MultimodeInterferometerModel

MultimodeInterferometerModel(
    *,
    length: Annotated[float, minimum=0, units='μm'],
    input_offsets: collections.abc.Sequence[Annotated[float, units='μm']]
    | None = None,
    output_offsets: collections.abc.Sequence[Annotated[float, units='μm']]
    | None = None,
    width: Annotated[float, exclusiveMinimum=0, units='μm'] | None = None,
    port_spec: photonforge.PortSpec | None = None,
    access_width: Annotated[float, exclusiveMinimum=0, units='μm']
    | None = None,
    access_port_spec: photonforge.PortSpec | None = None,
    num_modes: Annotated[int, exclusiveMinimum=0] | None = None,
    mesh_refinement: Annotated[float, exclusiveMinimum=0] | None = None,
    verbose: bool = True,
) -> None

Multimode interferometer model.

Args

• length: Length of the multimode section.
• input_offsets: Lateral position of each input on the input face, measured from the center of the section. If None, the positions are read from the component’s own ports.
• output_offsets: Lateral position of each output on the output face. If None, read from the component’s ports.
• width: Width of the multimode section. The access cross-section is widened to it, every profile growing by the same amount so cladding margins are preserved. If None, and no port_spec is given, the section is measured off the component.
• port_spec: Full cross-section of the multimode section, for when neither widening the access stack nor slicing the component is what is wanted. Overrides width.
• access_width: Width of the access waveguides where they meet the multimode section. This is the end of the taper (if any), not the routing width. If None, the component’s own port specification is used.
• access_port_spec: Full access cross-section, overriding access_width.
• num_modes: Number of modes to solve for in the multimode section. If None, an estimate from the width and wavelength is used. Modes that the section does not guide are discarded after solving, and a warning is issued if the highest retained mode still carries appreciable power, which means the count was too low.
• mesh_refinement: Minimal number of mesh elements per wavelength for the mode solves.
• verbose: Control solver verbosity.

A wide section supports many lateral modes. An access waveguide launched at one edge excites them with coefficients $c_\nu$, they accumulate different phases, and at particular lengths they rephase into one or more images of the input. This model computes that directly:

$$S_{ji} = \sum_\nu c^{(i)}_\nu c^{(j)}_\nu \exp\left(i \beta_\nu L\right)$$

with $\beta_\nu$ from a mode solve of the multimode cross-section and $c_\nu$ the overlap of the access mode, shifted to that port’s offset, with each multimode mode.

Note

The section can be described in three ways, in falling order of precedence: port_spec for the whole cross-section, width to widen the access stack, or neither, in which case Component.slice_profile reads the drawn section and the access specification supplies everything the profiles do not carry. The last of those describes what is actually drawn, cladding included, so a component whose cladding layer is left out of the layout will be solved without one.

Methods

Method	Description
autograd_smatrix	Compute an autograd-compatible S matrix for traced parameters.
black_box_component	Create a black-box component using this model.
estimate_cost	Estimate the cost for S matrix computation.
s_matrix	Compute the S matrix for a component using this model.
setup_time_stepper	Obtain a time stepper for a component using this model.
start	Launch the mode solves and return a runner.
transform	Apply a transformation to this model.
update	Update this model.

autograd_smatrix

autograd_smatrix(
    self,
    *,
    component,
    traced_params,
    frequencies,
    component_for_params,
    param_names,
    show_progress=True,
    model_kwargs=None,
)

Compute an autograd-compatible S matrix for traced parameters.

Important

This is an abstract method that must be implemented by derived classes that support autograd-based S-matrix computation.

Args

• component (Component): Nominal component associated with this autograd evaluation.
• traced_params (ndarray): Traced parameter vector used by autograd.
• frequencies (Sequence[float]): Frequency values at which to calculate the scattering parameters (in Hz).
• component_for_params (Callable[[ndarray], Component]): Callback that returns the component for a given traced parameter vector.
• param_names (Sequence[str]): Flattened traced parameter names aligned with traced_params.
• show_progress (bool): Progress display hint from Component.s_matrix.
• model_kwargs (dict[str, Any] | None): Model-specific keyword arguments forwarded from Component.s_matrix.

Returns

AutogradSMatrix: Autograd-compatible S matrix.

black_box_component

black_box_component(
    self,
    num_inputs: int | None = None,
    num_outputs: int | None = None,
    port_spec: str | photonforge.PortSpec | None = None,
    technology: photonforge.Technology | None = None,
    name: str | None = None,
) -> photonforge.Component

Create a black-box component using this model.

Args

• num_inputs: Number of input ports. Required only when the model was built without input_offsets.
• num_outputs: Number of output ports. Required only when the model was built without output_offsets.
• port_spec: Port specification for the component. If None, look for "port_spec" in config.default_kwargs.
• technology: Component technology. If None, the default technology is used.
• name: Component name. If None, a default is used.

Returns

Component with ports and model.

estimate_cost

estimate_cost(self, *args, **kwargs)

Estimate the cost for S matrix computation.

All arguments are passed to the model’s start method with the addition of the keyword argument cost_estimation=True.

Returns

float: Cost estimation.

s_matrix

s_matrix(self, component, frequencies, show_progress=True, model_kwargs={})

Compute the S matrix for a component using this model.

Args

• component (Component): Component to perform the calculation.
• frequencies (Sequence[float]): Frequency values at which to calculate the scattering parameters (in Hz).
• show_progress (bool): If True, show computation progress.
• model_kwargs (dict[str, object]): Keyword arguments passed to Model.start. Accepted arguments depend on the model type.

Returns

SMatrix: Computed S matrix.

Example

Compute only the responses from mode 0 of P0 with Tidy3D to reduce the number and cost of simulations:

>>> model = pf.Tidy3DModel()
>>> s_matrix = model.s_matrix(  # doctest: +SKIP
...     component,
...     frequencies,
...     model_kwargs={"inputs": ("P0@0",)},
... )

A port name such as ("P0",) selects all modes of that port. All outputs for the selected inputs are returned; responses from unselected inputs are not computed. Use Model.estimate_cost with the same inputs passed directly to estimate the reduced run.

setup_time_stepper

setup_time_stepper(
    self,
    component,
    time_step,
    carrier_frequency=0,
    show_progress=True,
    time_stepper_kwargs={},
)

Obtain a time stepper for a component using this model.

Args

• component (Component): Component for the time stepper.
• time_step (float): The interval between time steps (in seconds).
• carrier_frequency (float): The carrier frequency used to construct the time stepper. The carrier should be omitted from the input signals, as it is handled automatically by the time stepper.
• show_progress (bool): If True, show computation progress.
• time_stepper_kwargs (dict[str, object]): Keyword arguments passed to TimeStepper.setup. Each time stepper type can accept a different set of arguments. Check the documentation for the each time stepper’s setup_state method for more information.

Returns

TimeStepper: Initialized time stepper.

start

start(
    self,
    component: photonforge.Component,
    frequencies: collections.abc.Sequence[float],
    verbose: bool | None = None,
    **kwargs: object,
) -> '_MultimodeInterferometerRunner'

Launch the mode solves and return a runner.

Args

• component: Component with its optical ports on the two faces of the multimode section.
• frequencies: Frequencies at which to evaluate the response.
• verbose: Overrides the model’s verbose.
• **kwargs: Unused.

Returns

Result object with attributes status and s_matrix.

transform

transform(
    self, translation=(0, 0), rotation=0, scaling=1, x_reflection=False
)

Apply a transformation to this model.

The base implementation is a no-op and returns self. Derived classes can override this method to transform model-specific geometry settings.

Args

• translation (Sequence[float] | complex): Translation vector.
• rotation (float): Rotation angle in degrees.
• scaling (float): Magnification factor.
• x_reflection (bool): Mirror across the horizontal axis.

Returns

Model: This object with transformations applied.

update

update(self, *args, **kwargs)

Update this model.

All contents of the model are updated with the contents from the updated version. object contents or modifications introduced after the model creation (outside of the original parametric function) are not propagated.

The model’s time stepper does not participate in the update, unless the __init__ method of the derived model class replaces it via set_time_stepper.

Args

• *args (object): Positional arguments to the parametric model.
• **kwargs (object): Keyword arguments to the parametric model.

Returns

Model: This model.

Note

The original keyword arguments used to generate the model are stored and updated with the passed kwargs. This updated version is used in the function call and will be stored for future updates. Positional arguments are not stored.

Attributes

Attribute	Description
parametric_function	str: Function used to update the model.
parametric_kwargs	dict[str, object]: Keyword arguments used to update the model.
properties	Properties: Object properties.
random_variables	list[RandomVariable]: Random variables associated to the model’s parameters.
time_stepper	TimeStepper | None: Time stepper associated with this model.

parametric_function

str: Function used to update the model.

parametric_kwargs

dict[str, object]: Keyword arguments used to update the model.

properties

Properties: Object properties.

random_variables

list[RandomVariable]: Random variables associated to the model’s parameters.

time_stepper

TimeStepper | None: Time stepper associated with this model.