiss_iw:
nw = len(g.data[:,0,0])
for wi in range(nw):
g.data[wi,:,:] = inv( inv(G_ij_iw[name].data[wi,:,:]) + Sigma_imp_iw[name].data[wi,:,:] )
fit_fermionic_gf_tail(g)
def full_full_Gweiss_iw_from_G_proj_iw_and_Sigma_imp_iw(Gweiss_iw, G_proj_iw, Sigma_imp_iw, bosonic_fit = False):
for C, g in Gweiss_iw:
nw = len(g.data[:,0,0])
for wi in range(nw):
g.data[wi,:,:] = inv(inv(G_proj_iw[C].data[wi,:,:]) + Sigma_imp_iw[C].data[wi,:,:])
if bosonic_fit:
fit_bosonic_tail(Gweiss_iw[C])
else:
fit_fermionic_gf_tail(Gweiss_iw[C])
def blockwise_get_G_loc_tau_from_G_loc_iw(G_loc_iw,
fit_tail_starting_iw = 14.0, ntau = None):
if mpi.is_master_node(): print "blockwise_get_G_loc_tau_from_G_loc_iw"
fit_fermionic_gf_tail(G_loc_iw, starting_iw=fit_tail_starting_iw)
if ntau is None:
ntau = 3*len(G_loc_iw.data[:,0,0])
Nc = len(G_loc_iw.data[0,0,:])
G_loc_tau = GfImTime(indices = range(Nc), beta = G_loc_iw.beta, n_points = ntau, statistic = 'Fermion')
G_loc_tau << InverseFourier(G_loc_iw)
return G_loc_tau
def blockwise_fill_Gweiss_iw_from_Gijw_and_Sigma_imp_iw(Gweiss_iw,Gijw,Sigma_imp_iw, mapping = lambda i,j: [0,0], bosonic_fit = False):
if mpi.is_master_node(): print "blockwise_fill_Gweiss_iw_from_Gijw_and_Sigma_imp_iw"
n_sites = len(Gweiss_iw.data[0,0,:])
nw = len(Gweiss_iw.data[:,0,0])
Gtemp = numpy.zeros((nw,n_sites,n_sites), dtype=numpy.complex_)
for i in range(n_sites):
for j in range(n_sites):
Gtemp[:,i,j] = Gijw[:,mapping(i,j)[0], mapping(i,j)[1]]
invGtemp = Gtemp[:,:,:]
for wi in range(nw):
#print "in Gweiss fill: wi:",wi
#print Gtemp[wi,:,:]
invGtemp[wi,:,:] = inv(Gtemp[wi,:,:])
Gweiss_iw.data[wi,:,:] = inv(invGtemp[wi,:,:] + Sigma_imp_iw.data[wi,:,:])
if bosonic_fit:
fit_bosonic_tail(Gweiss_iw)
else:
fit_fermionic_gf_tail(Gweiss_iw)
def blockwise_flexible_Gweiss_iw_from_Gweiss_iw_Gijw_and_G_imp_iw(Gweiss_iw,Gijw,G_imp_iw,
mapping, sign, sign_up_to ):
if mpi.is_master_node(): print "blockwise_flexible_Gweiss_iw_from_Gweiss_iw_Gijw_and_G_imp_iw"
n_sites = len(Gweiss_iw.data[0,0,:])
nw = len(Gweiss_iw.data[:,0,0])
Gtemp = numpy.zeros((nw,n_sites,n_sites), dtype=numpy.complex_)
for i in range(n_sites):
for j in range(n_sites):
Gtemp[:,i,j] = Gijw[:,mapping(i,j)[0], mapping(i,j)[1]]
invGtemp = Gtemp[:,:,:]
for wi in range(nw):
n_mats = wi-nw/2
if sign_up_to == -1: sign_up_to = nw
if ( n_mats>=0 and n_mats<sign_up_to) \
or n_mats<0 and abs(n_mats)-1<sign_up_to:
sgn = sign
else: sgn= -sign
invGtemp[wi,:,:] = inv(Gtemp[wi,:,:])
Gweiss_iw.data[wi,:,:] = inv( inv(Gweiss_iw.data[wi,:,:]) + sgn*(invGtemp[wi,:,:] - inv(G_imp_iw.data[wi,:,:])) )
fit_fermionic_gf_tail(Gweiss_iw)
def invf(Qw,
beta,
ntau,
n_iw,
statistic,
fit_tail,
fit_tail_like_sigma=False,
no_loc=True):
g = GfImFreq(indices=[0], beta=beta, n_points=n_iw, statistic=statistic)
gtau = GfImTime(indices=[0], beta=beta, n_points=ntau, statistic=statistic)
g.data[:, 0, 0] = Qw[:]
if fit_tail:
assert statistic == 'Fermion', "no tail fiting for bosonic functions!"
if fit_tail_like_sigma:
fit_and_remove_constant_tail(sig, starting_iw=14.0, max_order=5)
fit_fermionic_sigma_tail(g,
starting_iw=(10.0 if no_loc else 14.0),
no_hartree=True,
no_loc=no_loc)
else:
fit_fermionic_gf_tail(
g) ############# !!!!!!!!!! add the bosonic option
gtau << InverseFourier(g)
return gtau.data[:, 0, 0]
def ph_symmetric_Gweiss_causal_cautionary( data, ntau=5000):
assert sorted(data.impurity_struct.keys()) == ['1x1','2x1','2x2'], "not applicable to any other scheme than nested plaquette. impurity_struct: "+str(data.impurity_struct.keys())
print "######### Checking causality of Gweiss ########"
data.Gweiss_iw_unfit = data.Gweiss_iw.copy()
data.Delta_iw = data.Gweiss_iw.copy()
data.Delta_iw_fit = data.Gweiss_iw.copy()
gs = []
for C in data.impurity_struct.keys():
gs.append ( GfImTime(indices = data.impurity_struct[C], beta = data.beta, n_points =ntau, statistic = 'Fermion') )
data.Delta_tau = BlockGf(name_list = data.impurity_struct.keys(), block_list = gs, make_copies = False)
data.Delta_tau_fit = data.Delta_tau.copy()
for C, g in data.Gweiss_iw:
print ">>>>>>>>>>>>>>>>>> block ",C
nsites = len(g.data[0,:,0])
if nsites==4: Nx=Ny=2
elif nsites==2: Nx,Ny=2,1
elif nsites==1: Nx=Ny=1
else: assert False, "wrong number of sites"
H0 = initCubicTBH(Nx, Ny, 1, 0, -0.25, cyclic=False)
print H0
data.Delta_iw[C] = get_Delta_from_Gweiss_and_H0(g, H0, data.mus['up'])
for i in range(nsites):
data.Delta_iw[C].data[:,i,i] -= data.Delta_iw[C].data[:,i,i].real
if nsites>1:
for i,j in ([(0,1)] if nsites==2 else [(0,1),(1,3),(3,2),(2,0)]):
data.Delta_iw[C].data[:,i,j] -= data.Delta_iw[C].data[:,i,j].imag
data.Delta_iw[C].data[:,j,i] -= data.Delta_iw[C].data[:,j,i].imag
if nsites>2:
for i,j in [(0,3),(1,2)]:
data.Delta_iw[C].data[:,i,j] -= data.Delta_iw[C].data[:,i,j].real
data.Delta_iw[C].data[:,j,i] -= data.Delta_iw[C].data[:,j,i].real
impose_real_valued_in_imtime(data.Delta_iw[C])
#data.dump_general( quantities = ['Delta_iw'], suffix='-check' )
fit_fermionic_sigma_tail(data.Delta_iw[C])
data.Delta_tau[C] << InverseFourier(data.Delta_iw[C])
d2tauDelta = second_derivative(data.Delta_tau[C].data.real,data.beta/ntau)
ws = numpy.zeros((ntau-2,nsites))
needs_fixing = False
for taui in range(0,ntau-2):
w,v = numpy.linalg.eig(d2tauDelta[taui,:,:].real)
#print "eigvalues: ", w
ws[taui,:] = sorted(numpy.real(w))
if len([ww for ww in numpy.ravel(ws) if ww>0])>0:
needs_fixing = True
print "max eigenvalue: ",numpy.amax(numpy.ravel(ws))
if needs_fixing:
print "WARNING: Delta_iw[%s] unphysical and needs fixing!!!"%C
for att in range(3):
P = 0.01
epss = []
Vs = []
kinds = []
if nsites==4:
epss.extend([0.19668414224046424, -0.242286049378347, -0.4851071850062886, 0.6083462424661663])
Vs.extend([1.111030853547017, 0.95763987021629182, 1.3705081047849843, 0.80333649203756208])
kinds.extend([0,1,0,1])
elif nsites<4:
epss.extend([0.19668414224046424, -0.242286049378347])
Vs.extend([1.111030853547017, 0.95763987021629182])
kinds.extend([0,0])
for T in [0.025*nsites]:
epss,Vs = fit(data.Delta_iw[C], epss, Vs, kinds, P, n_mats = 5, max_its = 10000, T=T )
W,V = ph_symm_V_from_params(epss, Vs, kinds, Nsites=nsites)
G_from_params(data.Delta_iw_fit[C], P, W, V)
epss.extend([1.0,1.0])
Vs.extend([0.001,0.001])
kinds.extend([0,1])
for T in [0.00025*nsites]:
stochastic_complete(data.Delta_iw[C], data.Delta_iw_fit[C], [-0.0001,0.0001], [-3.0,3.0], 10000,
T = T, max_its=40000, n_mats = 5, printout=None, Nit_print=1000)
fit_fermionic_sigma_tail(data.Delta_iw_fit[C])
data.Delta_tau_fit[C] << InverseFourier(data.Delta_iw_fit[C])
data.Gweiss_iw[C] = get_Gweiss_from_Delta_and_H0(data.Delta_iw_fit[C], H0, data.mus['up'])
impose_real_valued_in_imtime(data.Gweiss_iw[C])
fit_fermionic_gf_tail(data.Gweiss_iw[C])
#data.dump_general( quantities = ['Delta_iw_fit','Gweiss_iw_unfit','Gweiss_iw'], suffix='-check' )
max_diff_Gweiss = numpy.amax(numpy.abs(data.Gweiss_iw[C].data - data.Gweiss_iw_unfit[C].data))
max_diff_Delta = numpy.amax(numpy.abs(data.Delta_iw[C].data - data.Delta_iw_fit[C].data))
print "---- max diff Gweiss: ", max_diff_Gweiss
print "---- max diff Delta: ", max_diff_Delta
if max_diff_Gweiss<2e-3 and max_diff_Delta<2e-3:
print "---- ---- fit satsfactory!"
break
else:
if att<2:
print "---- ---- fit not satsfactory! trying again..."
else:
print "---- ---- fit not satsfactory! tried already 3 times. better luck next time."
print "######### DONE!!! ########"