I use them in astronomical data indexing when doing cross-match searches. That is, “could there be a star or other moving object in within 0.5 arcsec of this po

I use them in astronomical data indexing when doing cross-match searches. That is, “could there be a star or other moving object in within 0.5 arcsec of this point in the sky?” Sky catalogs have many billions of objects but the density per solid angle of the sky is extremely variable, and moving objects also make lookups really complicated. Sky catalogs are big enough that they are not storable in memory, and may be in big Parquet tables on the network, so the full lookup is quite expensive. Bloom filters are great for this because the backing dataset changes extremely slowly, like a few times a year when a survey publishes a new data release.