diff --git a/academic_codes/2020.01.05_calculation_of_Chern_number_by_definition_method/fix_gauge_and_calculate_Chern_number.py b/academic_codes/2020.01.05_calculation_of_Chern_number_by_definition_method/fix_gauge_and_calculate_Chern_number.py
new file mode 100644
index 0000000..aac9fb1
--- /dev/null
+++ b/academic_codes/2020.01.05_calculation_of_Chern_number_by_definition_method/fix_gauge_and_calculate_Chern_number.py
@@ -0,0 +1,90 @@
+"""
+This code is supported by the website: https://www.guanjihuan.com
+The newest version of this code is on the web page: https://www.guanjihuan.com/archives/3932
+"""
+
+import numpy as np
+from math import *
+import time
+import cmath
+
+
+def hamiltonian(kx, ky):  # 量子反常霍尔QAH模型（该参数对应的陈数为2）
+    t1 = 1.0
+    t2 = 1.0
+    t3 = 0.5
+    m = -1.0
+    matrix = np.zeros((2, 2), dtype=complex)
+    matrix[0, 1] = 2*t1*cos(kx)-1j*2*t1*cos(ky)
+    matrix[1, 0] = 2*t1*cos(kx)+1j*2*t1*cos(ky)
+    matrix[0, 0] = m+2*t3*sin(kx)+2*t3*sin(ky)+2*t2*cos(kx+ky)
+    matrix[1, 1] = -(m+2*t3*sin(kx)+2*t3*sin(ky)+2*t2*cos(kx+ky))
+    return matrix
+
+
+def main():
+    start_time = time.time()
+    n = 20  # 积分密度
+    delta = 1e-9  # 求导的偏离量
+    chern_number = 0  # 陈数初始化
+    for kx in np.arange(-pi, pi, 2*pi/n):
+        for ky in np.arange(-pi, pi, 2*pi/n):
+            H = hamiltonian(kx, ky)
+            eigenvalue, eigenvector = np.linalg.eig(H)
+            vector = eigenvector[:, np.argsort(np.real(eigenvalue))[0]]  # 价带波函数
+           
+            H_delta_kx = hamiltonian(kx+delta, ky) 
+            eigenvalue, eigenvector = np.linalg.eig(H_delta_kx)
+            vector_delta_kx = eigenvector[:, np.argsort(np.real(eigenvalue))[0]]   # 略偏离kx的波函数
+
+            H_delta_ky = hamiltonian(kx, ky+delta)  
+            eigenvalue, eigenvector = np.linalg.eig(H_delta_ky)
+            vector_delta_ky = eigenvector[:, np.argsort(np.real(eigenvalue))[0]]  # 略偏离ky的波函数
+
+            H_delta_kx_ky = hamiltonian(kx+delta, ky+delta)  
+            eigenvalue, eigenvector = np.linalg.eig(H_delta_kx_ky)
+            vector_delta_kx_ky = eigenvector[:, np.argsort(np.real(eigenvalue))[0]]  # 略偏离kx和ky的波函数
+
+            index = np.argmax(np.abs(vector))
+            precision = 0.0001
+            vector = find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=precision, index=index)
+            vector_delta_kx = find_vector_with_fixed_gauge_by_making_one_component_real(vector_delta_kx, precision=precision, index=index)
+            vector_delta_ky = find_vector_with_fixed_gauge_by_making_one_component_real(vector_delta_ky, precision=precision, index=index)
+            vector_delta_kx_ky  = find_vector_with_fixed_gauge_by_making_one_component_real(vector_delta_kx_ky, precision=precision, index=index)
+
+            # 价带的波函数的贝里联络(berry connection) # 求导后内积
+            A_x = np.dot(vector.transpose().conj(), (vector_delta_kx-vector)/delta)   # 贝里联络Ax（x分量）
+            A_y = np.dot(vector.transpose().conj(), (vector_delta_ky-vector)/delta)   # 贝里联络Ay（y分量）
+            
+            A_x_delta_ky = np.dot(vector_delta_ky.transpose().conj(), (vector_delta_kx_ky-vector_delta_ky)/delta)  # 略偏离ky的贝里联络Ax
+            A_y_delta_kx = np.dot(vector_delta_kx.transpose().conj(), (vector_delta_kx_ky-vector_delta_kx)/delta)  # 略偏离kx的贝里联络Ay
+
+            # 贝里曲率(berry curvature)
+            F = (A_y_delta_kx-A_y)/delta-(A_x_delta_ky-A_x)/delta
+
+            # 陈数(chern number)
+            chern_number = chern_number + F*(2*pi/n)**2
+    chern_number = chern_number/(2*pi*1j)
+    print('Chern number = ', chern_number)
+    end_time = time.time()
+    print('运行时间(min)=', (end_time-start_time)/60)
+
+
+def find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None):
+    vector = np.array(vector)
+    if index == None:
+        index = np.argmax(np.abs(vector))
+    sign_pre = np.sign(np.imag(vector[index]))
+    for phase in np.arange(0, 2*np.pi, precision):
+        sign =  np.sign(np.imag(vector[index]*cmath.exp(1j*phase)))
+        if np.abs(np.imag(vector[index]*cmath.exp(1j*phase))) < 1e-9 or sign == -sign_pre:
+            break
+        sign_pre = sign
+    vector = vector*cmath.exp(1j*phase)
+    if np.real(vector[index]) < 0:
+        vector = -vector
+    return vector 
+
+
+if __name__ == '__main__':
+    main()
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