Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling
<|reference_start|>Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling: Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive and require accurate representations of Earth structures and earthquake sources. We propose a novel artificial intelligence (AI) simulator, Conditional Generative Modeling for Ground Motion (CGM-GM), to synthesize high-frequency and spatially continuous earthquake ground motion waveforms. CGM-GM leverages earthquake magnitudes and geographic coordinates of earthquakes and sensors as inputs, learning complex wave physics and Earth heterogeneities, without explicit physics constraints. This is achieved through a probabilistic autoencoder that captures latent distributions in the time-frequency domain and variational sequential models for prior and posterior distributions. We evaluate the performance of CGM-GM using small-magnitude earthquake records from the San Francisco Bay Area, a region with high seismic risks. CGM-GM demonstrates a strong potential for outperforming a state-of-the-art non-ergodic empirical ground motion model and shows great promise in seismology and beyond.<|reference_end|>
@article{ren2024learning,
    title={Learning Physics for Unveiling Hidden Earthquake Ground Motions via
  Conditional Generative Modeling},
    author={Pu Ren, Rie Nakata, Maxime Lacour, Ilan Naiman, Nori Nakata, Jialin
  Song, Zhengfa Bi, Osman Asif Malik, Dmitriy Morozov, Omri Azencot, N.
  Benjamin Erichson, and Michael W. Mahoney},
    journal={arXiv preprint arXiv:2407.15089},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.15089},
    primaryClass={physics.geo-ph cs.AI cs.LG}
}