Seismicity, Statistical Physics Approaches to

Sornette, Didier; Werner, M. J.

doi:10.1007/978-0-387-30440-3_467

Cited by 19 publications

(13 citation statements)

References 222 publications

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“…scale invariance) that seems to apply in the collective properties of earthquakes and faulting has motivated the statistical mechanics approach. By using the mathematical tools of probability theory and statistics, statistical mechanics can be used to estimate the macroscopic properties of fault and earthquake populations from the specification of the relevant microscopic constituents and their interactions [10].…”

Section: (B) the Classical Statistical Mechanics Approachmentioning

confidence: 99%

Generalized statistical mechanics approaches to earthquakes and tectonics

2016

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Despite the extreme complexity that characterizes the mechanism of the earthquake generation process, simple empirical scaling relations apply to the collective properties of earthquakes and faults in a variety of tectonic environments and scales. The physical characterization of those properties and the scaling relations that describe them attract a wide scientific interest and are incorporated in the probabilistic forecasting of seismicity in local, regional and planetary scales. Considerable progress has been made in the analysis of the statistical mechanics of earthquakes, which, based on the principle of entropy, can provide a physical rationale to the macroscopic properties frequently observed. The scale-invariant properties, the (multi) fractal structures and the long-range interactions that have been found to characterize fault and earthquake populations have recently led to the consideration of non-extensive statistical mechanics (NESM) as a consistent statistical mechanics framework for the description of seismicity. The consistency between NESM and observations has been demonstrated in a series of publications on seismicity, faulting, rock physics and other fields of geosciences. The aim of this review is to present in a concise manner the fundamental macroscopic properties of earthquakes and faulting and how these can be derived by using the notions of statistical mechanics and NESM, providing further insights into earthquake physics and fault growth processes.

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Section: (B) the Classical Statistical Mechanics Approachmentioning

confidence: 99%

Generalized statistical mechanics approaches to earthquakes and tectonics

2016

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“…However, supplementary experimental work and testing is required before the evidence becomes compelling. According to Sornette and Werner (2009), complexity may not only emerge from inherent non-linear dynamics of the active tectonic grain as required by SOC; quenched heterogeneity in the stress field and production rates may also be of great importance. It is also noteworthy that Celikoglu et al (2010) showed that it is possible to obtain q-exponential distributions of interevent times with models not involving criticality.…”

Section: Discussionmentioning

confidence: 99%

On the Nature and Dynamics of the Seismogenetic System of South California, Usa: An Analysis Based on Non-Extensive Statistical Physics

2017

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“…Earthquakes, which are essentially a fracturing phenomenon, show a flow of energy release events from the micro-to the macroscale. Present-day state of the art is the microscopic simulation of fracture on the molecular scale [22], real-time observation at the nanoscale [66], the stochastic or continuum description at the mesoscale [23,24], and the statistical description of earthquakes on the fault system or global scale [25,26].…”

Section: Big Data For World-wide and Multiscale Problemsmentioning

confidence: 99%

From human mobility to renewable energies

Raischel

Moreira

Lind

2014

Eur. Phys. J. Spec. Top.

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Abstract.We address and discuss recent trends in the analysis of big data sets, with the emphasis on studying multiscale phenomena. Applications of big data analysis in different scientific fields are described and two particular examples of multiscale phenomena are explored in more detail. The first one deals with wind power production at the scale of single wind turbines, the scale of entire wind farms and also at the scale of a whole country. Using open source data we show that the wind power production has an intermittent character at all those three scales, with implications for defining adequate strategies for stable energy production. The second example concerns the dynamics underlying human mobility, which presents different features at different scales.For that end, we analyze 12-month data of the Eduroam database within Portuguese universities, and find that, at the smallest scales, typically within a set of a few adjacent buildings, the characteristic exponents of average displacements are different from the ones found at the scale of one country or one continent. Big data: the emergence of a new paradigmIn some sense, the notion of Information Age is slowly fading from the perception of our society. For decades, national and international research has been creating impressive amounts of data, and often from various unrelated measurement sources [1]. Computational methods have been serving the needs of the scientific community and the need for higher computational power has driven the invention of more efficient computational codes and triggered the development of new hardware. Simultaneously, the internet has been instrumental in fostering international research collaborations and divulging scientific knowledge.Today, obtaining data is no longer a problem. Information is there, available for everyone at any time. Given the computational power of today's computers and clusters, even single research groups can create and store large data volumes. The challenge in today's research is more often what to do with the data we have. How to manage all the information we have in such large data sources? Which phenomena can we now study? The recent technological progress together with the new challenges naturally lead to a new paradigm in computational sciences, which is partially described by the term big data.In this paper we discuss the utility of big data for approaching the empirical study of phenomena up to now unreachable. We discuss the usage of big data in the study of two specific phenomena, that up to now were unreachable, namely wind energy production and human

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Seismicity, Statistical Physics Approaches to

Cited by 19 publications

References 222 publications

Generalized statistical mechanics approaches to earthquakes and tectonics

Generalized statistical mechanics approaches to earthquakes and tectonics

On the Nature and Dynamics of the Seismogenetic System of South California, Usa: An Analysis Based on Non-Extensive Statistical Physics

From human mobility to renewable energies

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