Collaborative Research: CMG--Stochastic Quantization for Modeling the Dynamics of Regional Seismicity

对地震活动动力学的预测理解是现代地球物理学的最大挑战之一。要实现这样的理解，需要探索性数据分析和相关的数学建模相结合。该项目将为模拟和分析区域地震活动提供一个框架，其基础是随机量化方法和对标记点过程使用非线性滤波。由此产生的描述将使人们能够表示区域断层网络，包括复杂的几何、记忆、相互作用和结构非均质性等细节。拟议的研究将扩展现有地球物理模型中捕捉到的想法。特别是，最重要的目标之一是加强传染病类型余震序列(ETAS)方法在短期地震模拟和预测中的作用，并通过纳入区域断层系统的已知方面来提高模型在更大空间和时间尺度上的性能。该项目构建的模型将根据南加州观测到的地震活动进行测试，并将利用南加州地震数据中心(SCEDC)和南加州地震中心社区断层模型(SCEC CFM)的高质量数据。自然灾害对社会构成威胁，地震可能是对构造活跃地区建筑环境的最大威胁。该项目将结合最先进的数学方法和地震活动数据，有助于对地震活动动力学的预测理解。最终，拟议的工作将用于制定地震预报战略，这将在国际地震可预测性研究合作实验室(CSEP)内进行测试，该合作实验室最近由SCEC组织。该项目的协作和跨学科方法使其成为研究生和年轻科学家的理想培训场所。

Predictive understanding of the dynamics of seismicity is one of the greatest challenges of modern geophysics. To accomplish such an understanding requires a combination of exploratory data analysis and relevant mathematical modeling. This project will provide a framework for modeling and analyzing regional seismicity based on the stochastic quantization approach and the use of non-linear filtering for marked point processes. The resulting description will allow one to represent regional fault networks, including details such as complex geometry, memory, interactions, and structural heterogeneities. The proposed research will expand upon ideas captured in existing geophysical models. In particular, one of the most important goals is to enhance Epidemic Type Aftershock Sequence (ETAS) approach to short-term earthquake modeling and forecasts and improve the model performance on larger spatial and temporal scales by incorporating known aspects of regional fault systems. The models constructed in the project will be tested on the observed seismicity of southern California and will leverage high-quality data from Southern California Earthquake Data Center (SCEDC) and the Southern California Earthquake Center Community Fault Model (SCEC CFM).Natural hazards pose a threat to society, and earthquakes are probably the greatest danger to the built environment in tectonically active areas. This project will contribute to the predictive understanding of the seismicity dynamics by merging the state-of-the-art mathematical methods and seismicity data. Ultimately, the proposed work will be used to formulate earthquake forecasting strategies, which will be tested within the international Collaboratory for the Study of Earthquake Predictability (CSEP), recently organized by SCEC. The collaborative and cross-disciplinary approach of this project makes it an ideal training ground for graduate students and young scientists.