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Methods Assistant

Describe your problem and get a recommendation of the right numerical method (Mie, BEM, DGTD, RCWA…), relevant references, and a direct link to the tool in the Lab.

v0.1.0·Updated 2026-06-10
Model & Assumptions Experimental
Model
Semantic search over course-note passages using all-MiniLM-L6-v2 embeddings (in-browser). Optional AI synthesis via Claude Haiku using retrieved passages as context.
Assumptions
Retrieval quality depends on the embedding model and the corpus (course notes on computational photonics methods). AI answers are grounded in retrieved passages but may contain inaccuracies.
Limitations
Corpus is limited to available course notes — not exhaustive. AI mode requires a user-provided Anthropic API key (stored in session or localStorage). Answers should be verified against the source passages.

Methods Assistant

Nanophotonics solver recommendations
Retrieval

Ask about methods

Ask a physics or numerical-method question. I search a corpus of computational-photonics course notes and return relevant passages. With an API key, Claude synthesizes an answer from the retrieved context.
First query downloads the embedding model (~20 MB, cached).

Anthropic API Key

Your key is sent directly to api.anthropic.com — it never touches any NanophotonicsLab server. By default, it is kept only for this session. Privacy policy

How it works: your query is embedded in the browser with all-MiniLM-L6-v2 (via Transformers.js) and matched against pre-computed chunks of course notes. With an API key, Claude Haiku synthesizes an answer from the retrieved passages. Without a key, passages are shown verbatim.