An algorithm inspired by a popular song-matching app is helping Stanford scientists find previously overlooked earthquakes in large databases of ground motion measurements. They call their algorithm Fingerprint And Similarity Thresholding, or FAST, and it could transform how seismologists detect microquakes – temblors that do not pack enough punch to register as earthquakes when analyzed by conventional methods. While microquakes do not threaten buildings or people, monitoring them could help scientists predict how frequently, and where, larger quakes are likely to occur. The FAST technique, circumvents both of these shortcomings by taking all of the recorded data from a seismic station and chopping the continuous signal into segments of a few seconds each. The signals are then compressed into compact representations, or “fingerprints,” for rapid processing. Earthquakes occurring on the same section of a fault have similar fingerprints, regardless of their magnitudes.