error

[fatima2000]

Hi, I would like to use the Hubbard-I solver on SrVO3 .I tried using Ce-gamma.py script.

this is the script I used for SrVO3.indmftpr

3 ! Nsort

1 1 I would like to use the Hubbard-I solver on SrVO3 .I tried using Ce-gamma.py script.3 !Mult(isrt)

3 ! lmax

complex

1 0 0 0 ! l included for each sort

0 0 0 0 ! l included for each sort

cubic

1 1 2 0 ! l included for each sort

0 0 2 0 ! l included for each sort

01 ! t2g Wannier function will be constructed

0 ! no spin-orbit

cubic

1 1 0 0 ! l included for each sort

0 0 0 0 ! l included for each sort

-0.075 0.14 ! Energy window relative to E_f

0.59953

and this is the script I used for SrVO3.py:

from pytriqs.Wien2k.SumK_LDA import from pytriqs.Wien2k.SumK_LDA_Wien2k_input import from pytriqs.Solvers.HubbardI.Solver_HubbardI import Solver_HubbardI

LDAFilename = 'SrVO3' Beta = 40 Uint = 2.70 JHund = 0.70 Loops = 3 # Number of DMFT sc-loops Mix = 0.7 # Mixing factor in QMC DC_type = 0 # 0...FLL, 1...Held, 2... AMF, 3...Lichtenstein DC_Mix = 1.0 # 1.0 ... all from imp; 0.0 ... all from Gloc

useBlocs = False # use bloc structure from LDA input useMatrix = True # use the U matrix calculated from Slater coefficients instead of (U+2J, U, U-J)

HDFfilename = LDAFilename+'.h5'

Convert DMFT input:

Can be commented after the first run

Converter = SumK_LDA_Wien2k_input(Filename=LDAFilename,repacking=False) Converter.convert_DMFT_input()

check if there are previous runs:

previous_runs = 0 previous_present = False

if MPI.IS_MASTER_NODE(): ar = HDF_Archive(HDFfilename,'a') if 'iterations' in ar: previous_present = True previous_runs = ar['iterations'] else: previous_runs = 0 previous_present = False del ar

MPI.barrier() previous_runs = MPI.bcast(previous_runs) previous_present = MPI.bcast(previous_present)

Init the SumK class

SK=SumK_LDA(HDFfile=LDAFilename+'.h5',UseLDABlocs=False)

Norb = SK.corr_shells[0][3] l = SK.corr_shells[0][2]

Init the Solver:

S = Solver_HubbardI(Beta = Beta, Uint = Uint, JHund = JHund, l = l, Verbosity=2) S.Nmoments=10

if (previous_present):

load previous data:

MPI.report("Using stored data for initialisation") if (MPI.IS_MASTER_NODE()): ar = HDF_Archive(HDFfilename,'a') S.Sigma <<= ar['SigmaF'] del ar S.Sigma = MPI.bcast(S.Sigma) SK.load()

DMFT loop:

for Iteration_Number in range(1,Loops+1): itn = Iteration_Number + previous_runs

# put Sigma into the SumK class:
SK.put_Sigma(Sigmaimp = [ S.Sigma ])

# Compute the SumK, possibly fixing mu by dichotomy
if SK.Density_Required and (Iteration_Number > 0):
    Chemical_potential = SK.find_mu( precision = 0.000001 )
else:
    MPI.report("No adjustment of chemical potential\nTotal density  = %.3f"%SK.total_density(mu=Chemical_potential))

# Density:
S.G <<= SK.extract_Gloc()[0]
MPI.report("Total charge of Gloc : %.6f"%S.G.total_density())
dm = S.G.density()

if ((Iteration_Number==1)and(previous_present==False)):

SK.SetDoubleCounting( dm, U_interact = Uint, J_Hund = JHund, orb = 0, useDCformula = DC_type)

# set atomic levels:
eal = SK.eff_atomic_levels()[0]
S.set_atomic_levels( eal = eal )

# update hdf5
if (MPI.IS_MASTER_NODE()):
    ar = HDF_Archive(HDFfilename,'a')
    ar['Chemical_Potential%s'%itn] = Chemical_potential
    del ar

# solve it:
S.Solve()

if (MPI.IS_MASTER_NODE()):
    ar = HDF_Archive(HDFfilename)
    ar['iterations'] = itn

# Now mix Sigma and G:
if ((itn>1)or(previous_present)):
    if (MPI.IS_MASTER_NODE()):
        MPI.report("Mixing Sigma and G with factor %s"%Mix)
        if ('SigmaF' in ar):
            S.Sigma <<= Mix * S.Sigma + (1.0-Mix) * ar['SigmaF']
        if ('GF' in ar):
            S.G <<= Mix * S.G + (1.0-Mix) * ar['GF']

    S.G = MPI.bcast(S.G)
    S.Sigma = MPI.bcast(S.Sigma)

if (MPI.IS_MASTER_NODE()):
    ar['SigmaF'] = S.Sigma
    ar['GF'] = S.G

# after the Solver has finished, set new double counting: 
dm = S.G.density()
SK.SetDoubleCounting( dm, U_interact = Uint, J_Hund = JHund, orb = 0, useDCformula = DC_type )
# correlation energy calculations:
correnerg = 0.5 * (S.G * S.Sigma).total_density()
MPI.report("Corr. energy = %s"%correnerg)
if (MPI.IS_MASTER_NODE()):
    ar['correnerg%s'%itn] = correnerg
    ar['DCenerg%s'%itn] = SK.DCenerg
    del ar

#Save stuff:
SK.save()
if (MPI.IS_MASTER_NODE()):
    print 'DC after solver: ',SK.dc_imp[SK.invshellmap[0]]

# do some analysis:
MPI.report("Orbital densities of impurity Green function:")
dm1 = S.G.density()
for s in dm1:
    MPI.report("Block %s: "%s)
    for ii in range(len(dm1[s])):
        str = ''
        for jj in range(len(dm1[s])):
            if (dm1[s][ii,jj].real>0):
                str += "   %.4f"%(dm1[s][ii,jj].real)
            else:
                str += "  %.4f"%(dm1[s][ii,jj].real)
        MPI.report(str)
MPI.report("Total charge of impurity problem : %.6f"%S.G.total_density())

find exact chemical potential

if (SK.Density_Required): SK.Chemical_potential = SK.find_mu( precision = 0.000001 ) dN,d = SK.calc_DensityCorrection(Filename = LDAFilename+'.qdmft')

MPI.report("Trace of Density Matrix: %s"%d)

correlation energy:

if (MPI.IS_MASTER_NODE()): ar = HDF_Archive(HDFfilename) itn = ar['iterations'] correnerg = ar['correnerg%s'%itn] DCenerg = ar['DCenerg%s'%itn] del ar correnerg -= DCenerg[0] f=open(LDAFilename+'.qdmft','a') f.write("%.16f\n"%correnerg) f.close()

The error message I got is:

Starting on 1 Nodes at : 2013-05-14 06:10:38.033072

Reading input from SrVO3.ctqmcout...

Reading symmetry input from SrVO3.symqmc...

Traceback (most recent call last):

File "SrVO3.py", line 67, in

SK.put_Sigma(Sigmaimp = [ S.Sigma ]) 

File

"/usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Wien2k/SumK_LDA.py",

line 806, in put_Sigma

self.Sigmaimp[icrsh][self.mapinv[s][bl]][ind1,ind2] <<= Sigmaimp[s][bl][ind1,ind2]

File

"/usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Base/GF_Local/GF.py",

line 227, in getitem

raise IndexError, "bloc index '" + repr(key) + "' incorrect. Possible indices are : "+

repr(self.__Indices)

IndexError: bloc index ''up0'' incorrect. Possible indices are : ['up', 'down']

can you help me?

thank you

[leopo]

I think this has already been discussed before, you may want to check the discussion here:

https://github.com/TRIQS/TRIQS/issues/92

[fatima2000]

Dear Leonid, Thanks for your previous helps, As you said I deleted the old .h5 before restarting calculations with the new script but again I confronted another error. The error is: Solver has not yet converged Mixing Sigma and G with factor 0.7 DC for shell 0 and block up = 2.991580 DC for shell 0 and block down = 2.991580 DC energy for shell 0 = 1.69139343302 Traceback (most recent call last):
File "SrVO3.py", line 122, in
correnerg = 0.5 * (S.G \ S.Sigma).total_density()
File "/usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Base/GF_Local/GF.py", line 356, in total_density
return sum([ g.total_density() for i,g in self ]).real File "/usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Base/GF_Local/_GFBloc_concept_impl.py", line 157, in total_density
return numpy.trace(self.density()) RuntimeError: Triqs runtime error at /usr/local/codes/dmftproj/TRIQS-TRIQS-6f4c392/pytriqs/Base/GF_Local/C++/GF_Bloc_ImFreq.cpp : 47

Trace is: /usr/local/codes/dmftproj/triqs_build/pytriqs/Base/GF_Local/libLocalGreenFunction_c.so GF_Bloc_ImFreq::density() const 0x19f8 [0x2b40642133b8] /usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Base/GF_Local/_pytriqs_GF.so boost::python::objects::caller_py_function_implboost::python::detail::caller<PyArray<std::complex<double, 2> (GF_BlocImFreq::)() const, boost::python::default_call_policies, boost::mpl::vector2<PyArray<std::complex, 2>, GF_Bloc_ImFreq &> > >::operator()(object, object) 0x39 [0x2b4061198969]
/usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so boost::python::objects::function::call(object, object) const 0x1af [0x2b4061763edf] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so 0xe6138 [0x2b4061764138] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const &) const 0x43 [0x2b406174f3b3] /usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/boost/mpi.so boost::detail::function::function_obj_invoker2<boost::_bi::bind_t<bool, boost::python::detail::translate_exception<boost::mpi::python::object_without_skeleton, boost::mpi::python::translate_exception >, boost::_bi::list3boost::arg<1, boost::arg<2>, boost::_bi::valueboost::mpi::python::translate_exception > >, bool, boost::python::detail::exception_handler const &, boost::function0 const &>::invoke(boost::detail::function::function_buffer &, boost::python::detail::exception_handler const &, boost::function0 const &) 0x1c [0x2b40674fe69c] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const &) const 0x26 [0x2b406174f396] /usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/boost/mpi.so boost::detail::function::function_obj_invoker2<boost::_bi::bind_t<bool, boost::python::detail::translate_exception<boost::mpi::exception, boost::mpi::python::translate_exception >, boost::_bi::list3boost::arg<1, boost::arg<2>, boost::_bi::valueboost::mpi::python::translate_exception > >, bool, boost::python::detail::exception_handler const &, boost::function0 const &>::invoke(boost::detail::function::function_buffer &, boost::python::detail::exception_handler const &, boost::function0 const &) 0x1c [0x2b40674f58cc] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const &) const 0x26 [0x2b406174f396] /usr/local/codes/dmftproj/triqs_build/INSTALL_DIR/lib/python2.7/site-packages/pytriqs/Base/GF_Local/_pytriqs_GF.so boost::detail::function::function_obj_invoker2<boost::_bi::bind_t<bool, boost::python::detail::translateexception<std::string ()(std::string const &)>, boost::_bi::list3boost::arg<1, boost::arg<2>, boost::_bi::value<void (*)(std::string const &)> > >, bool, boost::python::detail::exception_handler const &, boost::function0 const &>::invoke(boost::detail::function::function_buffer &, boost::python::detail::exception_handler const &, boost::function0 const &) 0x13 [0x2b4061187933] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so boost::python::handle_exception_impl(boost::function0) 0x29 [0x2b406174f199] /usr/local/codes/dmftproj/triqs_build/foreignlibs/boost/libboost_for_triqs.so 0xe43d4 [0x2b40617623d4] /usr/lib64/libpython2.7.so.1.0 PyObject_Call 0x53 [0x3f14249383] /usr/lib64/libpython2.7.so.1.0 PyEval_EvalFrameEx 0x3cd5 [0x3f142debb5] /usr/lib64/libpython2.7.so.1.0 PyEval_EvalFrameEx 0x587e [0x3f142e075e] /usr/lib64/libpython2.7.so.1.0 PyEval_EvalFrameEx 0x587e [0x3f142e075e] /usr/lib64/libpython2.7.so.1.0 PyEval_EvalCodeEx 0x855 [0x3f142e19a5] /usr/lib64/libpython2.7.so.1.0 PyEval_EvalCode 0x32 [0x3f142e1ad2] /usr/lib64/libpython2.7.so.1.0 [0x3f142fbd5c] /usr/lib64/libpython2.7.so.1.0 PyRun_FileExFlags 0x90 [0x3f142fcb60] /usr/lib64/libpython2.7.so.1.0 PyRun_SimpleFileExFlags 0xdf [0x3f142fd5df] /usr/lib64/libpython2.7.so.1.0 Py_Main 0xbe5 [0x3f1430ef15] /lib64/libc.so.6 __libc_start_main 0xed [0x3f01c2169d] /usr/bin/python [0x400651] GF_Bloc_ImFreq::density : Green Function is not as 1/omega or less !!!

what should I do now? Thank you for your help.

[leopo]

It seems your Green's function does not have a correct asymptotic behavior. If you still have the problem could you post here the actual script you have been using?

[fatima2000]

Thanks for your previous guidance, Note that, I've done LDA + DMFT calculation for the Ce-gamma with Hubbard-I solver, now want to do LDA + DMFT calculations for combination SrVO3 with CT-QMC solver but Unfortunately, the script is not correct for SrVO3.py And is not fully executed. Do I need to have another script or procedures of the Ce-gamma calculations with the Hubbard-I solver is done differently? and this is the script I used for SrVO3.py:

from pytriqs.Wien2k.SumK_LDA import from pytriqs.Wien2k.SumK_LDA_Wien2k_input import from pytriqs.Wien2k.Solver_MultiBand import from pytriqs.Base.GF_Local import from pytriqs.Base.Archive.HDF_Archive import * LDAFilename='srvo3' U = 2.7 J = 0.65 Beta = 40 Loops = 10 # Number of DMFT sc-loops Mix = 1.0 # Mixing factor of Sigma after solution of the AIM DeltaMix = 1.0 # Mixing factor of Delta as input for the AIM DC_type = 1 # DC type: 0 FLL, 1 Held, 2 AMF useBlocs = True # use bloc structure from LDA input useMatrix = False # True: Slater parameters, False: Kanamori parameters U+2J, U, U-J use_spinflip = False # use the full rotational invariant interaction? prec_mu = 0.0001 QMCcycles = 20000 Length_cycle = 200 Warming_iterations = 2000 Converter = SumK_LDA_Wien2k_input(Filename=LDAFilename,repacking=True) Converter.convert_DMFT_input() MPI.barrier() previous_runs = 0 previous_present = False if MPI.IS_MASTER_NODE(): ar = HDF_Archive(LDAFilename+'.h5','a') if 'iterations' in ar: previous_present = True previous_runs = ar['iterations'] del ar previous_runs = MPI.bcast(previous_runs) previous_present = MPI.bcast(previous_present)

if previous runs are present, no need for recalculating the bloc structure:

calc_blocs = useBlocs and (not previous_present) SK=SumK_LDA(HDFfile=LDAFilename+'.h5',UseLDABlocs=calc_blocs)

Norb = SK.corr_shells[0][3] l = SK.corr_shells[0][2] S=Solver_MultiBand(Beta=Beta,U_interact=U,J_Hund=J,Norb=Norb,useMatrix=useMatrix, T=SK.T[0] ,GFStruct=SK.GFStruct_Solver[0],map=SK.map[0], l=l, deg_orbs=SK.deg_shells[0], use_spinflip=use_spinflip)

S.N_Cycles = QMCcycles S.Length_Cycle = Length_cycle S.N_Warmup_Cycles = Warming_iterations if (previous_present): if (MPI.IS_MASTER_NODE()): ar = HDF_Archive(LDAFilename+'.h5','a') S.Sigma <<= ar['SigmaF'] del ar S.Sigma = MPI.bcast(S.Sigma) for IterationNumber in range(1,Loops+1) :

  SK.symm_deg_GF(S.Sigma,orb=0)                           # symmetrise Sigma
  SK.put_Sigma(Sigmaimp = [ S.Sigma ])                    # put Sigma into the SumK class:

  Chemical_potential = SK.find_mu( precision = prec_mu )  # find the chemical potential
  S.G <<= SK.extract_Gloc()[0]                            # calculation of the local Green function
  MPI.report("Total charge of Gloc : %.6f"%S.G.total_density())

  if ((IterationNumber==1)and(previous_present==False)):
      # Init the DC term and the real part of Sigma, if no previous run was found:
      dm = S.G.density()
      SK.SetDoubleCounting( dm, U_interact = U, J_Hund = J, orb = 0, useDCformula = DC_type)
      S.Sigma <<= GF_Initializers.Const(SK.dc_imp[0]['up'][0,0])

  # now calculate new G0:
  if (MPI.IS_MASTER_NODE()):
      # We can do a mixing of Delta in order to stabilize the DMFT iterations:
      S.G0 <<= S.Sigma + inverse(S.G)
      ar = HDF_Archive(LDAFilename+'.h5','a')
      if ((IterationNumber>1) or (previous_present)):
          MPI.report("Mixing input Delta with factor %s"%DeltaMix)
          Delta = (DeltaMix * S.G0.Delta()) + (1.0-DeltaMix) * ar['DeltaF']
          S.G0 <<= S.G0 + S.G0.Delta() - Delta

      ar['DeltaF'] = S.G0.Delta()
      S.G0 <<= inverse(S.G0)
      del ar

  S.G0 = MPI.bcast(S.G0)

  # Solve the impurity problem:
  S.Solve()

  # solution done, do the post-processing:
  MPI.report("Total charge of impurity problem : %.6f"%S.G.total_density())

  # Now mix Sigma and G with factor Mix, if wanted:
  if ((IterationNumber>1) or (previous_present)):
      if (MPI.IS_MASTER_NODE()):
          ar = HDF_Archive(LDAFilename+'.h5','a')
          MPI.report("Mixing Sigma and G with factor %s"%Mix)
          S.Sigma <<= Mix * S.Sigma + (1.0-Mix) * ar['SigmaF']
          S.G <<= Mix * S.G + (1.0-Mix) * ar['GF']
          del ar
      S.G = MPI.bcast(S.G)
      S.Sigma = MPI.bcast(S.Sigma)

  # Write the final Sigma and G to the hdf5 archive:
  if (MPI.IS_MASTER_NODE()):
      ar = HDF_Archive(LDAFilename+'.h5','a')
      ar['iterations'] = previous_runs + IterationNumber
      ar['SigmaF'] = S.Sigma
      ar['GF'] = S.G
      del ar

  # Now set new double counting:
  dm = S.G.density()
  SK.SetDoubleCounting( dm, U_interact = U, J_Hund = J, orb = 0, useDCformula = DC_type)

  #Save stuff:
  SK.save()

Kind regards.

[aichhorn]

The script looks fine. What does it mean, 'is not correct' and 'is not fully executed'. Where is the problem?

[parcollet]

No answer for 2 months. Closing.,