From 4677ff429dcaef2dcc509ca8c22997b839d4f520 Mon Sep 17 00:00:00 2001 From: guanjihuan Date: Fri, 12 Aug 2022 11:37:37 +0800 Subject: [PATCH] 0.0.120 --- API_Reference.py | 5 ++- PyPI/setup.cfg | 2 +- PyPI/src/guan.egg-info/PKG-INFO | 2 +- PyPI/src/guan/__init__.py | 64 +++++++++++++++++++++++++++++++-- 4 files changed, 68 insertions(+), 5 deletions(-) diff --git a/API_Reference.py b/API_Reference.py index 82fded3..08b7598 100644 --- a/API_Reference.py +++ b/API_Reference.py @@ -1,5 +1,6 @@ import guan +import math # Module 1: basic functions @@ -245,7 +246,9 @@ guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_ chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_function, precision=100, print_show=0) -chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=10, precision_of_Wilson_loop=100, print_show=0) +chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, 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, num_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0) chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg index cca0740..a99c33d 100644 --- a/PyPI/setup.cfg +++ b/PyPI/setup.cfg @@ -1,7 +1,7 @@ [metadata] # replace with your username: name = guan -version = 0.0.119 +version = 0.0.120 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 feed411..89af6bf 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: 0.0.119 +Version: 0.0.120 Summary: An open source python package Home-page: https://py.guanjihuan.com Author: guanjihuan diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py index a548148..6637f5b 100644 --- a/PyPI/src/guan/__init__.py +++ b/PyPI/src/guan/__init__.py @@ -2,7 +2,7 @@ # With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated in this package, such as file reading/writing, figure plotting, data processing. -# The current version is guan-0.0.119, updated on August 10, 2022. +# The current version is guan-0.0.120, updated on August 12, 2022. # Installation: pip install --upgrade guan @@ -1551,7 +1551,7 @@ def calculate_chern_number_for_square_lattice(hamiltonian_function, precision=10 chern_number = chern_number/(2*math.pi*1j) return chern_number -def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=10, precision_of_Wilson_loop=100, print_show=0): +def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0): delta = 2*math.pi/precision_of_plaquettes chern_number = 0 for kx in np.arange(-math.pi, math.pi, delta): @@ -1592,6 +1592,66 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_funct chern_number = chern_number/(2*math.pi) return chern_number +def calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_case(hamiltonian_function, num_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0): + delta = 2*math.pi/precision_of_plaquettes + chern_number = 0 + for kx in np.arange(-math.pi, math.pi, delta): + if print_show == 1: + print(kx) + for ky in np.arange(-math.pi, math.pi, delta): + vector_array = [] + # line_1 + for i0 in range(precision_of_Wilson_loop): + H_delta = hamiltonian_function(kx+delta/precision_of_Wilson_loop*i0, ky) + eigenvalue, eigenvector = np.linalg.eig(H_delta) + vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] + vector_array.append(vector_delta) + # line_2 + for i0 in range(precision_of_Wilson_loop): + H_delta = hamiltonian_function(kx+delta, ky+delta/precision_of_Wilson_loop*i0) + eigenvalue, eigenvector = np.linalg.eig(H_delta) + vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] + vector_array.append(vector_delta) + # line_3 + for i0 in range(precision_of_Wilson_loop): + H_delta = hamiltonian_function(kx+delta-delta/precision_of_Wilson_loop*i0, ky+delta) + eigenvalue, eigenvector = np.linalg.eig(H_delta) + vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] + vector_array.append(vector_delta) + # line_4 + for i0 in range(precision_of_Wilson_loop): + H_delta = hamiltonian_function(kx, ky+delta-delta/precision_of_Wilson_loop*i0) + eigenvalue, eigenvector = np.linalg.eig(H_delta) + vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] + vector_array.append(vector_delta) + Wilson_loop = 1 + dim = len(num_of_bands) + for i0 in range(len(vector_array)-1): + dot_matrix = np.zeros((dim , dim), dtype=complex) + i01 = 0 + for dim1 in num_of_bands: + i02 = 0 + for dim2 in num_of_bands: + dot_matrix[i01, i02] = np.dot(vector_array[i0][:, dim1].transpose().conj(), vector_array[i0+1][:, dim2]) + i02 += 1 + i01 += 1 + det_value = np.linalg.det(dot_matrix) + Wilson_loop = Wilson_loop*det_value + dot_matrix_plus = np.zeros((dim , dim), dtype=complex) + i01 = 0 + for dim1 in num_of_bands: + i02 = 0 + for dim2 in num_of_bands: + dot_matrix_plus[i01, i02] = np.dot(vector_array[len(vector_array)-1][:, dim1].transpose().conj(), vector_array[0][:, dim2]) + i02 += 1 + i01 += 1 + det_value = np.linalg.det(dot_matrix_plus) + Wilson_loop = Wilson_loop*det_value + arg = np.log(Wilson_loop)/1j + chern_number = chern_number + arg + chern_number = chern_number/(2*math.pi) + return chern_number + def calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0): if np.array(hamiltonian_function(0, 0)).shape==(): dim = 1