A seismologist at Caltech is analyzing data from 120 seismic sensors placed along a fault line. If 25% of the sensors detect a tremor within the first 10 seconds, and three times that number detect it within the next 20 seconds, how many sensors have not detected the tremor after 30 seconds?

Wed, 06 May 2026 04:55:56 +0000

**How Caltech Seismologists Track Tremors in Real Time – A Closer Look at Sensor Data** As earthquake monitoring becomes increasingly data-driven, interest in how scientists quickly detect and interpret seismic activity is growing—especially along major fault zones like the one monitored by a team at Caltech. Recent analysis reveals striking patterns in how tremors ripple through sensor networks, raising questions about early warning precision and response speed. When a rupture begins, nearly a quarter of a network detects a signal within 10 seconds, and three times that number follow within the next 20. This rapid, cascading detection offers crucial insight into how scientists assess risk—and manage uncertainty in milliseconds. For residents in seismic-prone regions across the U.S., understanding this analysis helps clarify both public alerts and scientific limitations. **Understanding Real-Time Detection Networks** A team of seismologists at Caltech is monitoring 120 seismic sensors strategically placed along an active fault line. Once a disturbance begins, initial data shows that 25% of these sensors register tremors within the first 10 seconds. Given that 120 sensors form the network, this translates to 30 sensors detecting the event early. But the signal doesn’t stop there: within the next 20 seconds, three times that number—90 more sensors—record the tremor, bringing the cumulative total to 120—indicating full network activation. This immediate response pattern reflects how modern sensor arrays balance sensitivity and speed, essential for timely alerts.