guanjihuan/guanjihuan.com
1
1
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
guanjihuan 2024-01-25 16:05:04 +08:00
parent 2603da57d1
commit 275a12024d
5 changed files with 7 additions and 54 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
2020.12.31_DOS_calculation_using_Dyson_equations/cubic_lattice/DOS_calculation_using_Dyson_equations_in_cubic_lattice.py
View File

@ -4,9 +4,6 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
""" """
import numpy as np import numpy as np
import matplotlib.pyplot as plt
from math import *
def matrix_00(width, length): def matrix_00(width, length):
h00 = np.zeros((width*length, width*length)) h00 = np.zeros((width*length, width*length))
@ -20,12 +17,10 @@ def matrix_00(width, length):
h00[(x+1)*width+y, x*width+y] = 1 h00[(x+1)*width+y, x*width+y] = 1
return h00 return h00
def matrix_01(width, length): def matrix_01(width, length):
h01 = np.identity(width*length) h01 = np.identity(width*length)
return h01 return h01
def main(): def main():
height = 2 # z height = 2 # z
width = 3 # y width = 3 # y
@ -40,8 +35,7 @@ def main():
for j0 in range(width): for j0 in range(width):
print(' y=', j0+1, ':') print(' y=', j0+1, ':')
for k0 in range(length): for k0 in range(length):
print(' x=', k0+1, ' ', -np.imag(G_ii_n_array[i0, k0*width+j0, k0*width+j0])/pi) # 态密度 print(' x=', k0+1, ' ', -np.imag(G_ii_n_array[i0, k0*width+j0, k0*width+j0])/np.pi) # 态密度
def G_ii_n_with_Dyson_equation(width, length, height, E, eta, h00, h01): def G_ii_n_with_Dyson_equation(width, length, height, E, eta, h00, h01):
dim = length*width dim = length*width
@ -76,27 +70,22 @@ def G_ii_n_with_Dyson_equation(width, length, height, E, eta, h00, h01):
G_ii_n_array[i, :, :] = G_ii_n_minus G_ii_n_array[i, :, :] = G_ii_n_minus
return G_ii_n_array return G_ii_n_array
def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2 def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2
dim = H00.shape[0] dim = H00.shape[0]
G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V)) G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V))
return G_nn_n return G_nn_n
def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2 def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2
G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n) G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n)
return G_in_n return G_in_n
def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2 def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2
G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus) G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus)
return G_ni_n return G_ni_n
def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i
G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus) G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus)
return G_ii_n return G_ii_n
if __name__ == '__main__': if __name__ == '__main__':
main() main()

13
2020.12.31_DOS_calculation_using_Dyson_equations/cubic_lattice/DOS_calculation_using_Dyson_equations_in_cubic_lattice_version_II.py
View File

@ -4,9 +4,6 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
""" """
import numpy as np import numpy as np
import matplotlib.pyplot as plt
from math import *
def matrix_00(width, length): def matrix_00(width, length):
h00 = np.zeros((width*length, width*length)) h00 = np.zeros((width*length, width*length))
@ -20,12 +17,10 @@ def matrix_00(width, length):
h00[(x+1)*width+y, x*width+y] = 1 h00[(x+1)*width+y, x*width+y] = 1
return h00 return h00
def matrix_01(width, length): def matrix_01(width, length):
h01 = np.identity(width*length) h01 = np.identity(width*length)
return h01 return h01
def main(): def main():
height = 2 # z height = 2 # z
width = 3 # y width = 3 # y
@ -36,7 +31,6 @@ def main():
h01 = matrix_01(width, length) h01 = matrix_01(width, length)
G_ii_n_with_Dyson_equation_version_II(width, length, height, E, eta, h00, h01) G_ii_n_with_Dyson_equation_version_II(width, length, height, E, eta, h00, h01)
def G_ii_n_with_Dyson_equation_version_II(width, length, height, E, eta, h00, h01): def G_ii_n_with_Dyson_equation_version_II(width, length, height, E, eta, h00, h01):
dim = length*width dim = length*width
G_11_1 = np.linalg.inv((E+eta*1j)*np.identity(dim)-h00) G_11_1 = np.linalg.inv((E+eta*1j)*np.identity(dim)-h00)
@ -71,29 +65,24 @@ def G_ii_n_with_Dyson_equation_version_II(width, length, height, E, eta, h00, h0
for j0 in range(width): for j0 in range(width):
print(' y=', j0+1, ':') print(' y=', j0+1, ':')
for k0 in range(length): for k0 in range(length):
print(' x=', k0+1, ' ', -np.imag(G_ii_n_minus[k0*width+j0, k0*width+j0])/pi) # 态密度 print(' x=', k0+1, ' ', -np.imag(G_ii_n_minus[k0*width+j0, k0*width+j0])/np.pi) # 态密度
def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2 def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2
dim = H00.shape[0] dim = H00.shape[0]
G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V)) G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V))
return G_nn_n return G_nn_n
def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2 def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2
G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n) G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n)
return G_in_n return G_in_n
def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2 def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2
G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus) G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus)
return G_ni_n return G_ni_n
def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i
G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus) G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus)
return G_ii_n return G_ii_n
if __name__ == '__main__': if __name__ == '__main__':
main() main()

9
2020.12.31_DOS_calculation_using_Dyson_equations/cubic_lattice/get_DOS_by_direct_inverseion_of_Hamiltonian_of_cubic_lattice.py
View File

@ -4,9 +4,6 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
""" """
import numpy as np import numpy as np
import matplotlib.pyplot as plt
from math import *
def hamiltonian(width, length, height): def hamiltonian(width, length, height):
h = np.zeros((width*length*height, width*length*height)) h = np.zeros((width*length*height, width*length*height))
@ -27,7 +24,6 @@ def hamiltonian(width, length, height):
h[k0*width*length+(i0+1)*width+j0, k0*width*length+i0*width+j0] = 1 h[k0*width*length+(i0+1)*width+j0, k0*width*length+i0*width+j0] = 1
return h return h
def main(): def main():
height = 2 # z height = 2 # z
width = 3 # y width = 3 # y
@ -40,10 +36,7 @@ def main():
for j0 in range(width): for j0 in range(width):
print(' y=', j0+1, ':') print(' y=', j0+1, ':')
for i0 in range(length): for i0 in range(length):
print(' x=', i0+1, ' ', -np.imag(green[k0*width*length+i0*width+j0, k0*width*length+i0*width+j0])/pi) # 态密度 print(' x=', i0+1, ' ', -np.imag(green[k0*width*length+i0*width+j0, k0*width*length+i0*width+j0])/np.pi) # 态密度
if __name__ == "__main__": if __name__ == "__main__":
main() main()

13
2020.12.31_DOS_calculation_using_Dyson_equations/square_lattice/DOS_calculation_using_Dyson_equations_in_square_lattice.py
View File

@ -4,9 +4,6 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
""" """
import numpy as np import numpy as np
import matplotlib.pyplot as plt
from math import *
def matrix_00(width): def matrix_00(width):
h00 = np.zeros((width, width)) h00 = np.zeros((width, width))
@ -15,12 +12,10 @@ def matrix_00(width):
h00[width0+1, width0] = 1 h00[width0+1, width0] = 1
return h00 return h00
def matrix_01(width): def matrix_01(width):
h01 = np.identity(width) h01 = np.identity(width)
return h01 return h01
def main(): def main():
width = 2 width = 2
length = 3 length = 3
@ -34,8 +29,7 @@ def main():
# print(G_ii_n_array[i0, :, :],'\n') # print(G_ii_n_array[i0, :, :],'\n')
print('x=', i0+1, ':') print('x=', i0+1, ':')
for j0 in range(width): for j0 in range(width):
print(' y=', j0+1, ' ', -np.imag(G_ii_n_array[i0, j0, j0])/pi) # 态密度 print(' y=', j0+1, ' ', -np.imag(G_ii_n_array[i0, j0, j0])/np.pi) # 态密度
def G_ii_n_with_Dyson_equation(width, length, E, eta, h00, h01): def G_ii_n_with_Dyson_equation(width, length, E, eta, h00, h01):
G_ii_n_array = np.zeros((length, width, width), complex) G_ii_n_array = np.zeros((length, width, width), complex)
@ -69,27 +63,22 @@ def G_ii_n_with_Dyson_equation(width, length, E, eta, h00, h01):
G_ii_n_array[i, :, :] = G_ii_n_minus G_ii_n_array[i, :, :] = G_ii_n_minus
return G_ii_n_array return G_ii_n_array
def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2 def Green_nn_n(E, eta, H00, V, G_nn_n_minus): # n>=2
dim = H00.shape[0] dim = H00.shape[0]
G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V)) G_nn_n = np.linalg.inv((E+eta*1j)*np.identity(dim)-H00-np.dot(np.dot(V.transpose().conj(), G_nn_n_minus), V))
return G_nn_n return G_nn_n
def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2 def Green_in_n(G_in_n_minus, V, G_nn_n): # n>=2
G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n) G_in_n = np.dot(np.dot(G_in_n_minus, V), G_nn_n)
return G_in_n return G_in_n
def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2 def Green_ni_n(G_nn_n, V, G_ni_n_minus): # n>=2
G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus) G_ni_n = np.dot(np.dot(G_nn_n, V.transpose().conj()), G_ni_n_minus)
return G_ni_n return G_ni_n
def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i def Green_ii_n(G_ii_n_minus, G_in_n_minus, V, G_nn_n, G_ni_n_minus): # n>=i
G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus) G_ii_n = G_ii_n_minus+np.dot(np.dot(np.dot(np.dot(G_in_n_minus, V), G_nn_n), V.transpose().conj()),G_ni_n_minus)
return G_ii_n return G_ii_n
if __name__ == '__main__': if __name__ == '__main__':
main() main()

9
2020.12.31_DOS_calculation_using_Dyson_equations/square_lattice/get_DOS_by_direct_inverseion_of_Hamiltonian_of_square_lattice.py
View File

@ -4,9 +4,6 @@ The newest version of this code is on the web page: https://www.guanjihuan.com/a
""" """
import numpy as np import numpy as np
import matplotlib.pyplot as plt
from math import *
def hamiltonian(width, length): def hamiltonian(width, length):
h = np.zeros((width*length, width*length)) h = np.zeros((width*length, width*length))
@ -20,7 +17,6 @@ def hamiltonian(width, length):
h[(i0+1)*width+j0, i0*width+j0] = 1 h[(i0+1)*width+j0, i0*width+j0] = 1
return h return h
def main(): def main():
width = 2 width = 2
length = 3 length = 3
@ -32,10 +28,7 @@ def main():
# print(green[i0*width+0: i0*width+width, i0*width+0: i0*width+width], '\n') # print(green[i0*width+0: i0*width+width, i0*width+0: i0*width+width], '\n')
print('x=', i0+1, ':') print('x=', i0+1, ':')
for j0 in range(width): for j0 in range(width):
print(' y=', j0+1, ' ', -np.imag(green[i0*width+j0, i0*width+j0])/pi) print(' y=', j0+1, ' ', -np.imag(green[i0*width+j0, i0*width+j0])/np.pi)
if __name__ == "__main__": if __name__ == "__main__":
main() main()