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The present work investigates the evolution of linear perturbations of time-dependent ideal fluid flows with advected quantities, expressed in terms of the second order variations of the action corresponding to a Lagrangian defined on a…

Fluid Dynamics · Physics 2024-04-02 Darryl D. Holm , Ruiao Hu , Oliver D. Street

We present a proof-of-principle implementation of the first fully covariant filtering scheme applied to relativistic fluid turbulence. The filtering is performed with respect to special observers, identified dynamically as moving with the…

High Energy Astrophysical Phenomena · Physics 2025-01-07 T. Celora , M. J. Hatton , I. Hawke , N. Andersson

We make a perturbative analysis of spatially covariant gravity only respecting spatial symmetries, of which the Lagrangian includes the dynamic lapse function and the coupling term of spatial curvature and extrinsic curvature. We show that…

General Relativity and Quantum Cosmology · Physics 2022-12-29 Xuezheng Zhu

Oceanic surface flows are dominated by finite-time Lagrangian coherent structures that separate regions of qualitatively different dynamical behavior. Among these, eddy boundaries are of particular interest. Their exact identification is…

Atmospheric and Oceanic Physics · Physics 2019-05-17 Benedict Lünsmann , Holger Kantz

We present a constructive derivation of a time-dependent deformation functional theory -- a collective variable approach to the nonequalibrium quantum many-body problem. It is shown that the motion of infinitesimal fluid elements (i.e. a…

Strongly Correlated Electrons · Physics 2011-09-19 I. V. Tokatly

Due to large scale flow inhomogeneities and the effects of temperature, turbulence small-scale structure in thermal convection is still an active field of investigation, especially considering sophisticated Lagrangian statistics. Here we…

Turbulence in the upper ocean in the submesoscale range (scales smaller than the deformation radius) plays an important role for the heat exchange with the atmosphere and for oceanic biogeochemistry. Its dynamics should strongly depend on…

Fluid Dynamics · Physics 2021-03-31 Stefano Berti , Guillaume Lapeyre

Vehicle trajectory data collected via GPS-enabled devices have played increasingly important roles in estimating network-wide traffic, given their broad spatial-temporal coverage and representativeness of traffic dynamics. This paper…

Physics and Society · Physics 2018-10-01 Jielun Liu , Ke Han , Xiqun , Chen , Ghim Ping Ong

Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge. They are non-negative, skewed, heavy tailed, contain a…

Methodology · Statistics 2015-06-22 Erwan Koch , Philippe Naveau

Methods of dynamical system's theory are used for numerical study of transport and mixing of passive particles (water masses, temperature, salinity, pollutants, etc.) in simple kinematic ocean models composed with the main Eulerian coherent…

Chaotic Dynamics · Physics 2015-06-26 M. V. Budyansky , M. Yu. Uleysky , S. V. Prants

High-dimensional multivariate spatial-temporal data arise frequently in a wide range of applications; however, there are relatively few statistical methods that can simultaneously deal with spatial, temporal and variable-wise dependencies…

Methodology · Statistics 2020-02-05 Elynn Y. Chen , Xin Yun , Rong Chen , Qiwei Yao

New aspects of turbulence are uncovered if one considers flow motion from the perspective of a fluid particle (known as the Lagrangian approach) rather than in terms of a velocity field (the Eulerian viewpoint). Using a new experimental…

Fluid Dynamics · Physics 2009-11-07 N. Mordant , J. Delour , E. Leveque , A. Arneodo , J. -F. Pinton

As a mathematical model of high-speed flow and shock wave propagation in a complex multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts with sharp…

Numerical Analysis · Mathematics 2021-11-24 Dylan Matthew Copeland , Siu Wun Cheung , Kevin Huynh , Youngsoo Choi

This paper introduces a linear state-space model with time-varying dynamics. The time dependency is obtained by forming the state dynamics matrix as a time-varying linear combination of a set of matrices. The time dependency of the weights…

Machine Learning · Statistics 2014-10-06 Jaakko Luttinen , Tapani Raiko , Alexander Ilin

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate…

Applications · Statistics 2012-03-02 Huiyan Sang , Mikyoung Jun , Jianhua Z. Huang

In this paper, a useful reinterpretation of the city as a porous medium justifies the application of well-known models on fluid dynamics to develop a multi-model study of urban air pollution due to traffic flow in a large city. Thus, to…

Numerical Analysis · Mathematics 2025-02-21 N. Garcia-Chan , L. J. Alvarez-Vazquez , A. Martinez , M. E. Vazquez-Mendez

We present a unified derivation of covariant time derivatives, which transform as tensors under a time-dependent coordinate change. Such derivatives are essential for formulating physical laws in a frame-independent manner. Three specific…

Chaotic Dynamics · Physics 2009-11-07 Jean-Luc Thiffeault

Swarming phenomena are ubiquitous in various physical, biological, and social systems, where simple local interactions between individual units lead to complex global patterns. A common feature of diverse swarming phenomena is that the…

Statistical Mechanics · Physics 2023-04-05 Yang Tian , Yunhui Xu , Pei Sun

Lagrangian formulation of kinematic wave provides a more accurate representation than the most commonly used Eulerian formulation. Furthermore, Lagrangian representation offers a flexibility to study certain traffic phenomena (e.g. capacity…

Optimization and Control · Mathematics 2018-04-26 Sosina Gashaw , Jérôme Härri , Paola Goatin

We develop a convex framework for spatially varying coefficient quantile regression that, for each predictor, separates a location-invariant \emph{global} effect from a \emph{spatial deviation}. An adaptive group penalty selects whether a…

Methodology · Statistics 2025-11-26 Hou Jian , Meng Tan , Tian Maozai