From 23be72b2c1c8579adec05f7de0189634a7f80454 Mon Sep 17 00:00:00 2001
From: guanjihuan <guanjihuan@163.com>
Date: Wed, 15 Jun 2022 15:02:17 +0800
Subject: [PATCH] update

---
 .../2D_Haldane_model.py                           |  2 +-
 .../Chern_number_in_Haldane_model.py              | 15 +++++++++------
 ...er_in_Haldane_model_by_integration_method_2.py | 14 +++++++++-----
 ...er_in_Haldane_model_by_integration_method_3.py | 14 +++++++++-----
 4 files changed, 28 insertions(+), 17 deletions(-)

diff --git a/academic_codes/2019.10.24_Halmiltonian_and_bands_of_Haldane_model/2D_Haldane_model.py b/academic_codes/2019.10.24_Halmiltonian_and_bands_of_Haldane_model/2D_Haldane_model.py
index 9f84494..632278c 100755
--- a/academic_codes/2019.10.24_Halmiltonian_and_bands_of_Haldane_model/2D_Haldane_model.py
+++ b/academic_codes/2019.10.24_Halmiltonian_and_bands_of_Haldane_model/2D_Haldane_model.py
@@ -25,7 +25,7 @@ def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a
     h1[0, 1] = h1[1, 0].conj()
 
     # 最近邻项也可写成这种形式
-    # h1[1, 0] = t1+t1*cmath.exp(1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)-t1*cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)
+    # h1[1, 0] = t1+t1*cmath.exp(1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)+t1*cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)
     # h1[0, 1] = h1[1, 0].conj()
 
     # 次近邻项
diff --git a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model.py b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model.py
index a542708..d6c8e66 100755
--- a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model.py
+++ b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model.py
@@ -4,18 +4,17 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
 """
 
 import numpy as np
-import matplotlib.pyplot as plt
 from math import *   # 引入pi, cos等
 import cmath
 import time
 import functools  # 使用偏函数functools.partial()
 
 
-def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a为原子间距，不赋值的话默认为1/sqrt(3)）
+def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量（a为原子间距，不赋值的话默认为1/sqrt(3)）
     # 初始化为零矩阵
-    h0 = np.zeros((2, 2))*(1+0j)   # 乘(1+0j)是为了把h0转为复数
-    h1 = np.zeros((2, 2))*(1+0j)
-    h2 = np.zeros((2, 2))*(1+0j)
+    h0 = np.zeros((2, 2), dtype=complex)
+    h1 = np.zeros((2, 2), dtype=complex)
+    h2 = np.zeros((2, 2), dtype=complex)
 
     # 质量项(mass term), 用于打开带隙
     h0[0, 0] = M
@@ -25,6 +24,10 @@ def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a
     h1[1, 0] = t1*(cmath.exp(1j*k2*a)+cmath.exp(1j*sqrt(3)/2*k1*a-1j/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j/2*k2*a))
     h1[0, 1] = h1[1, 0].conj()
 
+    # # 最近邻项也可写成这种形式
+    # h1[1, 0] = t1+t1*cmath.exp(1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)+t1*cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)
+    # h1[0, 1] = h1[1, 0].conj()
+
     #次近邻项 # 对应陈数为-1
     h2[0, 0] = t2*cmath.exp(-1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
     h2[1, 1] = t2*cmath.exp(1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
@@ -88,4 +91,4 @@ def main():
 
 
 if __name__ == '__main__':
-    main()
+    main()
\ No newline at end of file
diff --git a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_2.py b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_2.py
index eefbcda..d4a3cc2 100755
--- a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_2.py
+++ b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_2.py
@@ -11,11 +11,11 @@ import time
 import functools  # 使用偏函数functools.partial()
 
 
-def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a为原子间距，不赋值的话默认为1/sqrt(3)）
+def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量（a为原子间距，不赋值的话默认为1/sqrt(3)）
     # 初始化为零矩阵
-    h0 = np.zeros((2, 2))*(1+0j)   # 乘(1+0j)是为了把h0转为复数
-    h1 = np.zeros((2, 2))*(1+0j)
-    h2 = np.zeros((2, 2))*(1+0j)
+    h0 = np.zeros((2, 2), dtype=complex)
+    h1 = np.zeros((2, 2), dtype=complex)
+    h2 = np.zeros((2, 2), dtype=complex)
 
     # 质量项(mass term), 用于打开带隙
     h0[0, 0] = M
@@ -25,6 +25,10 @@ def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a
     h1[1, 0] = t1*(cmath.exp(1j*k2*a)+cmath.exp(1j*sqrt(3)/2*k1*a-1j/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j/2*k2*a))
     h1[0, 1] = h1[1, 0].conj()
 
+    # # 最近邻项也可写成这种形式
+    # h1[1, 0] = t1+t1*cmath.exp(1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)+t1*cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)
+    # h1[0, 1] = h1[1, 0].conj()
+
     #次近邻项 # 对应陈数为-1
     h2[0, 0] = t2*cmath.exp(-1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
     h2[1, 1] = t2*cmath.exp(1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
@@ -84,4 +88,4 @@ def main():
 
 
 if __name__ == '__main__':
-    main()
+    main()
\ No newline at end of file
diff --git a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_3.py b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_3.py
index c76d62d..09e3d9f 100755
--- a/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_3.py
+++ b/academic_codes/2020.07.13_calculation_of_Chern_number_in_Haldane_model/Chern_number_in_Haldane_model_by_integration_method_3.py
@@ -11,11 +11,11 @@ import time
 import functools  # 使用偏函数functools.partial()
 
 
-def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a为原子间距，不赋值的话默认为1/sqrt(3)）
+def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量# Haldane哈密顿量（a为原子间距，不赋值的话默认为1/sqrt(3)）
     # 初始化为零矩阵
-    h0 = np.zeros((2, 2))*(1+0j)   # 乘(1+0j)是为了把h0转为复数
-    h1 = np.zeros((2, 2))*(1+0j)
-    h2 = np.zeros((2, 2))*(1+0j)
+    h0 = np.zeros((2, 2), dtype=complex)
+    h1 = np.zeros((2, 2), dtype=complex)
+    h2 = np.zeros((2, 2), dtype=complex)
 
     # 质量项(mass term), 用于打开带隙
     h0[0, 0] = M
@@ -25,6 +25,10 @@ def hamiltonian(k1, k2, M, t1, t2, phi, a=1/sqrt(3)):  # Haldane哈密顿量(a
     h1[1, 0] = t1*(cmath.exp(1j*k2*a)+cmath.exp(1j*sqrt(3)/2*k1*a-1j/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j/2*k2*a))
     h1[0, 1] = h1[1, 0].conj()
 
+    # # 最近邻项也可写成这种形式
+    # h1[1, 0] = t1+t1*cmath.exp(1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)+t1*cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a)
+    # h1[0, 1] = h1[1, 0].conj()
+
     #次近邻项 # 对应陈数为-1
     h2[0, 0] = t2*cmath.exp(-1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
     h2[1, 1] = t2*cmath.exp(1j*phi)*(cmath.exp(1j*sqrt(3)*k1*a)+cmath.exp(-1j*sqrt(3)/2*k1*a+1j*3/2*k2*a)+cmath.exp(-1j*sqrt(3)/2*k1*a-1j*3/2*k2*a))
@@ -92,4 +96,4 @@ def main():
 
 
 if __name__ == '__main__':
-    main()
+    main()
\ No newline at end of file