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guanjihuan 2022-07-12 23:23:26 +08:00
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"""
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/22604
"""
import numpy as np
import cmath
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
vector_1 = np.array([np.sqrt(0.5), np.sqrt(0.5)])*cmath.exp(np.random.uniform(0, 1)*1j)
vector_2 = np.array([1, 0])*cmath.exp(np.random.uniform(0, 1)*1j)
print('\n随机规范的原向量:', vector_1)
vector_1 = find_vector_with_fixed_gauge_by_making_one_component_real(vector_1, precision=0.001)
print('固定规范后的向量:', vector_1)
print('\n随机规范的原向量:', vector_2)
vector_2 = find_vector_with_fixed_gauge_by_making_one_component_real(vector_2, precision=0.001)
print('固定规范后的向量:', vector_2)
# # 可直接使用Guan软件包来调用以上函数https://py.guanjihuan.com。
# # 安装命令pip install --upgrade guan。
# import guan
# print('\n随机规范的原向量', vector_1)
# vector_1 = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector_1, precision=0.001)
# print('固定规范后的向量:', vector_1)
# print('\n随机规范的原向量', vector_2)
# vector_2 = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector_2, precision=0.001)
# print('固定规范后的向量:', vector_2)

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"""
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/22604
"""
import numpy as np
import math
import cmath
# from numba import jit
# @jit
def rotation_of_degenerate_vectors(vector1, vector2, index1=None, index2=None, precision=0.01, criterion=0.01, show_theta=0):
vector1 = np.array(vector1)
vector2 = np.array(vector2)
if index1 == None:
index1 = np.argmax(np.abs(vector1))
if index2 == None:
index2 = np.argmax(np.abs(vector2))
if np.abs(vector1[index2])>criterion or np.abs(vector2[index1])>criterion:
for theta in np.arange(0, 2*math.pi, precision):
if show_theta==1:
print(theta)
for phi1 in np.arange(0, 2*math.pi, precision):
for phi2 in np.arange(0, 2*math.pi, precision):
vector1_test = cmath.exp(1j*phi1)*vector1*math.cos(theta)+cmath.exp(1j*phi2)*vector2*math.sin(theta)
vector2_test = -cmath.exp(-1j*phi2)*vector1*math.sin(theta)+cmath.exp(-1j*phi1)*vector2*math.cos(theta)
if np.abs(vector1_test[index2])<criterion and np.abs(vector2_test[index1])<criterion:
vector1 = vector1_test
vector2 = vector2_test
break
if np.abs(vector1_test[index2])<criterion and np.abs(vector2_test[index1])<criterion:
break
if np.abs(vector1_test[index2])<criterion and np.abs(vector2_test[index1])<criterion:
break
return vector1, vector2
def hamiltonian_of_BBH_model(kx, ky, gamma_x=0.5, gamma_y=0.5, lambda_x=1, lambda_y=1):
# label of atoms in a unit cell
# (2) —— (0)
# | |
# (1) —— (3)
hamiltonian = np.zeros((4, 4), dtype=complex)
hamiltonian[0, 2] = gamma_x+lambda_x*cmath.exp(1j*kx)
hamiltonian[1, 3] = gamma_x+lambda_x*cmath.exp(-1j*kx)
hamiltonian[0, 3] = gamma_y+lambda_y*cmath.exp(1j*ky)
hamiltonian[1, 2] = -gamma_y-lambda_y*cmath.exp(-1j*ky)
hamiltonian[2, 0] = np.conj(hamiltonian[0, 2])
hamiltonian[3, 1] = np.conj(hamiltonian[1, 3])
hamiltonian[3, 0] = np.conj(hamiltonian[0, 3])
hamiltonian[2, 1] = np.conj(hamiltonian[1, 2])
return hamiltonian
# For kx=0
print('\nFor kx=0:\n')
eigenvalue, eigenvector = np.linalg.eigh(hamiltonian_of_BBH_model(kx=0, ky=0))
print(eigenvalue, '\n')
print(eigenvector[:, 0])
print(eigenvector[:, 1], '\n')
# For kx=0.005
print('\nFor kx=0.005:\n')
eigenvalue, eigenvector = np.linalg.eigh(hamiltonian_of_BBH_model(kx=0.005, ky=0))
print(eigenvalue, '\n')
print(eigenvector[:, 0])
print(eigenvector[:, 1], '\n\n')
# Rotaion
vector1, vector2 = rotation_of_degenerate_vectors(eigenvector[:, 0], eigenvector[:, 1], precision=0.01, criterion=0.01, show_theta=1)
print()
print(vector1)
print(vector2, '\n')
# # 可直接使用Guan软件包来调用以上函数https://py.guanjihuan.com。
# # 安装命令pip install --upgrade guan。
# import guan
# vector1, vector2 = guan.rotation_of_degenerate_vectors(vector1, vector2, index1=None, index2=None, precision=0.01, criterion=0.01, show_theta=0)
# hamiltonian = guan.hamiltonian_of_BBH_model(kx, ky, gamma_x=0.5, gamma_y=0.5, lambda_x=1, lambda_y=1)