English
Related papers

Related papers: A Linear Modeling Approach on LTGP Signals and Sei…

200 papers

In molecular systems containing conical intersections (CIs), a nontrivial geometric phase (GP) appears in the nuclear and electronic wave-functions in the adiabatic representation. We study GP effects in nuclear dynamics of an N-dimensional…

Quantum Physics · Physics 2015-01-12 Loic Joubert-Doriol , Ilya G. Ryabinkin , Artur F. Izmaylov

Due to their relevance to geophysical systems, the investigation of multiscale systems through the lens of statistical mechanics has gained popularity in recent years. The aim of our work is the characterization of the nonequilibrium…

Statistical Mechanics · Physics 2024-11-12 Niccolò Cocciaglia , Dario Lucente

This study presents a pilot investigation into a novel method for reconstructing real-time ground motion during small magnitude earthquakes (M < 4.5), removing the need for computationally expensive source characterization and simulation…

Geophysics · Physics 2025-11-06 Youngkyu Kim , Qingkai Kong , Youngsoo Choi , Arben Pitarka , Byounghyun Yoo

The nonlinear mechanical responses of rocks and soils to seismic waves play an important role in earthquake physics, influencing ground motion from source to site. Continuous geophysical monitoring, such as ambient noise interferometry, has…

Nonlinear dynamical systems are ubiquitous in nature and they are hard to forecast. Not only they may be sensitive to small perturbations in their initial conditions, but they are often composed of processes acting at multiple scales.…

Chaotic Dynamics · Physics 2025-10-06 Chenyu Dong , Davide Faranda , Adriano Gualandi , Valerio Lucarini , Gianmarco Mengaldo

This paper shows how the dynamics of the PhotoPlethysmoGraphic (PPG) signal, an easily accessible biological signal from which valuable diagnostic information can be extracted, of young and healthy individuals performs at different…

Signal Processing · Electrical Eng. & Systems 2020-06-11 Javier de Pedro-Carracedo , David Fuentes-Jimenez , Ana M. Ugena , Ana P. Gonzalez-Marcos

The detection of earthquakes is a fundamental prerequisite for seismology and contributes to various research areas, such as forecasting earthquakes and understanding the crust/mantle structure. Recent advances in machine learning…

Geophysics · Physics 2023-07-14 Tomoki Tokuda , Hiromichi Nagao

Continuous GPS and broadband seismic monitoring have revealed a variety of disparate slip patterns especially in shallow dipping subduction zones, among which regular earthquakes, slow slip events and silent quakes1,2. Slow slip events are…

Geophysics · Physics 2015-05-13 Christophe Voisin , Jean-Robert Grasso , Eric Larose , François Renard

In Geosciences a class of phenomena that is widely studied given its real impact on human life are the tectonic faults slip. These landslides have different ways to manifest, ranging from aseismic events of slow displacement (slow slips) to…

Geophysics · Physics 2023-04-18 José Augusto Proença Maia Devienne

Seismic phase association connects earthquake arrival time measurements to their causative sources. Effective association must determine the number of discrete events, their location and origin times, and it must differentiate real arrivals…

Geophysics · Physics 2023-01-18 Ian W. McBrearty , Gregory C. Beroza

Transient electric signals emitted prior to earthquake occurrence are recorded at certain sites in the Earth's crust termed sensitive. These field observations enforce the laboratory investigation of the dielectric response of rocks forming…

Geophysics · Physics 2011-10-04 A. N. Papathanassiou , I. Sakellis , J. Grammatikakis

Automatic event detection from time series signals has wide applications, such as abnormal event detection in video surveillance and event detection in geophysical data. Traditional detection methods detect events primarily by the use of…

Machine Learning · Computer Science 2018-09-26 Yue Wu , Youzuo Lin , Zheng Zhou , David Chas Bolton , Ji Liu , Paul Johnson

Machine learning is becoming increasingly important in scientific and technological progress, due to its ability to create models that describe complex data and generalize well. The wealth of publicly-available seismic data nowadays…

Electric signals have been recently recorded at the Earth's surface with amplitudes appreciably larger than those hitherto reported. Their entropy in natural time is smaller than that, $S_u$, of a ``uniform'' distribution. The same holds…

Geophysics · Physics 2009-11-11 P. A. Varotsos , N. V. Sarlis , E. S. Skordas , H. K. Tanaka

Estimates of seismic wave speeds in the Earth (seismic velocity models) are key input parameters to earthquake simulations for ground motion prediction. Owing to the non-uniqueness of the seismic inverse problem, typically many velocity…

On 1 August 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy. The goal of the CSEP-Italy experiment is to test earthquake…

Geophysics · Physics 2015-03-13 M. J. Werner , J. D. Zechar , W. Marzocchi , S. Wiemer

We present a highly scalable 3D fully-coupled Earth & ocean model of earthquake rupture and tsunami generation. We model seismic, acoustic and surface gravity wave propagation in elastic (Earth) and acoustic (ocean) materials sourced by…

Numerical simulation of seismicity has been successfully developed and used for the two last decades. Presently, the general theory of modeling and the progress in computational techniques provide wide options for simulation of seismic and…

Geophysics · Physics 2015-07-17 Aleksandr M. Linkov , Liliana Rybarska-Rusinek , Victor V. Zoubkov

Functions of brain areas in complex animals are believed to rely on the dynamics of networks of neurons rather than on single neurons. On the other hand, the network dynamics reflect and arise from the integration and coordination of the…

Neurons and Cognition · Quantitative Biology 2017-01-03 Stefano Cavallari

We introduce Markov Random Geometric Graphs (MRGGs), a growth model for temporal dynamic networks. It is based on a Markovian latent space dynamic: consecutive latent points are sampled on the Euclidean Sphere using an unknown Markov…

Machine Learning · Computer Science 2022-03-10 Quentin Duchemin , Yohann de Castro
‹ Prev 1 4 5 6 7 8 10 Next ›