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error in ctqmc solver with wien2triqs:Monte Carlo Error : the rate is not finite in move Insert3 #18

Closed zanat closed 12 years ago

zanat commented 12 years ago

I have an error when I try to run wien2triqs with ctqmc solver, with: Monte Carlo Error : the rate is not finite in move Insert3

no errors in the first iteration of ctqmc solver but in the (02) second iteration the program ends with error,

I have this lines after the run of dmftproj in wien2k :

The charge of the orbital is : 5.84384 Writing the file case.ctqmcout... Writing the file case.symqmc... Writing the file case.parproj... Writing the file case.sympar... Writing the file case.outbwin...

END OF THE PRGM Starting on 1 Nodes at : 2011-11-19 23:31:49.034242 Reading input from Os_qdmft.ctqmcout... Reading symmetry input from Os_qdmft.symqmc... Dichotomy adjustment of Chemical_Potential to obtain Total Density = 16.000000 +/- 0.000100 Chemical_Potential = -0.500000
Total Density = 15.307047 0.000000 < Chemical_Potential < -0.500000 16.107064 < Total Density < 15.307047 -0.066914 < Chemical_Potential < -0.500000 16.019393 < Total Density < 15.307047 -0.078705 < Chemical_Potential < -0.500000 16.002808 < Total Density < 15.307047 -0.080405 < Chemical_Potential < -0.500000 16.000388 < Total Density < 15.307047 -0.080641 < Chemical_Potential < -0.500000 16.000053 < Total Density < 15.307047 Chemical_Potential found in 5 iterations : Total Density = 16.000053;Chemical_Potential = -0.080641 Total charge of Gloc : 5.846901 /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Wien2k/SumK_LDA.py:687: ComplexWarning: Casting complex values to real discards the imaginary part dm[icrsh][self.mapinv[iorb][bl]][ind1,ind2] = densmat[bl][i,j] DC for shell 0 and block up = 9.921472 DC for shell 0 and block down = 9.921472 DC energy for shell 0 = 26.2926202201 DC for shell 1 and block up = 9.921472 DC for shell 1 and block down = 9.921472 DC energy for shell 1 = 26.2926202201

Optional parameters defined to their default values: *Global_Moves -> [] Description : A list of global moves

*Fitting_Frequency_Start -> 50 Description : Frequency at which the fit starts

*Record_Statistics_Configurations -> False Description : (Expert only) Get the kink length statistics

*Quantum_Numbers_Selection -> <function at 0x17b6b90> Description : (Prototype) A function to select quantum numbers

*Use_F -> False Description : (Expert only) Compute F

*Random_Generator_Name -> Description : Name of the random number generator

*Keep_Full_MC_Series -> False Description : (Expert only) Store the Green's function for later analysis

*N_Legendre_Coeffs -> 50 Description : Number of Legendre coefficients that are used in practice

*Measured_Operators -> {} Description : A dict of operators that will be averaged

*N_Time_Slices_Gtau -> 10000 Description : Number of times slices in G_tau

*N_Frequencies_Accumulated -> 100 Description : Number of frequencies to accumulate

*Time_Accumulation -> False Description : Do we accumulate in imaginary-time?

*Random_Seed -> 34788 Description : Seed for the random generator

*Eta -> 0.0 Description : (Expert only) Value of eta, the minimum value of the det

*Legendre_Accumulation -> True Description : Do we accumulate in legendre?

*Proba_Move -> 1.0 Description : Probability to move operators

*Proba_Insert_Remove -> 1.0 Description : Probability to insert/remove operators

*Measured_Time_Correlators -> {} Description : A dict of operators, whose time correlations are to be measured

Hamiltonian with Eps0 term : 1.35 C^(down0,0)C(down0,0)C^(down1,1)C(down1,1) + 1.35 C^(down0,0)C(down0,0)C^(down2,2)C(down2,2) + 1.35 C^(down0,0)C(down0,0)C^(down3,3)C(down3,3) + 1.35 C^(down0,0)C(down0,0)C^(down4,4)C(down4,4) + 1.35 C^(down1,1)C(down1,1)C^(down2,2)C(down2,2) + 1.35 C^(down1,1)C(down1,1)C^(down3,3)C(down3,3) + 1.35 C^(down1,1)C(down1,1)C^(down4,4)C(down4,4) + 1.35 C^(down2,2)C(down2,2)C^(down3,3)C(down3,3) + 1.35 C^(down2,2)C(down2,2)C^(down4,4)C(down4,4) + 1.35 C^(down3,3)C(down3,3)C^(down4,4)C(down4,4) + 3.3 C^(down0,0)C(down0,0)C^(up0,0)C(up0,0) + 2.0 C^(down0,0)C(down0,0)C^(up1,1)C(up1,1) + 2.0 C^(down0,0)C(down0,0)C^(up2,2)C(up2,2) + 2.0 C^(down0,0)C(down0,0)C^(up3,3)C(up3,3) + 2.0 C^(down0,0)C(down0,0)C^(up4,4)C(up4,4) + 2.0 C^(down1,1)C(down1,1)C^(up0,0)C(up0,0) + 3.3 C^(down1,1)C(down1,1)C^(up1,1)C(up1,1) + 2.0 C^(down1,1)C(down1,1)C^(up2,2)C(up2,2) + 2.0 C^(down1,1)C(down1,1)C^(up3,3)C(up3,3) + 2.0 C^(down1,1)C(down1,1)C^(up4,4)C(up4,4) + 2.0 C^(down2,2)C(down2,2)C^(up0,0)C(up0,0) + 2.0 C^(down2,2)C(down2,2)C^(up1,1)C(up1,1) + 3.3 C^(down2,2)C(down2,2)C^(up2,2)C(up2,2) + 2.0 C^(down2,2)C(down2,2)C^(up3,3)C(up3,3) + 2.0 C^(down2,2)C(down2,2)C^(up4,4)C(up4,4) + 2.0 C^(down3,3)C(down3,3)C^(up0,0)C(up0,0) + 2.0 C^(down3,3)C(down3,3)C^(up1,1)C(up1,1) + 2.0 C^(down3,3)C(down3,3)C^(up2,2)C(up2,2) + 3.3 C^(down3,3)C(down3,3)C^(up3,3)C(up3,3) + 2.0 C^(down3,3)C(down3,3)C^(up4,4)C(up4,4) + 2.0 C^(down4,4)C(down4,4)C^(up0,0)C(up0,0) + 2.0 C^(down4,4)C(down4,4)C^(up1,1)C(up1,1) + 2.0 C^(down4,4)C(down4,4)C^(up2,2)C(up2,2) + 2.0 C^(down4,4)C(down4,4)C^(up3,3)C(up3,3) + 3.3 C^(down4,4)C(down4,4)C^(up4,4)C(up4,4) + 1.35 C^(up0,0)C(up0,0)C^(up1,1)C(up1,1) + 1.35 C^(up0,0)C(up0,0)C^(up2,2)C(up2,2) + 1.35 C^(up0,0)C(up0,0)C^(up3,3)C(up3,3) + 1.35 C^(up0,0)C(up0,0)C^(up4,4)C(up4,4) + 1.35 C^(up1,1)C(up1,1)C^(up2,2)C(up2,2) + 1.35 C^(up1,1)C(up1,1)C^(up3,3)C(up3,3) + 1.35 C^(up1,1)C(up1,1)C^(up4,4)C(up4,4) + 1.35 C^(up2,2)C(up2,2)C^(up3,3)C(up3,3) + 1.35 C^(up2,2)C(up2,2)C^(up4,4)C(up4,4) + 1.35 C^(up3,3)C(up3,3)C^(up4,4)C(up4,4) - 10.175955810027299 C^(up0,0)C(up0,0) - 10.012478754073946 C^(up1,1)C(up1,1) - 10.012478754073946 C^(up2,2)C(up2,2) - 10.070431413969255 C^(up3,3)C(up3,3) - 10.070431413969255 C^(up4,4)C(up4,4) - 10.175955810027299 C^(down0,0)C(down0,0) - 10.012478754073946 C^(down1,1)C(down1,1) - 10.012478754073946 C^(down2,2)C(down2,2) - 10.070431413969255 C^(down3,3)C(down3,3) - 10.070431413969255 C^(down4,4)C(down4,4) Inv Fourier done 1%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 2%; 3%; 4%; 5%; 6%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 7%; 8%; 9%; 10%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 11%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 12%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 13%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 14%; 15%; 16%; 17%; 18%; 19%; 20%; 21%; 22%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 23%; 24%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 25%; 26%; 27%; 28%; 29%; 30%; 31%; 32%; 33%; 34%; 35%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 36%; 37%; 38%; 39%; 40%; 41%; 42%; 43%; Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! 44%; 45%; 46%; 47%; 48%; 49%; 50%; 51%; 52%; 53%; 54%; 55%; 56%; 57%; 58%; 59%; 60%; 61%; 62%; 63%; 64%; 65%; 66%; 67%; 68%; 69%; 70%; 71%; 72%; 73%; 74%; 75%; 76%; 77%; 78%; 79%; 80%; 81%; 82%; 83%; 84%; 85%; 86%; 87%; 88%; 89%; 90%; 91%; 92%; 93%; 94%; 95%; 96%; 97%; 98%; 99%; Move acceptance probability Move set : All moves Acceptance probability of move : INSERT : 0.644174 Move set : INSERT Acceptance probability of move : Insert0 : 0.645209 Acceptance probability of move : Insert1 : 0.652206 Acceptance probability of move : Insert2 : 0.646056 Acceptance probability of move : Insert3 : 0.64099 Acceptance probability of move : Insert4 : 0.641175 Acceptance probability of move : Insert5 : 0.648641 Acceptance probability of move : Insert6 : 0.646106 Acceptance probability of move : Insert7 : 0.643748 Acceptance probability of move : Insert8 : 0.640569 Acceptance probability of move : Insert9 : 0.637143 Acceptance probability of move : REMOVE : 0.641093 Move set : REMOVE Acceptance probability of move : Remove0 : 0.647515 Acceptance probability of move : Remove1 : 0.635865 Acceptance probability of move : Remove2 : 0.643769 Acceptance probability of move : Remove3 : 0.634925 Acceptance probability of move : Remove4 : 0.640759 Acceptance probability of move : Remove5 : 0.644758 Acceptance probability of move : Remove6 : 0.642036 Acceptance probability of move : Remove7 : 0.64457 Acceptance probability of move : Remove8 : 0.641115 Acceptance probability of move : Remove9 : 0.635697 Acceptance probability of move : Move C Delta : 0.798248 Monte-Carlo : Time measurements (cpu time) : time elapsed total : 7987 seconds Solver Hybridization Expansion has ended. Total charge of impurity problem : 5.877018 DC for shell 0 and block up = 9.977356 DC for shell 0 and block down = 9.977356 DC energy for shell 0 = 26.5922665608 DC for shell 1 and block up = 9.977356 DC for shell 1 and block down = 9.977356 DC energy for shell 1 = 26.5922665608 Dichotomy adjustment of Chemical_Potential to obtain Total Density = 16.000000 +/- 0.000100 Chemical_Potential = -0.580641
Total Density = 15.335968 -0.080641 < Chemical_Potential < -0.580641 16.116768 < Total Density < 15.335968 -0.155415 < Chemical_Potential < -0.580641 16.012104 < Total Density < 15.335968 -0.155415 < Chemical_Potential < -0.163028 16.012104 < Total Density < 15.999392 -0.162664 < Chemical_Potential < -0.163028 16.000005 < Total Density < 15.999392 Chemical_Potential found in 4 iterations : Total Density = 16.000005;Chemical_Potential = -0.162664 Total charge of Gloc : 5.873627 Mixing input G0inv with factor 1.0

Hamiltonian with Eps0 term : 1.35 C^(down0,0)C(down0,0)C^(down1,1)C(down1,1) + 1.35 C^(down0,0)C(down0,0)C^(down2,2)C(down2,2) + 1.35 C^(down0,0)C(down0,0)C^(down3,3)C(down3,3) + 1.35 C^(down0,0)C(down0,0)C^(down4,4)C(down4,4) + 1.35 C^(down1,1)C(down1,1)C^(down2,2)C(down2,2) + 1.35 C^(down1,1)C(down1,1)C^(down3,3)C(down3,3) + 1.35 C^(down1,1)C(down1,1)C^(down4,4)C(down4,4) + 1.35 C^(down2,2)C(down2,2)C^(down3,3)C(down3,3) + 1.35 C^(down2,2)C(down2,2)C^(down4,4)C(down4,4) + 1.35 C^(down3,3)C(down3,3)C^(down4,4)C(down4,4) + 3.3 C^(down0,0)C(down0,0)C^(up0,0)C(up0,0) + 2.0 C^(down0,0)C(down0,0)C^(up1,1)C(up1,1) + 2.0 C^(down0,0)C(down0,0)C^(up2,2)C(up2,2) + 2.0 C^(down0,0)C(down0,0)C^(up3,3)C(up3,3) + 2.0 C^(down0,0)C(down0,0)C^(up4,4)C(up4,4) + 2.0 C^(down1,1)C(down1,1)C^(up0,0)C(up0,0) + 3.3 C^(down1,1)C(down1,1)C^(up1,1)C(up1,1) + 2.0 C^(down1,1)C(down1,1)C^(up2,2)C(up2,2) + 2.0 C^(down1,1)C(down1,1)C^(up3,3)C(up3,3) + 2.0 C^(down1,1)C(down1,1)C^(up4,4)C(up4,4) + 2.0 C^(down2,2)C(down2,2)C^(up0,0)C(up0,0) + 2.0 C^(down2,2)C(down2,2)C^(up1,1)C(up1,1) + 3.3 C^(down2,2)C(down2,2)C^(up2,2)C(up2,2) + 2.0 C^(down2,2)C(down2,2)C^(up3,3)C(up3,3) + 2.0 C^(down2,2)C(down2,2)C^(up4,4)C(up4,4) + 2.0 C^(down3,3)C(down3,3)C^(up0,0)C(up0,0) + 2.0 C^(down3,3)C(down3,3)C^(up1,1)C(up1,1) + 2.0 C^(down3,3)C(down3,3)C^(up2,2)C(up2,2) + 3.3 C^(down3,3)C(down3,3)C^(up3,3)C(up3,3) + 2.0 C^(down3,3)C(down3,3)C^(up4,4)C(up4,4) + 2.0 C^(down4,4)C(down4,4)C^(up0,0)C(up0,0) + 2.0 C^(down4,4)C(down4,4)C^(up1,1)C(up1,1) + 2.0 C^(down4,4)C(down4,4)C^(up2,2)C(up2,2) + 2.0 C^(down4,4)C(down4,4)C^(up3,3)C(up3,3) + 3.3 C^(down4,4)C(down4,4)C^(up4,4)C(up4,4) + 1.35 C^(up0,0)C(up0,0)C^(up1,1)C(up1,1) + 1.35 C^(up0,0)C(up0,0)C^(up2,2)C(up2,2) + 1.35 C^(up0,0)C(up0,0)C^(up3,3)C(up3,3) + 1.35 C^(up0,0)C(up0,0)C^(up4,4)C(up4,4) + 1.35 C^(up1,1)C(up1,1)C^(up2,2)C(up2,2) + 1.35 C^(up1,1)C(up1,1)C^(up3,3)C(up3,3) + 1.35 C^(up1,1)C(up1,1)C^(up4,4)C(up4,4) + 1.35 C^(up2,2)C(up2,2)C^(up3,3)C(up3,3) + 1.35 C^(up2,2)C(up2,2)C^(up4,4)C(up4,4) + 1.35 C^(up3,3)C(up3,3)C^(up4,4)C(up4,4) - 2.537454018078277 C^(up0,0)C(up0,0) - 2.496584765934286 C^(up1,1)C(up1,1) - 2.496584765934286 C^(up2,2)C(up2,2) - 2.5110729238031597 C^(up3,3)C(up3,3) - 2.5110729238031597 C^(up4,4)C(up4,4) - 2.537454018078277 C^(down0,0)C(down0,0) - 2.496584765934286 C^(down1,1)C(down1,1) - 2.496584765934286 C^(down2,2)C(down2,2) - 2.5110729238031597 C^(down3,3)C(down3,3) - 2.5110729238031597 C^(down4,4)C(down4,4) Inv Fourier done Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! Node : 0 WARNING : RESIZING THE MATRIX : it will be slow if it happens too often ! Traceback (most recent call last): File "Os_qdmft.py", line 97, in S.Solve() File "/home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/init.py", line 296, in Solve C_Module.MC_solve(self.dict ) # C++ solver RuntimeError: Triqs runtime error at /home/zanat/WIEN2k_11/SRC_triqsdmft/triqs/mc_tools/./mc_move_set1.hpp : 175

Trace is :

/home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so triqs::mc_tools::move_setstd::complex::Try() 0x140 [0x2b7fdcd1c180] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so triqs::mc_tools::details::move_implstd::complex<double, triqs::mc_tools::move_setstd::complex >::Try() 0x12 [0x2b7fdcd1c302] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so triqs::mc_tools::mc_genericstd::complex<double, triqs::python_tools::improved_python_dict, triqs::mc_tools::Step::Metropolisstd::complex >::run(boost::function<bool ()()> const&) 0x10f [0x2b7fdcd17f7f] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so MC_Hybridization_Matsu::solve(boost::python::api::object) 0x196 [0x2b7fdcd12176] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so boost::python::objects::caller_py_function_impl<boost::python::detail::caller<void ()(boost::python::api::object), boost::python::default_call_policies, boost::mpl::vector2<void, boost::python::api::object> > >::operator()(object, object) 0x1c [0x2b7fdcd2e1ac] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::objects::function::call(object, object) const 0x2be [0x2b7fd4098f8e] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so 0xf51e8 [0x2b7fd40991e8] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const&) const 0x43 [0x2b7fd4083833] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Solvers/HybridizationExpansion/_pytriqs_Solver_HybridizationExpansion.so boost::detail::function::function_obj_invoker2<boost::_bi::bind_t<bool, boost::python::detail::translate_exception<H5::Exception ()(H5::Exception const&)>, boost::_bi::list3boost::arg<1, boost::arg<2>, boost::_bi::value<void ()(H5::Exception 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 [0x2b7fdcd2dc23] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const&) const 0x23 [0x2b7fd4083813] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-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&) 0xf [0x2b7fd9754f2f] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const&) const 0x23 [0x2b7fd4083813] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-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&) 0xf [0x2b7fd974c45f] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::detail::exception_handler::operator()(boost::function0 const&) const 0x23 [0x2b7fd4083813] /home/zanat/WIEN2k_11/BIN_triqsdmft/lib/python2.7/dist-packages/pytriqs/Base/GF_Local/_pytriqs_GF.so boost::detail::function::function_obj_invoker2<boost::_bi::bind_t<bool, boost::python::detail::translate_exception<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 [0x2b7fd326ea73] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so boost::python::handle_exception_impl(boost::function0) 0x29 [0x2b7fd40835d9] /home/zanat/WIEN2k_11/BLD_triqsdmft/foreignlibs/boost/libboost_for_triqs.so 0xf66e4 [0x2b7fd409a6e4] /usr/bin/python PyObject_Call 0x44 [0x45d864] /usr/bin/python PyEval_EvalFrameEx 0x9be [0x496c4e] /usr/bin/python PyEval_EvalCodeEx 0x6a5 [0x49d885] /usr/bin/python PyEval_EvalFrameEx 0x802 [0x496a92] /usr/bin/python PyEval_EvalCodeEx 0x145 [0x49d325] /usr/bin/python PyEval_EvalCode 0x32 [0x4ecb02] /usr/bin/python [0x4fdc74] /usr/bin/python PyRun_FileExFlags 0x90 [0x42c182] /usr/bin/python PyRun_SimpleFileExFlags 0x2dd [0x42cb4a] /usr/bin/python Py_Main 0xac9 [0x418c9e] /lib/x86_64-linux-gnu/libc.so.6 __libc_start_main 0xff [0x2b7fcf995eff] /usr/bin/python [0x4c62b1]

Monte Carlo Error : the rate is not finite in move Insert3 forrtl: severe (24): end-of-file during read, unit 32, file /home/zanat/WIEN2k/Os_qdmft/Os_qdmft/Os_qdmft.qdmft

aichhorn commented 12 years ago

Your atomic levels in the second iteration look suspicious, they change from -10 to -2, roughly. The Gloc seems to be okay, getting the new G0 seems to be not okay. Try to remove everything that is related to mixing Sigma, and also G0. Not just setting Mix=1.0, but litterally removing the parts form the scripts (sometimes I encountered issues with the reading of GF's from the hdf archive in this context). Without looking at the script your are using it is hard to tell what can go wrong.

zanat commented 12 years ago

in the following, the script i used it in wien2triqs and the input to dmftproj case.indmftpr, I introduce the modification related to mult=2 of for the correlated atom.

the script ctqmc_2a.py : corrected and adopted to mult=2

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 GF_Initializers from pytriqs.Base.GF_Local import inverse

import os LDAFilename = os.getcwd().rpartition('/')[2]

U = 2.0 J = 0.65 Beta = 40 Loops = 3 # Number of DMFT sc-loops Mix = 1.0 # Mixing factor of Sigma after solution of the AIM G0inv_Mix = 1.0 # Mixing factor of the inverse of G0 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 = 0.000001 QMCcycles = 1000 #0x2 only for test use : value/10/2 Length_cycle = 10 #0x2 in order to speedup the run Warming_iterations = 100 #0x2 NN_Matsubara_Frequencies = 1025

HDFfilename = LDAFilename+'.h5'

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 S.N_Matsubara_Frequencies = NN_Matsubara_Frequencies

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())
  dm = S.G.density()

  if ((IterationNumber==1)and(previous_present==False)):
      # Init the DC term and the real part of Sigma, if no previous run was found:
      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 G0^-1, in order to stabilize the DMFT iterations:
      # corresponds to a mixing of Delta
      S.G0 <<= S.Sigma + inverse(S.G)
      ar = HDF_Archive(HDFfilename,'a')
      if ((IterationNumber>1) or (previous_present)):
          MPI.report("Mixing input G0inv with factor %s"%G0inv_Mix)
          S.G0 <<= G0inv_Mix * S.G0 + (1.0-G0inv_Mix) * ar['G0invF']
      ar['G0invF'] = S.G0
      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:
  ar = HDF_Archive(HDFfilename,'a')
  if ((IterationNumber>1) or (previous_present)):
      if (MPI.IS_MASTER_NODE()):
          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']
      S.G = MPI.bcast(S.G)
      S.Sigma = MPI.bcast(S.Sigma)
  del ar

  # Write the final Sigma and G to the hdf5 archive:
  if (MPI.IS_MASTER_NODE()):
      ar = HDF_Archive(HDFfilename)
      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()

find exact chemical potential

if (SK.Density_Required): SK.Chemical_potential = SK.find_mu( precision = prec_mu ) 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]

if MULT = 2

correnerg  = 2. * correnerg
f=open(LDAFilename+'.qdmft','a')
f.write("%.16f\n"%correnerg)
f.close()

end of ctqmc_2a script

case.indmftpr for Os hcp mult=2

1 ! Nsort 2 ! Mult(Nsort) 3 ! lmax cubic ! choice of angular harmonics 1 1 2 0 ! l included for each sort 0 0 0 0 ! If split into ireps, gives number of ireps. for a given orbital (otherwise 0) 0 ! ! SO flag -5.0 8.0 ! use this, then we try adjust it ! t2g + eg + Op

zanat commented 12 years ago

in the following, the script i used it in wien2triqs and the input to dmftproj case.indmftpr, I introduce the modification related to mult=2 of for the correlated atom.

the script ctqmc_2a.py : corrected and adopted to mult=2

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 GF_Initializers from pytriqs.Base.GF_Local import inverse

import os LDAFilename = os.getcwd().rpartition('/')[2]

U = 2.0 J = 0.65 Beta = 40 Loops = 3 # Number of DMFT sc-loops Mix = 1.0 # Mixing factor of Sigma after solution of the AIM G0inv_Mix = 1.0 # Mixing factor of the inverse of G0 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 = 0.000001 QMCcycles = 1000 #0x2 only for test use : value/10/2 Length_cycle = 10 #0x2 in order to speedup the run Warming_iterations = 100 #0x2 NN_Matsubara_Frequencies = 1025

HDFfilename = LDAFilename+'.h5'

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 S.N_Matsubara_Frequencies = NN_Matsubara_Frequencies

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()) dm = S.G.density()

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

Init the DC term and the real part of Sigma, if no previous

run was found: 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 G0^-1, in order to stabilize the DMFT iterations:

  # corresponds to a mixing of Delta
  S.G0 <<= S.Sigma + inverse(S.G)
  ar = HDF_Archive(HDFfilename,'a')
  if ((IterationNumber>1) or (previous_present)):
      MPI.report("Mixing input G0inv with factor %s"%G0inv_Mix)
      S.G0 <<= G0inv_Mix \* S.G0 + (1.0-G0inv_Mix) \* ar['G0invF']
  ar['G0invF'] = S.G0
  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:

ar = HDF_Archive(HDFfilename,'a') if ((IterationNumber>1) or (previous_present)): if (MPI.IS_MASTER_NODE()): 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'] S.G = MPI.bcast(S.G) S.Sigma = MPI.bcast(S.Sigma) del ar

Write the final Sigma and G to the hdf5 archive:

if (MPI.IS_MASTER_NODE()): ar = HDF_Archive(HDFfilename) 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()

find exact chemical potential

if (SK.Density_Required): SK.Chemical_potential = SK.find_mu( precision = prec_mu ) 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]

if MULT = 2

correnerg = 2. * correnerg f=open(LDAFilename+'.qdmft','a') f.write("%.16f\n"%correnerg) f.close()

end of ctqmc_2a script

case.indmftpr for Os hcp mult=2

1 ! Nsort 2 ! Mult(Nsort) 3 ! lmax cubic ! choice of angular harmonics 1 1 2 0 ! l included for each sort 0 0 0 0 ! If split into ireps, gives number of ireps. for a given orbital (otherwise 0) 0 ! ! SO flag -5.0 8.0 ! use this, then we try adjust it ! t2g + eg + Op

On Fri, Dec 23, 2011 at 8:52 PM, Markus Aichhorn < reply@reply.github.com

wrote:

Your atomic levels in the second iteration look suspicious, they change from -10 to -2, roughly. The Gloc seems to be okay, getting the new G0 seems to be not okay. Try to remove everything that is related to mixing Sigma, and also G0. Not just setting Mix=1.0, but litterally removing the parts form the scripts (sometimes I encountered issues with the reading of GF's from the hdf archive in this context). Without looking at the script your are using it is hard to tell what can go wrong.

Reply to this email directly or view it on GitHub: https://github.com/TRIQS/TRIQS/issues/18#issuecomment-3264140

Dr. Zanat K. Guelma University Physics Laboratory Of Condensed Matter Algeria zanat.k@gmail.com

aichhorn commented 12 years ago

The calculation of the new G0 is the problem. Instead of the lines:

now calculate new G0:

if (MPI.IS_MASTER_NODE()):

We can do a mixing of G0^-1, in order to stabilize the DMFT iterations:

  # corresponds to a mixing of Delta
  S.G0 <<= S.Sigma + inverse(S.G)
  ar = HDF_Archive(HDFfilename,'a')
  if ((IterationNumber>1) or (previous_present)):
      MPI.report("Mixing input G0inv with factor %s"%G0inv_Mix)
      S.G0 <<= G0inv_Mix \* S.G0 + (1.0-G0inv_Mix) \* ar['G0invF']
  ar['G0invF'] = S.G0
  S.G0 <<= inverse(S.G0)
  del ar

just write:

S.G0 <<= inverse(S.Sigma+inverse(S.G))

Then it should work. The mixing of G0 is normally not necessary, so we just don't do it. Be careful: In your test you are doing a 5 orbital calculation with just a thousand MC iterations. What you get out will be basically noise, and not a lot of useful data.

zanat commented 12 years ago

thank you, I will try this. about the MC iteration, I lower it just when the error occurs in the run, a debug or test run again, thank you very much and happy new year

On Mon, Jan 2, 2012 at 2:15 PM, Markus Aichhorn < reply@reply.github.com

wrote:

The calculation of the new G0 is the problem. Instead of the lines:

now calculate new G0:

if (MPI.IS_MASTER_NODE()):

We can do a mixing of G0^-1, in order to stabilize the DMFT

iterations:

corresponds to a mixing of Delta

 S.G0 <<= S.Sigma + inverse(S.G)
 ar = HDF_Archive(HDFfilename,'a')
 if ((IterationNumber>1) or (previous_present)):
     MPI.report("Mixing input G0inv with factor %s"%G0inv_Mix)
     S.G0 <<= G0inv_Mix \* S.G0 + (1.0-G0inv_Mix) \* ar['G0invF']
 ar['G0invF'] = S.G0
 S.G0 <<= inverse(S.G0)
 del ar

just write:

S.G0 <<= inverse(S.Sigma+inverse(S.G))

Then it should work. The mixing of G0 is normally not necessary, so we just don't do it. Be careful: In your test you are doing a 5 orbital calculation with just a thousand MC iterations. What you get out will be basically noise, and not a lot of useful data.

Reply to this email directly or view it on GitHub: https://github.com/TRIQS/TRIQS/issues/18#issuecomment-3329568

Dr. Zanat K. Guelma University Physics Laboratory Of Condensed Matter Algeria zanat.k@gmail.com