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0.0.112

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guanjihuan 2022-07-20 15:03:44 +08:00
parent c9389df4fc
commit 9e81112614
3 changed files with 32 additions and 2 deletions
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4
API_Reference.py
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@ -111,6 +111,10 @@ hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1)
hamiltonian = guan.hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3)) hamiltonian = guan.hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3))
hamiltonian = guan.effective_hamiltonian_of_graphene(qx, qy, t=1, staggered_potential=0, valley_index=0)
hamiltonian = guan.effective_hamiltonian_of_graphene_after_discretization(qx, qy, t=1, staggered_potential=0, valley_index=0)
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)
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))

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 = 0.0.111 version = 0.0.112
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

28
PyPI/src/guan/__init__.py
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@ -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. # 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-0.0.111, updated on July 19, 2022. # The current version is guan-0.0.112, updated on July 20, 2022.
# Installation: pip install --upgrade guan # Installation: pip install --upgrade guan
@ -476,6 +476,32 @@ def hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3)):
hamiltonian = h0 + h1 hamiltonian = h0 + h1
return hamiltonian return hamiltonian
def effective_hamiltonian_of_graphene(qx, qy, t=1, staggered_potential=0, valley_index=0):
hamiltonian = np.zeros((2, 2), dtype=complex)
hamiltonian[0, 0] = staggered_potential
hamiltonian[1, 1] = -staggered_potential
constant = -np.sqrt(3)/2
if valley_index == 0:
hamiltonian[0, 1] = constant*t*(qx-1j*qy)
hamiltonian[1, 0] = constant*t*(qx+1j*qy)
else:
hamiltonian[0, 1] = constant*t*(-qx-1j*qy)
hamiltonian[1, 0] = constant*t*(-qx+1j*qy)
return hamiltonian
def effective_hamiltonian_of_graphene_after_discretization(qx, qy, t=1, staggered_potential=0, valley_index=0):
hamiltonian = np.zeros((2, 2), dtype=complex)
hamiltonian[0, 0] = staggered_potential
hamiltonian[1, 1] = -staggered_potential
constant = -np.sqrt(3)/2
if valley_index == 0:
hamiltonian[0, 1] = constant*t*(np.sin(qx)-1j*np.sin(qy))
hamiltonian[1, 0] = constant*t*(np.sin(qx)+1j*np.sin(qy))
else:
hamiltonian[0, 1] = constant*t*(-np.sin(qx)-1j*np.sin(qy))
hamiltonian[1, 0] = constant*t*(-np.sin(qx)+1j*np.sin(qy))
return hamiltonian
def hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1, period=0): def hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1, period=0):
h00 = np.zeros((4*N, 4*N), dtype=complex) # hopping in a unit cell h00 = np.zeros((4*N, 4*N), dtype=complex) # hopping in a unit cell
h01 = np.zeros((4*N, 4*N), dtype=complex) # hopping between unit cells h01 = np.zeros((4*N, 4*N), dtype=complex) # hopping between unit cells