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Related papers: A Non-ergodic Effective Amplitude Ground-Motion Mo…

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A new approach for creating a non-ergodic $PSA$ ground-motion model (GMM) is presented which account for the magnitude dependence of the non-ergodic effects. In this approach, the average $PSA$ scaling is controlled by an ergodic $PSA$ GMM,…

Applications · Statistics 2021-07-21 Grigorios Lavrentiadis , Norman A. Abrahamson

Recent developments in non-ergodic ground-motion models (GMMs) explicitly model systematic spatial variations in source, site, and path effects, reducing standard deviation to 30-40% of ergodic models and enabling more accurate…

Machine Learning · Computer Science 2025-12-24 Maxime Lacour , Pu Ren , Rie Nakata , Nori Nakata , Michael Mahoney

This paper provides an overview and introduction to the development of non-ergodic ground-motion models, GMMs. It is intended for a reader who is familiar with the standard approach for developing ergodic GMMs. It starts with a brief…

This study presents the development and application of a scalable non-ergodic ground motion model (NGMM) for the Los Angeles area. The NGMM is trained and validated on physics-based simulated ground-motion data from a recent Statewide…

Applications · Statistics 2026-05-26 Jinyan Zhao , Grigorios Lavrentiadis , Domniki Asimaki

A new mechanism for Geodesic acoustic mode (GAM) excitation by a not fully slowed down energetic particle (EP) beam is analysed to explain experimental observations in Large Helical Device. It is shown that the positive velocity space…

Plasma Physics · Physics 2016-01-20 Jintao Cao , Zhiyong Qiu , Fulvio Zonca

The ETAS model is widely employed to model the spatio-temporal distribution of earthquakes, generally using spatially invariant parameters. We propose an efficient method for the estimation of spatially varying parameters, using the…

Geophysics · Physics 2017-06-28 Shyam Nandan , Guy Ouillon , Stefan Wiemer , Didier Sornette

We present a data-driven framework for ground-motion synthesis that generates three-component acceleration time histories conditioned on moment magnitude, rupture distance , time-average shear-wave velocity at the top $30m$ ($V_{S30}$), and…

A partially non-ergodic ground-motion prediction equation is estimated for Europe and the Middle East. Therefore, a hierarchical model is presented that accounts for regional differences. For this purpose, the scaling of ground-motion…

Geophysics · Physics 2016-03-30 Nicolas M. Kuehn , Frank Scherbaum

The nonlinear dynamics of energetic particle (EP) driven geodesic acoustic modes (EGAM) in tokamaks is investigated, and compared with the beam-plasma system (BPS). The EGAM is studied with the global gyrokinetic (GK) particle-in-cell code…

Plasma Physics · Physics 2019-01-16 A. Biancalani , N. Carlevaro , A. Bottino , G. Montani , Z. Qiu

The nonlinear dynamics of energetic-particle (EP) driven geodesic acoustic modes (EGAM) is investigated here. A numerical analysis with the global gyrokinetic particle-in-cell code ORB5 is performed, and the results are interpreted with the…

Plasma Physics · Physics 2018-02-14 A. Biancalani , I. Chavdarovski , Z. Qiu , A. Bottino , D. Del Sarto , A. Ghizzo , O. Gurcan , P. Morel , I. Novikau

Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized…

Adaptive Gradient Descent with Energy (AEGD) is a variant of gradient descent (GD) designed to mitigate step-size sensitivity through an energy-based formulation. AEGD is notable for its unconditional energy stability, which guarantees…

Optimization and Control · Mathematics 2025-12-16 Lin Feng , Hailiang Liu

The spatio-temporal properties of seismicity give us incisive insight into the stress state evolution and fault structures of the crust. Empirical models based on self-exciting point-processes continue to provide an important tool for…

Geophysics · Physics 2023-03-01 Jack B. Muir , Zachary E. Ross

Objective: Surface electromyogram (EMG) signals have typically been assumed to follow a Gaussian distribution. However, the presence of non-Gaussian signals associated with muscle activity has been reported in recent studies, and there is…

Signal Processing · Electrical Eng. & Systems 2019-12-11 Akira Furui , Hideaki Hayashi , Toshio Tsuji

We introduce the Bayesian Global Sky Model (B-GSM), a novel data-driven Bayesian approach to modelling radio foregrounds at frequencies <400~MHz. B-GSM aims to address the limitations of previous models by incorporating robust error…

Instrumentation and Methods for Astrophysics · Physics 2025-11-12 George Carter , Will Handley , Mark Ashdown , Nima Razavi-Ghods

In this work the finite $\beta$-effects of an electron branch of the geodesic acoustic mode (el-GAM) driven by electron temperature gradient (ETG) modes is presented. The work is based on a fluid description of the ETG mode retaining…

Plasma Physics · Physics 2013-12-23 Johan Anderson , Hans Nordman , Andreas Skyman , Raghvendra Singh , Predhiman Kaw

The spatio-temporal Epidemic Type Aftershock Sequence (ETAS) model is widely used to describe the self-exciting nature of earthquake occurrences. While traditional inference methods provide only point estimates of the model parameters, we…

Taking the collisionless damping of geodesic acoustic mode (GAM) as an example, the physics processes underlying wave particle resonances in the short wavelength limit are clarified. As illus- trative application, GAM excitation by…

Plasma Physics · Physics 2018-02-14 Liu Chen , Zhiyong Qiu , Fulvio Zonca

The recently proposed non-Gaussian Mat\'{e}rn random field models, generated through Stochastic Partial differential equations (SPDEs), are extended by considering the class of Generalized Hyperbolic processes as noise forcings. The models…

Applications · Statistics 2013-07-25 David Bolin , Jonas Wallin

The Exponential Moving Average (EMA) is a cornerstone of widely used optimizers such as Adam. However, existing theoretical analyses of Adam-style methods have notable limitations: their guarantees can remain suboptimal in the zero-noise…

Machine Learning · Computer Science 2026-04-17 Ganzhao Yuan
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