From 9de98e961b6bce9e29092f72ca83adec68055598 Mon Sep 17 00:00:00 2001 From: guanjihuan Date: Fri, 26 Jan 2024 00:09:17 +0800 Subject: [PATCH] 0.1.80 --- PyPI/setup.cfg | 2 +- PyPI/src/guan.egg-info/PKG-INFO | 2 +- .../band_structures_and_wave_functions.py | 36 ++++++++++++-- PyPI/src/guan/density_of_states.py | 49 ++++++++++++++++--- 4 files changed, 75 insertions(+), 14 deletions(-) diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg index 335dafe..f5a0437 100644 --- a/PyPI/setup.cfg +++ b/PyPI/setup.cfg @@ -1,7 +1,7 @@ [metadata] # replace with your username: name = guan -version = 0.1.79 +version = 0.1.80 author = guanjihuan author_email = guanjihuan@163.com description = An open source python package diff --git a/PyPI/src/guan.egg-info/PKG-INFO b/PyPI/src/guan.egg-info/PKG-INFO index c810d3e..71e1af2 100644 --- a/PyPI/src/guan.egg-info/PKG-INFO +++ b/PyPI/src/guan.egg-info/PKG-INFO @@ -1,6 +1,6 @@ Metadata-Version: 2.1 Name: guan -Version: 0.1.79 +Version: 0.1.80 Summary: An open source python package Home-page: https://py.guanjihuan.com Author: guanjihuan diff --git a/PyPI/src/guan/band_structures_and_wave_functions.py b/PyPI/src/guan/band_structures_and_wave_functions.py index 96b47e9..3051560 100644 --- a/PyPI/src/guan/band_structures_and_wave_functions.py +++ b/PyPI/src/guan/band_structures_and_wave_functions.py @@ -116,9 +116,35 @@ def find_vector_with_the_same_gauge_with_binary_search(vector_target, vector_ref print('Phase=', phase) return vector_target -# 通过使得波函数的一个非零分量为实数，得到固定规范的波函数 +# 通过乘一个相反的相位角，实现波函数的一个非零分量为实数，从而得到固定规范的波函数 @guan.statistics_decorator -def find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None): +def find_vector_with_fixed_gauge_by_making_one_component_real(vector, index=None): + import numpy as np + import cmath + vector = np.array(vector) + if index == None: + index = np.argmax(np.abs(vector)) + angle = cmath.phase(vector[index]) + vector = vector*cmath.exp(-1j*angle) + return vector + +# 通过乘一个相反的相位角，实现波函数的一个非零分量为实数，从而得到固定规范的波函数（在一组波函数中选取最大的那个分量） +@guan.statistics_decorator +def find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array): + import numpy as np + import guan + vector_sum = 0 + Num_k = np.array(vector_array).shape[0] + for i0 in range(Num_k): + vector_sum += np.abs(vector_array[i0]) + index = np.argmax(np.abs(vector_sum)) + for i0 in range(Num_k): + vector_array[i0] = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector_array[i0], index=index) + return vector_array + +# 循环查找规范使得波函数的一个非零分量为实数，得到固定规范的波函数 +@guan.statistics_decorator +def loop_find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None): import numpy as np import cmath vector = np.array(vector) @@ -135,9 +161,9 @@ def find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision= vector = -vector return vector -# 通过使得波函数的一个非零分量为实数，得到固定规范的波函数（在一组波函数中选取最大的那个分量） +# 循环查找规范使得波函数的一个非零分量为实数，得到固定规范的波函数（在一组波函数中选取最大的那个分量） @guan.statistics_decorator -def find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array, precision=0.005): +def loop_find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array, precision=0.005): import numpy as np import guan vector_sum = 0 @@ -146,7 +172,7 @@ def find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array vector_sum += np.abs(vector_array[i0]) index = np.argmax(np.abs(vector_sum)) for i0 in range(Num_k): - vector_array[i0] = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector_array[i0], precision=precision, index=index) + vector_array[i0] = guan.loop_find_vector_with_fixed_gauge_by_making_one_component_real(vector_array[i0], precision=precision, index=index) return vector_array # 旋转两个简并的波函数（说明：参数比较多，算法效率不高） diff --git a/PyPI/src/guan/density_of_states.py b/PyPI/src/guan/density_of_states.py index 082d9ed..04690e3 100644 --- a/PyPI/src/guan/density_of_states.py +++ b/PyPI/src/guan/density_of_states.py @@ -55,7 +55,7 @@ def local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, local_dos[i3, i2, i1] = local_dos[i3, i2, i1]-np.imag(green[i1*N2*N3*internal_degree+i2*N3*internal_degree+i3*internal_degree+i, i1*N2*N3*internal_degree+i2*N3*internal_degree+i3*internal_degree+i])/math.pi return local_dos -# 利用Dyson方程，计算方格子的局域态密度（其中，h00的维度为：dim_h00 = N2*internal_degree） +# 使用Dyson方程，计算方格子的局域态密度（其中，h00的维度为：dim_h00 = N2*internal_degree） @guan.statistics_decorator def local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01): import numpy as np @@ -68,14 +68,14 @@ def local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy 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): + for _ in range(i1): green_nn_n = guan.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): + for _ in range(N1-1-i1): green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening) green_nn_n_minus = green_nn_n green_ii_n = guan.green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus) @@ -89,7 +89,42 @@ def local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy local_dos[i2, i1] = local_dos[i2, i1] - np.imag(green_ii_n_minus[i2*internal_degree+i, i2*internal_degree+i])/math.pi return local_dos -# 利用Dyson方程，计算立方格子的局域态密度（其中，h00的维度为：dim_h00 = N2*N3*internal_degree） +# 使用Dyson方程，计算方格子的局域态密度，方法二（其中，h00的维度为：dim_h00 = N2*internal_degree） +@guan.statistics_decorator +def local_density_of_states_for_square_lattice_using_dyson_equation_with_second_method(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01): + import numpy as np + import math + import guan + h01 = np.array(h01) + if np.array(h00).shape==(): + dim = 1 + else: + dim = np.array(h00).shape[0] + local_dos = np.zeros((N2, N1)) + green_11_1 = guan.green_function(fermi_energy, h00, broadening) + for i1 in range(N1): + green_nn_n_right_minus = green_11_1 + green_nn_n_left_minus = green_11_1 + if i1!=0: + for _ in range(i1-1): + green_nn_n_right = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_right_minus, broadening) + green_nn_n_right_minus = green_nn_n_right + if i1!=N1-1: + for _ in range(N1-i1-2): + G_nn_n_left = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_left_minus, broadening) + green_nn_n_left_minus = G_nn_n_left + if i1==0: + green_ii_n = np.linalg.inv((fermi_energy+broadening*1j)*np.identity(dim)-h00-np.dot(np.dot(h01, green_nn_n_left_minus), h01.transpose().conj())) + elif i1!=0 and i1!=N1-1: + green_ii_n = np.linalg.inv((fermi_energy+broadening*1j)*np.identity(dim)-h00-np.dot(np.dot(h01.transpose().conj(), green_nn_n_right_minus), h01)-np.dot(np.dot(h01, green_nn_n_left_minus), h01.transpose().conj())) + elif i1==N1-1: + green_ii_n = np.linalg.inv((fermi_energy+broadening*1j)*np.identity(dim)-h00-np.dot(np.dot(h01.transpose().conj(), green_nn_n_right_minus), h01)) + for i2 in range(N2): + for i in range(internal_degree): + local_dos[i2, i1] = local_dos[i2, i1] - np.imag(green_ii_n[i2*internal_degree+i, i2*internal_degree+i])/math.pi + return local_dos + +# 使用Dyson方程，计算立方格子的局域态密度（其中，h00的维度为：dim_h00 = N2*N3*internal_degree） @guan.statistics_decorator def local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01): import numpy as np @@ -102,14 +137,14 @@ def local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, green_in_n_minus = green_11_1 green_ni_n_minus = green_11_1 green_ii_n_minus = green_11_1 - for i1_0 in range(i1): + for _ in range(i1): green_nn_n = guan.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): + for _ in range(N1-1-i1): green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening) green_nn_n_minus = green_nn_n green_ii_n = guan.green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus) @@ -124,7 +159,7 @@ def local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, 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])/math.pi return local_dos -# 利用Dyson方程，计算方格子条带（考虑了电极自能）的局域态密度（其中，h00的维度为：dim_h00 = N2*internal_degree） +# 使用Dyson方程，计算方格子条带（考虑了电极自能）的局域态密度（其中，h00的维度为：dim_h00 = N2*internal_degree） @guan.statistics_decorator 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): import numpy as np