version 0.0.52
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@ -64,7 +64,7 @@ eigenvector = guan.calculate_eigenvector(hamiltonian)
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vector_target = guan.find_vector_with_the_same_gauge_with_binary_search(vector_target, vector_ref, show_error=1, show_times=0, show_phase=0, n_test=10001, precision=1e-6)
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vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None)
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# calculate Green functions
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# Green functions
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green = guan.green_function(fermi_energy, hamiltonian, broadening, self_energy=0)
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green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening, self_energy=0)
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green_in_n = guan.green_function_in_n(green_in_n_minus, h01, green_nn_n)
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@ -78,7 +78,7 @@ self_energy, gamma = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy
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green, gamma_right, gamma_left = guan.green_function_with_leads(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian)
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G_n = guan.electron_correlation_function_green_n_for_local_current(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian)
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# calculate density of states
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# density of states
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total_dos = guan.total_density_of_states(fermi_energy, hamiltonian, broadening=0.01)
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total_dos_array = guan.total_density_of_states_with_fermi_energy_array(fermi_energy_array, hamiltonian, broadening=0.01)
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local_dos = guan.local_density_of_states_for_square_lattice(fermi_energy, hamiltonian, N1, N2, internal_degree=1, broadening=0.01)
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@ -87,22 +87,21 @@ local_dos = guan.local_density_of_states_for_square_lattice_using_dyson_equation
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local_dos = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01)
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local_dos = guan.local_density_of_states_for_square_lattice_with_self_energy_using_dyson_equation(fermi_energy, h00, h01, N2, N1, right_self_energy, left_self_energy, internal_degree=1, broadening=0.01)
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# calculate conductance
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# quantum transport
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conductance = guan.calculate_conductance(fermi_energy, h00, h01, length=100)
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conductance_array = guan.calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01, length=100)
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conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, 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)
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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)
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conductance_array = guan.calculate_conductance_with_scattering_length_array(fermi_energy, h00, h01, length_array, disorder_intensity=2.0, disorder_concentration=1.0, calculation_times=1)
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# scattering matrix
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transmission_matrix = guan.calculate_six_terminal_transmission_matrix(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10)
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if_active = guan.if_active_channel(k_of_channel)
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k_of_channel, velocity_of_channel, eigenvalue, eigenvector = guan.get_k_and_velocity_of_channel(fermi_energy, h00, h01)
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k_right, k_left, velocity_right, velocity_left, f_right, f_left, u_right, u_left, ind_right_active = guan.get_classified_k_velocity_u_and_f(fermi_energy, h00, h01)
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transmission_matrix, reflection_matrix, k_right, k_left, velocity_right, velocity_left, ind_right_active = guan.calculate_scattering_matrix(fermi_energy, h00, h01, length=100)
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guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, on_print=1, on_write=0)
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# calculate topological invariant
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# topological invariant
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chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_function, precision=100)
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chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=10, precision_of_Wilson_loop=100)
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chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300)
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@ -1,7 +1,7 @@
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[metadata]
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# replace with your username:
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name = guan
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version = 0.0.51
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version = 0.0.52
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author = guanjihuan
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author_email = guanjihuan@163.com
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description = An open source python package
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@ -929,6 +929,73 @@ def calculate_conductance_with_scattering_length_array(fermi_energy, h00, h01, l
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conductance_array = conductance_array/calculation_times
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return conductance_array
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## multi-terminal transmission
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def calculate_six_terminal_transmission_matrix(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10):
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# ---------------- Geometry ----------------
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# lead2 lead3
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# lead1(L) lead4(R)
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# lead6 lead5
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# h00 and h01 in leads
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h00_for_lead_1 = h00_for_lead_4
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h00_for_lead_2 = h00_for_lead_2
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h00_for_lead_3 = h00_for_lead_2
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h00_for_lead_5 = h00_for_lead_2
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h00_for_lead_6 = h00_for_lead_2
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h00_for_lead_4 = h00_for_lead_4
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h01_for_lead_1 = h01_for_lead_4.transpose().conj()
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h01_for_lead_2 = h01_for_lead_2
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h01_for_lead_3 = h01_for_lead_2
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h01_for_lead_4 = h01_for_lead_4
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h01_for_lead_5 = h01_for_lead_2.transpose().conj()
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h01_for_lead_6 = h01_for_lead_2.transpose().conj()
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# hopping matrix from lead to center
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h_lead1_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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h_lead2_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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h_lead3_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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h_lead4_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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h_lead5_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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h_lead6_to_center = np.zeros((internal_degree*width, internal_degree*width*length), dtype=complex)
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move = moving_step_of_leads # the step of leads 2,3,6,5 moving to center
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h_lead1_to_center[0:internal_degree*width, 0:internal_degree*width] = h01_for_lead_1.transpose().conj()
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h_lead4_to_center[0:internal_degree*width, internal_degree*width*(length-1):internal_degree*width*length] = h01_for_lead_4.transpose().conj()
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for i0 in range(width):
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begin_index = internal_degree*i0+0
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end_index = internal_degree*i0+internal_degree
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h_lead2_to_center[begin_index:end_index, internal_degree*(width*(move+i0)+(width-1))+0:internal_degree*(width*(move+i0)+(width-1))+internal_degree] = h01_for_lead_2.transpose().conj()[begin_index:end_index, begin_index:end_index]
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h_lead3_to_center[begin_index:end_index, internal_degree*(width*(length-move-1-i0)+(width-1))+0:internal_degree*(width*(length-move-1-i0)+(width-1))+internal_degree] = h01_for_lead_3.transpose().conj()[begin_index:end_index, begin_index:end_index]
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h_lead5_to_center[begin_index:end_index, internal_degree*(width*(length-move-1-i0)+0)+0:internal_degree*(width*(length-move-1-i0)+0)+internal_degree] = h01_for_lead_5.transpose().conj()[begin_index:end_index, begin_index:end_index]
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h_lead6_to_center[begin_index:end_index, internal_degree*(width*(i0+move)+0)+0:internal_degree*(width*(i0+move)+0)+internal_degree] = h01_for_lead_6.transpose().conj()[begin_index:end_index, begin_index:end_index]
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# self energy
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self_energy1, gamma1 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_1, h01_for_lead_1, h_lead1_to_center)
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self_energy2, gamma2 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_2, h01_for_lead_1, h_lead2_to_center)
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self_energy3, gamma3 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_3, h01_for_lead_1, h_lead3_to_center)
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self_energy4, gamma4 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_4, h01_for_lead_1, h_lead4_to_center)
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self_energy5, gamma5 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_5, h01_for_lead_1, h_lead5_to_center)
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self_energy6, gamma6 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00_for_lead_6, h01_for_lead_1, h_lead6_to_center)
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gamma_array = [gamma1, gamma2, gamma3, gamma4, gamma5, gamma6]
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# Green function
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green = np.linalg.inv(fermi_energy*np.eye(internal_degree*width*length)-center_hamiltonian-self_energy1-self_energy2-self_energy3-self_energy4-self_energy5-self_energy6)
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# Transmission
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transmission_matrix = np.zeros((6, 6), dtype=complex)
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channel_lead_4 = guan.calculate_conductance(fermi_energy, h00_for_lead_4, h01_for_lead_4, length=3)
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channel_lead_2 = guan.calculate_conductance(fermi_energy, h00_for_lead_2, h01_for_lead_2, length=3)
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for i0 in range(6):
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for j0 in range(6):
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if j0!=i0:
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transmission_matrix[i0, j0] = np.trace(np.dot(np.dot(np.dot(gamma_array[i0], green), gamma_array[j0]), green.transpose().conj()))
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for i0 in range(6):
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if i0 == 0 or i0 == 3:
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transmission_matrix[i0, i0] = channel_lead_4
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else:
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transmission_matrix[i0, i0] = channel_lead_2
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for i0 in range(6):
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for j0 in range(6):
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if j0!=i0:
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transmission_matrix[i0, i0] = transmission_matrix[i0, i0]-transmission_matrix[i0, j0]
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transmission_matrix = np.real(transmission_matrix)
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return transmission_matrix
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## scattering matrix
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