scholarly journals Methods for the Evaluation of the Stochastic Properties of the Ionosphere for Earthquake Prediction—Random Matrix Theory

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 413 ◽  
Author(s):  
Leontýna Břizová ◽  
Jan Kříž ◽  
Filip Studnička ◽  
Jan Šlégr
Keyword(s):  
Earthquake Prediction ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Time Series Data ◽  
Matrix Theory ◽  
Low Frequency ◽  
Lower Ionosphere ◽  
Causal Chain ◽  
Series Data ◽  
Stochastic Properties

Seismo-ionospheric coupling is a field of great interest and is currently subject to rigorous study; using both ground and satellite data and many phenomenological features, the ionospheric precursors of earthquakes were identified. In this work, we present methods to study the stochastic properties of the lower ionosphere, derived from the data obtained with very low frequency (VLF) receivers at frequencies in the range of 19.6 to 37.5 kHz. Two main approaches are described: auto-correlation and random matrix theory treatments of amplitude time series data. It is shown that before shallow earthquakes with magnitudes greater than four, there are measurable changes that can be used in earthquake prediction. Although the exact form of the causal chain that leads to these changes are currently subject to diligent study, we believe that the investigations described herein are worth adding to the repertoire of ionospheric precursors.

scholarly journals Random Matrix Theory for Low-Frequency Sound Propagation in the Ocean: A Spectral Statistics Test

2018 ◽  
Vol 26 (01) ◽  
pp. 1850002 ◽  
Author(s):  
Denis Makarov
Keyword(s):  
Random Matrix Theory ◽  
Random Matrix ◽  
Sound Propagation ◽  
Matrix Theory ◽  
Low Frequency ◽  
Deep Ocean ◽  
Direct Monte Carlo Simulation ◽  
Novel Approach ◽  
Direct Numerical Solution ◽  
Spectral Statistics

Problem of long-range sound propagation in the randomly-inhomogeneous deep ocean is considered. We examine a novel approach for modeling of wave propagation, developed by Hegewisch and Tomsovic. This approach relies on construction of a wavefield propagator using the random matrix theory (RMT). We study the ability of the RMT-based propagator to reproduce properties of the propagator corresponding to direct numerical solution of the parabolic equation. It is shown that mode coupling described by the RMT-based propagator is basically consistent with the direct Monte-Carlo simulation. The agreement is worsened only for relatively short distances, when long-lasting cross-mode correlations are significant. It is shown that the RMT-based propagator with properly chosen range step can reproduce some coherent features in spectral statistics.

SSA, Random Matrix Theory, and Noise-Reduced Correlations

2016 ◽  
Author(s):  
Jan W Dash ◽  
Xipei Yang ◽  
Mario Bondioli ◽  
Harvey J. Stein
Keyword(s):  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory

History—an overview

2018 ◽  
Author(s):  
Oriol Bohigas ◽  
Hans A. Weidenmüller
Keyword(s):  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Rapid Development ◽  
The Past ◽  
History Of ◽  
And Mathematics

An overview of the history of random matrix theory (RMT) is provided in this chapter. Starting from its inception, the authors sketch the history of RMT until about 1990, focusing their attention on the first four decades of RMT. Later developments are partially covered. In the past 20 years RMT has experienced rapid development and has expanded into a number of areas of physics and mathematics.

scholarly journals Correction to: Anomaly Classification for Earthquake Prediction in Radon Time Series Data Using Stacking and Automatic Anomaly Indication Function

2021 ◽  
Author(s):  
Adil Aslam Mir ◽  
Fatih Vehbi Çelebi ◽  
Muhammad Rafique ◽  
M. R. I. Faruque ◽  
Mayeen Uddin Khandaker ◽  
...  
Keyword(s):  
Time Series ◽  
Earthquake Prediction ◽  
Time Series Data ◽  
Series Data ◽  
Anomaly Classification
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