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import only for the necessary need

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guanjihuan 2023-10-03 10:37:16 +08:00
parent 2d36804856
commit bc213ccc9d
2 changed files with 266 additions and 55 deletions
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8
API_Reference/API_Reference.py
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@ -229,6 +229,7 @@ hamiltonian = guan.hamiltonian_of_cubic_lattice(k1, k2, k3)
hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1) hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1)
# 石墨烯的哈密顿量 # 石墨烯的哈密顿量
import math
hamiltonian = guan.hamiltonian_of_graphene(k1, k2, staggered_potential=0, t=1, a=1/math.sqrt(3)) hamiltonian = guan.hamiltonian_of_graphene(k1, k2, staggered_potential=0, t=1, a=1/math.sqrt(3))
# 石墨烯有效模型的哈密顿量 # 石墨烯有效模型的哈密顿量
@ -241,9 +242,11 @@ hamiltonian = guan.effective_hamiltonian_of_graphene_after_discretization(qx, qy
hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1, period=0) hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1, period=0)
# Haldane模型的哈密顿量 # Haldane模型的哈密顿量
import math
hamiltonian = guan.hamiltonian_of_haldane_model(k1, k2, M=2/3, t1=1, t2=1/3, phi=math.pi/4, a=1/math.sqrt(3)) hamiltonian = guan.hamiltonian_of_haldane_model(k1, k2, M=2/3, t1=1, t2=1/3, phi=math.pi/4, a=1/math.sqrt(3))
# 准一维Haldane模型条带的哈密顿量 # 准一维Haldane模型条带的哈密顿量
import math
hamiltonian = guan.hamiltonian_of_haldane_model_in_quasi_one_dimension(k, N=10, M=2/3, t1=1, t2=1/3, phi=math.pi/4, period=0) hamiltonian = guan.hamiltonian_of_haldane_model_in_quasi_one_dimension(k, N=10, M=2/3, t1=1, t2=1/3, phi=math.pi/4, period=0)
# 一个量子反常霍尔效应的哈密顿量 # 一个量子反常霍尔效应的哈密顿量
@ -580,21 +583,26 @@ chern_number = guan.calculate_chern_number_for_square_lattice_with_wilson_loop(h
chern_number = guan.calculate_chern_number_for_square_lattice_with_wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0) chern_number = guan.calculate_chern_number_for_square_lattice_with_wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0)
# 通过高效法计算贝利曲率 # 通过高效法计算贝利曲率
import math
k_array, berry_curvature_array = guan.calculate_berry_curvature_with_efficient_method(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0) k_array, berry_curvature_array = guan.calculate_berry_curvature_with_efficient_method(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0)
# 通过高效法计算贝利曲率（可计算简并的情况） # 通过高效法计算贝利曲率（可计算简并的情况）
import math
k_array, berry_curvature_array = guan.calculate_berry_curvature_with_efficient_method_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], k_min=-math.pi, k_max=math.pi, precision=100, print_show=0) k_array, berry_curvature_array = guan.calculate_berry_curvature_with_efficient_method_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], k_min=-math.pi, k_max=math.pi, precision=100, print_show=0)
# 通过Wilson loop方法计算贝里曲率 # 通过Wilson loop方法计算贝里曲率
import math
k_array, berry_curvature_array = guan.calculate_berry_curvature_with_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0) k_array, berry_curvature_array = guan.calculate_berry_curvature_with_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0)
# 通过Wilson loop方法计算贝里曲率（可计算简并的情况） # 通过Wilson loop方法计算贝里曲率（可计算简并的情况）
import math
k_array, berry_curvature_array = guan.calculate_berry_curvature_with_wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], k_min=-math.pi, k_max=math.pi, precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0) k_array, berry_curvature_array = guan.calculate_berry_curvature_with_wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], k_min=-math.pi, k_max=math.pi, precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0)
# 计算蜂窝格子的陈数（高效法） # 计算蜂窝格子的陈数（高效法）
chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0)
# 计算Wilson loop # 计算Wilson loop
import math
wilson_loop_array = guan.calculate_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0) wilson_loop_array = guan.calculate_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0)

301
Source_Code/PyPI/src/guan/__init__.py
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