tidy3d.CustomPoleResidue#

class CustomPoleResidue[source]#

Bases: CustomDispersiveMedium, PoleResidue

A spatially varying dispersive medium described by the pole-residue pair model.

Parameters:

name (Optional[str] = None) – Optional unique name for medium.
frequency_range (Optional[Tuple[float, float]] = None) – [units = (Hz, Hz)]. Optional range of validity for the medium.
allow_gain (bool = False) – Allow the medium to be active. Caution: simulations with a gain medium are unstable, and are likely to diverge.Simulations where ‘allow_gain’ is set to ‘True’ will still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.
nonlinear_spec (Union[NonlinearSpec, NonlinearSusceptibility] = None) – Nonlinear spec applied on top of the base medium properties.
modulation_spec (Optional[ModulationSpec] = None) – Modulation spec applied on top of the base medium properties.
heat_spec (Union[FluidSpec, SolidSpec, NoneType] = None) – Specification of the medium heat properties. They are used for solving the heat equation via the HeatSimulation interface. Such simulations can be used for investigating the influence of heat propagation on the properties of optical systems. Once the temperature distribution in the system is found using HeatSimulation object, Simulation.perturbed_mediums_copy() can be used to convert mediums with perturbation models defined into spatially dependent custom mediums. Otherwise, the heat_spec does not directly affect the running of an optical Simulation.
eps_inf (SpatialDataArray) – [units = None (relative permittivity)]. Relative permittivity at infinite frequency (\(\epsilon_\infty\)).
poles (Tuple[Tuple[tidy3d.components.data.data_array.SpatialDataArray, tidy3d.components.data.data_array.SpatialDataArray], ...] = ()) – [units = (rad/sec, rad/sec)]. Tuple of complex-valued (\(a_i, c_i\)) poles for the model.
interp_method (Literal['nearest', 'linear'] = nearest) – Interpolation method to obtain permittivity values that are not supplied at the Yee grids; For grids outside the range of the supplied data, extrapolation will be applied. When the extrapolated value is smaller (greater) than the minimal (maximal) of the supplied data, the extrapolated value will take the minimal (maximal) of the supplied data.
subpixel (bool = False) – If True and simulation’s subpixel is also True, applies subpixel averaging of the permittivity on the interface of the structure, including exterior boundary and intersection interfaces with other structures.

Notes

In this method, the frequency-dependent permittivity \(\epsilon(\omega)\) is expressed as a sum of resonant material poles [1].

\[\epsilon(\omega) = \epsilon_\infty - \sum_i \left[\frac{c_i}{j \omega + a_i} + \frac{c_i^*}{j \omega + a_i^*}\right]\]

For each of these resonant poles identified by the index \(i\), an auxiliary differential equation is used to relate the auxiliary current \(J_i(t)\) to the applied electric field \(E(t)\). The sum of all these auxiliary current contributions describes the total dielectric response of the material.

\[\frac{d}{dt} J_i (t) - a_i J_i (t) = \epsilon_0 c_i \frac{d}{dt} E (t)\]

Hence, the computational cost increases with the number of poles.

References

Example

>>> x = np.linspace(-1, 1, 5)
>>> y = np.linspace(-1, 1, 6)
>>> z = np.linspace(-1, 1, 7)
>>> coords = dict(x=x, y=y, z=z)
>>> eps_inf = SpatialDataArray(np.ones((5, 6, 7)), coords=coords)
>>> a1 = SpatialDataArray(-np.random.random((5, 6, 7)), coords=coords)
>>> c1 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)
>>> a2 = SpatialDataArray(-np.random.random((5, 6, 7)), coords=coords)
>>> c2 = SpatialDataArray(np.random.random((5, 6, 7)), coords=coords)
>>> pole_res = CustomPoleResidue(eps_inf=eps_inf, poles=[(a1, c1), (a2, c2)])
>>> eps = pole_res.eps_model(200e12)

See also

Notebooks

Fitting dispersive material models

Lectures

Modeling dispersive material in FDTD

Attributes

loss_upper_bound

Not implemented yet.

Methods

`eps_dataarray_freq`(frequency)	Permittivity array at `frequency`.
`from_medium`(medium)	Convert a `CustomMedium` to a pole residue model.
`poles_on_grid`(coords)	Spatial profile of poles interpolated at the supplied coordinates.
`to_medium`()	Convert to a `CustomMedium`.

eps_inf#

poles#

eps_dataarray_freq(frequency)[source]#

Permittivity array at frequency.

Parameters:: frequency (float) – Frequency to evaluate permittivity at (Hz).
Returns:: The permittivity evaluated at frequency.
Return type:: Tuple[SpatialDataArray, SpatialDataArray, SpatialDataArray]

poles_on_grid(coords)[source]#

Spatial profile of poles interpolated at the supplied coordinates.

Parameters:: coords (Coords) – The grid point coordinates over which interpolation is performed.
Returns:: The poles interpolated at the supplied coordinate.
Return type:: Tuple[Tuple[ArrayComplex3D, ArrayComplex3D], …]

classmethod from_medium(medium)[source]#

Convert a CustomMedium to a pole residue model.

Parameters:: medium (CustomMedium) – The medium with permittivity and conductivity to convert.
Returns:: The pole residue equivalent.
Return type:: CustomPoleResidue

to_medium()[source]#

Convert to a CustomMedium. Requires the pole residue model to only have a pole at 0 frequency, corresponding to a constant conductivity term.

Returns:: The non-dispersive equivalent with constant permittivity and conductivity.
Return type:: CustomMedium

property loss_upper_bound#: Not implemented yet.

__hash__()#: Hash method.

tidy3d.CustomPoleResidue

Contents

tidy3d.CustomPoleResidue#