Complexity of Recent Earthquake Swarms in Greece in Terms of Non-Extensive Statistical Physics

Sardeli, Eirini; Michas, Georgios; Pavlou, Kyriaki; Vallianatos, Filippos; Karakonstantis, Andreas; Chatzopoulos, Georgios

doi:10.3390/e25040667

Cited by 6 publications

(3 citation statements)

References 97 publications

(231 reference statements)

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“…Such weak interaction systems do not have a Boltzmann distribution, but rather a powerlaw distribution with heavy tails, enhanced by (multi) fractal geometry, long-range interactions, and intermittence or large fluctuations between various possible states. These systems correspond precisely to seismic phenomena (Sardeli et al, 2023;Sigalotti et al, 2023;Vallianatos et al, 2016). For such systems, Tsallis (1988) established nonextensive statistical mechanics and generalized Boltzmann-Gibbs statistical mechanics.…”

Section: Deep Underground Science and Engineeringmentioning

confidence: 98%

Dynamically triggered seismicity on a tectonic scale: A review

Qi,

Wang,

Kocharyan

et al. 2023

Deep Underground Science and Engineering

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Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments. In the past several decades, earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering, earthquake prediction, and the desire to use the mechanism of earthquake triggering to reduce, prevent, or trigger earthquakes. Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes. In the past several decades, some models have been developed, including static, dynamic, quasi‐static, and other models. Some reviews have been published, but explosion‐triggered seismicity was not included. In recent years, some new results on earthquake triggering have emerged. Therefore, this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area. Instead of a complete review of the relevant literature, this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.

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Section: Deep Underground Science and Engineeringmentioning

confidence: 98%

Dynamically triggered seismicity on a tectonic scale: A review

Qi,

Wang,

Kocharyan

et al. 2023

Deep Underground Science and Engineering

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“…These methods have been applied to a wide range of fields, such as high energy scattering processes [4,5,6], Ising systems [7], cosmic ray physics [8,9], plasma physics [10,11], ultracold gases [12], non-Gaussian diffusion processes in small complex systems [13,14], power grid frequency [15], bacterial DNA [16], financial time series [17,18] and traffic delays [19,20]. Recent years have also witnessed an increase in its application in environmental sciences, including wind statistics [21], air pollution statistics [22,23], rainfall statistics [24], sea surface currents [25], earthquake swarms [26,27] and water quality time series [28]. The dynamics of river water quality indicators, which involve a complex interplay of physical, chemical, and biological processes, can be viewed as a superposition of various dynamics across different time scales.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Spatio-Temporal Water Quality Dynamics for the River Thames using Superstatistical Methods and Machine Learning

He,

Boehringer,

Schäfer

et al. 2024

Preprint

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By employing superstatistical methods and machine learning we analyse measured time series of water quality indicators of the River Thames. Particular emphasis is on the dynamics of dissolved oxygen. The probability density functions (PDFs) of dissolved oxygen, with trend substracted, exhibit heavy tails that are well-fitted by q-Gaussian distributions. We investigate how the entropic index q depends on the distance to the sea. Regression analysis reveals feature importances for oxygen concentration predictions, with temperature, pH, and time of the year playing a major role. We also forecast oxygen concentrations through the application of a state-of-the-art machine learning model, the Transformer. Within this context, the Informer model exhibits superior performance. The effectiveness of the Informer model is attributed to the self-attention mechanism, which emphasizes the half-life cycle of dissolved oxygen and its temporal dynamics during periods from morning to early afternoon and from late evening to early morning. Our research can help to inform policymakers in ecological health assessments, assisting in river water quality forecasting and helping to maintain healthy aquatic ecosystems.

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“…Collective parameters can be extremely useful for characterizing the clustering properties of seismicity [ 19 , 20 , 21 , 22 ]; moreover, more recently, it has been suggested that they can be related to the behavior of seismogenetic sources at a regional scale [ 23 ]. Therefore, they may be of interest to infer the seismogenic potential of still poorly investigated areas.…”

Section: Introductionmentioning

confidence: 99%

Clustering Analysis of Seismicity in the Anatolian Region with Implications for Seismic Hazard

Zaccagnino,

Telesca,

Tan

et al. 2023

Entropy

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The Anatolian region is one of the most seismically active tectonic settings in the world. Here, we perform a clustering analysis of Turkish seismicity using an updated version of the Turkish Homogenized Earthquake Catalogue (TURHEC), which contains the recent developments of the still ongoing Kahramanmaraş seismic sequence. We show that some statistical properties of seismic activity are related to the regional seismogenic potential. Mapping the local and global coefficients of variation of inter-event times of crustal seismicity which occurred during the last three decades, we find that territories prone to major seismic events during the last century usually host globally clustered and locally Poissonian seismic activity. We suggest that regions with seismicity associated with higher values of the global coefficient of variation of inter-event times, CV, are likely to be more prone to hosting large earthquakes in the near future than other regions characterized by lower values, if their largest seismic events have the same magnitude. If our hypothesis is confirmed, clustering properties should be considered as a possible additional information source for the assessment of seismic hazard. We also find positive correlations between global clustering properties, the maximum magnitude and the seismic rate, while the b-value of the Gutenberg–Richter law is weakly correlated with them. Finally, we identify possible changes in such parameters before and during the 2023 Kahramanmaraş seismic sequence.

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Complexity of Recent Earthquake Swarms in Greece in Terms of Non-Extensive Statistical Physics

Cited by 6 publications

References 97 publications

Dynamically triggered seismicity on a tectonic scale: A review

Dynamically triggered seismicity on a tectonic scale: A review

Analyzing Spatio-Temporal Water Quality Dynamics for the River Thames using Superstatistical Methods and Machine Learning

Clustering Analysis of Seismicity in the Anatolian Region with Implications for Seismic Hazard

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