Neural-Networks

At the end of May 2023, a few days into LIGO’s fourth observing run, the Hanford detector started throwing out a new kind of noise: a narrow line near 589 Hz, lasting less than 0.4 seconds. The neural network that had sorted LIGO’s glitches since 2017 looked at 267 of them and called them “Whistle”, with an average confidence of 0.976. That was wrong, and the network was sure of it. A replacement classifier, built by the Gravity Spy team, looked at the same events and shrugged. It split them across three classes, with confidence scores between 0.35 and 0.46. For a model that only knows 23 categories, that kind of hesitation is the right answer to a glitch it has never seen. It’s since been identified as a new class, discussed on the project’s volunteer forum under the plain name “589 Hz”. ...

In three nights the Perseids peak under a new moon, the darkest Perseid maximum in five years. I’ll be up at Troodos with a reclining chair and a tally sheet, counting by eye the way people have counted meteors for a century. Overhead, a network of more than 1,300 cameras will be counting too, and solving an orbit for every meteor bright enough to trigger two of them at once. What made that automation possible is a piece of software: a neural network that learned to tell a meteor from an aeroplane. ...