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0.0.114

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guanjihuan
2022-07-20 18:49:30 +08:00
parent 87ef3a433a
commit 327c06cd6b
3 changed files with 27 additions and 7 deletions
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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.
# 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