ZhangLi

class micromagneticmodel.ZhangLi(**kwargs)

Zhang-Li spin transfer torque dynamics term.

\[\frac{\text{d}\mathbf{m}}{\text{d}t} = -\frac{1+\alpha\beta}{1+\alpha^{2}} \mathbf{m} \times (\mathbf{m} \times (\mathbf{u} \cdot \boldsymbol\nabla) \mathbf{m}) - \frac{\beta - \alpha}{1+\alpha^{2}} \mathbf{m} \times (\mathbf{u} \cdot \boldsymbol\nabla)\mathbf{m}\]

A time-dependent current can be specified by providing a time-dependent pre-factor that is used to multiply u. The time-dependence can either be specified by providing a callable func that is evaluated at time steps dt or by passing a dictionary tcl_strings of tcl strings that are written to the mif file.

Parameters:

• beta (numbers.Real) – A single scalar value can be passed.

• u (number.Real, array-like, dict, discretisedfield.Field) – Spin-drift velocity in m/s. If a scalar value or Field with nvdim==1 is passed, the current is assumed to flow in x direction. A vector (array_like of length 3) or a Field with nvdim==3 can be used to specify arbitrary current direction. When using a dict either all elements must be scalar (current in x direction) or a vector must be used for each key.

• func (callable, optional) – Callable to define arbitrary time-dependence, multiplies u. Called at times that are multiples of dt. Must return a single number.

• dt (numbers.Real, optional (required for func)) – Time steps in seconds to evaluate callable func at.

• tcl_strings (dict, optional) – Dictionary of tcl strings to be included into the mif file for more control over specific time-dependencies. Must contain the following keys: script, script_args, and script_name. Refer to the OOMMF documentation for more details (behaves similar to Slonczewski current/Oxs_SpinXferEvolve: https://math.nist.gov/oommf/doc/userguide20a3/userguide/Standard_Oxs_Ext_Child_Clas.html#SX).

Examples

1. Defining the Zhang-Li dynamics term using scalar.

>>> import micromagneticmodel as mm
...
>>> zhangli = mm.ZhangLi(beta=0.01, u=5e6)

2. Defining the Zhang-Li dynamics term using discretisedfield.Field.

>>> import discretisedfield as df
...
>>> region = df.Region(p1=(0, 0, 0), p2=(5e-9, 5e-9, 5e-9))
>>> mesh = df.Mesh(region=region, n=(5, 5, 5))
>>> beta = 0.012
>>> u = df.Field(mesh, nvdim=1, value=1e5)
>>> zhangli = mm.ZhangLi(beta=beta, u=u)

3. Defining a sinusoidal decaying current.

>>> import micromagneticmodel as mm
>>> import numpy as np
...
>>> def sin_wave(t):
...     omega = 2 * np.pi / 1e-9
...     return np.sin(omega * t)
>>> zhangli = mm.ZhangLi(beta=0.01, u=5e6, func=sin_wave, dt=1e-13)

4. Defining the Zhang-Li dynamics term using vector.

>>> zhangli = mm.ZhangLi(beta=0.1, u=(0, 0, 1e12))

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Methods

__add__	Binary + operator.
__dir__	Default dir() implementation.
__eq__	Relational operator ==.
__iter__	Iterator.
__repr__	Representation string.
dmdt

Properties

beta	Descriptor allowing setting attributes only with scalars (numbers.Real).
dt	Descriptor allowing setting attributes only with scalars (numbers.Real).
func	Descriptor allowing setting attributes only with values of a certain type.
name	Name.
tcl_strings	Descriptor allowing setting attributes with a dictionary, which has keys defined by key_descriptor and values defined by value_descriptor.
u	custom type for Zhand-Li current density u.

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