def dos_plot(BETA, tp, filestr, ax=None):
"""Plots double occupation"""
if ax is None:
_, ax = plt.subplots()
with h5.File(filestr.format(tp=tp, BETA=BETA), 'r') as results:
fl_dos = []
tau, w_n = gf.tau_wn_setup(dict(BETA=BETA, N_MATSUBARA=BETA))
for u_str in results:
lastit = results[u_str].keys()[-1]
giwd, _ = get_giw(results[u_str], lastit, tau, w_n)
fl_dos.append(-1. / np.pi * gf.fit_gf(w_n[:3], giwd.imag)(0.))
u_range = np.array([float(u_str[1:]) for u_str in results.keys()])
ax.scatter(u_range, fl_dos, s=120, marker='>', vmin=0, vmax=2. / np.pi)
ax.set_title('Hysteresis loop of the \n density of states')
ax.set_ylabel(r'$A(\omega=0)$')
ax.set_xlabel('U/D')
def estimate_dos_at_fermi_level_T_vs_U(tp, ulist, temp, phase):
dos_fl = []
save_file = 'dimer_ipt_{}_tp{:.2}.npy'.format(phase, tp)
if os.path.exists(save_file):
return -np.load(save_file)
for T in temp:
w_n = gf.matsubara_freq(1 / T, 3)
filestr = 'disk/phase_Dimer_ipt_{}_tp{}/B{:.5}/giw.npy'.format(
phase, tp, 1 / T)
gfs = np.load(filestr)
dos_fl.append(
np.array([gf.fit_gf(w_n, gfs[i][0][:3])(0.) for i in ulist]))
np.save(save_file, dos_fl)
return -np.array(dos_fl)
def estimate_dos_at_fermi_level_U_vs_tp(tpr, ulist, beta, phase):
dos_fl = []
w_n = gf.matsubara_freq(beta, 3)
save_file = 'dimer_ipt_{}_B{}.npy'.format(phase, beta)
if os.path.exists(save_file):
return -np.load(save_file).T
for tp in tpr:
filestr = 'disk/phase_Dimer_ipt_{}_B{}/tp{:.3}/giw.npy'.format(
phase, beta, tp)
gfs = np.load(filestr)
dos_fl.append(
np.array([gf.fit_gf(w_n, gfs[i][0][:3])(0.) for i in ulist]))
np.save(save_file, dos_fl)
return -np.array(dos_fl).T
def dos_at_fermi_level_temp(xlist, temp, phasename, datapath):
dos_fl = []
save_file = 'phase_dimer_ipt_{}.npy'.format(phasename)
if os.path.exists(save_file):
dos_fl = np.load(save_file)
return dos_fl
for T in temp:
w_n = gf.matsubara_freq(1 / T, 3)
filestr = datapath.format(phasename, 1 / T)
gfs = np.load(filestr)
dos_fl.append(np.array([gf.fit_gf(w_n, gfs[i][0][:3])(0.)
for i in xlist]))
dos_fl = -np.array(dos_fl)
np.save(save_file, dos_fl)
return dos_fl
def dos_at_fermi_level_fixbeta(xlist, ylist, beta, phasename, datapath):
dos_fl = []
w_n = gf.matsubara_freq(beta, 3)
save_file = 'phase_dimer_ipt_{}.npy'.format(phasename)
if os.path.exists(save_file):
dos_fl = np.load(save_file)
return dos_fl
for xdat in xlist:
filestr = datapath.format(phasename, xdat)
gfs = np.load(filestr)
dos_fl.append(np.array([gf.fit_gf(w_n, gfs[i][0][:3])(0.)
for i in ylist]))
dos_fl = -np.array(dos_fl).T
np.save(save_file, dos_fl)
return dos_fl
def phase_diag_b(BETA_range, tp, filestr='HF_DIM_tp{tp}_B{BETA}.h5'):
for BETA in BETA_range:
tau, w_n = gf.tau_wn_setup(dict(BETA=BETA, N_MATSUBARA=BETA))
with h5.File(filestr.format(tp=tp, BETA=BETA), 'r') as results:
fl_dos = []
for u_str in results.keys():
lastit = results[u_str].keys()[-1]
giwd, _ = get_giw(results[u_str], lastit, tau, w_n)
fl_dos.append(gf.fit_gf(w_n[:3], giwd.imag)(0.))
u_range = np.array([float(u_str[1:]) for u_str in results.keys()])
plt.scatter(u_range,
np.ones(len(fl_dos)) / BETA,
c=fl_dos,
s=150,
vmin=-2,
vmax=0)
plt.ylim([0, 0.04])
plt.title(r'Phase diagram at $t_\perp={}$'.format(tp))
plt.ylabel(r'$T/D$')
plt.xlabel('$U/D$')
def fit_dos(beta, avg, filestr='disk/SB_PM_B{}'):
"""Fits for all Green's functions at a given beta their
density of states at the Fermi energy
Parameters
----------
beta: float inverse temperature
avg: int number of last iterations to average over
Return
------
arrays of Interaction, Fitted and source GF imaginary part
"""
u_range = []
figiw = []
lgiw = []
ulist = sorted([u_str for u_str in os.listdir(filestr.format(beta))
if 'U' in u_str])
for u_str in ulist:
sim_dir = os.path.join(filestr.format(beta), u_str)
last_iterations = sorted(
[it for it in os.listdir(sim_dir) if 'it' in it])[-avg:]
with open(sim_dir + '/setup', 'r') as read:
setup = json.load(read)
setup['U'] = float(u_str[1:])
tau, w_n = gf.tau_wn_setup(setup)
giw, _ = get_giw(sim_dir, last_iterations, tau, w_n, setup)
gfit = gf.fit_gf(w_n[:3], giw.imag)
figiw.append(gfit)
lgiw.append(giw)
u_range = np.asarray([float(u_str[1:]) for u_str in ulist])
return u_range, figiw, lgiw
def test_fit_gf():
"""Test the interpolation of Green function in Bethe Lattice"""
w_n = gf.matsubara_freq(100, 3)
giw = gf.greenF(w_n).imag
cont_g = gf.fit_gf(w_n, giw)
assert abs(cont_g(0.) + 2.) < 1e-4
for beta, result in zip(betarange, results):
u_zet = [matsubara_Z(sigma.imag, beta) for _, sigma in result]
axz.plot(Drange, u_zet, '+-', label='$\\beta={}$'.format(beta))
axz.set_title('Hysteresis loop of the quasiparticle weigth')
axz.legend(loc=0)
axz.set_ylabel('Z')
axz.set_xlabel('D/U')
###############################################################################
# Spectral density at Fermi level
# -------------------------------
figf, axf = plt.subplots()
for beta, result in zip(betarange, results):
tau, w_n = tau_wn_setup(dict(BETA=beta, N_MATSUBARA=3))
u_fl = [-fit_gf(w_n, g_iwn.imag)(0.) for g_iwn, _ in result]
axf.plot(Drange, u_fl, 'x:', label='$\\beta={}$'.format(beta))
axf.set_ylabel('Dos(0)')
axf.set_xlabel('D/U')
###############################################################################
# Double occupation
# -----------------
#
figd, axd = plt.subplots()
for beta, result in zip(betarange, results):
tau, w_n = tau_wn_setup(dict(BETA=beta, N_MATSUBARA=2**11))
V = np.asarray([
2 * (0.5 * s * g + 1 / 8. / w_n**2).real.sum() / beta