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In general terms, earthquakes are the result of brittle failure within the heterogeneous crust of the Earth. However, the rupture process of a heterogeneous material is a complex physical problem that is difficult to model deterministically due to numerous parameters and physical conditions, which are largely unknown. Considering the variability within the parameterization, it is necessary to analyze earthquakes by means of different approaches. Computational physics may offer alternative ways to study brittle rock failure by generating synthetic seismic data based on physical and statistical models and through the use of only few free parameters. The fiber bundle model (FBM) is a stochastic discrete model of material failure, which is able to describe complex rupture processes in heterogeneous materials. In this article, we present a computer code called the stochasTic Rupture Earthquake MOdeL, TREMOL. This code is based on the principle of the FBM to investigate the rupture process of asperities on the earthquake rupture surface. In order to validate TREMOL, we carried out a parametric study to identify the best parameter configuration while minimizing computational efforts. As test cases, we applied the final configuration to 10 Mexican subduction zone earthquakes in order to compare the synthetic results by TREMOL with seismological observations. According to our results, TREMOL is able to model the rupture of an asperity that is essentially defined by two basic dimensions: (1) the size of the fault plane and (2) the size of the maximum asperity within the fault plane. Based on these data and few additional parameters, TREMOL is able to generate numerous earthquakes as well as a maximum magnitude for different scenarios within a reasonable error range. The simulated earthquake magnitudes are of the same order as the real earthquakes. Thus, TREMOL can be used to analyze the behavior of a single asperity or a group of asperities since TREMOL considers the maximum magnitude occurring on a fault plane as a function of the size of the asperity. TREMOL is a simple and flexible model that allows its users to investigate the role of the initial stress configuration and the dimensions and material properties of seismic asperities. Although various assumptions and simplifications are included in the model, we show that TREMOL can be a powerful tool to deliver promising new insights into earthquake rupture processes. ; The authors are grateful to two anonymous reviewers and the editor for their relevant and constructive comments that have greatly contributed to improving the paper. M. Monterrubio-Velasco and J. de la Puente thank the European Union's Horizon 2020 Programme under the ChEESE Project (https://cheese-coe.eu/, last access: 1 May 2019), grant agreement no. 823844, for partially funding this work. M. Monterrubio- Velasco and A. Aguilar-Meléndez thank CONACYT for support of this research project. Quetzalcoatl Rodríguez-Pérez was supported by the Mexican National Council for Science and Technology (CONACYT) (Catedras program, project 1126). This project has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 777778, MATHROCKS, and from the Spanish Ministry project TIN2016-80957-P. Initial funding for the project through grant UNAM-PAPIIT IN108115 is also gratefully acknowledged. ; Peer Reviewed ; Postprint (published version)

In general terms, earthquakes are the result of brittle failure within the heterogeneous crust of the Earth. However, the rupture process of a heterogeneous material is a complex physical problem that is difficult to model deterministically due to numerous parameters and physical conditions, which are largely unknown. Considering the variability within the parameterization, it is necessary to analyze earthquakes by means of different approaches. Computational physics may offer alternative ways to study brittle rock failure by generating synthetic seismic data based on physical and statistical models and through the use of only few free parameters. The fiber bundle model (FBM) is a stochastic discrete model of material failure, which is able to describe complex rupture processes in heterogeneous materials. In this article, we present a computer code called the stochasTic Rupture Earthquake MOdeL, TREMOL. This code is based on the principle of the FBM to investigate the rupture process of asperities on the earthquake rupture surface. In order to validate TREMOL, we carried out a parametric study to identify the best parameter configuration while minimizing computational efforts. As test cases, we applied the final configuration to 10 Mexican subduction zone earthquakes in order to compare the synthetic results by TREMOL with seismological observations. According to our results, TREMOL is able to model the rupture of an asperity that is essentially defined by two basic dimensions: (1) the size of the fault plane and (2) the size of the maximum asperity within the fault plane. Based on these data and few additional parameters, TREMOL is able to generate numerous earthquakes as well as a maximum magnitude for different scenarios within a reasonable error range. The simulated earthquake magnitudes are of the same order as the real earthquakes. Thus, TREMOL can be used to analyze the behavior of a single asperity or a group of asperities since TREMOL considers the maximum magnitude occurring on a fault plane as a function of the size of the asperity. TREMOL is a simple and flexible model that allows its users to investigate the role of the initial stress configuration and the dimensions and material properties of seismic asperities. Although various assumptions and simplifications are included in the model, we show that TREMOL can be a powerful tool to deliver promising new insights into earthquake rupture processes. ; The authors are grateful to two anonymous reviewers and the editor for their relevant and constructive comments that have greatly contributed to improving the paper. M. Monterrubio-Velasco and J. de la Puente thank the European Union's Horizon 2020 Programme under the ChEESE Project (https://cheese-coe.eu/, last access: 1 May 2019), grant agreement no. 823844, for partially funding this work. M. Monterrubio- Velasco and A. Aguilar-Meléndez thank CONACYT for support of this research project. Quetzalcoatl Rodríguez-Pérez was supported by the Mexican National Council for Science and Technology (CONACYT) (Catedras program, project 1126). This project has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 777778, MATHROCKS, and from the Spanish Ministry project TIN2016-80957-P. Initial funding for the project through grant UNAM-PAPIIT IN108115 is also gratefully acknowledged. ; Peer Reviewed ; Postprint (published version)

Earthquake aftershocks display spatiotemporal correlations arising from their self-organized critical behavior. Dynamic deterministic modeling of aftershock series is challenging to carry out due to both the physical complexity and uncertainties related to the different parameters which govern the system. Nevertheless, numerical simulations with the help of stochastic models such as the fiber bundle model (FBM) allow the use of an analog of the physical model that produces a statistical behavior with many similarities to real series. FBMs are simple discrete element models that can be characterized by using few parameters. In this work, the aim is to present a new model based on FBM that includes geometrical characteristics of fault systems. In our model, the faults are not described with typical geometric measures such as dip, strike, and slip, but they are incorporated as weak regions in the model domain that could increase the likelihood to generate earthquakes. In order to analyze the sensitivity of the model to input parameters, a parametric study is carried out. Our analysis focuses on aftershock statistics in space, time, and magnitude domains. Moreover, we analyzed the synthetic aftershock sequences properties assuming initial load configurations and suitable conditions to propagate the rupture. As an example case, we have modeled a set of real active faults related to the Northridge, California, earthquake sequence. We compare the simulation results to statistical characteristics from the Northridge sequence determining which range of parameters in our FBM version reproduces the main features observed in real aftershock series. From the results obtained, we observe that two parameters related to the initial load configuration are determinant in obtaining realistic seismicity characteristics: (1) parameter P, which represents the initial probability order, and (2) parameter π, which is the percentage of load distributed to the neighboring cells. The results show that in order to reproduce statistical characteristics of the real sequence, larger πfrac values (0.85<πfrac<0.95) and very low values of P (0.0

Emerging high-performance computing systems, combined with increasingly detailed 3-D Earth models and physically consistent numerical wave propagation solvers, are opening up new opportunities for urgent seismic computing. This may help, for instance, to guide emergency response teams in the wake of large earthquakes. A key component of urgent seismic computing is the early availability of source mechanism estimates, well before conventional and time-consuming moment tensor inversions are carried out and published. Here, we introduce a methodology that rapidly estimates focal mechanisms (FM) for moderate and large earthquakes (Mw > 4.0) by means of statistical and clustering algorithms. The fundamental rationale behind the method is that events of a certain size tend to be similar to other events of similar size in similar locations. In this work, two different strategies are used to provide different FM solutions: the first is based only in spatial considerations including statistical analysis, and the other one is based on a data clustering algorithm. We exemplify our methodology with six different subsets of the open-access Global Centroid Moment Tensor (GCMT) catalog. Specifically, our study datasets include events from Japan, New Zealand, California, Mexico, Iceland, and Italy, which represent six seismically active regions, with a large FM variability. Our results show a 70–85% agreement between our fast FM estimates and inversion results, depending on the particular tectonic region, dataset size, and magnitude threshold. In addition, our FM estimation strategies only spend few seconds for processing, since they are totally independent of seismic record retrieval and inversion. Albeit not meant to be a substitute for CMT inversions, our methodologies can bridge the time gap between earthquake detection and FM inversion. ; The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under the grant agreement no. 823844, the Center of Excellence for Exascale in Solid Earth (ChEESE CoE Project). ; Peer Reviewed ; Postprint (published version)

Seismicity and magnitude distributions are fundamental for seismic hazard analysis. The Mexican subduction margin along the Pacific Coast is one of the most active seismic zones in the world, which makes it an optimal region for observation and experimentation analyses. Some remarkable seismicity features have been observed on a subvolume of this subduction region, suggesting that the observed simplicity of earthquake sources arises from the rupturing of single asperities. This subregion has been named SUB3 in a recent seismotectonic regionalization of Mexico. In this work, we numerically test this hypothesis using the TREMOL (sThochastic Rupture Earthquake MOdeL) v0.1.0 code. As test cases, we choose four of the most significant recent events (6.5 < Mw < 7.8) that occurred in the Guerrero–Oaxaca region (SUB3) during the period 1988–2018, and whose associated seismic histories are well recorded in the regional catalogs. Synthetic seismicity results show a reasonable fit to the real data, which improves when the available data from the real events increase. These results give support to the hypothesis that single-asperity ruptures are a distinctive feature that controls seismicity in SUB3. Moreover, a fault aspect ratio sensitivity analysis is carried out to study how the synthetic seismicity varies. Our results indicate that asperity shape is an important modeling parameter controlling the frequency–magnitude distribution of synthetic data. Therefore, TREMOL provides appropriate means to model complex seismicity curves, such as those observed in the SUB3 region, and highlights its usefulness as a tool to shed additional light on the earthquake process. ; We thank the two anonymous reviewers whose comments and suggestions helped improve and clarify this paper. The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under the grant agreement no. 823844, the ChEESE CoE Project. Marisol Monterrubio-Velasco, Otilio Rojas, and Josep de la Puente thank the ChEESE CoE Project. Quetzalcoatl Rodríguez-Pérez was supported by the Mexican National Council for Science and Technology (CONACYT) (Cátedras program – project 1126). ; Peer Reviewed ; Postprint (published version)

The multifractal detrended fluctuation algorithm is applied to a series of distances and elapsed times between consecutive earthquakes recorded along the years 2000–2018 in the Canterbury region (New Zealand). The time evolution of several multifractal parameters (Hurst exponent, Hölder central and maximum exponents, spectral amplitude, asymmetry, and complexity index) is analyzed. Peaks of multifractal parameters, with statistical significance exceeding 95%, are associated with three earthquakes of notable magnitude (equaling or exceeding Mw = 5.7). Additionally, some other peaks are also associated with the swarm of earthquakes of moderate magnitude. Possible shortcomings created by this assignment to mainshocks or swarms can be removed by comparing the results corresponding to elapsed times and interevent distances between consecutive events. Additionally, the Buishand test, which is used to verify the statistical significance of the detected peaks, also discriminates between mainshocks of notable seismic magnitude and swarms of earthquakes with moderate magnitude. The obtained results, based on the multifractal structure of the seismic activity, could also represent some advances in predicting, with sufficient time, forthcoming mainshocks of high magnitude and mitigate their destructive effects. ; The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation program, under Grant Agreement No. 823844, the ChEESE CoE Project. ; Peer Reviewed ; Postprint (published version)