Detection of Swarm Earthquakes Increased Tenfold! AI Visualizes the Quiet Movement of a Supervolcano

1. Introduction: The New Breath of the "Sleeping Giant"

The name Yellowstone is not only symbolic of the first national park in the United States but has also frequently made headlines as a synonym for the "supervolcano." Recently, a research team led by Professor Bin Li from Western Ontario University employed the latest deep learning algorithms to reanalyze 15 years of seismic waveform archives. The results were shocking—86,276 events emerged, about ten times the number of earthquakes registered in the official catalog.Phys.org

2. What Machine Learning Did Not "Miss"

Traditionally, earthquake detection relied heavily on expert visual checks, which had limitations in handling vast amounts of data. The research team used convolutional neural networks (CNN) to achieve high-precision trigger judgments in just a few seconds. Notably, the post-process that suppressed "false positives" involved cross-matching with existing catalogs, re-localizing epicenters, and automatically estimating magnitudes, eliminating noise and chemical explosion signals. As a result, previously buried micro-events were "rediscovered."Phys.org

3. The Mystery of Swarm Earthquakes and "Fractal Faults"

According to the analysis, over 55% of the detected earthquakes were classified as "swarms." The research team introduced fractal dimensions into the spatiotemporal clustering of events, presenting a model where destruction propagates in a leapfrog manner due to immature and coarse faults. This contrasts with mature fault zones like Southern California and suggests that the caldera's unique hydrothermal environment may hold the key.Phys.orgReddit

4. USGS's Update on a "Practical Monitoring Network"

In its updated crisis response plan for 2024, the Yellowstone Volcano Observatory (YVO) of the US Geological Survey (USGS) has announced plans to monitor earthquakes, hydrothermal explosions, and fumarole activity with cameras and real-time seismometers. Observation leader Dr. Mike Poland stated in field verification that "reports from tourists and staff can sometimes be the fastest sensors," and evaluated that swarm research directly contributes to optimizing monitoring locations.KRTV NEWS Great Falls

5. What the Depth of the Magma Cap Says About "Eruption Probability"

An independent study in April 2025 used artificial microseisms with vibration tracking to identify a "magma cap" about 3 km below the caldera. A structure that allows gases to escape was confirmed, concluding that a catastrophic eruption in the near future is unlikely. This machine learning study supports this scenario while suggesting a mechanism where localized fluid pressure increases trigger small-scale swarms.The Washington Post

6. The "Hot Wind" of Social Media: Reassurance, Caution, and Conspiracy Theories

• Reassurance Group: "More data = evidence of improved risk management" "It's good news that AI has made things 'visible'"

• Caution Group: "Ten times the number of earthquakes? Is this an eruption flag?" "Tourists should cancel immediately"

• Conspiracy Theory Group: "Proof that the government has been hiding the truth" "Is the next step weather weapons?" In the Reddit r/science thread, a passage from the paper stating "fluid diffusion is key" was quoted, leading to evidence-focused discussions, while on X (formerly Twitter), "#YellowstoneSupervolcano" briefly trended.
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7. Experts Interpret the "Meaning of Swarms"

Professor Li points out that "swarm earthquakes ≠ eruption precursors," suggesting instead that the caldera may function as a "safety valve" to release pressure. The USGS also estimates that the eruption probability is less than 0.00014 per year on a 10,000-year scale, emphasizing that while swarms should be noted, they are not indicators of fear.

8. Geothermal Energy and "Risk Transfer"

The area around Yellowstone has high geothermal potential, but the study suggests that "the higher the heat flow, the more immature faults there are, increasing drilling risks." Safe geothermal development will require high-resolution catalogs generated by AI.

9. Impact on Tourism and Cultural Landscapes

With over 4 million visitors annually, the improvement in earthquake detection accuracy is beginning to affect walkway design and guide route reviews. The local business community positively views "accurate risk information as protecting tourism," and advanced "science tourism" projects are underway.

10. Media Challenges: Breaking Away from Sensationalism

While headlines about "catastrophic eruptions" have previously driven clicks, scientific reporting in the AI era requires a perspective that does not simplistically equate "increased detection numbers = increased danger." Utilizing open data provided by USGS and academic journals and linking to primary information will be key to curbing misinformation on social media.

11. Future Outlook: New Norms in Volcanic Disaster Prevention Shaped by AI

Machine learning-based earthquake monitoring is expanding from extraterrestrial applications, like NASA's InSight Mars lander, to everyday life, such as the Android earthquake detection network. The Yellowstone research is expected to evolve as a "testbed" into fault friction models, fluid movement simulations, and multimodal data fusion.

12. Conclusion

The "sleeping giant" is indeed stirring. However, its heartbeat is not a metronome for imminent eruption but the complex breathing of the Earth's depths. With the new stethoscope of machine learning, we have begun to walk the path of coexistence based on data, neither in fear nor overconfidence.