0.0.150
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@ -218,6 +218,8 @@ conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, d
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conductance = guan.calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100)
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conductance = guan.calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100)
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conductance = guan.calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100)
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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)
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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)
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conductance_array = guan.calculate_conductance_with_disorder_concentration_array(fermi_energy, h00, h01, disorder_concentration_array, disorder_intensity=2.0, length=100, calculation_times=1, print_show=0)
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conductance_array = guan.calculate_conductance_with_disorder_concentration_array(fermi_energy, h00, h01, disorder_concentration_array, disorder_intensity=2.0, length=100, calculation_times=1, print_show=0)
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@ -1,7 +1,7 @@
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[metadata]
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[metadata]
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# replace with your username:
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# replace with your username:
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name = guan
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name = guan
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version = 0.0.149
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version = 0.0.150
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author = guanjihuan
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author = guanjihuan
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author_email = guanjihuan@163.com
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author_email = guanjihuan@163.com
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description = An open source python package
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description = An open source python package
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@ -1,6 +1,6 @@
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Metadata-Version: 2.1
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Metadata-Version: 2.1
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Name: guan
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Name: guan
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Version: 0.0.149
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Version: 0.0.150
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Summary: An open source python package
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Summary: An open source python package
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Home-page: https://py.guanjihuan.com
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Home-page: https://py.guanjihuan.com
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Author: guanjihuan
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Author: guanjihuan
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@ -2,7 +2,7 @@
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# 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.
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# 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.
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# The current version is guan-0.0.149, updated on December 21, 2022.
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# The current version is guan-0.0.150, updated on December 22, 2022.
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# Installation: pip install --upgrade guan
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# Installation: pip install --upgrade guan
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@ -1214,6 +1214,26 @@ def calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_i
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conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
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conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
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return conductance
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return conductance
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def calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_concentration=0.5, vacancy_potential=1e9, length=100):
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right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01)
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dim = np.array(h00).shape[0]
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for ix in range(length):
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random_vacancy = np.zeros((dim, dim))
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for dim0 in range(dim):
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if np.random.uniform(0, 1)<=vacancy_concentration:
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random_vacancy[dim0, dim0] = vacancy_potential
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if ix == 0:
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green_nn_n = guan.green_function(fermi_energy, h00+random_vacancy, broadening=0, self_energy=left_self_energy)
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green_0n_n = copy.deepcopy(green_nn_n)
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elif ix != length-1:
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green_nn_n = guan.green_function_nn_n(fermi_energy, h00+random_vacancy, h01, green_nn_n, broadening=0)
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green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
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else:
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green_nn_n = guan.green_function_nn_n(fermi_energy, h00+random_vacancy, h01, green_nn_n, broadening=0, self_energy=right_self_energy)
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green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
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conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
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return conductance
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def 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):
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def 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):
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dim = np.array(disorder_intensity_array).shape[0]
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dim = np.array(disorder_intensity_array).shape[0]
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conductance_array = np.zeros(dim)
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conductance_array = np.zeros(dim)
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