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guan-0.0.24

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guanjihuan
2021-11-05 21:52:30 +08:00
parent 8f2aac1681
commit 83fdd8a619
3 changed files with 38 additions and 1 deletions
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1
API_reference.py
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@@ -74,6 +74,7 @@ local_dos = guan.local_density_of_states_for_square_lattice(fermi_energy, hamilt
local_dos = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, N3, internal_degree=1, broadening=0.01) local_dos = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, N3, internal_degree=1, broadening=0.01)
local_dos = guan.local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01) local_dos = guan.local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01)
local_dos = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01) local_dos = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01)
local_dos = local_density_of_states_for_square_lattice_with_self_energy_using_dyson_equation(fermi_energy, h00, h01, N2, N1, right_self_energy, left_self_energy, internal_degree=1, broadening=0.01)
# calculate conductance # Source code: https://py.guanjihuan.com/calculate_conductance # calculate conductance # Source code: https://py.guanjihuan.com/calculate_conductance
transfer = guan.transfer_matrix(fermi_energy, h00, h01) transfer = guan.transfer_matrix(fermi_energy, h00, h01)

2
PyPI/setup.cfg
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@@ -1,7 +1,7 @@
[metadata] [metadata]
# replace with your username: # replace with your username:
name = guan name = guan
version = 0.0.23 version = 0.0.24
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

36
PyPI/src/guan/calculate_density_of_states.py
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@@ -100,4 +100,40 @@ def local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy,
for i3 in range(N3): for i3 in range(N3):
for i in range(internal_degree): for i in range(internal_degree):
local_dos[i3, i2, i1] = local_dos[i3, i2, i1] -np.imag(green_ii_n_minus[i2*N3*internal_degree+i3*internal_degree+i, i2*N3*internal_degree+i3*internal_degree+i])/pi local_dos[i3, i2, i1] = local_dos[i3, i2, i1] -np.imag(green_ii_n_minus[i2*N3*internal_degree+i3*internal_degree+i, i2*N3*internal_degree+i3*internal_degree+i])/pi
return local_dos
def local_density_of_states_for_square_lattice_with_self_energy_using_dyson_equation(fermi_energy, h00, h01, N2, N1, right_self_energy, left_self_energy, internal_degree=1, broadening=0.01):
# dim_h00 = N2*internal_degree
local_dos = np.zeros((N2, N1))
green_11_1 = green_function(fermi_energy, h00+left_self_energy, broadening)
for i1 in range(N1):
green_nn_n_minus = green_11_1
green_in_n_minus = green_11_1
green_ni_n_minus = green_11_1
green_ii_n_minus = green_11_1
for i2_0 in range(i1):
if i2_0 == N1-1-1:
green_nn_n = green_function_nn_n(fermi_energy, h00+right_self_energy, h01, green_nn_n_minus, broadening)
else:
green_nn_n = green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening)
green_nn_n_minus = green_nn_n
if i1!=0:
green_in_n_minus = green_nn_n
green_ni_n_minus = green_nn_n
green_ii_n_minus = green_nn_n
for size_0 in range(N1-1-i1):
if size_0 == N1-1-i1-1:
green_nn_n = green_function_nn_n(fermi_energy, h00+right_self_energy, h01, green_nn_n_minus, broadening)
else:
green_nn_n = green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening)
green_nn_n_minus = green_nn_n
green_ii_n = green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus)
green_ii_n_minus = green_ii_n
green_in_n = green_function_in_n(green_in_n_minus, h01, green_nn_n)
green_in_n_minus = green_in_n
green_ni_n = green_function_ni_n(green_nn_n, h01, green_ni_n_minus)
green_ni_n_minus = green_ni_n
for i2 in range(N2):
for i in range(internal_degree):
local_dos[i2, i1] = local_dos[i2, i1] - np.imag(green_ii_n_minus[i2*internal_degree+i, i2*internal_degree+i])/pi
return local_dos return local_dos