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From the 2 of 6 linked papers with an AI index.

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6 papers

physics.geo-ph2026

How to quantify earthquake predictability? Advances in earthquake forecasting and predictability limits

Jiancang Zhuang, Didier Sornette

The paper proposes an information‑theoretic framework that quantifies how predictable earthquakes are by measuring entropy gaps and information gains, applying it to point‑process…

physics.geo-ph2026

Non-normal amplification in multitype Hawkes-ETAS models of earthquake triggering

Didier Sornette

The paper extends the ETAS earthquake‑triggering framework to a three‑type Hawkes model that distinguishes strike‑slip, normal, and reverse faults, showing that non‑normal branchin…

physics.geo-ph2025

Haicheng and Tangshan Earthquakes as potential Dragon-Kings

Jiawei Li, Didier Sornette

The dragon-king earthquake hypothesis proposes that some very large to great earthquakes are not merely the extreme end of the frequency-magnitude Gutenberg-Richter distribution (F…

cond-mat.stat-mech2025

Self-Similar Bridge between Regular and Critical Regions

V. I. Yukalov, E. P. Yukalova, D. Sornette

In statistical and nonlinear systems, two qualitatively distinct parameter regions are typically identified: the regular region, characterized by smooth behavior of key quantities,…

physics.geo-ph2025

Estimating Magnitude Completeness in Earthquake Catalogs: A Comparative Study of Catalog-based Methods

Xinyi Wang, Jiawei Li, Ao Feng +1

Without rigorous attention to the completeness of earthquake catalogs, claims of new discoveries or forecasting skills cannot be deemed credible. Therefore, estimating the complete…

physics.geo-ph2025

Integrating Artificial Intelligence and Geophysical Insights for Earthquake Forecasting: A Cross-Disciplinary Review

Zhang Ying, Wen Congcong, Sornette Didier +1

Earthquake forecasting remains a significant scientific challenge, with current methods falling short of achieving the performance necessary for meaningful societal benefits. Tradi…