ALPS 2 Tutorials:DMFT-05 OSMT

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Tutorial 05: Orbitally Selective Mott Transition

An interesting phenomenon in multi-orbital models is the orbitally selective Mott transition, first examined by Anisimov et al. A variant of this, a momentum-selective Mott transition, has recently been discussed in cluster calculations as a cluster representation of pseudogap physics.

In an orbitally selective Mott transition some of the orbitals involved become Mott insulating as a function of doping or interactions, while others stay metallic.

As a minimal model we consider two bands: a wide band and a narrow band. In addition to the intra-orbital Coulomb repulsion U we consider interactions U', and J, with U' = U-2J. We limit ourselves to Ising-like interactions - a simplification that is often problematic for real compounds.

We choose here a case with two bandwidth t1=0.5 and t2=1 and density-density like interactions of U'=U/2, J=U/4, and U between 1.8 and 2.8, where the first case shows a Fermi liquid-like behavior in both orbitals, the U=2.2 is orbitally selective, and U=2.8 is insulating in both orbitals.

The python command lines for running the simulations are found in Alternatively, you can use the Vistrails file:

import pyalps
import numpy as np
import matplotlib.pyplot as plt
import pyalps.plot

#prepare the input parameters
for cp in [[1.8,0.45],[2.2,0.55],[2.8,0.7]]: 
             'CONVERGED'           : 0.001,
             'FLAVORS'             : 4,
             'H'                   : 0,
             'H_INIT'              : 0.,
             'MAX_IT'              : 15,
             'MAX_TIME'            : 600,
             'MU'                  : 0,
             'N'                   : 500,
             'NMATSUBARA'          : 500,
             'N_MEAS'              : 2000,
             'N_ORDER'             : 50,
             'SEED'                : 0,
             'SOLVER'              : 'hybridization',
             'SC_WRITE_DELTA'      : 1,
             'SYMMETRIZATION'      : 1,
             'SWEEPS'              : 10000,
             'BETA'                : 30,
             'THERMALIZATION'      : 500,
             'U'                   : cp[0],
             'J'                   : cp[1],
             't0'                  : 0.5,
             't1'                  : 1,
             'CHECKPOINT'          : 'dump'

#write the input file and run the simulation
for p in parms:
   input_file = pyalps.writeParameterFile('parm_u_'+str(p['U'])+'_j_'+str(p['J']),p)
   res = pyalps.runDMFT(input_file) 

A paper using the same sample parameters can be found here.

As discussed in the previous tutorial ALPS 2 Tutorials:DMFT-04 Mott, the (non-)metallicity of the Green's function is best observed by plotting the data on a logarithmic scale.

listobs = ['0', '2']   # flavor 0 is SYMMETRIZED with 1, flavor 2 is SYMMETRIZED with 3
data = pyalps.loadMeasurements(pyalps.getResultFiles(pattern='parm_u_*h5'), respath='/simulation/results/G_tau', what=listobs, verbose=True)
for d in pyalps.flatten(data):
   d.x = d.x*d.props["BETA"]/float(d.props["N"])
   d.y = -d.y
   d.props['label'] = r'$U=$'+str(d.props['U'])+'; flavor='+str(d.props['observable'][len(d.props['observable'])-1])
plt.title('DMFT-05: Orbitally Selective Mott Transition on the Bethe lattice')

Convergency may be checked by, showing all iterations of G_f^{it}(\tau) on logarithmic scale.

Tutorial by Emanuel - Please don't hesitate to ask!