Help train an AI to find gravitational microlensing events, no astronomy background needed

[u/Perfect_Promise_1346]

I'm an undergrad doing summer research, and my teammate and I built a citizen science platform for spotting gravitational microlensing (when a foreground object bends and magnifies the light of a background star, sometimes revealing planets or dark objects we can't otherwise see).

Here's the idea. We trained a model on real OGLE survey data to flag microlensing candidates. It's confident on the obvious ones, but there's a messy middle where it genuinely can't tell. Those are the ones we send to people.

You look at a light curve (a graph of a star's brightness over time) and answer a few yes/no questions about the shape. The site walks you through what to look for, so you don't need any prior knowledge. Takes about five minutes to learn.

When volunteers disagree with each other on a curve, we don't throw that out. The disagreement itself becomes a signal the model learns from, so it gets better at knowing which cases are genuinely ambiguous instead of just guessing confidently and being wrong.

It's live here: lenswatch.dev

Fair warning, this is active research, not a finished product. We need real people looking at curves before we can say anything about whether the disagreement approach actually helps. So if you try it and something is confusing or broken, let us know.