This commit is contained in:
guanjihuan 2024-05-07 22:24:07 +08:00
parent 194b90a0d8
commit 9b7540e445
5 changed files with 43 additions and 11 deletions

View File

@ -1,7 +1,7 @@
[metadata] [metadata]
# replace with your username: # replace with your username:
name = guan name = guan
version = 0.1.96 version = 0.1.97
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

View File

@ -1,6 +1,6 @@
Metadata-Version: 2.1 Metadata-Version: 2.1
Name: guan Name: guan
Version: 0.1.96 Version: 0.1.97
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

View File

@ -49,6 +49,10 @@ def transfer_matrix(fermi_energy, h00, h01):
else: else:
dim = np.array(h00).shape[0] dim = np.array(h00).shape[0]
transfer = np.zeros((2*dim, 2*dim), dtype=complex) transfer = np.zeros((2*dim, 2*dim), dtype=complex)
if dim == 1:
transfer[0:dim, 0:dim] = np.dot(1/h01, fermi_energy*np.identity(dim)-h00)
transfer[0:dim, dim:2*dim] = np.dot(-1/h01, h01.transpose().conj())
else:
transfer[0:dim, 0:dim] = np.dot(np.linalg.inv(h01), fermi_energy*np.identity(dim)-h00) transfer[0:dim, 0:dim] = np.dot(np.linalg.inv(h01), fermi_energy*np.identity(dim)-h00)
transfer[0:dim, dim:2*dim] = np.dot(-1*np.linalg.inv(h01), h01.transpose().conj()) transfer[0:dim, dim:2*dim] = np.dot(-1*np.linalg.inv(h01), h01.transpose().conj())
transfer[dim:2*dim, 0:dim] = np.identity(dim) transfer[dim:2*dim, 0:dim] = np.identity(dim)

View File

@ -15,6 +15,12 @@ def preprocess_for_parallel_calculations(parameter_array_all, task_num=1, task_i
parameter_array = parameter_array_all[task_index*num_parameter:num_all] parameter_array = parameter_array_all[task_index*num_parameter:num_all]
return parameter_array return parameter_array
# 判断一个数是否接近于整数
def close_to_integer(value, abs_tol=1e-3):
import math
result = math.isclose(value, round(value), abs_tol=abs_tol)
return result
# 根据子数组的第index个元素对子数组进行排序index从0开始 # 根据子数组的第index个元素对子数组进行排序index从0开始
def sort_array_by_index_element(original_array, index): def sort_array_by_index_element(original_array, index):
sorted_array = sorted(original_array, key=lambda x: x[index]) sorted_array = sorted(original_array, key=lambda x: x[index])

View File

@ -16,6 +16,10 @@ def calculate_conductance(fermi_energy, h00, h01, length=100):
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
dim = np.array(h00).shape[0]
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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
@ -53,6 +57,9 @@ def calculate_conductance_with_barrier(fermi_energy, h00, h01, length=100, barri
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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
@ -79,6 +86,9 @@ def calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensi
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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()))
conductance_averaged += conductance conductance_averaged += conductance
conductance_averaged = conductance_averaged/calculation_times conductance_averaged = conductance_averaged/calculation_times
@ -104,6 +114,9 @@ def calculate_conductance_with_disorder_array(fermi_energy, h00, h01, disorder_a
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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
@ -127,6 +140,9 @@ def calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_i
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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
@ -151,6 +167,9 @@ def calculate_conductance_with_disorder_inside_unit_cell_which_keeps_translation
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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
@ -175,6 +194,9 @@ def calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_co
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, 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) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
if dim == 1:
conductance = np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())
else:
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