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G0_iw is not invertible in first iteration #136

Closed cmtcl18 closed 4 years ago

cmtcl18 commented 4 years ago

Hi Alex, As the previous issue is close, I opened a new issue. As per the suggestion, I used the soliDMFT code, but got error while solving the impurity for shell 0. The out.txt file that you have sent to me, run without error during solving for impurity model for shell 0. Here I am giving the output of the calculation using soliDMFT code.

WARNING: The product of atomic operators has a matrix element in the off-diagonal block (2,4) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (4,6) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (4,6) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (6,4) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (6,2) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (16,14) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (11,16) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (14,11) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (6,4) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (6,4) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (11,14) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (6,4) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (2,6) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: The product of atomic operators has a matrix element in the off-diagonal block (2,6) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian! WARNING: Tau discontinuity of G_tau deviates appreciably from -1 .... max_element |g(0) + g(beta) + 1| = 0.0169918 WARNING: Tau discontinuity of G_tau deviates appreciably from -1 .... max_element |g(0) + g(beta) + 1| = 0.0322339 [Rank 0] Timings for all measures: Measure | seconds
Average sign | 4.99893
Density Matrix for local static observable | 1.72085
G_tau measure | 59.2427
Total measure time | 65.9625
[Rank 0] Acceptance rate for all moves: Move set Insert two operators: 0.00312868 Move Insert Delta_up_0: 0.00311836 Move Insert Delta_down_0: 0.00313901 Move set Remove two operators: 0.00306528 Move Remove Delta_up_0: 0.00305837 Move Remove Delta_down_0: 0.00307218 Move set Insert four operators: 2.38689e-05 Move Insert Delta_up_0_up_0: 3.43504e-05 Move Insert Delta_up_0_down_0: 1.64235e-05 Move Insert Delta_down_0_up_0: 1.61089e-05 Move Insert Delta_down_0_down_0: 2.85935e-05 Move set Remove four operators: 2.35078e-05 Move Remove Delta_up_0_up_0: 3.24203e-05 Move Remove Delta_up_0_down_0: 1.4306e-05 Move Remove Delta_down_0_up_0: 1.73408e-05 Move Remove Delta_down_0_down_0: 2.99645e-05 Move Shift one operator: 0.193737 [Rank 0] Warmup lasted: 60.4364 seconds [00:01:00] [Rank 0] Simulation lasted: 325.042 seconds [00:05:25] [Rank 0] Number of measures: 83333 Total number of measures: 999996 Average sign: 1 /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density() /home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py:795: ComplexWarning: Casting complex values to real discards the imaginary part density_shell[icrsh] = solvers[icrsh].G_iw.total_density()

Total charge of impurity problem: 5.39536 Total charge convergency of impurity problem: 0.10046

Density matrix: up_0 [[ 0.95453704 -0. 0. ] [-0. 0.75953365 -0. ] [ 0. -0. 0.97351506]] ('eigenvalues: ', array([0.75953365, 0.95453704, 0.97351506])) down_0 [[ 0.97064228 -0. 0. ] [-0. 0.7673585 -0. ] [ 0. -0. 0.96977338]] ('eigenvalues: ', array([0.7673585 , 0.96977338, 0.97064228]))

*** Correlated Shell type # 1 : Total charge of impurity problem = 1.606798 Density matrix: up_0 [[ 0.40169949 -0. -0. ] [-0. 0.20084974 -0. ] [-0. -0. 0.20084974]] down_0 [[ 0.40169949 -0. -0. ] [-0. 0.20084974 -0. ] [-0. -0. 0.20084974]] Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in Traceback (most recent call last): File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 160, in main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) main() File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/run_dmft.py", line 151, in main observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables = dmft_cycle(general_parameters, solver_parameters, advanced_parameters, observables) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 606, in dmft_cycle observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps observables, dft_mu, G_loc_all_dft, density_mat_dft) File "/home/hp/TEST_cal/CCRO_NM/soliDMFT-master/dmft_cycle.py", line 671, in _dmft_steps solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/tools.py", line 39, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return x.inverse() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/block_gf.py", line 413, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse return self.class( name_block_generator = [ (n, g.inverse()) for n,g in self], make_copies=False) File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 603, in inverse r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert r.invert() File "/home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py", line 589, in invert wrapped_aux._gf_invert_data_in_place(d) wrapped_aux._gf_invert_data_in_place(d) wrapped_aux._gf_invert_data_in_place(d) RuntimeError wrapped_aux._gf_invert_data_in_place(d) RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 3 wrapped_aux._gf_invert_data_in_place(d) RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 4

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 5

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 6

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 7

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 8

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 9

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 10

wrapped_aux._gf_invert_data_in_place(d)

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 11

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 0

RuntimeError: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 1

: .. Error occurred at Sat Apr 18 14:17:27 2020

.. Error .. calling C++ overload .. _gf_invert_data_in_place(array_view <dcomplex,3> a) -> void .. in implementation of function wrapped_aux._gf_invert_data_in_place .. C++ error was : Inverse/Det error : matrix is not invertible .. Error occurred on node 2

Warm Regards CMTCL

the-hampel commented 4 years ago

Okay that is good news! So this shows, that it is not related to any segmentation fault! Now, we need to figure out, why your script crashes and mine does work. Do you have any ideas?

Regarding the error that my script throws: I looked at the h5 file you gave me and the non-interacting local Green's function is badly conditioned. triqs tries to invert it here: solvers[icrsh].G0_iw << inverse(solvers[icrsh].Sigma_iw + inverse(solvers[icrsh].G_iw)) Since Sigma_iw is zero at this point (0th DMFT iteration) it is simply this operation which fails: inverse(inverse(solvers[icrsh].G_iw))) If I try to manually invert it first once and it looks like this: image But it should look like something like this: image So I assume your input data from DFT is not good, because in the first plot many of the data points are just 0, so the inversion did not work properly. I noticed that you only have something like 35 kpoints or so? This could lead to problems maybe, can you try to increase the number of kpoints? What kind of kpoint Grid are you using?

Second idea: reduce the energy window. Your energy window in enormously large, from -80 to 20 eV. Do you need all these states? Best, Alex

cmtcl18 commented 4 years ago

Dear Alex, I increased the number of kpoints and reduced the correlated subspace range. Here I am giving the self consistency python script in zip format and the error I got.

CCRO_NM_h5_file.zip

Starting run with 12 MPI rank(s) at : 2020-04-22 23:31:35.060862 iteration = 1 /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] Dichotomy adjustment of Chemical Potential to obtain Total Density = 230.000000 +/- 0.000100 /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] Warning: Imaginary part in density will be ignored (1.458255933400377e-11) Warning: Imaginary part in density will be ignored (2.772654504801064e-11) Chemical Potential = 0.500000
Total Density = 87.836734 Warning: Imaginary part in density will be ignored (4.8366536589333785e-11) Chemical Potential = 1.000000
Total Density = 87.836913 Warning: Imaginary part in density will be ignored (7.990021939486199e-11) Chemical Potential = 1.500000
Total Density = 87.837118 Warning: Imaginary part in density will be ignored (1.2694516708516173e-10) Chemical Potential = 2.000000
Total Density = 87.837348 Warning: Imaginary part in density will be ignored (1.9560959579125196e-10) Chemical Potential = 2.500000
Total Density = 87.837608 Warning: Imaginary part in density will be ignored (2.9386855110107923e-10) Chemical Potential = 3.000000
Total Density = 87.837897 Warning: Imaginary part in density will be ignored (4.319400322007716e-10) Chemical Potential = 3.500000
Total Density = 87.838219 Warning: Imaginary part in density will be ignored (6.228372348485778e-10) Chemical Potential = 4.000000
Total Density = 87.838573 Warning: Imaginary part in density will be ignored (8.828200871873193e-10) Chemical Potential = 4.500000
Total Density = 87.838963 Warning: Imaginary part in density will be ignored (1.232070644970898e-09) Chemical Potential = 5.000000
Total Density = 87.839389 Warning: Imaginary part in density will be ignored (1.6952804603037012e-09) Chemical Potential = 5.500000
Total Density = 87.839853 Warning: Imaginary part in density will be ignored (2.3024496691483485e-09) Chemical Potential = 6.000000
Total Density = 87.840357 Warning: Imaginary part in density will be ignored (3.089683789100156e-09) Chemical Potential = 6.500000
Total Density = 87.840903 Warning: Imaginary part in density will be ignored (4.100071663314881e-09) Chemical Potential = 7.000000
Total Density = 87.841492 Warning: Imaginary part in density will be ignored (5.384657216887117e-09) Chemical Potential = 7.500000
Total Density = 87.842125 Warning: Imaginary part in density will be ignored (7.003394369502271e-09) Chemical Potential = 8.000000
Total Density = 87.842805 Warning: Imaginary part in density will be ignored (9.026443075843778e-09) Chemical Potential = 8.500000
Total Density = 87.843533 Warning: Imaginary part in density will be ignored (1.1535143764131812e-08) Chemical Potential = 9.000000
Total Density = 87.844310 Warning: Imaginary part in density will be ignored (1.4623336221893088e-08) Chemical Potential = 9.500000
Total Density = 87.845138 Warning: Imaginary part in density will be ignored (1.839877024597159e-08) Chemical Potential = 10.000000
Total Density = 87.846019 Warning: Imaginary part in density will be ignored (2.2984299328110665e-08) Chemical Potential = 10.500000
Total Density = 87.846954 Warning: Imaginary part in density will be ignored (2.851955744166642e-08) Chemical Potential = 11.000000
Total Density = 87.847944 Warning: Imaginary part in density will be ignored (3.5162211239468726e-08) Chemical Potential = 11.500000
Total Density = 87.848992 Warning: Imaginary part in density will be ignored (4.308972557553232e-08) Chemical Potential = 12.000000
Total Density = 87.850099 Warning: Imaginary part in density will be ignored (5.250091339477232e-08) Chemical Potential = 12.500000
Total Density = 87.851266 Warning: Imaginary part in density will be ignored (6.361744007205909e-08) Chemical Potential = 13.000000
Total Density = 87.852495 Warning: Imaginary part in density will be ignored (7.66856206606565e-08) Chemical Potential = 13.500000
Total Density = 87.853787 Warning: Imaginary part in density will be ignored (9.197815784212491e-08) Chemical Potential = 14.000000
Total Density = 87.855144 Warning: Imaginary part in density will be ignored (1.097955522459581e-07) Chemical Potential = 14.500000
Total Density = 87.856567 Warning: Imaginary part in density will be ignored (1.3046831868779712e-07) Chemical Potential = 15.000000
Total Density = 87.858059 Warning: Imaginary part in density will be ignored (1.5435828712774334e-07) Chemical Potential = 15.500000
Total Density = 87.859619 Warning: Imaginary part in density will be ignored (1.8186035501532847e-07) Chemical Potential = 16.000000
Total Density = 87.861250 Warning: Imaginary part in density will be ignored (2.1340432984838177e-07) Chemical Potential = 16.500000
Total Density = 87.862954 Warning: Imaginary part in density will be ignored (2.494565038354848e-07) Chemical Potential = 17.000000
Total Density = 87.864731 Warning: Imaginary part in density will be ignored (2.90521087418846e-07) Chemical Potential = 17.500000
Total Density = 87.866582 Warning: Imaginary part in density will be ignored (3.3714182640473486e-07) Chemical Potential = 18.000000
Total Density = 87.868511 Warning: Imaginary part in density will be ignored (3.899037071294767e-07) Chemical Potential = 18.500000
Total Density = 87.870517 Warning: Imaginary part in density will be ignored (4.494336670327152e-07) Chemical Potential = 19.000000
Total Density = 87.872602 Warning: Imaginary part in density will be ignored (5.164027953081788e-07) Chemical Potential = 19.500000
Total Density = 87.874768 Warning: Imaginary part in density will be ignored (5.915266067025578e-07) Chemical Potential = 20.000000
Total Density = 87.877015 Warning: Imaginary part in density will be ignored (6.755665803444338e-07) Chemical Potential = 20.500000
Total Density = 87.879346 Warning: Imaginary part in density will be ignored (7.69330981593321e-07) Chemical Potential = 21.000000
Total Density = 87.881761 Warning: Imaginary part in density will be ignored (8.736753482657311e-07) Chemical Potential = 21.500000
Total Density = 87.884261 Warning: Imaginary part in density will be ignored (9.895033275141445e-07) Chemical Potential = 22.000000
Total Density = 87.886849 Warning: Imaginary part in density will be ignored (1.1177670299720303e-06) Chemical Potential = 22.500000
Total Density = 87.889524 Warning: Imaginary part in density will be ignored (1.2594670952456723e-06) Chemical Potential = 23.000000
Total Density = 87.892289 Warning: Imaginary part in density will be ignored (1.4156529827575852e-06) Chemical Potential = 23.500000
Total Density = 87.895145 Warning: Imaginary part in density will be ignored (1.5874221719314045e-06) Chemical Potential = 24.000000
Total Density = 87.898092 Warning: Imaginary part in density will be ignored (1.7759204214809545e-06) Chemical Potential = 24.500000
Total Density = 87.901132 Warning: Imaginary part in density will be ignored (1.9823402625438835e-06) Chemical Potential = 25.000000
Total Density = 87.904266 Warning: Imaginary part in density will be ignored (2.2079210767457e-06) Chemical Potential = 25.500000
Total Density = 87.907494 Warning: Imaginary part in density will be ignored (2.4539466607903755e-06) Chemical Potential = 26.000000
Total Density = 87.910819 Warning: Imaginary part in density will be ignored (2.721744671632895e-06) Chemical Potential = 26.500000
Total Density = 87.914241 Warning: Imaginary part in density will be ignored (3.012684366568875e-06) Chemical Potential = 27.000000
Total Density = 87.917761 Warning: Imaginary part in density will be ignored (3.3281747762383662e-06) Chemical Potential = 27.500000
Total Density = 87.921380 Warning: Imaginary part in density will be ignored (3.669661943300728e-06) Chemical Potential = 28.000000
Total Density = 87.925099 Warning: Imaginary part in density will be ignored (4.038626560147956e-06) Chemical Potential = 28.500000
Total Density = 87.928918 Warning: Imaginary part in density will be ignored (4.436580665214094e-06) Chemical Potential = 29.000000
Total Density = 87.932840 Warning: Imaginary part in density will be ignored (4.865064829085119e-06) Chemical Potential = 29.500000
Total Density = 87.936863 Warning: Imaginary part in density will be ignored (5.325643402207464e-06) Chemical Potential = 30.000000
Total Density = 87.940990 Warning: Imaginary part in density will be ignored (5.819901567524258e-06) Chemical Potential = 30.500000
Total Density = 87.945221 Warning: Imaginary part in density will be ignored (6.349440349135914e-06) Chemical Potential = 31.000000
Total Density = 87.949557 Warning: Imaginary part in density will be ignored (6.915871908162692e-06) Chemical Potential = 31.500000
Total Density = 87.953998 Warning: Imaginary part in density will be ignored (7.520815001205282e-06) Chemical Potential = 32.000000
Total Density = 87.958546 Warning: Imaginary part in density will be ignored (8.16588874202514e-06) Chemical Potential = 32.500000
Total Density = 87.963199 Warning: Imaginary part in density will be ignored (8.85270730941663e-06) Chemical Potential = 33.000000
Total Density = 87.967960 Warning: Imaginary part in density will be ignored (9.58287378282418e-06) Chemical Potential = 33.500000
Total Density = 87.972829 Warning: Imaginary part in density will be ignored (1.0357973951113453e-05) Chemical Potential = 34.000000
Total Density = 87.977806 Warning: Imaginary part in density will be ignored (1.1179568624033756e-05) Chemical Potential = 34.500000
Total Density = 87.982891 Warning: Imaginary part in density will be ignored (1.2049187391863345e-05) Chemical Potential = 35.000000
Total Density = 87.988086 Warning: Imaginary part in density will be ignored (1.2968320750564742e-05) Chemical Potential = 35.500000
Total Density = 87.993389 Warning: Imaginary part in density will be ignored (1.3938411917900723e-05) Chemical Potential = 36.000000
Total Density = 87.998803 Warning: Imaginary part in density will be ignored (1.4960849766669426e-05) Chemical Potential = 36.500000
Total Density = 88.004325 Warning: Imaginary part in density will be ignored (1.6036958963107646e-05) Chemical Potential = 37.000000
Total Density = 88.009958 Warning: Imaginary part in density will be ignored (1.7167992586899724e-05) Chemical Potential = 37.500000
Total Density = 88.015701 Warning: Imaginary part in density will be ignored (1.835512207050388e-05) Chemical Potential = 38.000000
Total Density = 88.021554 Warning: Imaginary part in density will be ignored (1.9599428024419825e-05) Chemical Potential = 38.500000
Total Density = 88.027517 Warning: Imaginary part in density will be ignored (2.0901891077599866e-05) Chemical Potential = 39.000000
Total Density = 88.033590 Warning: Imaginary part in density will be ignored (2.2263382050861183e-05) Chemical Potential = 39.500000
Total Density = 88.039773 Warning: Imaginary part in density will be ignored (2.3684650503833117e-05) Chemical Potential = 40.000000
Total Density = 88.046065 Warning: Imaginary part in density will be ignored (2.5166316506406478e-05) Chemical Potential = 40.500000
Total Density = 88.052468 Warning: Imaginary part in density will be ignored (2.6708858500902142e-05) Chemical Potential = 41.000000
Total Density = 88.058979 Warning: Imaginary part in density will be ignored (2.8312602932198427e-05) Chemical Potential = 41.500000
Total Density = 88.065600 Warning: Imaginary part in density will be ignored (2.9977713197358658e-05) Chemical Potential = 42.000000
Total Density = 88.072329 Warning: Imaginary part in density will be ignored (3.1704179554579924e-05) Chemical Potential = 42.500000
Total Density = 88.079166 Warning: Imaginary part in density will be ignored (3.349180589509758e-05) Chemical Potential = 43.000000
Total Density = 88.086111 Warning: Imaginary part in density will be ignored (3.534020013338401e-05) Chemical Potential = 43.500000
Total Density = 88.093163 Warning: Imaginary part in density will be ignored (3.724876182255512e-05) Chemical Potential = 44.000000
Total Density = 88.100321 Warning: Imaginary part in density will be ignored (3.9216671031522325e-05) Chemical Potential = 44.500000
Total Density = 88.107585 Warning: Imaginary part in density will be ignored (4.124287613051404e-05) Chemical Potential = 45.000000
Total Density = 88.114954 Warning: Imaginary part in density will be ignored (4.3326082066910584e-05) Chemical Potential = 45.500000
Total Density = 88.122427 Warning: Imaginary part in density will be ignored (4.546473929947753e-05) Chemical Potential = 46.000000
Total Density = 88.130003 Warning: Imaginary part in density will be ignored (4.765703214386264e-05) Chemical Potential = 46.500000
Total Density = 88.137681 Warning: Imaginary part in density will be ignored (4.990086522044334e-05) Chemical Potential = 47.000000
Total Density = 88.145461 Warning: Imaginary part in density will be ignored (5.2193854163879865e-05) Chemical Potential = 47.500000
Total Density = 88.153340 Warning: Imaginary part in density will be ignored (5.453331147074895e-05) Chemical Potential = 48.000000
Total Density = 88.161318 Warning: Imaginary part in density will be ignored (5.691623870728128e-05) Chemical Potential = 48.500000
Total Density = 88.169394 Warning: Imaginary part in density will be ignored (5.933930933078476e-05) Chemical Potential = 49.000000
Total Density = 88.177566 Warning: Imaginary part in density will be ignored (6.179886343747384e-05) Chemical Potential = 49.500000
Total Density = 88.185833 Warning: Imaginary part in density will be ignored (6.429089230238032e-05) Chemical Potential = 50.000000
Total Density = 88.194194 Warning: Imaginary part in density will be ignored (6.681102875383343e-05) Chemical Potential = 50.500000
Total Density = 88.202646 0.000000 < Chemical Potential < 50.500000 87.836579 < Total Density < 88.202646 FAILURE to adjust Chemical Potential to the value 230.000000 after 101 iterations. FAILURE returning (None, None) due to failure. Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType' Traceback (most recent call last): File "DMFTSC.py", line 99, in S[icrsh].G_iw << SK.extract_G_loc()[icrsh] ### Calculate local Green Function File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 678, in extract_G_loc ik=ik, mu=mu, iw_or_w=iw_or_w, with_Sigma=with_Sigma, with_dc=with_dc, beta=beta) File "/home/hp/miniconda2/lib/python2.7/site-packages/triqs_dft_tools/sumk_dft.py", line 560, in lattice_gf (idmat[ibl] mu) - (idmat[ibl] self.h_field (1 - 2 ibl)) TypeError: unsupported operand type(s) for : 'complex' and 'NoneType'.

In fact the chemical potential goes on increasing.

Thank You for your response.

Regards CMTCL

the-hampel commented 4 years ago

Something does not add up here. You said you reduced the correlated subspace range, but the number of electrons that you want to obtain increased from 197 to 230, that seems not correct: Dichotomy adjustment of Chemical Potential to obtain Total Density = 230.000000

What else did you change? The smaller the energy window for the correlated subspace, less electrons are in there. In the end you don't have an error here!

You need to roughly know how many electrons you expect and give this as a hint to your sumk object. For example if you know that you chemical potential from DFT is something like 13eV that just set this at the beginning of your calculation as:

sumk.set_mu(13)

Please check your input.

cmtcl18 commented 4 years ago

Dear Alex, Yes I increased the kpoints to 176, reduced the correlated subspace. This leads to the number of electron in correlated subspace is 171. In fact I am trying for a non_magnetic calculation. What I sent previously was for a magnetic calculation, for which there were more number of electrons in correlated subspace, even if the number of kpoints were increased. The same error is appearing. Starting run with 14 MPI rank(s) at : 2020-04-24 15:49:22.851147 iteration = 1 /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] Dichotomy adjustment of Chemical Potential to obtain Total Density = 171.000000 +/- 0.000100 /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] /home/hp/miniconda2/lib/python2.7/site-packages/pytriqs/gf/gf.py:359: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result. dat = self._data[ self._rank [slice(0,None)] + key_lst ] Warning: Imaginary part in density will be ignored (4.748306985098204e-06) Warning: Imaginary part in density will be ignored (4.434806317147541e-06) Chemical Potential = -0.500000
Total Density = 164.337015 -0.500000 < Chemical Potential < 0.000000 164.337015 < Total Density < 171.228632 Warning: Imaginary part in density will be ignored (4.737621334399415e-06) -0.016588 < Chemical Potential < 0.000000 170.934196 < Total Density < 171.228632 Warning: Imaginary part in density will be ignored (4.740007771372919e-06) -0.012881 < Chemical Potential < 0.000000 170.997407 < Total Density < 171.228632 Warning: Imaginary part in density will be ignored (4.740100758257659e-06) -0.012736 < Chemical Potential < 0.000000 170.999898 < Total Density < 171.228632 Warning: Imaginary part in density will be ignored (4.740104443096344e-06) -0.012730 < Chemical Potential < 0.000000 170.999996 < Total Density < 171.228632 Chemical Potential found in 5 iterations : Total Density = 170.999996;Chemical Potential = -0.012730 DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) Total charge of G_loc : 5.312483 DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) Dichotomy adjustment of Chemical Potential to obtain Total Density = 171.000000 +/- 0.000100 DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) DMFTSC.py:101: ComplexWarning: Casting complex values to real discards the imaginary part mpi.report("Total charge of G_loc : %.6f"%S[icrsh].G_iw.total_density()) Warning: Imaginary part in density will be ignored (4.740104443096344e-06) -0.012730 < Chemical Potential < -0.012730 170.999996 < Total Density < 170.999996 Chemical Potential found in 0 iterations : Total Density = 170.999996;Chemical Potential = -0.012730 Total charge of G_loc : 1.603357 DC for shell 0 and block up = 22.618668 DC for shell 0 and block down = 22.618668 DC energy for shell 0 = 53.8384748430639 DC for shell 1 and block up = 22.618668 DC for shell 1 and block down = 22.618668 DC energy for shell 1 = 53.8384748430639 DC for shell 2 and block up = 22.618668 DC for shell 2 and block down = 22.618668 DC energy for shell 2 = 53.8384748430639

=================================================================================== = BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES = PID 14787 RUNNING AT jatin-hp-z420-workstation = EXIT CODE: 139 = CLEANING UP REMAINING PROCESSES = YOU CAN IGNORE THE BELOW CLEANUP MESSAGES

YOUR APPLICATION TERMINATED WITH THE EXIT STRING: Segmentation fault (signal 11) This typically refers to a problem with your application. Please see the FAQ page for debugging suggestions

Is it first time occuring in case of WIEN2k plus TRIQS? This error is persisting since long time. I would be thankful for any suggestion, from those who are using WIEN2k plus TRIQS.

Thank you Alex for your response.

the-hampel commented 4 years ago

Okay so now your back to exactly the same error you had before. Please notice the difference. Your chemical potential finding worked now! So your problem that you had above is fixed. I am confused why the input changes etc. We should try to concentrate on one set of input parameters!

I am sure if you run this h5 file with my scripts (soliDMFT) than it will work. We need to use exactly the same scripts as before to the if the inversion to calculate G0_iw works now. Can you please run the calculation exactly as you did in the beginning of this thread. This should run at least for the first iteration. I would like to first fix the matrix is not invertible problem and then see why you get a segfault with your script.

P.S. could you please not post the output of all mpi threads but rather only show output from one task? Reading the error messages is quite cumbersome in this way.

cmtcl18 commented 4 years ago

Dear Alex, Did you get some way to fix the matrix is not invertible problem.
Infect this problem is occurring when the system contains more then one correlated atoms in the correlated sub space. I tried to run the calculation with soliDMFT code, but the output is similar to the first discussion that I have sent in this issue.

Here instead of giving whole output, I have given small part of the output. WARNING: The product of atomic operators has a matrix element in the off-diagonal block (2,6) You will not be able to use this density matrix to calculate expectations values of operators that do not commute with the local Hamiltonian!

the-hampel commented 4 years ago

No, with the input that you gave me this is not possible. I am confused. Did you try to run with more kpoints and you encountered the same problem, when you try to solve the second impurity?

What you post there is just a warning no error, you can get rid of it by setting in the solver parameters measure_density_matrix = False. And I do not understand, what you mean with similar? Can you confirm that you again encountered the matrix is not invertible problem?

In general this works, this is only related to your input generated from Wien2k. I cannot help you with that. Please try to generate meaningful input via Wien2k and post the error here. And also please attach as file the python script that you used for the calculation.

cmtcl18 commented 4 years ago

Hi Alex, The number of kpoints is increased to 249 in the irreducible Brillouin zone and the correlated subspace is reduced to smaller energy window. Here I am giving the python script in zip format. DMFTSC.zip

A part of the terminal output is shown here.

Dichotomy adjustment of Chemical Potential to obtain Total Density = 171.000001 +/- 0.000100 Warning: Imaginary part in density will be ignored (4.793774229264781e-06) -0.012387 < Chemical Potential < -0.012387 170.999929 < Total Density < 170.999929 Chemical Potential found in 0 iterations : Total Density = 170.999929;Chemical Potential = -0.012387 Total charge of G_loc : 1.614660 DC for shell 0 and block up = 22.547873 DC for shell 0 and block down = 22.547873 DC energy for shell 0 = 53.49830498560451 DC for shell 1 and block up = 22.547873 DC for shell 1 and block down = 22.547873 DC energy for shell 1 = 53.49830498560451 DC for shell 2 and block up = 22.547873 DC for shell 2 and block down = 22.547873 DC energy for shell 2 = 53.49830498560451

=================================================================================== = BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES = PID 22937 RUNNING AT jatin-hp-z420-workstation = EXIT CODE: 139 = CLEANING UP REMAINING PROCESSES = YOU CAN IGNORE THE BELOW CLEANUP MESSAGES

YOUR APPLICATION TERMINATED WITH THE EXIT STRING: Segmentation fault (signal 11) This typically refers to a problem with your application. Please see the FAQ page for debugging suggestions

Thank you for the response.

the-hampel commented 4 years ago

Hi, I tried a bit with your script I found some mistakes . A first very problematic issue is in line 112: 

S[icrsh].G0_iw << S[icrsh].Sigma_iw + inverse(S[icrsh].G_iw)

this is not correct. You need to perform the Dyson equation properly: 

S[icrsh].G0_iw << inverse(S[icrsh].Sigma_iw + inverse(S[icrsh].G_iw))

Furthermore the DC was not calculated per impurity, but only for the first one! I corrected a few more little things: DMFTSC_corr.py.zip

However, I can confirm that I also get a segmentation fault with this input (@Wentzell), which in general should not happen. However, The input is still not good. You said you created another h5 archive with more k points and smaller energy window? Can you try the corrected script with this h5?

the-hampel commented 4 years ago

Hi, did you try my corrections? Any success or problems?

cmtcl18 commented 4 years ago

Dear Alex, First of all thank you for helping me to debug the error and secondly I would like to apologize for my late respond due to certain unavoidable circumstances.

I used your corrected DMFTSC_corr.py python script, with higher number of kpoints (249) and the smaller correlated subspace [-5.0 4.0 ]Ry. Still the Segmentation fault is persisting.

Here, I am giving the last section of the terminal output.

YOUR APPLICATION TERMINATED WITH THE EXIT STRING: Segmentation fault (signal 11) This typically refers to a problem with your application. Please see the FAQ page for debugging suggestions

Even I used your corrected python script for LaMnO3 with four ineuivalent correlated Mn atoms, contains total 20 atoms. It's throwing the same Segmentation fault.

cmtcl18 commented 4 years ago

Hi All, What I noticed since last two months is that, the DFT plus DMFT calculation for systems ( SrVO3, LaMnO3) cubic phase working without any computational error. The problem arose so far when the compound contains more number of correlated atoms ( CaCu3Ru4O12 and ' LaMnO3' ).

I came across the articles by M. Zingl et. al. ( arXiv preprint arXiv:2004.12515 ) where they have used DFT (WIEN2k) plus DMFT.

Dear Manuel can you suggest why the segmentation fault is occurring during LDA plus DMFT calculation irrespective of the considered systems.

In fact I would like to thank Alex for the discussions and suggestions so far you have made.

Any suggestions regarding the LDA (WIEN2k) plus DMFT side would be higly appreciated.

Best Regards CMTCL

the-hampel commented 4 years ago

Hi CMTCL, I still think there might be a bug in your python script. Could you sent me an updated h5 input archive for CCRO or for LaMnO3 with more k-points? If I find some time I can have a look. But as I showed to you, everything works if you use my scripts. At least no segmentation fault. Therefore, I would try to find the differences between your and my script version (the one from github soliDMFT). Best, Alex

cmtcl18 commented 4 years ago

Hi Alex, Here I am giving the LaMno3.h5 file in zip format. LaMnO3_h5_file.zip

I have used the corrected python script that you have sent me.

Thank you for your response.

Best Regards CMTCL

the-hampel commented 4 years ago

Hi Cmtcl, I had finally time to look into the script and I found the mistake. Look in line 132: 

S[icrsh].solve(h_int=h_int, **p)

this is not correct as you have multiple sites and you have to hand over h_int per atomic site. You correctly set this up as a list of hamiltonians. So you have to specifiy which list item to handover:

S[icrsh].solve(h_int=h_int[icrsh], **p)

You see? Otherwise the solver is very confused what to do. This solves the segmentation fault! DMFTSC_corr.py.zip

I must have missed that, and I have to say that this behavior in cthyb is not very good, with a seg fault with the wrong input for h_int. Maybe, (@Wentzell) we could discuss how to prevent this by checking the type or shape of h_int.

However, the input you sent to me is still of very poor quality. The solver will crash with the error: 

Largest imaginary element of delta(infty) e.g. of the local part of G0: 0.113717, is larger than the set imag_threshold 1e-13

Again you included all bands in the selection of states? Please, use a simpler setup with only necessary bands around the fermi level first. After successfully doing so you can increase the number of bands... But you can check with your CCRO calculation.

Best, Alex

cmtcl18 commented 4 years ago

Dear Alex, I am really sorry for this late respond. Could you please describe what is bad quality of data, you have written above.

Best Regards CMTCL

the-hampel commented 4 years ago

Hi, Have you been able to correct your script with my fix? This is the most important point, so that we can close this issue.

The problem are the large imaginary elements in your local Hamiltonian. This seems not correct, as I described above. However, I cannot help you with that, this is related to your DFT calculation...

cmtcl18 commented 4 years ago

Hi Alex, I went through the corrected script DMFTSC_corr.py.zip.

In fact a key error is throwing at line 143 of the corrected script.

Then I iterate the Sigma_iw over all inequivalent correlated atoms using S[icrsh].Sigma_iw , still the key error is persisting.

Here, I am giving the python script, I have used. DMFTSC_corr_new.zip

the-hampel commented 4 years ago

Sorry, but this problem is now really related to your script and I do not have time to do your coding work. You must have made an error earlier in the script, or started from an existing calculation. But, you can check that all by yourself. Just include additional print commands to check where the error is appearing, or check the h5 archive.

I will close this issue now, since the original problem is resolved.