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GeoSci 精選 2026-03-30
本日選文(共 3 篇)。 [1024] SPIDER:用於雙差地震重定位的可擴展機率推論 SPIDER: Scalable Probabilistic Inference for Differential Earthquake Relocation 期刊:Earth and Space Science (AGU/Wiley) — eTOC Published:Wed, 25 Mar 2026 05:58:33 -0700 DOI:10.1029/2025JB032769 原文連結:連結 Summary (EN) Seismicity catalogs have grown hugely, but Bayesian double‐difference earthquake relocation struggles to scale to the millions of parameters involved. The authors introduce SPIDER, a scalable Bayesian framework for double‐difference hypocenter relocation that pairs a physics‑informed neural network Eikonal solver with Stochastic Gradient Langevin Dynamics to generate posterior samples jointly for entire catalogs. SPIDER explicitly whitens residual correlations that traditional formulations neglect, is designed for multi‑GPU parallelization, and is demonstrated on a synthetic catalog and three real catalogs from California and Japan, with proposed tools to analyze high‑dimensional posteriors. ...