Anomalous statistics of aftershock sequences generated by supershear ruptures
Bibliographic record
Abstract
Most earthquake ruptures propagate with speeds smaller than the Rayleigh wave velocity of the medium. These are called sub- Rayleigh ruptures. However, under suitable conditions, segments of otherwise sub- Rayleigh seismogenic ruptures can occasionally accelerate to speeds higher than the local shear wave velocity, giving rise to so-called supershear ruptures. The occurrence of supershear ruptures is usually associated with a locally higher value of pre-stress on the fault segment compared to the sub-Rayleigh segments of the same fault. Additionally, shear stress changes generated by the supershear rupture are radiated out unattenuated to distances comparable to the depth of rupture instead of rapidly decaying at much smaller distances from the rupture. This leads to aftershocks being distributed away from the fault on the supershear segment. This study attempts to verify whether these pre- and postseismic stress conditions and the resultant spatial aftershock distributions lead to discernible features in the statistical properties of the aftershock sequences of the earthquakes known to be associated with supershear ruptures. We analyze the Gutenberg-Richter scaling, the modified Omori law and Båth’s law for the aftershock sequences of two supershear mainshocks: the 1979 MW 6.5 Imperial Valley (California) and 2002 MW 7.9 Denali (Alaska) earthquakes. We observe that the b-value is always higher in the supershear zone than the rest of the sequence. We also observe that there is no systematic trend in the exponent of the modified Omori law when comparing the aftershocks in the supershear zone with the rest of the aftershocks. We argue that the b-value anomaly can be explained in terms of the off-fault distribution of aftershocks around the supershear segment of the rupture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".