Diffractive splitter

Visit the invrs-gym docs for the diffractive splitter challenge.

The diffractive splitter challenge is based on the “Design and rigorous analysis of a non-paraxial diffractive beamsplitter” slide deck retrieved from the LightTrans web site, and entails the design of a metasurface that evenly splits a normally-incident plane wave into a 7x7 array of beams, with diffraction angles of ±15 degrees.

The diffractive splitter eval metric is defined as follows:

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from invrs_gym import challenges

challenge = challenges.diffractive_splitter()
docstring = challenge.eval_metric.__doc__
print("\n".join([s[8:] for s in docstring.split("Args")[0].split("\n")[2:-2]]))

The eval metric rewards high total efficiency and minimum nonuniformity.
It is computed by,

    eval_metric = total_efficiency * (1 - uniformity_error)

In cases where multiple wavelengths or incident angles are considered, the
eval metric is the minimum across all excitation conditions.

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import os
import plotly.express as px
from IPython import display
from invrs_leaderboard import data

df = data.leaderboard_dataframe(base_path="../../../")
grid_spacing_nm = challenge.component.spec.grid_spacing * 1000
df["minimum_width_nm"] = df["minimum_width"] * grid_spacing_nm
df["minimum_spacing_nm"] = df["minimum_spacing"] * grid_spacing_nm
df["minimum_length_scale_nm"] = df["minimum_length_scale"] * grid_spacing_nm

def _trim_filename(name):
    return name if len(name) < 40 else name[:25] + "..." + name[-12:]

df["file"] = [_trim_filename(f) for f in df["file"]]

def plot_challenge_metrics(challenge_name: str) -> display.DisplayHandle:
    challenge_df = df[df["challenge"] == challenge_name]
    fig = px.scatter(
        challenge_df,
        x="minimum_length_scale_nm",
        y="eval_metric",
        color="file_prefix",
        hover_data=["file", "minimum_width_nm", "minimum_spacing_nm", "binarization_degree"],
    )
    if not os.path.exists("_plots/"):
        os.mkdir("_plots/")
    filename = f"_plots/eval_metric_{challenge_name}.html"
    fig.write_html(filename)
    return display.display(display.HTML(filename))

plot_challenge_metrics("diffractive_splitter")