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In many physical situations involving diverse length scales, waves or rays representing them travel through media characterized by spatially smooth, random, modest refactive index variations. "Primary" diffraction (by individual…

Classical Physics · Physics 2021-12-14 Eric J Heller , Ragnar Fleischmann , Tobias Kramer

In linearly stable shear flows at moderate Re, turbulence spontaneously decays despite the existence of a codimension-one manifold, termed the edge of chaos, which separates decaying perturbations from those triggering turbulence. We…

Fluid Dynamics · Physics 2015-06-17 Matthew Chantry , Tobias M. Schneider

While theoretically appealing, the application of the Wasserstein distance to large-scale machine learning problems has been hampered by its prohibitive computational cost. The sliced Wasserstein distance and its variants improve the…

Machine Learning · Computer Science 2022-03-18 Xiongjie Chen , Yongxin Yang , Yunpeng Li

In turbulent flows, energy production is associated with highly organized structures, known as coherent structures. Since these structures are three-dimensional, their detection remains challenging in the most common situation, when…

Fluid Dynamics · Physics 2023-09-12 Subharthi Chowdhuri , Tirtha Banerjee

Natural ecosystems are characterized by striking diversity of form and functions and yet exhibit deep symmetries emerging across scales of space, time and organizational complexity. Species-area relationships and species-abundance…

Transport in crowded, complex environments occurs across many spatial scales. Geometric restrictions can hinder the motion of individuals and, combined with crowding between individuals, can have drastic effects on global transport…

Physics and Society · Physics 2021-08-11 Daniel B. Wilson , Francis G. Woodhouse , Matthew J. Simpson , Ruth E. Baker

Long-lived flow patterns in the atmosphere such as weather fronts, mid-latitude blockings or tropical cyclones often induce extreme weather conditions. As a consequence, their description, detection, and tracking has received increasing…

Spatial confounding is a persistent challenge in spatial statistics, influencing the validity of statistical inference in models that analyze spatially-structured data. The concept has been interpreted in various ways but is broadly defined…

An accurate description of the structure and dynamics of interfacial water is essential for phospholipid membranes, since it determines their function and their interaction with other molecules. Here we consider water confined in stacked…

Soft Condensed Matter · Physics 2018-11-16 Sotiris Samatas , Carles Calero , Fausto Martelli , Giancarlo Franzese

We present a first order scheme based on a staggered grid for the shallow water equations with topography in two space dimensions, which enjoys several properties: positivity of the water height, preservation of constant states, and weak…

Numerical Analysis · Mathematics 2019-06-27 Raphaèle Herbin , Jean-Claude Latché , Youssouf Nasseri , Nicolas Therme

Water shapes and defines the properties of biological systems. Therefore, understanding the nature of the mutual interaction between water and biological systems is of primary importance for a proper assessment of biological activity and…

Soft Condensed Matter · Physics 2021-01-18 Fausto Martelli , Carles Calero , Giancarlo Fanzese

Rainfall in coastal areas of the tropics is often shaped by the presence of circulations directly associated with the topography, such as land-sea and/or mountain-valley breezes. In many regions the coastally-affected rainfall consitutes…

Atmospheric and Oceanic Physics · Physics 2016-05-09 Martin Bergemann , Christian Jakob , Todd P. Lane

Superstatistics is a general method from nonequilibrium statistical physics which has been applied to a variety of complex systems, ranging from hydrodynamic turbulence to traffic delays and air pollution dynamics. Here, we investigate…

Atmospheric and Oceanic Physics · Physics 2024-08-12 Benjamin Schäfer , Catherine M. Heppell , Hefin Rhys , Christian Beck

Street networks, as one of the oldest infrastructures of transport in the world, play a significant role in modernization, sustainable development, and human daily activities in both ancient and modern times. Although street networks have…

Physics and Society · Physics 2015-04-01 Bin Jiang , Atsuyuki Okabe

Scaling has been proposed as a powerful tool to analyze the properties of complex systems, and in particular for cities where it describes how various properties change with population. The empirical study of scaling on a wide range of…

Physics and Society · Physics 2018-04-18 Jules Depersin , Marc Barthelemy

Understanding how rivers adjust to the sediment load they carry is critical to predicting the evolution of landscapes. Presently, however, no physically based model reliably captures the dependence of basic river properties, such as its…

Fluid Dynamics · Physics 2022-03-09 Predrag Popović , Olivier Devauchelle , Anaïs Abramian , Eric Lajeunesse

Leveraging recent advances in technologies surrounding the Internet of Things, "smart" water systems are poised to transform water resources management by enabling ubiquitous real-time sensing and control. Recent applications have…

Systems and Control · Computer Science 2017-08-18 Matthew Bartos , Brandon Wong , Branko Kerkez

Global coastlines and their dense populations have an uncertain future due to increased flooding, storms, and human modification. The distributary channel networks of deltas and marshes that plumb these coastlines present diverse…

Geophysics · Physics 2022-06-01 Adam Konkol , Jon Schwenk , Eleni Katifori , John Burnham Shaw

Land use expansion is linked to major sustainability concerns including climate change, food security and biodiversity loss. This expansion is largely concentrated in so-called frontiers, defined here as places experiencing marked…

The Wasserstein distance received a lot of attention recently in the community of machine learning, especially for its principled way of comparing distributions. It has found numerous applications in several hard problems, such as domain…

Machine Learning · Statistics 2017-10-23 Nicolas Courty , Rémi Flamary , Mélanie Ducoffe
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