Fine-scale Segmentation and Spatiotemporal Variability of the 2010 Mw 8.8 Maule Aftershock Sequence Revealed by a Deep-Learning-Based Earthquake Catalog

We re-examine the aftershock sequence of the Mw 8.8 Maule earthquake in south-central Chile to understand how seismicity, magnitude-frequency distribution, and fault structure vary along the rupture zone. Using the International Maule Aftershock Deployment (IMAD) dataset, we analyze ten months of continuous data from 156 temporary stations and build a high-resolution aftershock catalog for the Maule rupture zone. We apply the BeamPower and Matched Filtering (BPMF) workflow, which integrates a deep-learning phase picker with backprojection-based association, relative relocation, and template matching. We initially detect and relocate 130,578 earthquakes, then use a subset of high-quality events as templates to identify smaller earthquakes missed by the initial detection. The final catalog contains about 537,390 earthquakes, nearly 13 times more than previous studies, with a completeness magnitude of approximately Mw 1.8 and magnitudes ranging from Mw 0.2 to Mw 6.2. A regional local magnitude (ML) calibration ensures homogeneous magnitude scales across the network. The dense catalog resolves detailed seismotectonic features along the rupture. In the Pichilemu region, aftershocks delineate a shallow normal fault system with L-shaped geometry, whereas the Concepción area exhibits aseismic patches. Using classical maximum likelihood and b-more-incomplete methods, we find that temporal b-values range between 1.2 and 1.6 early in the sequence and converge toward about 1.0. Meanwhile, spatial b-values are strongly segmented along strike, with higher values in the north and lower values in the south. These contrasts are consistent with along-strike variations in effective stress and pore fluid pressure on the plate interface, in line with previous studies.