def excite_system(mesh):
sim = Sim(mesh, name='dyn')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.alpha = 0.04
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load('m0.npy'))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
D = 0.09
dmi = DMI(D)
sim.add(dmi)
zeeman = Zeeman([0, 0, 3.75e-3], name='H')
sim.add(zeeman)
w0 = 0.02
def time_fun(t):
return np.exp(-w0 * t)
hx = TimeZeeman([0, 0, 1e-5], sinc_fun, name='h')
sim.add(hx, save_field=True)
ts = np.linspace(0, 20000, 5001)
for t in ts:
sim.run_until(t)
print 'sim t=%g' % t
def excite_system(mesh):
sim = Sim(mesh, name='dyn', driver='sllg')
sim.set_options(dt=1e-14, gamma=const.gamma, k_B=const.k_B)
sim.driver.alpha = 0.1
sim.mu_s = const.mu_s_1
sim.T = temperature_gradient
sim.set_m(np.load("m0.npy"))
J = 50.0 * const.k_B
exch = UniformExchange(J)
sim.add(exch)
D = 0.5 * J
dmi = DMI(D)
sim.add(dmi)
Hz = 0.2 * J / const.mu_s_1
zeeman = Zeeman([0, 0, Hz])
sim.add(zeeman)
dt = 2e-14 * 50 # 1e-12
ts = np.linspace(0, 1000 * dt, 501)
for t in ts:
sim.run_until(t)
sim.save_vtk()
sim.save_m()
print 'sim t=%g' % t
def excite_system(mesh):
sim = Sim(mesh, name='dyn', driver='sllg')
sim.set_options(dt=1e-14, gamma=const.gamma, k_B=const.k_B)
sim.alpha = 0.1
sim.mu_s = const.mu_s_1
sim.T = temperature_gradient
sim.set_m(np.load("m0.npy"))
J = 50.0 * const.k_B
exch = UniformExchange(J)
sim.add(exch)
D = 0.5 * J
dmi = DMI(D)
sim.add(dmi)
Hz = 0.2 * J / const.mu_s_1
zeeman = Zeeman([0, 0, Hz])
sim.add(zeeman)
dt = 2e-14 * 50 # 1e-12
ts = np.linspace(0, 1000 * dt, 501)
for t in ts:
sim.run_until(t)
sim.save_vtk()
sim.save_m()
print 'sim t=%g' % t
def test_dynamic():
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='dyn_spin', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m((0.8,0,-1))
Kx = Anisotropy(Ku=-0.05, axis=(0, 0, 1), name='Kz')
sim.add(Kx)
sim.p = (0,0,1)
sim.a_J = 0.0052
sim.alpha = 0.1
ts = np.linspace(0, 1200, 401)
for t in ts:
sim.run_until(t)
mz = sim.spin[2]
alpha, K, u = 0.1, 0.05, 0.0052
print(mz, u/(2*alpha*K))
#########################################################
# The system used in this test can be solved analytically, which gives that mz = u/(2*alpha*K),
# where K represents the easy-plane anisotropy.
###
assert abs(mz - u/(2*alpha*K))/mz< 5e-4
def relax_system_stage2():
mesh = CuboidMesh(nx=140 , ny=140, nz=1)
sim = Sim(mesh, name='dyn', driver='llg')
sim.alpha = 0.1
sim.do_precession = True
sim.gamma = const.gamma
sim.mu_s = spatial_mu
sim.set_m(np.load('skx.npy'))
J = 50 * const.k_B
exch = UniformExchange(J)
sim.add(exch)
D = 0.27 * J
dmi = DMI(D)
sim.add(dmi)
zeeman = Zeeman(spatial_H)
sim.add(zeeman)
ts = np.linspace(0, 2e-9, 201)
for t in ts:
sim.run_until(t)
sim.save_vtk()
sim.save_m()
print(t)
def dynamic(mesh):
sim = Sim(mesh, name='dyn', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.driver.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load('m0.npy'))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
Kx = Anisotropy(Ku=0.005, axis=(1, 0, 0), name='Kx')
sim.add(Kx)
sim.p = (0, 0, 1)
sim.u0 = 0.03
sim.driver.alpha = 0.1
ts = np.linspace(0, 1e3, 101)
for t in ts:
sim.run_until(t)
sim.save_vtk()
print t
def excite_system(mesh, Hy=0):
sim = Sim(mesh, name='dyn')
sim.driver.set_tols(rtol=1e-10, atol=1e-12)
sim.driver.alpha = 0.04
sim.driver.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load('m0.npy'))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
D = 0.18
dmi = DMI(D)
sim.add(dmi)
zeeman = Zeeman([0, Hy, 2e-2], name='H')
sim.add(zeeman)
hx = TimeZeeman([0, 0, 1e-5], sinc_fun, name='h')
sim.add(hx, save_field=True)
dt = 5
steps = 2001
for i in range(steps):
sim.run_until(i * dt)
sim.save_m()
print("step {}/{}".format(i, steps))
def excite_system(mesh, Hy=0):
sim = Sim(mesh, name="dyn")
sim.set_options(rtol=1e-10, atol=1e-12)
sim.alpha = 0.04
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load("m0.npy"))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
D = 0.18
dmi = DMI(D)
sim.add(dmi)
zeeman = Zeeman([0, Hy, 2e-2], name="H")
sim.add(zeeman)
hx = TimeZeeman([0, 0, 1e-5], sinc_fun, name="h")
sim.add(hx, save_field=True)
dt = 5
steps = 2001
for i in range(steps):
sim.run_until(i * dt)
def excite_system(mesh):
sim = Sim(mesh, name='dyn')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.driver.alpha = 0.04
sim.driver.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load('m0.npy'))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
D = 0.09
dmi = DMI(D)
sim.add(dmi)
zeeman = Zeeman([0, 0, 3.75e-3], name='H')
sim.add(zeeman)
w0 = 0.02
def time_fun(t):
return np.exp(-w0 * t)
hx = TimeZeeman([0, 0, 1e-5], sinc_fun, name='h')
sim.add(hx, save_field=True)
ts = np.linspace(0, 20000, 5001)
for t in ts:
sim.run_until(t)
print 'sim t=%g' % t
def relax_system(mesh, Dx=0.005, Dp=0.01):
mat = UnitMaterial()
sim = Sim(mesh, name='test_energy')
print('Created sim')
sim.set_tols(rtol=1e-10, atol=1e-12)
sim.alpha = mat.alpha
sim.gamma = mat.gamma
sim.pins = pin_fun
exch = UniformExchange(mat.J)
sim.add(exch)
print('Added UniformExchange')
anis = Anisotropy(Dx, axis=[1, 0, 0], name='Dx')
sim.add(anis)
print('Added Anisotropy')
anis2 = Anisotropy([0, 0, -Dp], name='Dp')
sim.add(anis2)
print('Added Anisotropy 2')
sim.set_m((1, 1, 1))
T = 100
ts = np.linspace(0, T, 201)
for t in ts:
# sim.save_vtk()
sim.run_until(t)
print('Running -', t)
# sim.save_vtk()
np.save('m0.npy', sim.spin)
def dynamic(mesh):
sim = Sim(mesh, name='dyn', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m(np.load('m0.npy'))
J = 1.0
exch = UniformExchange(J)
sim.add(exch)
Kx = Anisotropy(Ku=0.005, axis=(1, 0, 0), name='Kx')
sim.add(Kx)
sim.p = (0,0,1)
sim.u0 = 0.03
sim.alpha = 0.1
ts = np.linspace(0, 1e3, 101)
for t in ts:
sim.run_until(t)
sim.save_vtk()
print t
def relax_system(mesh, Dx=0.005, Dp=0.01):
mat = UnitMaterial()
sim = Sim(mesh, name='test_energy')
sim.set_tols(rtol=1e-10, atol=1e-12)
sim.alpha = mat.alpha
sim.gamma = mat.gamma
sim.pins = pin_fun
exch = UniformExchange(mat.J)
sim.add(exch)
anis = Anisotropy(Dx, axis=[1, 0, 0], name='Dx')
sim.add(anis)
anis2 = Anisotropy([0, 0, -Dp], name='Dp')
sim.add(anis2)
sim.set_m((1, 1, 1))
T = 100
ts = np.linspace(0, T, 201)
for t in ts:
# sim.save_vtk()
sim.run_until(t)
# sim.save_vtk()
np.save('m0.npy', sim.spin)
def test_dynamic():
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='dyn_spin', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m((0.8, 0, -1))
Kx = Anisotropy(Ku=-0.05, axis=(0, 0, 1), name='Kz')
sim.add(Kx)
sim.p = (0, 0, 1)
sim.u0 = 0.0052
sim.alpha = 0.1
ts = np.linspace(0, 1200, 401)
for t in ts:
sim.run_until(t)
mz = sim.spin[2]
alpha, K, u = 0.1, 0.05, 0.0052
print mz, u / (2 * alpha * K)
#########################################################
# The system used in this test can be solved analytically, which gives that mz = u/(2*alpha*K),
# where K represents the easy-plane anisotropy.
###
assert abs(mz - u / (2 * alpha * K)) / mz < 5e-4
def excite_system(T=0.1, H=0.15):
mesh = CuboidMesh(nx=28 * 3, ny=16 * 5, nz=1, pbc='2d')
sim = Sim(mesh, name='dyn', driver='sllg')
sim.set_options(dt=1e-14, gamma=const.gamma, k_B=const.k_B)
sim.alpha = 0.1
sim.mu_s = const.mu_s_1
sim.set_m(random_m)
J = 50 * const.k_B
exch = UniformExchange(J)
sim.add(exch)
D = 0.5 * J
dmi = DMI(D)
sim.add(dmi)
Hz = H * J / const.mu_s_1
zeeman = Zeeman([0, 0, Hz])
sim.add(zeeman)
sim.T = J / const.k_B * T
ts = np.linspace(0, 5e-11, 51)
for t in ts:
sim.run_until(t)
# sim.save_vtk()
np.save('m.npy', sim.spin)
plot_m(mesh, 'm.npy', comp='z')
def test_sim_spins(do_plot=False):
mesh = CuboidMesh(nx=10, ny=5, nz=1)
sim = Sim(mesh, name='10spin')
alpha = 0.1
gamma = 2.21e5
sim.alpha = alpha
sim.gamma = gamma
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
print(sim.spin)
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-9, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
#print sim.t, abs(sim.spin_length()[0] - 1)
av = sim.compute_average()
mx.append(av[0])
my.append(av[1])
mz.append(av[2])
#sim.save_vtk()
mz = np.array(mz)
# print mz
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
print(sim.stat())
if do_plot:
plot(real_ts,
mx,
my,
mz,
a_mx,
a_my,
a_mz,
name='spins.pdf',
title='integrating spins')
print(("Max Deviation = {0}".format(np.max(np.abs(mz - a_mz)))))
assert np.max(np.abs(mz - a_mz)) < 5e-7
def test_sim_single_spin_sllg(do_plot=False):
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='spin', driver='sllg')
alpha = 0.1
gamma = 2.21e5
sim.set_options(dt=5e-15, gamma=gamma)
sim.alpha = alpha
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-10, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
print(sim.t, abs(sim.spin_length()[0] - 1))
mx.append(sim.spin[0])
my.append(sim.spin[1])
mz.append(sim.spin[2])
mz = np.array(mz)
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
if do_plot:
plot(real_ts,
mx,
my,
mz,
a_mx,
a_my,
a_mz,
name='spin_sllg.pdf',
title='integrating a spin')
print(("Max Deviation = {0}".format(np.max(np.abs(mz - a_mz)))))
assert np.max(np.abs(mz - a_mz)) < 1e-8
def test_sim_pin():
mesh = CuboidMesh(nx=3, ny=2, nz=1)
sim = Sim(mesh)
sim.set_m((0, 0.8, 0.6))
sim.alpha = 0.1
sim.gamma = 1.0
sim.pins = pin_fun
anis = Anisotropy(Ku=1.0, axis=[0, 0, 1], name='Dx')
sim.add(anis)
sim.run_until(1.0)
assert sim.spin[0] == 0
assert sim.spin[2] != 0
def test_sim_pin():
mesh = CuboidMesh(nx=3, ny=2, nz=1)
sim = Sim(mesh)
sim.set_m((0, 0.8, 0.6))
sim.alpha = 0.1
sim.gamma = 1.0
sim.pins = pin_fun
anis = Anisotropy(Ku=1.0, axis=[0, 0, 1], name='Dx')
sim.add(anis)
sim.run_until(1.0)
assert sim.spin[0] == 0
assert sim.spin[2] != 0
def test_sim_spins(do_plot=False):
mesh = CuboidMesh(nx=10, ny=5, nz=1)
sim = Sim(mesh, name='10spin')
alpha = 0.1
gamma = 2.21e5
sim.alpha = alpha
sim.gamma = gamma
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
print(sim.spin)
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-9, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
#print sim.t, abs(sim.spin_length()[0] - 1)
av = sim.compute_average()
mx.append(av[0])
my.append(av[1])
mz.append(av[2])
#sim.save_vtk()
mz = np.array(mz)
# print mz
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
print(sim.stat())
if do_plot:
plot(real_ts, mx, my, mz, a_mx, a_my, a_mz, name='spins.pdf', title='integrating spins')
print(("Max Deviation = {0}".format(
np.max(np.abs(mz - a_mz)))))
assert np.max(np.abs(mz - a_mz)) < 5e-7
def relax_system(rtol=1e-10, atol=1e-12):
"""numerical solution"""
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='relax')
sim.set_options(rtol=rtol, atol=atol)
sim.alpha = 0.5
sim.gamma = 2.21e5
sim.mu_s = 1.0
sim.set_m((1.0, 0, 0))
sim.add(Zeeman((0, 0, 1e5)))
ts = np.linspace(0, 1e-9, 1001)
for t in ts:
sim.run_until(t)
def disable_test_sim_single_spin_llg_stt(do_plot=False):
ni = Nickel()
mesh = CuboidMesh(nx=1, ny=1, nz=1)
mesh.set_material(ni)
ni.alpha = 0.1
sim = Sim(mesh, driver='llg_stt')
sim.set_m((1, 0, 0))
H0 = 1
sim.add(Zeeman((0, 0, H0)))
dt = 1e-12
ts = np.linspace(0, 200 * dt, 101)
precession = ni.gamma / (1 + ni.alpha**2)
mz_ref = []
mxyz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
print(sim.t, abs(sim.spin_length()[0] - 1), sim.spin)
mz_ref.append(np.tanh(precession * ni.alpha * H0 * sim.t))
mxyz.append(np.copy(sim.spin))
mxyz = np.array(mxyz)
if do_plot:
ts_ns = np.array(real_ts) * 1e9
plt.plot(ts_ns, mxyz[:, 0], ".-", label="mx")
plt.plot(ts_ns, mxyz[:, 1], ".-", label="my")
plt.plot(ts_ns, mxyz[:, 2], ".-", label="mz")
plt.plot(ts_ns, mz_ref, "-", label="analytical")
plt.xlabel("time (ns)")
plt.ylabel("mz")
plt.title("integrating a macrospin")
plt.legend()
plt.savefig("test_llg_stt.png")
print(("Deviation = {0}".format(np.max(np.abs(mxyz[:, 2] - mz_ref)))))
assert np.max(np.abs(mxyz[:, 2] - mz_ref)) < 1e-9
def relax_system(rtol=1e-10, atol=1e-12):
"""numerical solution"""
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name="relax")
sim.set_options(rtol=rtol, atol=atol)
sim.alpha = 0.5
sim.gamma = 2.21e5
sim.mu_s = 1.0
sim.set_m((1.0, 0, 0))
sim.add(Zeeman((0, 0, 1e5)))
ts = np.linspace(0, 1e-9, 1001)
for t in ts:
sim.run_until(t)
def disable_test_sim_single_spin_llg_stt(do_plot=False):
ni = Nickel()
mesh = CuboidMesh(nx=1, ny=1, nz=1)
mesh.set_material(ni)
ni.alpha = 0.1
sim = Sim(mesh, driver='llg_stt')
sim.set_m((1, 0, 0))
H0 = 1
sim.add(Zeeman((0, 0, H0)))
dt = 1e-12
ts = np.linspace(0, 200 * dt, 101)
precession = ni.gamma / (1 + ni.alpha**2)
mz_ref = []
mxyz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
print(sim.t, abs(sim.spin_length()[0] - 1), sim.spin)
mz_ref.append(np.tanh(precession * ni.alpha * H0 * sim.t))
mxyz.append(np.copy(sim.spin))
mxyz = np.array(mxyz)
if do_plot:
ts_ns = np.array(real_ts) * 1e9
plt.plot(ts_ns, mxyz[:, 0], ".-", label="mx")
plt.plot(ts_ns, mxyz[:, 1], ".-", label="my")
plt.plot(ts_ns, mxyz[:, 2], ".-", label="mz")
plt.plot(ts_ns, mz_ref, "-", label="analytical")
plt.xlabel("time (ns)")
plt.ylabel("mz")
plt.title("integrating a macrospin")
plt.legend()
plt.savefig("test_llg_stt.png")
print(("Deviation = {0}".format(np.max(np.abs(mxyz[:, 2] - mz_ref)))))
assert np.max(np.abs(mxyz[:, 2] - mz_ref)) < 1e-9
def test_sim_single_spin_sllg(do_plot=False):
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='spin', driver='sllg')
alpha = 0.1
gamma = 2.21e5
sim.set_options(dt=5e-15, gamma=gamma)
sim.alpha = alpha
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-10, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
print(sim.t, abs(sim.spin_length()[0] - 1))
mx.append(sim.spin[0])
my.append(sim.spin[1])
mz.append(sim.spin[2])
mz = np.array(mz)
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
if do_plot:
plot(real_ts, mx, my, mz, a_mx, a_my, a_mz, name='spin_sllg.pdf', title='integrating a spin')
print(("Max Deviation = {0}".format(
np.max(np.abs(mz - a_mz)))))
assert np.max(np.abs(mz - a_mz)) < 1e-8
def test_sim_single_spin_vode(do_plot=False):
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='spin')
alpha = 0.1
gamma = 2.21e5
sim.alpha = alpha
sim.gamma = gamma
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-9, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
#print sim.t, abs(sim.spin_length()[0] - 1)
mx.append(sim.spin[0])
my.append(sim.spin[1])
mz.append(sim.spin[2])
mz = np.array(mz)
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
print sim.stat()
if do_plot:
plot(real_ts, mx, my, mz, a_mx, a_my, a_mz)
print("Max Deviation = {0}".format(
np.max(np.abs(mz - a_mz))))
assert np.max(np.abs(mz - a_mz)) < 5e-7
def test_sim_single_spin_vode(do_plot=False):
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='spin')
alpha = 0.1
gamma = 2.21e5
sim.alpha = alpha
sim.gamma = gamma
sim.mu_s = 1.0
sim.set_m((1, 0, 0))
H0 = 1e5
sim.add(Zeeman((0, 0, H0)))
ts = np.linspace(0, 1e-9, 101)
mx = []
my = []
mz = []
real_ts = []
for t in ts:
sim.run_until(t)
real_ts.append(sim.t)
#print sim.t, abs(sim.spin_length()[0] - 1)
mx.append(sim.spin[0])
my.append(sim.spin[1])
mz.append(sim.spin[2])
mz = np.array(mz)
a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts)
print sim.stat()
if do_plot:
plot(real_ts, mx, my, mz, a_mx, a_my, a_mz)
print("Max Deviation = {0}".format(np.max(np.abs(mz - a_mz))))
assert np.max(np.abs(mz - a_mz)) < 5e-7
def dynamic(mesh):
sim = Sim(mesh, name='dyn_spin', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.driver.gamma = 1.0
sim.mu_s = 1.0
sim.set_m((0.8,0,-1))
Kx = Anisotropy(Ku=-0.05, axis=(0, 0, 1), name='Kz')
sim.add(Kx)
sim.p = (0,0,1)
sim.u0 = 0.005
sim.driver.alpha = 0.1
ts = np.linspace(0, 1200, 401)
for t in ts:
sim.run_until(t)
#sim.save_vtk()
print t
def relax_system(mesh):
sim = Sim(mesh, name='relax')
sim.alpha = 0.1
sim.set_m(init_m)
J = 1
exch = UniformExchange(J)
sim.add(exch)
dmi = DMI(0.05 * J)
sim.add(dmi)
ts = np.linspace(0, 1, 11)
for t in ts:
print t, sim.spin_length() - 1
sim.run_until(t)
sim.save_vtk()
return sim.spin
def dynamic(mesh):
sim = Sim(mesh, name='dyn_spin', driver='slonczewski')
# sim.set_options(rtol=1e-10,atol=1e-14)
sim.gamma = 1.0
sim.mu_s = 1.0
sim.set_m((0.8, 0, -1))
Kx = Anisotropy(Ku=-0.05, axis=(0, 0, 1), name='Kz')
sim.add(Kx)
sim.p = (0, 0, 1)
sim.u0 = 0.005
sim.alpha = 0.1
ts = np.linspace(0, 1200, 401)
for t in ts:
sim.run_until(t)
#sim.save_vtk()
print t
def relax_system(mesh):
sim = Sim(mesh, name='relax')
sim.alpha = 0.1
sim.set_m(init_m)
J = 1
exch = UniformExchange(J)
sim.add(exch)
dmi = DMI(0.05 * J)
sim.add(dmi)
ts = np.linspace(0, 1, 11)
for t in ts:
print t, sim.spin_length() - 1
sim.run_until(t)
sim.save_vtk()
return sim.spin
def single_spin(alpha=0.01):
mat = Material()
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, driver='sllg')
sim.alpha = alpha
sim.gamma = mat.gamma
sim.mu_s = mat.mu_s
sim.T = 10000
sim.set_m((1, 1, 1))
#sim.add(Zeeman(1,(0, 0, 1)))
anis = Anisotropy(mat.K, direction=(0, 0, 1))
sim.add(anis)
dt = 0.5e-12
ts = np.linspace(0, 1000 * dt, 1001)
sx = []
sy = []
for t in ts:
sim.run_until(t)
sx.append(sim.spin[0])
sy.append(sim.spin[1])
print(t)
plt.plot(sx, sy)
plt.xlabel("$S_x$")
plt.ylabel("$S_y$")
plt.grid()
plt.axis((-0.9, 0.9, -0.9, 0.9))
plt.axes().set_aspect('equal')
plt.savefig("macrospin.pdf")
def single_spin(alpha=0.01):
mat = Material()
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, driver='sllg')
sim.alpha = alpha
sim.gamma = mat.gamma
sim.mu_s = mat.mu_s
sim.T = 10000
sim.set_m((1, 1, 1))
#sim.add(Zeeman(1,(0, 0, 1)))
anis = Anisotropy(mat.K, direction=(0, 0, 1))
sim.add(anis)
dt = 0.5e-12
ts = np.linspace(0, 1000 * dt, 1001)
sx = []
sy = []
for t in ts:
sim.run_until(t)
sx.append(sim.spin[0])
sy.append(sim.spin[1])
print(t)
plt.plot(sx, sy)
plt.xlabel("$S_x$")
plt.ylabel("$S_y$")
plt.grid()
plt.axis((-0.9, 0.9, -0.9, 0.9))
plt.axes().set_aspect('equal')
plt.savefig("macrospin.pdf")
def relax_system(mesh):
sim = Sim(mesh, name='dmi_2d')
sim.driver.alpha = 0.1
sim.driver.gamma=1.76e11
sim.mu_s = 1e-22
J = 1e-20
exch = UniformExchange(J)
sim.add(exch)
dmi = DMI(0.1 * J)
sim.add(dmi)
sim.set_m(init_m)
ts = np.linspace(0, 5e-10, 101)
for t in ts:
print(t)
sim.run_until(t)
#sim.save_vtk()
return sim.spin
from fidimag.atomistic import Sim from fidimag.common.cuboid_mesh import CuboidMesh from fidimag.atomistic import UniformExchange, Zeeman from fidimag.atomistic import Constant # Import physical constants from fidimag const = Constant() mesh = CuboidMesh(nx=1, ny=1, dx=1, dy=1) sim = Sim(mesh, name='relax_sk') sim.gamma = const.gamma sim.set_m((1, 0, 0)) sim.add(Zeeman((0, 0, 25.))) sim.run_until(1e-11) sim.set_tols(rtol=1e-10, atol=1e-12) sim.run_until(2e-11)
# Interactive mode (this needs so set up a proper backend
# when importing matplotlib for the first time)
plt.ion()
# Set False to avoid the execution of the following code
plt.show(False)
# ---------------------------------------------------------------------
sim.save_vtk()
# Now run the simulation printing the energy
for time in times:
if not run_from_ipython():
print('Time: ', time, ' s')
print('Total energy: ', sim.compute_energy(), ' J')
print('\n')
sim.run_until(time)
# Update the vector data for the plot (the spins do not move
# so we don't need to update the coordinates) and redraw
m = np.copy(sim.spin)
# reshape rows, transpose and filter according to top layer
m = m.reshape(-1, 3)
quiv.set_UVC(m[:, 0], m[:, 1], m[:, 2])
# Update title
ttime.set_text('Time: {:.4f} ns'.format(time * 1e9))
tenergy.set_text('Energy: {:.6e} J'.format(sim.compute_energy()))
# fig.show()
fig.canvas.draw()
from fidimag.atomistic import Sim from fidimag.common.cuboid_mesh import CuboidMesh from fidimag.atomistic import UniformExchange, Zeeman import fidimag.common.constant as const mesh = CuboidMesh(nx=1, ny=1, dx=1, dy=1) sim = Sim(mesh, name='relax_sk') sim.gamma = const.gamma sim.set_m((1, 0, 0)) sim.add(Zeeman((0, 0, 25.))) sim.run_until(1e-11) sim.set_tols(rtol=1e-10, atol=1e-12) sim.run_until(2e-11)
