0.0.91
This commit is contained in:
		| @@ -367,52 +367,52 @@ def sigma_z(): | ||||
| ## Kronecker product of Pauli matrices | ||||
|  | ||||
| def sigma_00(): | ||||
|     return np.kron(sigma_0(), sigma_0()) | ||||
|     return np.kron(guan.sigma_0(), guan.sigma_0()) | ||||
|  | ||||
| def sigma_0x(): | ||||
|     return np.kron(sigma_0(), sigma_x()) | ||||
|     return np.kron(guan.sigma_0(), guan.sigma_x()) | ||||
|  | ||||
| def sigma_0y(): | ||||
|     return np.kron(sigma_0(), sigma_y()) | ||||
|     return np.kron(guan.sigma_0(), guan.sigma_y()) | ||||
|  | ||||
| def sigma_0z(): | ||||
|     return np.kron(sigma_0(), sigma_z()) | ||||
|     return np.kron(guan.sigma_0(), guan.sigma_z()) | ||||
|  | ||||
| def sigma_x0(): | ||||
|     return np.kron(sigma_x(), sigma_0()) | ||||
|     return np.kron(guan.sigma_x(), guan.sigma_0()) | ||||
|  | ||||
| def sigma_xx(): | ||||
|     return np.kron(sigma_x(), sigma_x()) | ||||
|     return np.kron(guan.sigma_x(), guan.sigma_x()) | ||||
|  | ||||
| def sigma_xy(): | ||||
|     return np.kron(sigma_x(), sigma_y()) | ||||
|     return np.kron(guan.sigma_x(), guan.sigma_y()) | ||||
|  | ||||
| def sigma_xz(): | ||||
|     return np.kron(sigma_x(), sigma_z()) | ||||
|     return np.kron(guan.sigma_x(), guan.sigma_z()) | ||||
|  | ||||
| def sigma_y0(): | ||||
|     return np.kron(sigma_y(), sigma_0()) | ||||
|     return np.kron(guan.sigma_y(), guan.sigma_0()) | ||||
|  | ||||
| def sigma_yx(): | ||||
|     return np.kron(sigma_y(), sigma_x()) | ||||
|     return np.kron(guan.sigma_y(), guan.sigma_x()) | ||||
|  | ||||
| def sigma_yy(): | ||||
|     return np.kron(sigma_y(), sigma_y()) | ||||
|     return np.kron(guan.sigma_y(), guan.sigma_y()) | ||||
|  | ||||
| def sigma_yz(): | ||||
|     return np.kron(sigma_y(), sigma_z()) | ||||
|     return np.kron(guan.sigma_y(), guan.sigma_z()) | ||||
|  | ||||
| def sigma_z0(): | ||||
|     return np.kron(sigma_z(), sigma_0()) | ||||
|     return np.kron(guan.sigma_z(), guan.sigma_0()) | ||||
|  | ||||
| def sigma_zx(): | ||||
|     return np.kron(sigma_z(), sigma_x()) | ||||
|     return np.kron(guan.sigma_z(), guan.sigma_x()) | ||||
|  | ||||
| def sigma_zy(): | ||||
|     return np.kron(sigma_z(), sigma_y()) | ||||
|     return np.kron(guan.sigma_z(), guan.sigma_y()) | ||||
|  | ||||
| def sigma_zz(): | ||||
|     return np.kron(sigma_z(), sigma_z()) | ||||
|     return np.kron(guan.sigma_z(), guan.sigma_z()) | ||||
|  | ||||
|  | ||||
|  | ||||
| @@ -1387,7 +1387,7 @@ def calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01, | ||||
|     for fermi_energy in fermi_energy_array: | ||||
|         if print_show == 1: | ||||
|             print(fermi_energy) | ||||
|         conductance_array[i0] = np.real(calculate_conductance(fermi_energy, h00, h01, length)) | ||||
|         conductance_array[i0] = np.real(guan.calculate_conductance(fermi_energy, h00, h01, length)) | ||||
|         i0 += 1 | ||||
|     return conductance_array | ||||
|  | ||||
| @@ -1419,7 +1419,7 @@ def calculate_conductance_with_disorder_intensity_array(fermi_energy, h00, h01, | ||||
|         if print_show == 1: | ||||
|             print(disorder_intensity) | ||||
|         for times in range(calculation_times): | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|         i0 += 1 | ||||
|     conductance_array = conductance_array/calculation_times | ||||
|     return conductance_array | ||||
| @@ -1432,7 +1432,7 @@ def calculate_conductance_with_disorder_concentration_array(fermi_energy, h00, h | ||||
|         if print_show == 1: | ||||
|             print(disorder_concentration) | ||||
|         for times in range(calculation_times): | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|         i0 += 1 | ||||
|     conductance_array = conductance_array/calculation_times | ||||
|     return conductance_array | ||||
| @@ -1445,7 +1445,7 @@ def calculate_conductance_with_scattering_length_array(fermi_energy, h00, h01, l | ||||
|         if print_show == 1: | ||||
|             print(length) | ||||
|         for times in range(calculation_times): | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|             conductance_array[i0] = conductance_array[i0]+np.real(guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=disorder_intensity, disorder_concentration=disorder_concentration, length=length)) | ||||
|         i0 += 1 | ||||
|     conductance_array = conductance_array/calculation_times | ||||
|     return conductance_array | ||||
| @@ -1584,8 +1584,8 @@ def get_classified_k_velocity_u_and_f(fermi_energy, h00, h01): | ||||
|     lambda_right = np.zeros(dim, dtype=complex); lambda_left = np.zeros(dim, dtype=complex) | ||||
|     u_right = np.zeros((dim, dim), dtype=complex); u_left = np.zeros((dim, dim), dtype=complex) | ||||
|     for dim0 in range(2*dim): | ||||
|         if_active = if_active_channel(k_of_channel[dim0]) | ||||
|         if if_active_channel(k_of_channel[dim0]) == 1: | ||||
|         if_active = guan.if_active_channel(k_of_channel[dim0]) | ||||
|         if guan.if_active_channel(k_of_channel[dim0]) == 1: | ||||
|             direction = np.sign(velocity_of_channel[dim0]) | ||||
|         else: | ||||
|             direction = np.sign(np.imag(k_of_channel[dim0])) | ||||
| @@ -1648,7 +1648,7 @@ def calculate_scattering_matrix(fermi_energy, h00, h01, length=100): | ||||
|     reflection_matrix = np.dot(np.dot(np.linalg.inv(u_left), np.dot(green_00_n, temp)-np.identity(dim)), u_right) | ||||
|     for dim0 in range(dim): | ||||
|         for dim1 in range(dim): | ||||
|             if_active = if_active_channel(k_right[dim0])*if_active_channel(k_right[dim1]) | ||||
|             if_active = guan.if_active_channel(k_right[dim0])*guan.if_active_channel(k_right[dim1]) | ||||
|             if if_active == 1: | ||||
|                 transmission_matrix[dim0, dim1] = math.sqrt(np.abs(velocity_right[dim0]/velocity_right[dim1])) * transmission_matrix[dim0, dim1] | ||||
|                 reflection_matrix[dim0, dim1] = math.sqrt(np.abs(velocity_left[dim0]/velocity_right[dim1]))*reflection_matrix[dim0, dim1] | ||||
|   | ||||
		Reference in New Issue
	
	Block a user