H_norms = [0.05, 0.1, [], 1.0, 1.1, [], 2.0, 2.2, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [], 5.0]
# Selected norms for the second part of the simulation
H_norms = [0]
selected_H_norms = [0.5, 1.0, 1.5, 2.0, 3.0, 3.2, [], 5.0]
selected_H_norms = [0]
H_scale = 1
H_norms = sets.float_set(H_norms, H_scale)
selected_H_norms = sets.float_set(selected_H_norms, H_scale)
H_unit = T/mu0 # The unit for these values is T (Tesla)
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=H_direction,
norm_list=H_norms)
# A small deviation to avoid points of unstable equilibrium
H_dev = [0.0001, 0.0001, 0.0001]
new_Hs = []
for H in Hs:
new_Hs.append([Hi+H_devi for Hi, H_devi in zip(H, H_dev)])
new_Hs.append(H)
Hs = new_Hs
#--------------------------------------------
## Aux. functions
# This function returns a function to set the external field
# We need this because the field acting on iron will be higher
# at borders (non uniform in space).
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [],
5.0, 5.5, [], 12.0])
selected_B_norms = \
sets.float_set([0.0, 0.5, [], 3.5, 3.8, 3.9, 4.0, 4.1, 4.5, 5.0, [], 12.0])
delta_B = [0.002, 0.002, 0.002] # Tilt vector in T
#tilted_B_norms = [B_norm + delta_B for B_norm in B_norms]
#selected_B_norms = [B_norm + delta_B for B_norm in selected_B_norms]
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = []
delta_H = [dBi*B_unit/mu0 for dBi in delta_B]
for H in sets.vector_set(direction=B_direction,
norm_list=B_norms,
units=B_unit/mu0): # remember that H = B/mu0
Hs.append([Hi + dHi for Hi, dHi in zip(H, delta_H)])
Hs.append(H)
#--------------------------------------------
## Determine if we should run the pre simulation or the post simulation
# First we determine for what stages we have to compute the dynamics
i = 0
j = 1
selected_stages = []
for B_norm in B_norms:
selected_B_norm = selected_B_norms[i]
if abs(B_norm - selected_B_norm) < 1e-5:
#The list of values taken by the norm of the applied field
H_norms = [0.05, 0.1, [], 1.0, 1.1, [], 2.0, 2.2, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [],
5.0, 5.5, [], 8.0]
selected_H_norms = [3.6, 4.0, 4.2]
H_norms = sets.float_set(H_norms, H_scale)
selected_H_norms = sets.float_set(selected_H_norms, H_scale)
#print H_norms[32]
#sys.exit(0)
H_unit = T/mu0 # The unit for these values is T (Tesla)
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=H_direction,
norm_list=H_norms)
# A small deviation to avoid points of unstable equilibrium
H_dev = [0.0001, 0, 0.0001]
Hs = [[Hi+H_devi for Hi, H_devi in zip(H, H_dev)]
for H in Hs]
H_pinning_norm = -10.0
H_pinning, = sets.vector_set(direction=H_direction,
norm_list=[H_pinning_norm])
#--------------------------------------------
## The current density for spin-torque calculations
j = [SI(4e12, "A/m^2"), 0.0, 0.0]
exchange_coupling = SI(13.0e-12, "J/m") # Exchange coupling constant
m_sat = SI(0.86e6, "A/m") # Saturation magnetisation
#--------------------------------------------
## The initial configuration and how the applied field should change
m0 = [1, 0, 1] # Initial direction for the magnetisation
H_direction = [1, 1, 1] # The direction of the applied field
#The list of values taken by the norm of the applied field
H_norms = [10.0, 9.5, [], -10.0]
H_unit = SI(1e6, "A/m") # The unit for these values
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=H_direction, norm_list=H_norms, units=H_unit)
#--------------------------------------------
## Here we set up the simulation
# Create the material
mat_Py = nmag.MagMaterial(
name="Py",
Ms=m_sat,
exchange_coupling=exchange_coupling,
anisotropy=nmag.uniaxial_anisotropy(
axis=[1,0,0],
K1=SI(5e6, "J/m^3")),
llg_gamma_G=SI(0.2211e6, "m/A s"),
llg_damping=SI(0.5),
llg_normalisationfactor=SI(0.001e12, "1/s"))
)
mesh_name = "uniaxial_1d"
mesh_unit = SI(1e-9, "m")
layers = [(-10.0, 10.0)]
discretization = 1.0
new_mesh = True
# --------------------------------------------
## The initial configuration and how the applied field should change
m0 = [1, 0, 1] # Initial direction for the magnetisation
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=[1, -2, 3], norm_list=[-3.0, [200], 3.0], units=SI(1e6, "A/m"))
# --------------------------------------------
## Here we set up the simulation
# Create the simulation object
sim = nmag.Simulation("uniaxial_1d", do_demag=False)
# Creates the mesh from the layer structure
mesh_file_name = "%s.nmesh" % mesh_name
if not os.path.exists(mesh_file_name) or new_mesh:
print "Creating the mesh"
mesh_lists = unidmesher.mesh_1d(layers, discretization)
unidmesher.write_mesh(mesh_lists, out=mesh_file_name)
# Load the mesh
# The list of values taken by the norm of the applied field
H_norms = [0.6, 0.4,
0.2, 0.16, "...",
0, -0.005, "...",
-0.045, -0.0455, "...", # should contain Hc: we map it better!
-0.058] #, -0.065, "...", -0.2]
#H_norms = [0.6, 0.594186, "...", -0.2] # For now we stick at what we do with magpar
# The direction of the applied field
H_direction = [1, 1, 1]
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
# Note we express all in terms of the saturation magnetisation.
Hs = sets.vector_set(direction=H_direction, norm_list=H_norms,
units=material.m_sat)
# Initial magnetisation
def m0((x, y, z), mag_type):
import math
x = 1.0/math.sqrt(3)
return [x, x, x]
def out(line, header=False, file="dyn.dat"):
import os
if header and os.path.exists(file): return
f = open(file, "a")
f.write(line)
f.close()
out("# d/l_ex Hc/Ms Mr_x/Ms Mr_y/Ms\n", header=True)
B_norms = \
sets.float_set([0.0, 0.1, [], 2.0, 2.25, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [],
5.0, 5.5, [], 12.0])
selected_B_norms = \
sets.float_set([0.0, 0.5, [], 3.5, 3.8, 3.9, 4.0, 4.1, 4.5, 5.0, [], 12.0])
delta_B = 0.01 # Tilt amplitude used to induce oscillations
tilted_B_norms = [B_norm + delta_B for B_norm in B_norms]
selected_B_norms = [B_norm + delta_B for B_norm in selected_B_norms]
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=B_direction,
norm_list=B_norms,
units=B_unit/mu0) # remember that H = B/mu0
Hs_tilted = sets.vector_set(direction=B_direction,
norm_list=tilted_B_norms,
units=B_unit/mu0)
# A small deviation to avoid points of unstable equilibrium
H_dev = [SI(0.005e6, "A/m"), SI(0.005e6, "A/m"), 0]
Hs = [[Hi+H_devi for Hi, H_devi in zip(H, H_dev)]
for H in Hs]
Hs_tilted = [[Hi+H_devi for Hi, H_devi in zip(H, H_dev)]
for H in Hs_tilted]
#--------------------------------------------
## The current density for spin-torque calculations
return directions['m_Fe3O4']
def m0_CoFe2O4(r):
return directions['m_CoFe2O4']
# The direction of the applied field
B_direction = [0.0, 1.0, 0.0]
#The list of values taken by the norm of the applied field
B_norms = [-5.0, -4.9, [], 5.0]
B_unit = Tesla # The unit for these values
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=B_direction,
norm_list=sets.float_set(B_norms),
units=B_unit/mu0) # remember that H = B/mu0
# A small deviation to avoid points of unstable equilibrium
H_dev = [SI(0.005e6, "A/m")]*3
Hs = [[Hi+H_devi for Hi, H_devi in zip(H, H_dev)]
for H in Hs]
#--------------------------------------------
## Here we set up the simulation
# Create the simulation object
sim = nmag.Simulation("run", do_demag=False, adjust_tolerances=False)
# Set the coupling between the two magnetisations
Fe3O4_CoFe2O4_lc = Fe3O4_CoFe2O4_sup_lc*mesh_unit*discretization
