diff --git a/doc/source/index.rst b/doc/source/index.rst index 8891951175f4b73a6535ed11defda58b5e483dd0..363485adac1f3d082ba5c75ae75a763e648125e2 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -1,6 +1,17 @@ Welcome to TiPSi's documentation! ================================= +TiPSi is a package for Python 3 to make large-scale tight-binding Hamiltonians and +run Tight Binding Propagation Method (TBPM) calculations. TiPSi is optimized for +usage on cluster nodes. It uses FORTRAN code to do the number crunching, and +f2py to interface with Python. + +In general, a simulation consists of the following steps: + +- Make a tight-binding Hamiltonian +- Calculate correlation functions +- Analyze correlation functions + .. toctree:: :maxdepth: 2 :caption: Contents: diff --git a/tipsi/analysis.py b/tipsi/analysis.py index 063bed5dc389885e1422058c52de4d1b952872a4..0eec149e78888ccd7702db3b09752cfce0b1072b 100644 --- a/tipsi/analysis.py +++ b/tipsi/analysis.py @@ -403,11 +403,11 @@ def analyze_corr_DC(config, corr_DOS, corr_DC, \ n_energies = len(QE_indices) energies = energies_DOS[QE_indices] dc_prefactor = config.sample['nr_orbitals'] \ - / config.sample['area_unit_cell'] - + / config.sample['area_unit_cell'] \ + / (2 * np.pi) + # get DC conductivity DC = np.zeros((2, n_energies)) - DC_int = np.zeros((2, n_energies, tnr)) for i in range(2): for j in range(n_energies): @@ -415,13 +415,12 @@ def analyze_corr_DC(config, corr_DOS, corr_DC, \ dosval = DOS[QE_indices[j]] dcval = 0. for k in range(tnr): - W = window_DC(k, tnr) + W = window_DC(k + 1, tnr) cexp = np.exp(-1j * k * t_step * en) add_dcv = W * (cexp * corr_DC[i, j, k]).real dcval += add_dcv - DC_int[i, j, k] = dc_prefactor * t_step * dosval * dcval - DC[i, j] = np.amax(DC_int[i, j, :]) - + DC[i, j] = dc_prefactor * t_step * dosval * dcval + # correct for spin if config.generic['correct_spin']: DC = 2. * DC