tidy3d.components.material.multi_physics.MultiPhysicsMedium

class MultiPhysicsMedium

Contains multiple multi-physical properties as defined for each solver medium.

Parameters:

• attrs (dict = {}) – Dictionary storing arbitrary metadata for a Tidy3D object. This dictionary can be freely used by the user for storing data without affecting the operation of Tidy3D as it is not used internally. Note that, unlike regular Tidy3D fields, attrs are mutable. For example, the following is allowed for setting an attr obj.attrs['foo'] = bar. Also note that Tidy3D` will raise a TypeError if attrs contain objects that can not be serialized. One can check if attrs are serializable by calling obj.json().

• name (Optional[str] = None) – Medium name

• optical (Union[Medium, AnisotropicMedium, PECMedium, PoleResidue, Sellmeier, Lorentz, Debye, Drude, FullyAnisotropicMedium, CustomMedium, CustomPoleResidue, CustomSellmeier, CustomLorentz, CustomDebye, CustomDrude, CustomAnisotropicMedium, PerturbationMedium, PerturbationPoleResidue, LossyMetalMedium, Medium2D, AnisotropicMediumFromMedium2D, NoneType] = None) – Specifies optical properties.

• heat (Union[FluidSpec, SolidSpec, SolidMedium, FluidMedium, NoneType] = None) – Specifies properties for Heat simulations.

• charge (Union[ChargeConductorMedium, ChargeInsulatorMedium, SemiconductorMedium, NoneType] = None) – Specifies properties for Charge simulations.

Examples

For silica (\(SiO_2\)):

>>> import tidy3d as td
>>> SiO2 = td.MultiPhysicsMedium(
...   optical=td.Medium(permittivity=3.9),
...   charge=td.ChargeInsulatorMedium(permittivity=3.9), # redefining permittivity
...   name="SiO2",
... )

For a silicon MultiPhysicsMedium composed of an optical model from the material library and custom charge SemiconductorMedium:

>>> import tidy3d as td
>>> default_multiphysics_Si = td.MultiPhysicsMedium(
...     optical=td.material_library['cSi']['Green2008'],
...     charge=td.SemiconductorMedium(
...         N_c=2.86e19,
...         N_v=3.1e19,
...         E_g=1.11,
...         mobility_n=td.CaugheyThomasMobility(
...             mu_min=52.2,
...             mu=1471.0,
...             ref_N=9.68e16,
...             exp_N=0.68,
...             exp_1=-0.57,
...             exp_2=-2.33,
...             exp_3=2.4,
...             exp_4=-0.146,
...         ),
...         mobility_p=td.CaugheyThomasMobility(
...             mu_min=44.9,
...             mu=470.5,
...             ref_N=2.23e17,
...             exp_N=0.719,
...             exp_1=-0.57,
...             exp_2=-2.33,
...             exp_3=2.4,
...             exp_4=-0.146,
...         ),
...         R=[
...             td.ShockleyReedHallRecombination(
...                 tau_n=3.3e-6,
...                 tau_p=4e-6
...             ),
...             td.RadiativeRecombination(
...                 r_const=1.6e-14
...             ),
...             td.AugerRecombination(
...                 c_n=2.8e-31,
...                 c_p=9.9e-32
...             ),
...         ],
...         delta_E_g=td.SlotboomBandGapNarrowing(
...             v1=6.92 * 1e-3,
...             n2=1.3e17,
...             c2=0.5,
...             min_N=1e15,
...         ),
...         N_a=0,
...         N_d=0
...     )
... )

__init__(**kwargs)

Init method, includes post-init validators.

Methods

__init__(**kwargs)	Init method, includes post-init validators.
add_type_field()	Automatically place "type" field with model name in the model field dictionary.
construct([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy([deep, validate])	Copy a Tidy3dBaseModel.
dict(*[, include, exclude, by_alias, ...])	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
dict_from_file(fname[, group_path])	Loads a dictionary containing the model from a .yaml, .json, .hdf5, or .hdf5.gz file.
dict_from_hdf5(fname[, group_path, ...])	Loads a dictionary containing the model contents from a .hdf5 file.
dict_from_hdf5_gz(fname[, group_path, ...])	Loads a dictionary containing the model contents from a .hdf5.gz file.
dict_from_json(fname)	Load dictionary of the model from a .json file.
dict_from_yaml(fname)	Load dictionary of the model from a .yaml file.
from_file(fname[, group_path])	Loads a Tidy3dBaseModel from .yaml, .json, .hdf5, or .hdf5.gz file.
from_hdf5(fname[, group_path, custom_decoders])	Loads Tidy3dBaseModel instance to .hdf5 file.
from_hdf5_gz(fname[, group_path, ...])	Loads Tidy3dBaseModel instance to .hdf5.gz file.
from_json(fname, **parse_obj_kwargs)	Load a Tidy3dBaseModel from .json file.
from_orm(obj)
from_yaml(fname, **parse_obj_kwargs)	Loads Tidy3dBaseModel from .yaml file.
generate_docstring()	Generates a docstring for a Tidy3D mode and saves it to the __doc__ of the class.
get_sub_model(group_path, model_dict)	Get the sub model for a given group path.
get_submodels_by_hash()	Return a dictionary of this object's sub-models indexed by their hash values.
get_tuple_group_name(index)	Get the group name of a tuple element.
get_tuple_index(key_name)	Get the index into the tuple based on its group name.
help([methods])	Prints message describing the fields and methods of a Tidy3dBaseModel.
insert_traced_fields(field_mapping)	Recursively insert a map of paths to autograd-traced fields into a copy of this obj.
json(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
strip_traced_fields([starting_path, ...])	Extract a dictionary mapping paths in the model to the data traced by autograd.
to_file(fname)	Exports Tidy3dBaseModel instance to .yaml, .json, or .hdf5 file
to_hdf5(fname[, custom_encoders])	Exports Tidy3dBaseModel instance to .hdf5 file.
to_hdf5_gz(fname[, custom_encoders])	Exports Tidy3dBaseModel instance to .hdf5.gz file.
to_json(fname)	Exports Tidy3dBaseModel instance to .json file
to_static()	Version of object with all autograd-traced fields removed.
to_yaml(fname)	Exports Tidy3dBaseModel instance to .yaml file.
tuple_to_dict(tuple_values)	How we generate a dictionary mapping new keys to tuple values for hdf5.
update_forward_refs(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
updated_copy([path, deep, validate])	Make copy of a component instance with **kwargs indicating updated field values.
validate(value)

Attributes

heat_spec
name
optical
heat
charge
attrs

name

optical

heat

charge

__getattr__(name)

Delegate attribute lookup to inner media or fail fast.

Parameters:

name (str) – The attribute that could not be found on the MultiPhysicsMedium itself.

Returns:

• The attribute value obtained from a delegated sub-medium when

name is listed in DELEGATED_ATTRIBUTES. * None when name is explicitly ignored (e.g. "__deepcopy__").

Return type:

Any

Raises:

ValueError – If name is neither ignored nor in the delegation map, signalling that the caller may have intended to access optical, heat, or charge directly.

Notes

Only the attributes enumerated in the local DELEGATED_ATTRIBUTES dict are forwarded. Extend that mapping as additional cross-medium shim behaviour becomes necessary.

property heat_spec

__hash__()

Hash method.