0.0.151
This commit is contained in:
		| @@ -218,6 +218,8 @@ conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, d | |||||||
|  |  | ||||||
| conductance = guan.calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100) | conductance = guan.calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100) | ||||||
|  |  | ||||||
|  | conductance = guan.calculate_conductance_with_disorder_inside_unit_cell_which_keeps_translational_symmetry(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100) | ||||||
|  |  | ||||||
| conductance = guan.calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100) | conductance = guan.calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100) | ||||||
|  |  | ||||||
| conductance_array = guan.calculate_conductance_with_disorder_intensity_array(fermi_energy, h00, h01, disorder_intensity_array, disorder_concentration=1.0, length=100, calculation_times=1, print_show=0) | conductance_array = guan.calculate_conductance_with_disorder_intensity_array(fermi_energy, h00, h01, disorder_intensity_array, disorder_concentration=1.0, length=100, calculation_times=1, print_show=0) | ||||||
|   | |||||||
| @@ -1,7 +1,7 @@ | |||||||
| [metadata] | [metadata] | ||||||
| # replace with your username: | # replace with your username: | ||||||
| name = guan | name = guan | ||||||
| version = 0.0.150 | version = 0.0.151 | ||||||
| author = guanjihuan | author = guanjihuan | ||||||
| author_email = guanjihuan@163.com | author_email = guanjihuan@163.com | ||||||
| description = An open source python package | description = An open source python package | ||||||
|   | |||||||
| @@ -1,6 +1,6 @@ | |||||||
| Metadata-Version: 2.1 | Metadata-Version: 2.1 | ||||||
| Name: guan | Name: guan | ||||||
| Version: 0.0.150 | Version: 0.0.151 | ||||||
| Summary: An open source python package | Summary: An open source python package | ||||||
| Home-page: https://py.guanjihuan.com | Home-page: https://py.guanjihuan.com | ||||||
| Author: guanjihuan | Author: guanjihuan | ||||||
|   | |||||||
| @@ -2,7 +2,7 @@ | |||||||
|  |  | ||||||
| # With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated in this package, such as file reading/writing, figure plotting, data processing. | # With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated in this package, such as file reading/writing, figure plotting, data processing. | ||||||
|  |  | ||||||
| # The current version is guan-0.0.150, updated on December 22, 2022. | # The current version is guan-0.0.151, updated on December 25, 2022. | ||||||
|  |  | ||||||
| # Installation: pip install --upgrade guan | # Installation: pip install --upgrade guan | ||||||
|  |  | ||||||
| @@ -1214,6 +1214,26 @@ def calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_i | |||||||
|     conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) |     conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) | ||||||
|     return conductance |     return conductance | ||||||
|  |  | ||||||
|  | def calculate_conductance_with_disorder_inside_unit_cell_which_keeps_translational_symmetry(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100): | ||||||
|  |     right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01) | ||||||
|  |     dim = np.array(h00).shape[0] | ||||||
|  |     disorder = np.zeros((dim, dim)) | ||||||
|  |     for dim0 in range(dim): | ||||||
|  |         if np.random.uniform(0, 1)<=disorder_concentration: | ||||||
|  |             disorder[dim0, dim0] = np.random.uniform(-disorder_intensity, disorder_intensity) | ||||||
|  |     for ix in range(length): | ||||||
|  |         if ix == 0: | ||||||
|  |             green_nn_n = guan.green_function(fermi_energy, h00+disorder, broadening=0, self_energy=left_self_energy) | ||||||
|  |             green_0n_n = copy.deepcopy(green_nn_n) | ||||||
|  |         elif ix != length-1: | ||||||
|  |             green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0) | ||||||
|  |             green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) | ||||||
|  |         else: | ||||||
|  |             green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0, self_energy=right_self_energy) | ||||||
|  |             green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) | ||||||
|  |     conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) | ||||||
|  |     return conductance | ||||||
|  |  | ||||||
| def calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100): | def calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100): | ||||||
|     right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01) |     right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01) | ||||||
|     dim = np.array(h00).shape[0] |     dim = np.array(h00).shape[0] | ||||||
|   | |||||||
		Reference in New Issue
	
	Block a user