PyQuake3D: A Python Tool for 3‐D Earthquake Sequence Simulations of Seismic and Aseismic Slip
Abstract Simulating the full spectrum of fault slip behavior—from slow aseismic creep to dynamic earthquake rupture—is essential for advancing our understanding of fault mechanics and long‐term seismic hazard. However, few open‐source tools provide efficient three‐dimensional modeling of these processes with the flexibility needed for research across scales. Here we introduce PyQuake3D, an open‐source Python package for simulating fault slip evolution using quasi‐dynamic approximations. The code solves elastic interactions via the boundary element method and incorporates hierarchical matrix compression to reduce memory usage and computational cost. PyQuake3D is designed for scalability and portability, supporting both distributed‐memory parallelism (MPI) and optional Graphics Processing Unit (GPU) acceleration. We validate the code against established sequences of earthquakes and aseismic slip (SEAS) benchmarks and illustrate its ability to capture key phases of the seismic cycle, including nucleation, rupture propagation, arrest, interseismic stress accumulation, and postseismic relaxation. Applications include simulations of faults with spatially heterogeneous friction, a geologically constrained model of the East Anatolian Fault Zone, and a laboratory‐inspired triaxial experiment. These examples demonstrate the ability of PyQuake3D to resolve the spatiotemporal complexity of fault slip, including the interplay of geometry, frictional properties, and loading. By combining scalable numerical techniques with accessible software design, PyQuake3D provides a robust and extensible platform for modeling fault slip dynamics across a wide range of geophysical scenarios.
Authors
- Luca Dal Zilio (ORCID: https://orcid.org/0000-0002-5642-0894)
- Rongjiang Tang (ORCID: https://orcid.org/0000-0001-9559-2712)
- Fusheng Li (ORCID: https://orcid.org/0000-0001-7491-5535)
- Lu Gan
Institutions
- University of Electronic Science and Technology of China (CN)
- Nanyang Technological University (SG)
- Earth Observatory of Singapore (SG)
- Cloud Computing Center (CN)
Publication Details
- Journal
- Journal of Geophysical Research Machine Learning and Computation
- Published
- 2025-10-29
- DOI
- https://doi.org/10.1029/2025jh000871
- Primary Topic
- earthquake and tectonic studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Ministry of Education, India
- Bộ Giáo dục và Ðào tạo
- Earth Observatory of Singapore