From 327c06cd6b0b11762e40866b98a435105a2abb8f Mon Sep 17 00:00:00 2001
From: guanjihuan <guanjihuan@163.com>
Date: Wed, 20 Jul 2022 18:49:30 +0800
Subject: [PATCH] 0.0.114

---
 API_Reference.py          |  4 +++-
 PyPI/setup.cfg            |  2 +-
 PyPI/src/guan/__init__.py | 28 +++++++++++++++++++++++-----
 3 files changed, 27 insertions(+), 7 deletions(-)

diff --git a/API_Reference.py b/API_Reference.py
index 6037d37..2ff350c 100644
--- a/API_Reference.py
+++ b/API_Reference.py
@@ -89,6 +89,8 @@ hopping = guan.get_hopping_term_of_graphene_ribbon_along_zigzag_direction(N, eta
 
 hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_graphene(N1, N2, period_1=0, period_2=0)
 
+h00, h01 = guan.get_onsite_and_hopping_terms_of_2d_effective_graphene_along_one_direction(qy, t=1, staggered_potential=0, eta=0, valley_index=0)
+
 H0, H1, H2 = guan.get_onsite_and_hopping_terms_of_bhz_model(A=0.3645/5, B=-0.686/25, C=0, D=-0.512/25, M=-0.01, a=1)
 
 H0, H1, H2 = guan.get_onsite_and_hopping_terms_of_half_bhz_model_for_spin_up(A=0.3645/5, B=-0.686/25, C=0, D=-0.512/25, M=-0.01, a=1)
@@ -109,7 +111,7 @@ 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_graphene(k1, k2, M=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))
 
 hamiltonian = guan.effective_hamiltonian_of_graphene(qx, qy, t=1, staggered_potential=0, valley_index=0)
 
diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg
index b0b4028..26bf753 100644
--- a/PyPI/setup.cfg
+++ b/PyPI/setup.cfg
@@ -1,7 +1,7 @@
 [metadata]
 # replace with your username:
 name = guan
-version = 0.0.113
+version = 0.0.114
 author = guanjihuan
 author_email = guanjihuan@163.com
 description = An open source python package
diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py
index 91b58dd..550ce9e 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-0.0.113, updated on July 20, 2022.
+# The current version is guan-0.0.114, updated on July 20, 2022.
 
 # Installation: pip install --upgrade guan
 
@@ -345,9 +345,27 @@ def hamiltonian_of_finite_size_system_along_two_directions_for_graphene(N1, N2,
     hopping_1 = guan.get_hopping_term_of_graphene_ribbon_along_zigzag_direction(1)
     hopping_2 = np.zeros((4, 4), dtype=complex)
     hopping_2[3, 0] = 1
-    hamiltonian = guan.finite_size_along_two_directions_for_square_lattice(N1, N2, on_site, hopping_1, hopping_2, period_1, period_2)
+    hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(N1, N2, on_site, hopping_1, hopping_2, period_1, period_2)
     return hamiltonian
 
+def get_onsite_and_hopping_terms_of_2d_effective_graphene_along_one_direction(qy, t=1, staggered_potential=0, eta=0, valley_index=0):
+    constant = -np.sqrt(3)/2
+    h00 = np.zeros((2, 2), dtype=complex)
+    h00[0, 0] = staggered_potential
+    h00[1, 1] = -staggered_potential
+    h00[0, 1] = -1j*constant*t*np.sin(qy)
+    h00[1, 0] = 1j*constant*t*np.sin(qy)
+    h01 = np.zeros((2, 2), dtype=complex)
+    h01[0, 0] = eta
+    h01[1, 1] = eta
+    if valley_index == 0:
+        h01[0, 1] = constant*t*(-1j/2)
+        h01[1, 0] = constant*t*(-1j/2)
+    else:
+        h01[0, 1] = constant*t*(1j/2)
+        h01[1, 0] = constant*t*(1j/2)
+    return h00, h01
+
 def get_onsite_and_hopping_terms_of_bhz_model(A=0.3645/5, B=-0.686/25, C=0, D=-0.512/25, M=-0.01, a=1):
     E_s = C+M-4*(D+B)/(a**2)
     E_p = C-M-4*(D-B)/(a**2)
@@ -466,11 +484,11 @@ def hamiltonian_of_ssh_model(k, v=0.6, w=1):
     hamiltonian[1,0] = v+w*cmath.exp(1j*k)
     return hamiltonian
 
-def hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3)):
+def hamiltonian_of_graphene(k1, k2, staggered_potential=0, t=1, a=1/math.sqrt(3)):
     h0 = np.zeros((2, 2), dtype=complex)  # mass term
     h1 = np.zeros((2, 2), dtype=complex)  # nearest hopping
-    h0[0, 0] = M     
-    h0[1, 1] = -M
+    h0[0, 0] = staggered_potential     
+    h0[1, 1] = -staggered_potential
     h1[1, 0] = t*(cmath.exp(1j*k2*a)+cmath.exp(1j*math.sqrt(3)/2*k1*a-1j/2*k2*a)+cmath.exp(-1j*math.sqrt(3)/2*k1*a-1j/2*k2*a))   
     h1[0, 1] = h1[1, 0].conj()
     hamiltonian = h0 + h1