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Update quantum_transport_in_multi_lead_systems_with_guan.py

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guanjihuan 2022-01-20 01:15:14 +08:00
parent 615f68f3d2
commit 29f76af7fa
1 changed files with 8 additions and 45 deletions
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academic_codes/2021.02.08_quantum_transport_in_multi_lead_systems/quantum_transport_in_multi_lead_systems_with_guan.py
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@ -38,67 +38,30 @@ def main():
width = 5 width = 5
length = 50 length = 50
fermi_energy_array = np.arange(-4, 4, .01) fermi_energy_array = np.arange(-4, 4, .01)
# 中心区的哈密顿量 # 中心区的哈密顿量
H_center = get_center_hamiltonian(Nx=length, Ny=width) center_hamiltonian = get_center_hamiltonian(Nx=length, Ny=width)
# 电极的h00和h01 # 电极的h00和h01
lead_h00 = get_lead_h00(width) lead_h00 = get_lead_h00(width)
lead_h01 = get_lead_h01(width) lead_h01 = get_lead_h01(width)
transmission_12_array = [] transmission_12_array = []
transmission_13_array = [] transmission_13_array = []
transmission_14_array = [] transmission_14_array = []
transmission_15_array = [] transmission_15_array = []
transmission_16_array = [] transmission_16_array = []
transmission_1_all_array = [] transmission_1_all_array = []
for fermi_energy in fermi_energy_array: for fermi_energy in fermi_energy_array:
print(fermi_energy) print(fermi_energy)
# 几何形状如下所示： # 几何形状如下所示：
# lead2 lead3 # lead2 lead3
# lead1(L) lead4(R) # lead1(L) lead4(R)
# lead6 lead5 # lead6 lead5
transmission_matrix = guan.calculate_six_terminal_transmission_matrix(fermi_energy, h00_for_lead_4=lead_h00, h01_for_lead_4=lead_h01, h00_for_lead_2=lead_h00, h01_for_lead_2=lead_h01, center_hamiltonian=center_hamiltonian, width=width, length=length, internal_degree=1, moving_step_of_leads=0)
# 电极到中心区的跃迁矩阵 transmission_12_array.append(transmission_matrix[0, 1])
h_lead1_to_center = np.zeros((width, width*length), dtype=complex) transmission_13_array.append(transmission_matrix[0, 2])
h_lead2_to_center = np.zeros((width, width*length), dtype=complex) transmission_14_array.append(transmission_matrix[0, 3])
h_lead3_to_center = np.zeros((width, width*length), dtype=complex) transmission_15_array.append(transmission_matrix[0, 4])
h_lead4_to_center = np.zeros((width, width*length), dtype=complex) transmission_16_array.append(transmission_matrix[0, 5])
h_lead5_to_center = np.zeros((width, width*length), dtype=complex) transmission_1_all_array.append(transmission_matrix[0, 1]+transmission_matrix[0, 2]+transmission_matrix[0, 3]+transmission_matrix[0, 4]+transmission_matrix[0, 5])
h_lead6_to_center = np.zeros((width, width*length), dtype=complex)
move = 0 # the step of leads 2,3,6,5 moving to center
for i0 in range(width):
h_lead1_to_center[i0, i0] = 1
h_lead2_to_center[i0, width*(move+i0)+(width-1)] = 1
h_lead3_to_center[i0, width*(length-move-1-i0)+(width-1)] = 1
h_lead4_to_center[i0, width*(length-1)+i0] = 1
h_lead5_to_center[i0, width*(length-move-1-i0)+0] = 1
h_lead6_to_center[i0, width*(move+i0)+0] = 1
# 自能
self_energy1, gamma1 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead1_to_center)
self_energy2, gamma2 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead2_to_center)
self_energy3, gamma3 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead3_to_center)
self_energy4, gamma4 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead4_to_center)
self_energy5, gamma5 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead5_to_center)
self_energy6, gamma6 = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, lead_h00, lead_h01, h_lead6_to_center)
# 整体格林函数
green = np.linalg.inv(fermi_energy*np.eye(width*length)-H_center-self_energy1-self_energy2-self_energy3-self_energy4-self_energy5-self_energy6)
# Transmission
transmission_12 = np.trace(np.dot(np.dot(np.dot(gamma1, green), gamma2), green.transpose().conj()))
transmission_13 = np.trace(np.dot(np.dot(np.dot(gamma1, green), gamma3), green.transpose().conj()))
transmission_14 = np.trace(np.dot(np.dot(np.dot(gamma1, green), gamma4), green.transpose().conj()))
transmission_15 = np.trace(np.dot(np.dot(np.dot(gamma1, green), gamma5), green.transpose().conj()))
transmission_16 = np.trace(np.dot(np.dot(np.dot(gamma1, green), gamma6), green.transpose().conj()))
transmission_12_array.append(np.real(transmission_12))
transmission_13_array.append(np.real(transmission_13))
transmission_14_array.append(np.real(transmission_14))
transmission_15_array.append(np.real(transmission_15))
transmission_16_array.append(np.real(transmission_16))
transmission_1_all_array.append(np.real(transmission_12+transmission_13+transmission_14+transmission_15+transmission_16))
guan.plot(fermi_energy_array, transmission_12_array, xlabel='Fermi energy', ylabel='Transmission_12') guan.plot(fermi_energy_array, transmission_12_array, xlabel='Fermi energy', ylabel='Transmission_12')
guan.plot(fermi_energy_array, transmission_13_array, xlabel='Fermi energy', ylabel='Transmission_13') guan.plot(fermi_energy_array, transmission_13_array, xlabel='Fermi energy', ylabel='Transmission_13')
guan.plot(fermi_energy_array, transmission_14_array, xlabel='Fermi energy', ylabel='Transmission_14') guan.plot(fermi_energy_array, transmission_14_array, xlabel='Fermi energy', ylabel='Transmission_14')