def pade_tr(blockgf_iw, pade_n_omega_n, pade_eta, dos_n_points, dos_window, clip_threshold=0, n_points=1200):
g_iw = blockgf_iw
indices = [ind for ind in g_iw.indices]
tr_g = GfImFreq(indices = [0], mesh = g_iw[indices[0]].mesh)
for s, b in g_iw:
for i in range(len(b.data[0, :, :])):
tr_g << tr_g + b[i, i]
tr_g_lat_pade = GfReFreq(indices = [0], window = dos_window,
n_points = dos_n_points, name = 'Tr$G_{lat}$')
tr_g_lat_pade.set_from_pade(clip_g(tr_g, clip_threshold), n_points = pade_n_omega_n,
freq_offset = pade_eta)
return tr_g_lat_pade
from pytriqs.gf.local import GfReFreq, Omega, Wilson, inverse
import numpy
eps_d,t = 0.3, 0.2
# Create the real-frequency Green's function and initialize it
g = GfReFreq(indices = ['s','d'], window = (-2, 2), n_points = 1000, name = "$G_\mathrm{s+d}$")
g['d','d'] = Omega - eps_d
g['d','s'] = t
g['s','d'] = t
g['s','s'] = inverse( Wilson(1.0) )
g.invert()
# Plot it with matplotlib. 'S' means: spectral function ( -1/pi Imag (g) )
from pytriqs.plot.mpl_interface import oplot
oplot( g['d','d'], '-o', RI = 'S', x_window = (-1.8,1.8), name = "Impurity" )
oplot( g['s','s'], '-x', RI = 'S', x_window = (-1.8,1.8), name = "Bath" )
L = 10 # Number of Matsubara frequencies used in the Pade approximation
eta = 0.01 # Imaginary frequency shift
## Test Green's functions ##
# Two Lorentzians
def GLorentz(z):
return 0.7/(z-2.6+0.3*1j) + 0.3/(z+3.4+0.1*1j)
# Semicircle
def GSC(z):
return 2.0*(z + sqrt(1-z**2)*(log(1-z) - log(-1+z))/pi)
# A superposition of GLorentz(z) and GSC(z) with equal weights
def G(z):
return 0.5*GLorentz(z) + 0.5*GSC(z)
# Matsubara GF
gm = GfImFreq(indices = [0], beta = beta, name = "gm")
gm << Function(G)
gm.tail.zero()
gm.tail[1] = array([[1.0]])
# Analytic continuation of gm
g_pade = GfReFreq(indices = [0], window = (-5.995, 5.995), n_points = 1200, name = "g_pade")
g_pade.set_from_pade(gm, n_points = L, freq_offset = eta)
from pytriqs.archive import HDFArchive
R = HDFArchive('pade.output.h5','w')
R['g_pade'] = g_pade
from pytriqs.gf.local import GfReFreq, Omega, Wilson, inverse
import numpy
eps_d,t = 0.3, 0.2
# Create the real-frequency Green's function and initialize it
g = GfReFreq(indices = ['s','d'], window = (-2, 2), n_points = 1000, name = "$G_\mathrm{s+d}$")
g['d','d'] = Omega - eps_d
g['d','s'] = t
g['s','d'] = t
g['s','s'] = inverse( Wilson(1.0) )
g.invert()
# Plot it with matplotlib. 'S' means: spectral function ( -1/pi Imag (g) )
from pytriqs.plot.mpl_interface import *
oplot( g['d','d'], '-o', RI = 'S', x_window = (-1.8,1.8), name = "Impurity" )
oplot( g['s','s'], '-x', RI = 'S', x_window = (-1.8,1.8), name = "Bath" )
plt.show()
def GLorentz(z):
return 0.7 / (z - 2.6 + 0.3 * 1j) + 0.3 / (z + 3.4 + 0.1 * 1j)
# Semicircle
def GSC(z):
return 2.0 * (z + sqrt(1 - z**2) * (log(1 - z) - log(-1 + z)) / pi)
# A superposition of GLorentz(z) and GSC(z) with equal weights
def G(z):
return 0.5 * GLorentz(z) + 0.5 * GSC(z)
# Matsubara GF
gm = GfImFreq(indices=[0], beta=beta, name="gm")
gm << Function(G)
gm.tail.zero()
gm.tail[1] = array([[1.0]])
# Analytic continuation of gm
g_pade = GfReFreq(indices=[0],
window=(-5.995, 5.995),
n_points=1200,
name="g_pade")
g_pade.set_from_pade(gm, n_points=L, freq_offset=eta)
from pytriqs.archive import HDFArchive
R = HDFArchive('pade.output.h5', 'w')
R['g_pade'] = g_pade
def pade_spin(blockgf_iw, spin, pade_n_omega_n, pade_eta, dos_n_points, dos_window, clip_threshold=0, n_points=1200):
g_iw = blockgf_iw[spin]
indices = g_iw.indices
g_pade = GfReFreq(indices = indices, window = dos_window, n_points = dos_n_points, name = 'Tr$G_{lat}$')
g_pade.set_from_pade(g_iw, n_points = pade_n_omega_n, freq_offset = pade_eta)
return g_pade
from pytriqs.gf.local import GfReFreq, Omega, Wilson, inverse import numpy eps_d,V = 0.3, 0.2 # Create the real-frequency Green's function and initialize it g = GfReFreq(indices = ['s','d'], window = (-2, 2), n_points = 1000, name = "s+d") g['d','d'] = Omega - eps_d g['d','s'] = V g['s','d'] = V g['s','s'] = inverse( Wilson(1.0) ) g.invert() # Plot it with matplotlib. 'S' means: spectral function ( -1/pi Imag (g) ) from pytriqs.plot.mpl_interface import oplot oplot( g['d','d'], '-o', RI = 'S', x_window = (-1.8,1.8), name = "Impurity" ) oplot( g['s','s'], '-x', RI = 'S', x_window = (-1.8,1.8), name = "Bath" )
from pytriqs.gf.local import GfReFreq
from pytriqs.gf.local.descriptors import SemiCircular
from pytriqs.archive import HDFArchive
import numpy
R = HDFArchive('myfile.h5', 'w')
for D in range(1, 10, 2):
g = GfReFreq(indices=[0], window=(-2.00, 2.00), name="D=%s" % D)
g << SemiCircular(half_bandwidth=0.1 * D)
R[g.name] = g
import numpy as np
from pytriqs.gf.local import GfReFreq, SemiCircular
g = GfReFreq(indices=['eg1', 'eg2'],
window=(-5, 5),
n_points=1000,
name="egBlock")
g['eg1', 'eg1'] = SemiCircular(half_bandwidth=1)
g['eg2', 'eg2'] = SemiCircular(half_bandwidth=2)
from pytriqs.plot.mpl_interface import oplot
oplot(g['eg1', 'eg1'], '-o', RI='S') # S : spectral function
oplot(g['eg2', 'eg2'], '-x', RI='S')
