Exemplo n.º 1
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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
Exemplo n.º 2
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def test_exch_3d():
    """
    Test the exchange field of the spins in this 3D mesh:

    bottom layer:
    8  9  10  11
    4  5  6   7       x 2
    0  1  2   3

    The assertions are the mx component
    of the: 0, 1, 2, .. 7 spins

    Remember the new new ordering: fx1, fy1, fz1, fx2, ...

    """
    mesh = CuboidMesh(nx=4, ny=3, nz=2)
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()
    # print field
    assert field[0] == 1
    assert field[3] == 0 + 1 + 2 + 1
    assert field[6] == 1 + 2 + 3 + 2
    assert field[9] == 2 + 3 + 3

    assert field[4 * 3] == 1
    assert field[5 * 3] == 5
    assert field[6 * 3] == 10
    assert field[7 * 3] == 11
Exemplo n.º 3
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def relax_system(mesh):

    # Only relaxation
    sim = Sim(mesh, name='relax')

    # Simulation parameters
    sim.driver.set_tols(rtol=1e-8, atol=1e-10)
    sim.alpha = 0.5
    sim.driver.gamma = 2.211e5 / mu0
    sim.mu_s = 1e-27 / mu0
    sim.driver.do_precession = False

    # The initial state passed as a function
    sim.set_m(init_m)
    # sim.set_m(np.load('m0.npy'))

    # Energies
    exch = UniformExchange(J=2e-20)
    sim.add(exch)

    anis = Anisotropy(0.01 * 2e-20, axis=(0, 0, 1))
    sim.add(anis)

    # dmi = DMI(D=8e-4)
    # sim.add(dmi)

    # Start relaxation and save the state in m0.npy
    sim.relax(dt=1e-14,
              stopping_dmdt=1e4,
              max_steps=5000,
              save_m_steps=None,
              save_vtk_steps=None)

    np.save('m0.npy', sim.spin)
Exemplo n.º 4
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def test_skx_num():

    mesh = CuboidMesh(nx=120, ny=120, nz=1, periodicity=(True, True, False))

    sim = Sim(mesh, name='skx_num')
    sim.set_tols(rtol=1e-6, atol=1e-6)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)

    sim.do_procession = False

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 5e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0,
              stopping_dmdt=1e-2,
              max_steps=1000,
              save_m_steps=None,
              save_vtk_steps=None)

    skn = sim.skyrmion_number()
    print 'skx_number', skn
    assert skn > -1 and skn < -0.99
Exemplo n.º 5
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def test_exch_2d_pbc2d():
    """
    Test the exchange field components in a 2D mesh with PBCs
    The mesh sites:

            3     4     5    -->    (0,1,0)  (1,1,0)  (2,1,0)
     y ^    0     1     2           (0,0,0)  (1,0,0)  (2,0,0)
       |
       x -->

    The expected components are in increasing order along x

    """

    mesh = CuboidMesh(nx=3, ny=2, nz=1, periodicity=(True, True, False))
    print mesh.neighbours
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()

    expected_x = np.array([3, 4, 5, 3, 4, 5])
    expected_y = np.array([2, 2, 2, 2, 2, 2])

    # Since the field ordering is now: fx1 fy1 fz1 fx2 ...
    # We extract the x components jumping in steps of 3
    assert np.max(abs(field[::3] - expected_x)) == 0
    # For the y component is similar, now we start at the 1th
    # entry and jump in steps of 3
    assert np.max(abs(field[1::3] - expected_y)) == 0
    # Similar fot he z component
    assert np.max(field[2::3]) == 0
Exemplo n.º 6
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def test_exch_1d():
    """
    Test the x component of the exchange field
    in a 1D mesh, with the spin ordering:

    0 1 2 3 4 5

    """
    mesh = CuboidMesh(nx=5, ny=1, nz=1)
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()

    assert field[0] == 1
    assert field[1 * 3] == 2
    assert field[2 * 3] == 4
    assert field[3 * 3] == 6
    assert field[4 * 3] == 3

    assert np.max(field[2::3]) == 0
    assert np.max(field[1::3]) == 0
Exemplo n.º 7
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def relax_system_stage1():

    mesh = CuboidMesh(nx=140 , ny=140, nz=1)

    sim = Sim(mesh, name='relax', driver='llg')
    #sim.set_options(dt=1e-14, gamma=const.gamma, k_B=const.k_B)
    sim.alpha = 0.5
    sim.do_precession = False
    sim.gamma = const.gamma
    sim.mu_s = spatial_mu

    sim.set_m(init_m)

    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)

    sim.relax(dt=1e-14, stopping_dmdt=1e10, max_steps=1000,
              save_m_steps=100, save_vtk_steps=10)

    np.save('skx.npy', sim.spin)
    plot_m(mesh, 'skx.npy', comp='z')
Exemplo n.º 8
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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
Exemplo n.º 9
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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')
Exemplo n.º 10
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    # sim.set_options(rtol=1e-10,atol=1e-14)
    sim.driver.alpha = 1.0
    sim.driver.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)
    # sim.set_m(random_m)
    # sim.set_m(np.load('m_10000.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])
    sim.add(zeeman)

    sim.relax(dt=2.0,
              stopping_dmdt=1e-6,
              max_steps=1000,
              save_m_steps=100,
              save_vtk_steps=50)

    np.save('m0.npy', sim.spin)
Exemplo n.º 11
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.set_options(rtol=1e-12, atol=1e-14)
    sim.do_procession = False
    sim.alpha = 0.5
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.18
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0e-3, 2e-2], name='H')
    sim.add(zeeman)

    sim.relax(dt=2.0,
              stopping_dmdt=1e-8,
              max_steps=10000,
              save_m_steps=None,
              save_vtk_steps=100)

    np.save('m0.npy', sim.spin)
Exemplo n.º 12
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def relax_system(mesh, Hy=0):

    sim = Sim(mesh, name='relax')
    sim.driver.set_tols(rtol=1e-10, atol=1e-12)
    sim.driver.alpha = 0.5
    sim.driver.gamma = 1.0
    sim.mu_s = 1.0

    sim.do_precession = False

    sim.set_m(init_m)
    #sim.set_m(random_m)
    #sim.set_m(np.load('m_10000.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)

    sim.relax(dt=2.0,
              stopping_dmdt=1e-7,
              max_steps=10000,
              save_m_steps=100,
              save_vtk_steps=50)

    np.save('m0.npy', sim.spin)
Exemplo n.º 13
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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))
Exemplo n.º 14
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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
Exemplo n.º 15
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    # sim.set_options(rtol=1e-10,atol=1e-14)
    sim.driver.alpha = 1.0
    sim.driver.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)
    # sim.set_m(random_m)
    # sim.set_m(np.load('m_10000.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.relax(dt=2.0,
              stopping_dmdt=1e-6,
              max_steps=1000,
              save_m_steps=100,
              save_vtk_steps=50)

    np.save('m0.npy', sim.spin)
Exemplo n.º 16
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def relax_system(mesh, Dx=0.005, Dp=0.01):

    mat = UnitMaterial()

    sim = Sim(mesh, name='test_energy')
    print('Created sim')
    sim.driver.set_tols(rtol=1e-10, atol=1e-12)

    sim.alpha = mat.alpha
    sim.driver.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.driver.run_until(t)
        print(('Running -', t))

    # sim.save_vtk()
    np.save('m0.npy', sim.spin)
Exemplo n.º 17
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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)
Exemplo n.º 18
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=const.gamma)
    sim.alpha = 0.5
    sim.mu_s = const.mu_s_1

    sim.set_m(init_m)

    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)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13, stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000, save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)
Exemplo n.º 19
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def test_exch_3d():
    """
    Test the exchange field of the spins in this 3D mesh:

    bottom layer:
    8  9  10  11
    4  5  6   7       x 2
    0  1  2   3

    Assertions are according to the mx component of the spins, since J is set
    to 1


    Spin components are given according to the (i, j) index position in the
    lattice:

           i                lattice site
        [[ 0.  0.  0.]  --> 0    j=0
         [ 1.  0.  0.]  --> 1
         [ 2.  0.  0.]  --> 2
         [ 3.  0.  0.]  --> 3
         [ 0.  1.  0.]  --> 4    j=1
         [ 1.  1.  0.]
         ...

    Remember the field ordering: fx0, fy0, fz0, fx1, ...

    """
    mesh = CuboidMesh(nx=4, ny=3, nz=2)
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()
    # print field

    # Exchange from 0th spin
    assert field[0] == 1

    # Exchange from 1st spin
    #            spin: 2   0   5   13
    #              mx: 2   0   1   1
    assert field[3] == 2 + 0 + 1 + 1

    # Exchange from 2nd spin
    #            spin: 3   1   6   14
    #              mx: 3   1   2   2
    assert field[6] == 3 + 1 + 2 + 2

    # ...
    assert field[9] == 2 + 3 + 3

    assert field[4 * 3] == 1
    assert field[5 * 3] == 5
    assert field[6 * 3] == 10
    assert field[7 * 3] == 11
Exemplo n.º 20
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def test_exch_energy_1d():
    mesh = CuboidMesh(nx=2, ny=1, nz=1)
    sim = Sim(mesh)
    exch = UniformExchange(1.23)
    sim.add(exch)

    sim.set_m((0, 0, 1))

    energy = exch.compute_energy()
    assert energy == -1.23
Exemplo n.º 21
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def relax_neb(k, maxst, simname, init_im, interp, save_every=10000):
    """
    Execute a simulation with the NEB function of the FIDIMAG code

    The simulations are made for a specific spring constant 'k' (a float),
    number of images 'init_im', interpolations between images 'interp'
    (an array) and a maximum of 'maxst' steps.
    'simname' is the name of the simulation, to distinguish the
    output files.

    --> vtks and npys are saved in files starting with the 'simname' string

    """

    # Prepare simulation
    sim = Sim(mesh, name=simname)
    sim.driver.gamma = const.gamma

    # magnetisation in units of Bohr's magneton
    sim.mu_s = 2. * const.mu_B

    # Exchange constant in Joules: E = Sum J_{ij} S_i S_j
    J = 12. * const.meV
    exch = UniformExchange(J)
    sim.add(exch)

    # DMI constant in Joules: E = Sum D_{ij} S_i x S_j
    D = 2. * const.meV
    dmi = DMI(D, dmi_type='interfacial')
    sim.add(dmi)

    # Anisotropy along +z axis
    ku = Anisotropy(Ku=0.5 * const.meV, axis=[0, 0, 1], name='ku')
    sim.add(ku)

    # Initial images
    init_images = init_im

    # Number of images between each state specified before (here we need only
    # two, one for the states between the initial and intermediate state
    # and another one for the images between the intermediate and final
    # states). Thus, the number of interpolations must always be
    # equal to 'the number of initial states specified', minus one.
    interpolations = interp

    neb = NEB_Sundials(sim,
                       init_images,
                       interpolations=interpolations,
                       spring=k,
                       name=simname)

    neb.relax(max_steps=maxst,
              save_vtk_steps=save_every,
              save_npy_steps=save_every,
              stopping_dmdt=1e-2)
Exemplo n.º 22
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def test_skx_num_atomistic():
    """
    Test the *finite spin chirality* or skyrmion number for
    a discrete spins simulation in a two dimensional lattice

    The expression is (PRL 108, 017601 (2012)) :

    Q =     S_i \dot ( S_{i+1}  X  S_{j+1} )
         +  S_i \dot ( S_{i-1}  X  S_{j-1} )

    which measures the chirality taking two triangles of spins
    per lattice site i:
        S_{i} , S_{i + x} , S_{i + y}    and
        S_{i} , S_{i - x} , S_{i - y}

    The area of the two triangles cover a unit cell, thus the sum
    cover the whole area of the atomic lattice

    This test generate a skyrmion pointing down with unrealistic
    paremeters.

    """

    mesh = CuboidMesh(nx=120, ny=120, nz=1,
                      periodicity=(True, True, False))

    sim = Sim(mesh, name='skx_num')
    sim.set_tols(rtol=1e-6, atol=1e-6)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(lambda pos: init_m(pos, 60, 60, 20))

    sim.do_precession = False

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 5e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-2, max_steps=1000,
              save_m_steps=None, save_vtk_steps=None)

    skn = sim.skyrmion_number()
    print('skx_number', skn)
    assert skn > -1 and skn < -0.99
Exemplo n.º 23
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def relax_system():

    # 1D chain of 50 spins with a lattice constant of 0.27 A
    mesh = CuboidMesh(
        nx=nx,
        dx=dx,
        unit_length=1e-9,
        # pbc='1d'
    )

    # Initiate the simulation
    sim = Sim(mesh, name=sim_name)
    sim.gamma = const.gamma

    # magnetisation in units of Bohr's magneton
    sim.mu_s = 2 * const.mu_B

    # sim.set_options(gamma=const.gamma, k_B=const.k_B)

    # Initial magnetisation profile
    sim.set_m(init_m)

    # Exchange constant in Joules: E = Sum J_{ij} S_i S_j
    J = 12. * const.meV
    exch = UniformExchange(J)
    sim.add(exch)

    # DMI constant in Joules: E = Sum D_{ij} S_i x S_j
    D = 2. * const.meV
    dmi = DMI(D, dmi_type='interfacial')
    sim.add(dmi)

    # Anisotropy along +z axis
    ku = Anisotropy(Ku=0.5 * const.meV, axis=[0, 0, 1], name='ku')
    sim.add(ku)

    # Faster convergence
    sim.alpha = 0.5
    sim.do_precession = False

    sim.relax(dt=1e-13,
              stopping_dmdt=0.05,
              max_steps=700,
              save_m_steps=1000,
              save_vtk_steps=1000)

    # Save the last relaxed state
    np.save(sim_name + '.npy', sim.spin)
Exemplo n.º 24
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def test_exch_1d_pbc():
    mesh = CuboidMesh(nx=5, ny=1, nz=1, periodicity=(True, False, False))
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()
    assert field[0] == 1 + 4
    assert field[3] == 2
    assert field[6] == 4
    assert field[9] == 6
    assert field[12] == 3 + 0
    assert np.max(field[2::3]) == 0
    assert np.max(field[1::3]) == 0
Exemplo n.º 25
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def test_dw_dmi_atomistic(do_plot=False):

    mesh = CuboidMesh(nx=300, ny=1, nz=1)

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=const.gamma)
    sim.alpha = 0.5
    sim.mu_s = const.mu_s_1
    sim.do_precession = False

    sim.set_m(m_init_dw)

    J = 50.0 * const.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.01 * J
    dmi = DMI(D)
    sim.add(dmi)

    K = 0.005 * J
    anis = Anisotropy(K, axis=[1, 0, 0])
    sim.add(anis)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13,
              stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000,
              save_m_steps=100,
              save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

    xs = np.array([p[0] for p in mesh.coordinates]) - 150

    mx, my, mz = analytical(xs, A=J / 2.0, D=-D, K=K)
    mxyz = sim.spin.copy()
    mxyz = mxyz.reshape(-1, 3).T

    assert max(abs(mxyz[0, :] - mx)) < 0.001
    assert max(abs(mxyz[1, :] - my)) < 0.001
    assert max(abs(mxyz[2, :] - mz)) < 0.0006

    if do_plot:

        save_plot(xs, mxyz, mx, my, mz)
Exemplo n.º 26
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def test_exch_2d():
    mesh = CuboidMesh(nx=5, ny=2, nz=1)
    sim = Sim(mesh)
    exch = UniformExchange(1)
    sim.add(exch)

    sim.set_m(init_m, normalise=False)

    field = exch.compute_field()

    assert np.max(field[2::3]) == 0

    assert field[0] == 1
    assert field[3] == 2 + 1
    assert field[6] == 1 + 2 + 3
    assert field[9] == 2 + 3 + 4
    assert field[12] == 3 + 4
Exemplo n.º 27
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.mu_s = 1e-23
    sim.driver.gamma = 1.76e11
    sim.driver.alpha = 1.0
    J = 1e-22
    exch = UniformExchange(J)
    sim.add(exch)
    demag = Demag()
    sim.add(demag)
    sim.set_m(init_m)

    ts = np.linspace(0, 5e-10, 101)
    for t in ts:
        sim.driver.run_until(t)
        sim.save_vtk()
    np.save('m0.npy', sim.spin)
Exemplo n.º 28
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def create_simulation(R, B):
    mu_s = 3
    sim_hexagon = HexagonSim(
        R,  # R
        0.2715,  # a
        mu_s,  # mu_s
        name='unnamed')
    sim = sim_hexagon.sim

    # mask = (sim.mu_s / C.mu_B) > 1e-5
    exch = UniformExchange(5.881 * C.meV)
    sim.add(exch)
    dmi = DMI(D=1.557 * C.meV, dmi_type='interfacial')
    sim.add(dmi)
    sim.add(Zeeman([0., 0., B]))
    sim.add(Anisotropy(0.406 * C.meV, axis=[0, 0, 1]))

    return sim
Exemplo n.º 29
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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
Exemplo n.º 30
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def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=const.gamma)
    sim.alpha = 0.5
    sim.mu_s = const.mu_s_1
    sim.do_procession = False

    sim.set_m(m_init_dw)

    J = 50.0 * const.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.1 * J
    dmi = DMI(D, dmi_type='interfacial')
    sim.add(dmi)

    K = 0.02 * J
    anis = Anisotropy(K, axis=[0, 0, 1])
    sim.add(anis)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13,
              stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000,
              save_m_steps=100,
              save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

    xs = np.array([p[0] for p in mesh.pos]) - 150

    mx, my, mz = analytical(xs, A=J / 2.0, D=-D, K=K)
    mxyz = sim.spin.copy()
    mxyz.shape = (3, -1)

    save_plot(xs, mxyz, mx, my, mz)