fdtdx.DispersionModel

fdtdx.DispersionModel#

class fdtdx.DispersionModel(*, poles=())[source]#

Bases: TreeClass

Linear susceptibility built from a sum of 2nd-order ADE poles.

The high-frequency permittivity \(\varepsilon_\infty\) is NOT stored here - it lives in the parent Material as the existing permittivity field. This keeps a single source of truth for the inv_permittivities array.

Quick Reference#

Attributes

Methods

Attributes#

DispersionModel.is_isotropic#

Whether every pole applies the same parameters to all three axes.

DispersionModel.num_poles#

Number of poles in this model.

DispersionModel.poles: tuple[Pole, ...]#

Tuple of poles making up the susceptibility model.

Methods#

DispersionModel.aset(attr_name, val, create_new_ok=False)#

Sets an attribute of this class. In contrast to the classical .at[].set(), this method updates the class attribute directly and does not only operate on jax pytree leaf nodes. Instead, replaces the full attribute with the new value.

The attribute can either be the attribute name of this class, or for nested classes it can also be the attribute name of a class, which itself is an attribute of this class. The syntax for this operation could look like this: “a->b->[0]->[‘name’]”. Here, the current class has an attribute a, which has an attribute b, which is a list, which we index at index 0, which is an element of type dictionary, which we index using the dictionary key ‘name’.

Note that dictionary keys cannot contain square brackets or single quotes (even if they are escaped).

Parameters:

  • attr_name (str) – Name of attribute to set

  • val (Any) – Value to set the attribute to

  • create_new_ok (bool, optional) – If false (default), throw an error if the attribute does not exist. If true, creates a new attribute if the attribute name does not exist yet.

Returns:

Updated instance with new attribute value

Return type:

Self

DispersionModel.get_class_fields()#
Return type:

list[TreeClassField]

DispersionModel.get_public_fields()#
Return type:

list[TreeClassField]

DispersionModel.permittivity(omega, eps_inf=1.0)[source]#

Complex relative permittivity \(\varepsilon(\omega) = \varepsilon_\infty + \chi(\omega)\).

Raises ValueError for models with per-axis poles; use permittivity_axes() for those.

Parameters:

  • omega (complex | float) – Angular frequency (rad/s).

  • eps_inf (float) – High-frequency permittivity. Defaults to 1.0 (vacuum).

Returns:

Relative permittivity at omega.

Return type:

complex

DispersionModel.permittivity_axes(omega, eps_inf=1.0)[source]#

Per-axis complex relative permittivity \(\varepsilon_a(\omega) = \varepsilon_{\infty,a} + \chi_a(\omega)\).

Parameters:

  • omega (complex | float) – Angular frequency (rad/s).

  • eps_inf (float | tuple[float, float, float]) – High-frequency permittivity — scalar or per-axis 3-tuple (the diagonal of the ε∞ tensor). Defaults to 1.0.

Returns:

Relative permittivity at omega per axis (x, y, z).

Return type:

tuple

DispersionModel.susceptibility(omega)[source]#

Evaluate the complex susceptibility \(\chi(\omega)\).

Uses the exp(-i omega t) Fourier convention (damping appears with a -i gamma omega term in the Lorentz denominator).

Raises ValueError for models with per-axis poles; use susceptibility_axes() for those.

Parameters:

omega (complex | float) – Angular frequency (rad/s).

Returns:

\(\chi(\omega) = \sum_p \chi_p(\omega)\).

Return type:

complex

DispersionModel.susceptibility_axes(omega)[source]#

Evaluate the per-axis complex susceptibility \((\chi_x, \chi_y, \chi_z)\).

Uses the exp(-i omega t) Fourier convention (damping appears with a -i gamma omega term in the Lorentz denominator). For an isotropic model all three entries are equal.

Parameters:

omega (complex | float) – Angular frequency (rad/s).

Returns:

\(\chi_a(\omega) = \sum_p \chi_{p,a}(\omega)\) for each axis a in (x, y, z).

Return type:

tuple

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