First experience of seismodeformation monitoring of Baikal rift zone (by the example of South-Baikal earthquake of 27 August 2008)

A novel method of data processing – a structural functions curvature analysis method – was applied to the time series of seismodeformation monitoring of Baikal rift zone from April to November 2008, revealing the unique features of monitoring variable behaviour that can be considered as a revelation of precursors to the intensive South-Biakal earthquake (<I>M</I>=6.3, at 09:31 on 27 August 2008). The idea of a new approach leans upon basic ideas of modern physics of self-organized criticality and open non-equilibrium systems in general

Flicker-noise spectroscopy in earthquake prediction research

International audienceThe problem of earthquake prediction and the methods of identification of geophysical precursory signals are discussed. To get information on the dynamics of earthquake preparation processes, fluctuations in geophysical time series are analyzed with the method of flicker-noise spectroscopy. Integral indices ? power spectra and various moments ("structural functions") ? are used as information relations. We demonstrate that the method allows us to reveal earthquake precursors

Regular and stochastic behavior of Parkinsonian pathological tremor signals

Regular and stochastic behavior in the time series of Parkinsonian pathological tremor velocity is studied on the basis of the statistical theory of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We have developed a new method of analyzing and diagnosing Parkinson's disease (PD) by taking into consideration discreteness, fluctuations, long- and short-range correlations, regular and stochastic behavior, Markov and non-Markov effects and dynamic alternation of relaxation modes in the initial time signals. The spectrum of the statistical non-Markovity parameter reflects Markovity and non-Markovity in the initial time series of tremor. The relaxation and kinetic parameters used in the method allow us to estimate the relaxation scales of diverse scenarios of the time signals produced by the patient in various dynamic states. The local time behavior of the initial time correlation function and the first point of the non-Markovity parameter give detailed information about the variation of pathological tremor in the local regions of the time series. The obtained results can be used to find the most effective method of reducing or suppressing pathological tremor in each individual case of a PD patient. Generally, the method allows one to assess the efficacy of the medical treatment for a group of PD patients.Comment: 39 pages, 10 figures, 1 table Physica A, in pres

A simple mathematical model for anomalous diffusion via Fisher's information theory

Starting with the relative entropy based on a previously proposed entropy function $S_q[p]=\int dx p(x)(-\ln p(x))^q$, we find the corresponding Fisher's information measure. After function redefinition we then maximize the Fisher information measure with respect to the new function and obtain a differential operator that reduces to a space coordinate second derivative in the $q\to 1$ limit. We then propose a simple differential equation for anomalous diffusion and show that its solutions are a generalization of the functions in the Barenblatt-Pattle solution. We find that the mean squared displacement, up to a $q$-dependent constant, has a time dependence according to $\sim K^{1/q}t^{1/q}$, where the parameter $q$ takes values $q=\frac{2n-1}{2n+1}$ (superdiffusion) and $q=\frac{2n+1}{2n-1}$ (subdiffusion), $\forall n\geq 1$.Comment: 13 pages,3 figure

Regular and stochastic behavior of Parkinsonian pathological tremor signals

Regular and stochastic behavior in the time series of Parkinsonian pathological tremor velocity is studied on the basis of the statistical theory of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We have developed a new method of analyzing and diagnosing Parkinson's disease (PD) by taking into consideration discreteness, fluctuations, long- and short-range correlations, regular and stochastic behavior, Markov and non-Markov effects and dynamic alternation of relaxation modes in the initial time signals. The spectrum of the statistical non-Markovity parameter reflects Markovity and non-Markovity in the initial time series of tremor. The relaxation and kinetic parameters used in the method allow us to estimate the relaxation scales of diverse scenarios of the time signals produced by the patient in various dynamic states. The local time behavior of the initial time correlation function and the first point of the non-Markovity parameter give detailed information about the variation of pathological tremor in the local regions of the time series. The obtained results can be used to find the most effective method of reducing or suppressing pathological tremor in each individual case of a PD patient. Generally, the method allows one to assess the efficacy of the medical treatment for a group of PD patients. © 2006 Elsevier B.V. All rights reserved

NEW APPROACH TO STRONG EARTHQUAKE PREDICTION IN THE SOUTH BAIKAL REGION ON THE BASIS OF ROCK DEFORMATION MONITORING DATA: METHODOLOGY AND RESULTS

The Southern Baikal is located within the actively developing Baikal rift zone (BRZ) that is characterized by a significant seismic potential, and M>7 earthquakes occur periodically with intensive shaking in the epicenters (up to 10 units). The problem of prediction and forecasting of strong earthquakes has always been critical for this region, considering its increasing urbanization, industrial clusters and transport systems. The article describes the methodology based on rock deformation monitoring data, which aims at developing a technology capable of efficient prediction and forecasting of strong earthquakes. In the Institute of Earth’s Crust SB RAS a set of studies is carried out in order to solve this problem, including those associated with the instrumental study of current movements of the lithosphere through GPS geodesy and deformations of rocks by strain gauges. The existing GPS sites and deformation measurements are combined into the Large-Scale Research Facilities "South Baikal instrumental complex for monitoring hazardous geodynamic processes" in frame of the Shared Research Facilities "Geodynamics and Geochronology" at the Institute of the Earth’s Crust, Siberian Branch of the Russian Academy of Science.In this article, the deformation monitoring methodology is described in application to the monitoring sites installed in the study area. The description includes the details of its conceptual basis, technical support and data processing methods. The discussion focuses on the instrumental measurements of rock deformation related to three strong events in the study area – Kultuk (August 27, 2008), Bystrinskoe (September 21, 2020), and Kudara (December 10, 2020) earthquakes. The features of the deformation process before these seismic events are given special attention with account of the structural-geodynamic settings and positions of local monitoring sites relative to the earthquake epicenters

Scalar curvature of systems with fractal distribution functions

Starting with the relative entropy for two close statistical states we define the metric and calculate the scalar curvature $R$ for systems with classical, boson and fermion fractal distribution functions with moment order parameter $q$. In particular, we find that for $q\neq 1$ the scalar curvature is closer to zero implying that the fractal bosonic and fermionic systems are more stable than the standard ones.Comment: 9 pages, 2 figures, some typos were corrected, the Conclusions section was expande

НОВЫЙ ПОДХОД К ПРОГНОЗУ СИЛЬНЫХ ЗЕМЛЕТРЯСЕНИЙ В ЮЖНО-БАЙКАЛЬСКОМ РЕГИОНЕ НА ОСНОВЕ ДАННЫХ МОНИТОРИНГА ДЕФОРМАЦИИ ГОРНЫХ ПОРОД: МЕТОДОЛОГИЯ И РЕЗУЛЬТАТЫ

The Southern Baikal is located within the actively developing Baikal rift zone (BRZ) that is characterized by a significant seismic potential, and M>7 earthquakes occur periodically with intensive shaking in the epicenters (up to 10 units). The problem of prediction and forecasting of strong earthquakes has always been critical for this region, considering its increasing urbanization, industrial clusters and transport systems. The article describes the methodology based on rock deformation monitoring data, which aims at developing a technology capable of efficient prediction and forecasting of strong earthquakes. In the Institute of Earth’s Crust SB RAS a set of studies is carried out in order to solve this problem, including those associated with the instrumental study of current movements of the lithosphere through GPS geodesy and deformations of rocks by strain gauges. The existing GPS sites and deformation measurements are combined into the Large-Scale Research Facilities "South Baikal instrumental complex for monitoring hazardous geodynamic processes" in frame of the Shared Research Facilities "Geodynamics and Geochronology" at the Institute of the Earth’s Crust, Siberian Branch of the Russian Academy of Science.In this article, the deformation monitoring methodology is described in application to the monitoring sites installed in the study area. The description includes the details of its conceptual basis, technical support and data processing methods. The discussion focuses on the instrumental measurements of rock deformation related to three strong events in the study area – Kultuk (August 27, 2008), Bystrinskoe (September 21, 2020), and Kudara (December 10, 2020) earthquakes. The features of the deformation process before these seismic events are given special attention with account of the structural-geodynamic settings and positions of local monitoring sites relative to the earthquake epicenters.Южное Прибайкалье (ЮП) находится в пределах активно развивающейся Байкальской рифтовой зоны (БРЗ), обладающей значительным сейсмическим потенциалом. Здесь периодически происходят землетрясения с магнитудой более 7 и с интенсивностью сотрясений в эпицентрах до 10 баллов. В условиях высокой степени урбанизации ЮП и активного развития в его пределах промышленных кластеров и транспортных систем существенно повышается актуальность проблемы прогноза сильных землетрясений. В ИЗК СО РАН для решения этой проблемы проводится комплекс исследований по разным направлениям. Одно из них связано с инструментальным изучением современных движений литосферы на больших базах посредством GPS-геодезии и деформаций горных пород на малых базах штанговыми тензометрическими датчиками. Существующе пункты GPS и деформационных измерений объединены в уникальную научную установку «Южно-Байкальский инструментальный комплекс для мониторинга опасных геодинамических процессов» (УНУ «ЮБИК»), входящую в состав ЦКП «Геодинамика и геохронология».В статье рассмотрены методические вопросы деформационного мониторинга на малых базах. Описаны его концептуальная основа, техническая база и методы обработки получаемого фактического материла. На примере произошедших в последнее время в ЮП трех сильных землетрясений – Култукского (27.08.2008 г.), Быстринского (21.09.2020 г.) и Кударинского (10.12.2020 г.) – показаны предшествующие им особенности развития деформаций горных пород, а также влияние на них структурно-геодинамических условий в местах расположения пунктов мониторинга и пространственного положения этих пунктов относительно готовящегося очага землетрясения

Regular and stochastic behavior of Parkinsonian pathological tremor signals

Regular and stochastic behavior in the time series of Parkinsonian pathological tremor velocity is studied on the basis of the statistical theory of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We have developed a new method of analyzing and diagnosing Parkinson's disease (PD) by taking into consideration discreteness, fluctuations, long- and short-range correlations, regular and stochastic behavior, Markov and non-Markov effects and dynamic alternation of relaxation modes in the initial time signals. The spectrum of the statistical non-Markovity parameter reflects Markovity and non-Markovity in the initial time series of tremor. The relaxation and kinetic parameters used in the method allow us to estimate the relaxation scales of diverse scenarios of the time signals produced by the patient in various dynamic states. The local time behavior of the initial time correlation function and the first point of the non-Markovity parameter give detailed information about the variation of pathological tremor in the local regions of the time series. The obtained results can be used to find the most effective method of reducing or suppressing pathological tremor in each individual case of a PD patient. Generally, the method allows one to assess the efficacy of the medical treatment for a group of PD patients. © 2006 Elsevier B.V. All rights reserved