#axis.set_xlabel(r'$\frac{1}{T}$ $(\frac{1}{k})$')
axis.grid()
simDict = {
'tipPos': 0,
'Gs': 1.452e-7,
'G': 1.5e-9,
'u': 0,
'eta': 0,
}
for i, J in enumerate(J_list):
fourFe = Structure(atoms=[Fe1, Fe2, Fe2, Fe3],
JDict={
(0, 1): J,
(1, 2): J,
(2, 3): J
},
Bz=3)
lifeTimes = TemperatureVariation(fourFe, T_rangeShort,
**simDict).calcLifeTimesFullRates(V_bias)
dIdV1 = DIdV(fourFe, V_range, tipPos=0, T=1).getdIdV()
dIdV2 = DIdV(fourFe, V_range, tipPos=1, T=1).getdIdV()
ax[0].semilogy(1 / T_rangeShort,
2 / (lifeTimes[:, 0] + lifeTimes[:, 1]),
'--s',
label='J = ' + str(J),
markerfacecolor='none')
ax[1].plot(V_range / 1e-3,
dIdV1 / dIdV1[0],
Fe3 = Adatom(s=2,D=-2.1,E=0.311,g=2.11)
JList = np.linspace(0.05,0.1,2)
simDict = {'tipPos':0,'Gs':2.56e-7,'G':1.5e-9,'eta':0.5,'u':0.4}
fig,ax = plt.subplots(1,3,figsize=(12,4.5))
scaledtrans = transforms.ScaledTranslation(-0.55, -0.15, fig.dpi_scale_trans)
letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l']
for i,axis in enumerate(ax):
axis.text(0, 1, letters[i], fontsize=14, fontweight="bold", va="bottom", ha="left",
transform=axis.transAxes + scaledtrans)
for J in JList:
struct1 = Structure(atoms=[Fe1,Fe2,Fe2,Fe3,], JDict={(0,1):J,(1,2):J,(2,3):J},Bz = 0.2,)
struct2 = Structure(atoms=[Fe1,Fe2,Fe2,Fe3,], JDict={(0,1):J,(1,2):J,(2,3):J},Bz = 0.6,)
lifeTimes1 = TemperatureVariation(struct1,T_rangeShort,**simDict).calcLifeTimesFullRates(V_bias)
lifeTimes2 = TemperatureVariation(struct2,T_rangeShort,**simDict).calcLifeTimesFullRates(V_bias)
label1 = 'J = ' + ("%.2f" % J) + ', meV Bz = 0.2 T'
label2 = 'J = ' + ("%.2f" % J) + ', meV Bz = 0.6 T'
v1 = struct1.getEigenStates()
v2 = struct2.getEigenStates()
#w = struct.getEnergies()
print(label1)
print(getHigestProbabillity(v1[:,0],3,2))
print(label2)
print(getHigestProbabillity(v2[:,0],3,2))
avgLifetime1 = 2/(lifeTimes1[:,0]+lifeTimes1[:,1])
'tipPos': 0,
'Gs': 1.452e-7,
'G': 1.5e-9,
'u': 1,
},
{
'tipPos': 0,
'Gs': 1.452e-7,
'G': 1.5e-9,
'u': 0,
'b0': 0.75
},
]
for i, structDict in enumerate(structList):
struct = Structure(**structDict)
lifeTime = TemperatureVariation(
struct, T_rangeShort, **simList[0]).calcLifeTimesFullRates(V_bias)
ax[0].semilogy(1 / T_rangeShort,
2 / (lifeTime[:, 0] + lifeTime[:, 1]),
linestArray[i],
markerfacecolor='none')
struct = Structure(**structList[0])
for i, simDict in enumerate(simList):
lifeTime = TemperatureVariation(struct, T_rangeShort,
**simDict).calcLifeTimesFullRates(V_bias)
ax[1].semilogy(1 / T_rangeShort,
2 / (lifeTime[:, 0] + lifeTime[:, 1]),
linestArray[i],
from time import time
import matplotlib.pyplot as plt
import numpy as np
start = time()
Bloc_range = np.linspace(0, 2, 201)
J = 1.15
B = -1
V_bias = None
Fe1 = Adatom(s=2, D=-2.1, E=0.31, g=2.1)
Fe2 = Adatom(s=2, D=-3.6, E=0.31, g=2.1)
Fe3 = Adatom(s=2, D=-2.1, E=0.311, g=2.1)
trimer = Structure([Fe1, Fe2, Fe3], JDict={(0, 1): J, (1, 2): J}, Bz=B)
localField = LocalField(trimer,
Bloc_range,
tipPos=0,
u=0,
Gs=3.1e-6,
G=3e-9,
eta=0.2,
b0=0.5)
Neelprob, T1 = localField.calcNeelProb(V_bias)
fig, ax = plt.subplots(2, 1, sharex=True, figsize=(8, 6))
ax[0].semilogy(Bloc_range, Neelprob.T)
ax[1].plot(Bloc_range, T1 / 1e-6)
extremeB = np.zeros((len(JList), 2))
for i, J4 in enumerate(JList):
tempDict = {
'atoms': [Fe1, Fe2, Fe3, Fe4],
'JDict': {
(0, 1): J4,
(1, 2): J4,
(2, 3): J4
},
'Bz': 0.1
}
for j, B in enumerate(BList):
tempDict[FielDir] = B
struct = Structure(**tempDict)
v = struct.getEigenStates()
print(getHigestProbabillity(v[:, 0], 3, 2))
lifetimes[0,
j, :] = Measurement(struct,
**simDict).calcLifeTimesFullRates(V_bias)
avgLifetime = (lifetimes[0, :, 0] + lifetimes[0, :, 0]) / 2
extremeB[i, 0] = BList[np.argmin((avgLifetime))]
label = 'J= ' + ("%.2f" % J4) + ' meV'
if (i == 1 or i == 4 or i == 6):
#plt.figure()
#plt.title(label)
ax[0].semilogy(BList,
#]
fig, ax = plt.subplots(
3,
1,
figsize=(5, 10),
)
lifetimes = np.zeros((len(simList), len(valuesDict[magDir]), n))
overlap = np.zeros(len(valuesDict[magDir]))
dE = np.zeros((len(valuesDict[magDir]), 5), dtype=complex)
for key in valuesDict.keys():
for j, value in enumerate(valuesDict[key]):
tempDict = structDict.copy()
tempDict[key] = value
struct = Structure(**tempDict)
v = struct.getEigenStates()
w = struct.getEnergies()
overlap[j] = np.sum(np.abs(v[:, 0] * v[:, 1])**2)
dE[j, :] = (w[0:5] - w[0]) / meV
print(getHigestProbabillity(v[:, 0], 3, 2))
for i, simDict in enumerate(simList):
lifetimes[i, j, :] = Measurement(
struct, **simDict).calcLifeTimesFullRates(V_bias)
ax[0].semilogy(valuesDict[key],
lifetimes[0, :, 0],
'--sC0',
label=r'$\phi_0 \to \phi_1$',
markerfacecolor='none')
ax[0].semilogy(valuesDict[key],
J = 0.7
valueDict = {'k': np.arange(5, 400, 10)}
simDict = {'tipPos': 0, 'Gs': 2.56e-6, 'G': 1.5e-9, 'eta': 0, 'u': 0}
structDict = {
'atoms': [Fe1, Fe2, Fe2, Fe3],
'JDict': {
(0, 1): J,
(1, 2): J,
(2, 3): J
},
'Bz': 3,
}
fourFe1 = Structure(**structDict)
fourFe2 = BigStructure(**structDict, n=5, k=625)
fourFe3 = BigStructure(**structDict, n=5, k=10)
lifeTimes1 = TemperatureVariation(fourFe1, T_rangeShort,
**simDict).calcLifeTimesFullRates(V_bias)
lifeTimes2 = TemperatureVariation(fourFe2, T_rangeShort,
**simDict).calcLifeTimesFullRates(V_bias)
lifeTimes3 = TemperatureVariation(fourFe3, T_rangeShort,
**simDict).calcLifeTimesFullRates(V_bias)
avgLifetime1 = 2 / (lifeTimes1[:, 0] + lifeTimes1[:, 1])
for key in valueDict.keys():
error = np.zeros((3, len(valueDict[key])))
for j, value in enumerate(valueDict[key]):
#fig,ax = plt.subplots(1,2,figsize=(10,6))
fig1, ax1 = plt.subplots(1, 1)
maxPoint = np.zeros(len(BzList))
for J in JList:
#fig,ax = plt.subplots(1,2,figsize=(10,6))
for i, Bz in enumerate(BzList):
struct = Structure(
atoms=[
Fe1,
Fe2,
Fe2,
Fe4,
],
JDict={
(0, 1): J,
(1, 2): J,
(2, 3): J
},
Bz=Bz,
)
lifeTimes4 = TemperatureVariation(
struct, T_rangeShort, **simDict).calcLifeTimesFullRates(V_bias)
v = struct.getEigenStates()
w = struct.getEnergies()
label = ("Bz = %.2f" % Bz)
print(label)
print(getHigestProbabillity(v[:, 0], 3, 2))
print(getHigestProbabillity(v[:, 1], 3, 2))
"""
from FunctionsSpinHam import Adatom, Structure, DIdV
import matplotlib.pyplot as plt
import numpy as np
Fe1 = Adatom(s=2, D=-2.1, E=0.31, g=2.11)
Fe2 = Adatom(s=2, D=-3.6, E=0.31, g=2.11)
Fe3 = Adatom(s=2, D=-2.1, E=0.311, g=2.11)
Nv = 201
V_range = np.linspace(-0.03, 0.03, Nv)
vPoints = [-14.5, -8.5, 8.5, 14.5]
monomer = Structure(atoms=[Fe1, Fe2, Fe3],
JDict={
(0, 1): 1.15,
(1, 2): 1.15
},
Bz=2)
mV = 0.001
mu = 1e-6
f, ax = plt.subplots(1, 1, sharex=True, figsize=(8, 4))
for i in range(len(monomer.atoms)):
dIdV1 = DIdV(structure=monomer,
tipPos=i,
T=0.5,
V_range=V_range,
u=0.5,
eta=0,
G=2 / 3e7,