Photonic Device Auto-Design Agent

An autonomous photonic device design agent, inspired by Andrej Karpathy's autoresearch. Instead of a human manually tuning device geometry and running simulations, an LLM agent (e.g. Claude Code) takes over the design loop: it reads instructions and constraints from a Markdown file, modifies the device geometry in Python, visually verifies the layout, runs a fabrication design-rule check, submits FDTD simulations to Tidy3D's cloud solver, inspects the resulting field patterns, and decides whether to keep or discard each design — all without human intervention.

How It Works

Before the loop, the agent does a one-time literature review of the target device class — common topologies, underlying physics, state-of-the-art metrics — and captures it in output/principles.md as a stable design reference.

Each iteration then runs through a fixed loop:

Explore → Design → Verify (DRC + preview) → Simulate → Log (keep/discard)

Long-term memory spans two files: output/principles.md holds the literature review, and output/journal.md logs each experiment's hypothesis and lesson. Together they let the agent learn from both successes and failures and avoid repeating dead ends. The human's job is to define the problem (device type, constraints, target metric) in program.md; the agent does the engineering.

Example Designs

See a few examples of what the AI photonic designer has designed:

• 1x2splitter
• taper
• crossing

Project Structure

File	Role
program.md	Agent instructions, constraints, loop rules
design.py	Device geometry (the only file the agent modifies)
simulate.py	Runs Tidy3D FDTD simulation, extracts metric, plots fields
preview.py	Generates geometry preview for visual inspection
drc.py	Fabrication rule check via KLayout
orchestrate.py	Post-simulation bookkeeping: parses run log, updates TSV/journal, handles keep/discard
output/	All generated files (principles, logs, plots, journal, best design)

Setup

pip install tidy3d numpy matplotlib klayout
tidy3d configure --apikey=YOUR_API_KEY

Get your Tidy3D API key at tidy3d.simulation.cloud.

Running

Point Claude Code (or any compatible LLM agent with shell + Python execution) at program.md:

claude "Follow the instructions in program.md and start designing!"

The agent will run the loop for the number of experiments specified in program.md (default: 50). Watch progress in output/journal.md and output/results.tsv.

Customizing for a Different Device

To adapt this framework to a new photonic device:

1. Edit program.md — describe the target device, metric, and constraints.
2. Edit design.py — update the initial geometry and the evaluate() function that computes the target metric from simulation data.
3. The rest of the infrastructure (simulate.py, preview.py, drc.py, orchestrate.py) is device-agnostic and does not need to change.

Credits

Inspired by karpathy/autoresearch. Built on Tidy3D for FDTD simulation and KLayout for DRC.