Gravity Signals Could Detect Earthquakes At the Speed of Light

sciencehabit shares a report from Science.org: Two minutes after the world's biggest tectonic plate shuddered off the coast of Japan, the country's meteorological agency issued its final warning to about 50 million residents: A magnitude 8.1 earthquake had generated a tsunami that was headed for shore. But it wasn't until hours after the waves arrived that experts gauged the true size of the 11 March 2011 Tohoku quake. Ultimately, it rang in at a magnitude 9 -- releasing more than 22 times the energy experts predicted and leaving at least 18,000 dead, some in areas that never received the alert. Now, scientists have found a way to get more accurate size estimates faster, by using computer algorithms to identify the wake from gravitational waves that shoot from the fault at the speed of light. Recently, researchers involved in the hunt for gravitational waves -- ripples in space-time created by the movement of massive objects -- realized that those gravity signals, traveling at the speed of light, might also be used to monitor earthquakes. "The idea is that as soon as mass moves anywhere, the gravitational field changes, and ... everything feels it," says Bernard Whiting, a physicist at the University of Florida who worked on the Laser Interferometer Gravitational-Wave Observatory. "What was amazing was that the signal would be present even in seismometers." Sure enough, in 2016, Whiting and his colleagues reported that regular seismometers could detect these gravity signals. Earthquakes result in large shifts in mass; those shifts give off gravitational effects that deform both existing gravitational fields and the ground beneath seismometers. By measuring the difference between these two, the scientists concluded they could create a new kind of earthquake early warning system. Gravitational signals show up on seismometers before the arrival of the first seismic waves, in a portion of the seismogram that's traditionally ignored. By combining signals from dozens of seismometers on top of one another, scientists can identify patterns to interpret the size and location of large events, Whiting says. Now, Andrea Licciardi, a postdoc at Cote d'Azur University, and his colleagues have built a machine-learning algorithm to do that pattern recognition. They trained the model on hundreds of thousands of simulated earthquakes before testing it on the real data set from Tohoku. The model accurately predicted the earthquake's magnitude in about 50 seconds -- faster than other state-of-the-art early warning systems, researchers report today in Nature. "It's more than the seed of an idea -- they've shown that it can be done," Whiting says. "What we showed was a proof of principle. What they're showing is a proof of implementation."

Read more of this story at Slashdot.