Example #1
0
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.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)
Example #2
0
def relax_neb(k, maxst, simname, init_im, interp, save_every=10000):
    """
    Execute a simulation with the NEB function of the FIDIMAG code, for a
    nano disk

    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 folders starting with the 'simname'

    """

    # Prepare simulation
    # We define the small cylinder with the Magnetisation function
    sim = Sim(mesh)
    sim.Ms = cylinder

    # Energies

    # Exchange
    sim.add(UniformExchange(A=A))

    # Bulk DMI --> This produces a Bloch DW - like skyrmion
    sim.add(DMI(D=D))

    # No Demag, but this could have some effect
    # Demagnetization energy
    # sim.add(Demag())

    # Initial images (npy files or functions)
    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

    # Initiate the NEB algorithm driver
    neb = NEB_Sundials(sim,
                       init_images,
                       interpolations=interpolations,
                       spring=k,
                       name=simname)

    # Start the relaxation
    neb.relax(max_steps=maxst,
              save_vtk_steps=save_every,
              save_npy_steps=save_every,
              stopping_dmdt=1)
Example #3
0
def relax_neb(k, maxst, simname, init_im, interp, save_every=10000):
    """
    Execute a simulation with the NEB function of the FIDIMAG code, for an
    elongated particle (long cylinder)

    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
    # We define the cylinder with the Magnetisation function
    sim = Sim(mesh)
    sim.Ms = two_part

    #sim.add(UniformExchange(A=A))

    # Uniaxial anisotropy along x-axis
    sim.add(UniaxialAnisotropy(Kx, axis=(1, 0, 0)))

    # Define many initial states close to one extreme. We want to check
    # if the images in the last step, are placed mostly in equally positions
    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)
Example #4
0
def relax_system(sim):

    # init_images=[np.load('m_init.npy')]
    """
    n=20
    for i in range(1,n):
        theta = i*np.pi/n
        mx = -np.cos(theta)
        my = np.sin(theta)
        init_images.append((mx,my,0))
    """

    # init_images.append(np.load('m_final.npy'))

    init_images = [(-1, 0, 0), init_dw, (1, 0, 0)]

    neb = NEB_Sundials(
        sim, init_images, interpolations=[6, 6], name='neb', spring=1e8)

    # neb.add_noise(0.1)

    neb.relax(dt=1e-8, max_steps=5000, save_vtk_steps=500,
              save_npy_steps=500, stopping_dmdt=100)