e_f, Beta = -U / 2.0, 50
# The impurity solver
S = Solver(
Beta=Beta, # inverse temperature
GFstruct=[('up', [1]),
('down', [1])], # Structure of the Green's function
H_Local=U * N('up', 1) * N('down', 1), # Local Hamiltonian
Quantum_Numbers={ # Quantum Numbers
'Nup': N('up', 1), # (operators commuting with H_Local)
'Ndown': N('down', 1)
},
N_Cycles=500000, # Number of QMC cycles
Length_Cycle=200, # Length of one cycle
N_Warmup_Cycles=10000, # Warmup cycles
N_Legendre_Coeffs=50, # Number of Legendre coefficients
Random_Generator_Name='mt19937', # Name of the random number generator
Use_Segment_Picture=True, # Use the segment picture
Measured_Operators={ # Operators to be averaged
'Nimp': N('up', 1) + N('down', 1)
},
Global_Moves=[ # Global move in the QMC
(0.05, lambda (a, alpha, dag): ({
'up': 'down',
'down': 'up'
}[a], alpha, dag))
],
)
# Initialize the non-interacting Green's function S.G0
for spin, g0 in S.G0:
U = 2.5
Chemical_Potential = U / 2.0
Beta = 100
N_loops = 5
# Construct a CTQMC solver
from pytriqs.Solvers.Operators import * # imports the class manipulating C, C_dagger and N = C_dagger C
from pytriqs.Solvers.HybridizationExpansion import Solver # imports the solver class
S = Solver(
Beta=Beta, # inverse temperature
GFstruct=[('up', [1]), ('down', [1])], # Structure of the Green function
H_Local=U * N('up', 1) * N('down', 1), # Local Hamiltonian
Quantum_Numbers={
'Nup': N('up', 1),
'Ndown': N('down', 1)
}, # Quantum Numbers (operators commuting with H_Local)
N_Cycles=5000, # Number of QMC cycles
Length_Cycle=200, # Length of a cycle
N_Warmup_Cycles=1000, # How many warmup cycles
N_Legendre_Coeffs=30, # Use 30 Legendre coefficients to represent G(tau)
Random_Generator_Name=
"mt19937", # Use the Mersenne Twister 19937 random generator
Use_Segment_Picture=True) # Here we can use the segment picture
# Initalize the Green's function to a semi circular
S.G <<= SemiCircular(Half_Bandwidth)
# Now do the DMFT loop
for IterationNumber in range(N_loops):
# Compute S.G0 with the self-consistency condition while imposing paramagnetism
Chemical_Potential = U / 2.0
Beta = 100
# Construct a CTQMC solver
from pytriqs.Solvers.Operators import * # imports the class manipulating C, C_dagger and N = C_dagger C
from pytriqs.Solvers.HybridizationExpansion import Solver # imports the solver class
S = Solver(
Beta=Beta, # inverse temperature
GFstruct=[('up', [1]), ('down', [1])], # Structure of the Green function
H_Local=U * N('up', 1) * N('down', 1), # Local Hamiltonian
Quantum_Numbers={
'Nup': N('up', 1),
'Ndown': N('down', 1)
}, # Quantum Numbers (operators commuting with H_Local)
N_Cycles=
5000, #200000, # Number of QMC cycles
Length_Cycle=500,
N_Warmup_Cycles=5000,
N_Time_Slices_Delta=10000,
N_Time_Slices_Gtau=1000,
Random_Generator_Name="",
N_Legendre_Coeffs=30,
#Random_Generator_Name = "mt19937",
Use_Segment_Picture=True)
#S.Proba_Move = 0.0
#S.Global_Moves = [ (0.01, lambda (a,alpha,dag) : (a, alpha, dag)),
# (0.01, lambda (a,alpha,dag) : ({'up' : 'down', 'down' : 'up'}[a], alpha, dag)) ]
# init the Green function
#S.G <<= GF_Initializers.SemiCircular(Half_Bandwidth)
from pytriqs.Base.GF_Local import *
from pytriqs.Solvers.Operators import *
from pytriqs.Solvers.HybridizationExpansion import Solver
D, V, U = 1.0, 0.2, 4.0
e_f, Beta = -U/2.0, 50
# The impurity solver
S = Solver(Beta = Beta, # inverse temperature
GFstruct = [ ('up',[1]), ('down',[1]) ], # Structure of the Green's function
H_Local = U * N('up',1) * N('down',1), # Local Hamiltonian
Quantum_Numbers = { # Quantum Numbers
'Nup' : N('up',1), # (operators commuting with H_Local)
'Ndown' : N('down',1) },
N_Cycles = 100000, # Number of QMC cycles
Length_Cycle = 200, # Length of one cycle
N_Warmup_Iteration = 10000, # Warmup cycles
Use_Segment_Picture = True, # Use the segment picture
Global_Moves = [ # Global move in the QMC
(0.05, lambda (a,alpha,dag) : ( {'up':'down','down':'up'}[a],alpha,dag ) ) ],
)
from pytriqs.Base.Archive import HDF_Archive
import pytriqs.Base.Utility.MPI as MPI
for random_name in ['mt11213b','lagged_fibonacci607']:
# Solve using random_name as a generator
S.Random_Generator_Name = random_name
for spin, g0 in S.G0 :
g0 <<= inverse( iOmega_n - e_f - V**2 * Wilson(D) )
