#STM simulation
tip = GPAW('tip')
srf = GPAW('srf')
h0, s0 = pickle.load(open('lead_hs.pckl'))
h1, s1 = pickle.load(open('tip_hs.pckl'))
h2, s2 = pickle.load(open('srf_hs.pckl'))
assert abs(h0.imag).max() < 1e-14
assert abs(s0.imag).max() < 1e-14
h0 = h0.real
s0 = h0.real
stm = STM(tip, srf,
hs10=(h0[0], s0[0]),
hs1=(h1[0], s1[0]),
hs2=(h2[0], s2[0]),
hs20=(h0[0], s0[0]),
align_bf=0)
stm.set(dmin=5)
stm.initialize()
stm.scan()
stm.linescan()
if 0:
stm.plot(repeat=[3, 3])
energy_tolerance = 0.0003
niter_tolerance = 0
equal(e1, -5.29095, energy_tolerance)
niter3 = calc.get_number_of_iterations()
calc.write('srf.gpw', region='surface', cvl=2)
dump_hs(calc, 'srf', region='surface', cvl=2)
#STM simulation
tip = GPAW('tip')
srf = GPAW('srf')
h0, s0 = pickle.load(open('lead_hs.pckl'))
h1, s1 = pickle.load(open('tip_hs.pckl'))
h2, s2 = pickle.load(open('srf_hs.pckl'))
stm = STM(tip,
srf,
hs10=(h0[0], s0[0]),
hs1=(h1[0], s1[0]),
hs2=(h2[0], s2[0]),
hs20=(h0[0], s0[0]),
align_bf=0)
stm.set(dmin=5)
stm.initialize()
stm.scan()
stm.linescan()
if 0:
stm.plot(repeat=[3, 3])
energy_tolerance = 0.0003
niter_tolerance = 0
# tip data
tip = GPAW('tip', txt=None)
h1, s1 = pickle.load(open('tip_hs.pckl')) # h and s matrix
h10, s10 = pickle.load(open('tip_p_hs.pckl')) #principal layer h and s matrix
# surface data
srf = GPAW('srf', txt=None)
h2, s2 = pickle.load(open('srf_hs.pckl'))
h20, s20 = pickle.load(open('srf_p_hs.pckl'))
# set up the stm-calculator
stm = STM(tip, srf,
hs1=(h1[0], s1[0]), # tip
hs10=(h10[0], s10[0]), # tip principal layer
hs2=(h2[0], s2[0]), # surface
hs20=(h20[0], s20[0]), # surface principal layer
bias = 0.05, # bias
de = 0.05/7., # spacing of the energy grid at which the
# Green's functions should be evaluated
logfile='scan.log')
stm.set(dmin=6) # set tip to surface distance
stm.initialize()
stm.scan()
stm.linescan([[0, 0], [27, 27]]) # linescan along the [111] direction
# plot the current map and the linescan
stm.plot(label='I[nA]')
tip = GPAW('tip', txt=None)
h1, s1 = pickle.load(open('tip_hs.pckl')) # h and s matrix
h10, s10 = pickle.load(open('tip_p_hs.pckl')) #principal layer h and s matrix
# surface data
srf = GPAW('srf', txt=None)
h2, s2 = pickle.load(open('srf_hs.pckl'))
h20, s20 = pickle.load(open('srf_p_hs.pckl'))
# set up the stm-calculator
stm = STM(
tip,
srf,
hs1=(h1[0], s1[0]), # tip
hs10=(h10[0], s10[0]), # tip principal layer
hs2=(h2[0], s2[0]), # surface
hs20=(h20[0], s20[0]), # surface principal layer
bias=0.05, # bias
de=0.05 / 7., # spacing of the energy grid at which the
# Green's functions should be evaluated
logfile='scan.log')
stm.set(dmin=6) # set tip to surface distance
stm.initialize()
stm.scan()
stm.linescan([[0, 0], [27, 27]]) # linescan along the [111] direction
# plot the current map and the linescan
stm.plot(label='I[nA]')