Self-similar branching of aftershock sequences
β Scribed by James R. Holliday; Donald L. Turcotte; John B. Rundle
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 763 KB
- Volume
- 387
- Category
- Article
- ISSN
- 0378-4371
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β¦ Synopsis
In this paper we propose a branching aftershock sequence (BASS) model for seismicity. We suggest that the BASS model is a preferred alternative to the widely studied epidemic type aftershock sequence (ETAS) model. In the BASS model an initial, or seed, earthquake is specified. The subsequent earthquakes are obtained from the statistical distributions of magnitude, time, and location. The magnitude scaling is based on a combination of the Gutenberg-Richter scaling relation and the modified BΓ₯th's law for the scaling relation of aftershocks relative to the magnitude of the seed earthquake. Omori's law specifies the distribution of earthquake times, and a modified form of Omori's law specifies the distribution of earthquake locations. Since the BASS model is specified by the four scaling relations, it is fully self-similar. This is not the case for ETAS. We also give a deterministic version of BASS and show that it satisfies Tokunaga side-branching statistics in a similar way to diffusion-limited aggregation (DLA).
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## Abstract In this paper we study the limit behavior of weighted averages of some random sequence related to Bernoulli random variables, and apply the results to average density of selfβsimilar measures. Β© 2011 WILEYβVCH Verlag GmbH & Co. KGaA, Weinheim
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