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We analyze energy spreading for a system that features mixed chaotic phase-space, whose control parameters (or slow degrees of freedom) vary quasi-statically. For demonstration purpose we consider the restricted 3~body problem, where the…

Statistical Mechanics · Physics 2022-05-10 Yehoshua Winsten , Doron Cohen

This paper introduces the Attracting Random Walks model, which describes the dynamics of a system of particles on a graph with $n$ vertices. At each step, a single particle moves to an adjacent vertex (or stays at the current one) with…

Probability · Mathematics 2020-06-01 Julia Gaudio , Yury Polyanskiy

Spatiotemporal dynamics models are fundamental for various domains, from heat propagation in materials to oceanic and atmospheric flows. However, currently available neural network-based spatiotemporal modeling approaches fall short when…

Machine Learning · Computer Science 2025-02-11 Valerii Iakovlev , Harri Lähdesmäki

Spreading processes on top of active dynamics provide a novel theoretical framework for capturing emerging collective behavior in living systems. I consider run-and-tumble dynamics coupled with coagulation/decoagulation reactions that lead…

Statistical Mechanics · Physics 2025-05-29 Matteo Paoluzzi

Vessel trajectory prediction is a critical component for ensuring maritime traffic safety and avoiding collisions. Due to the inherent uncertainty in vessel behavior, trajectory prediction systems must adopt a multimodal approach to…

Artificial Intelligence · Computer Science 2025-03-12 Jin Wenzhe , Tang Haina , Zhang Xudong

Decadal temperature prediction provides crucial information for quantifying the expected effects of future climate changes and thus informs strategic planning and decision-making in various domains. However, such long-term predictions are…

Machine Learning · Computer Science 2023-04-20 Jinfu Ren , Yang Liu , Jiming Liu

The importance of modelling temperature fields goes beyond the need to understand a region's climate and serves too as a starting point for understanding their socioeconomic, and health consequences. The topography of the study region…

Applications · Statistics 2016-04-05 Camila M. Casquilho-Resende , Nhu D. Le , James V. Zidek

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a dynamic statistical model to quantify the impact of climate change on the structural…

Applications · Statistics 2022-08-17 Xinyi Lu , Mevin B. Hooten , Ann M. Raiho , David K. Swanson , Carl A. Roland , Sarah E. Stehn

Turbulence, namely, irregular fluctuations in space and time characterize fluid flows in general and atmospheric flows in particular.The irregular,i.e., nonlinear space-time fluctuations on all scales contribute to the unpredictable nature…

General Physics · Physics 2007-05-23 J. S. Pethkar , A. M. Selvam

Characterising the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study,…

Atmospheric and Oceanic Physics · Physics 2016-09-28 Gualtiero Badin , Daniela I. V. Domeisen

We develop a general theory dealing with stochastic models for dynamical systems that are governed by various nonlinear, ordinary or partial differential, equations. In particular, we address the problem how flows in the random medium…

chao-dyn · Physics 2009-10-31 Piotr Garbaczewski

In this article, we derive the stochastic master equations corresponding to the statistical model of a heat bath. These stochastic differential equations are obtained as continuous time limits of discrete models of quantum repeated…

Quantum Physics · Physics 2010-06-17 Ion Nechita , Clément Pellegrini

Studies agree on a significant global mean sea level rise in the 20th century and its recent 21st century acceleration in the satellite record. At regional scale, the evolution of sea level probability distributions is often assumed to be…

Atmospheric and Oceanic Physics · Physics 2023-04-05 Fabrizio Falasca , Andrew Brettin , Laure Zanna , Stephen M. Griffies , Jianjun Yin , Ming Zhao

Over the last few decades, climate scientists have devoted much effort to the development of large numerical models of the atmosphere and the ocean. While there is no question that such models provide important and useful information on…

Atmospheric and Oceanic Physics · Physics 2009-08-25 Michel Crucifix , Jonathan Rougier

Forest fire spreading is a complex phenomenon characterized by a stochastic behavior. Nowadays, the enormous quantity of georeferenced data and the availability of powerful techniques for their analysis can provide a very careful picture of…

Populations and Evolution · Quantitative Biology 2023-09-06 Roberto Beneduci , Giovanni Mascali

The horizontal dynamics of a bouncing ball interacting with an irregular surface is investigated and is found to demonstrate behavior analogous to a random walk. Its stochastic character is substantiated by the calculation of a permutation…

Physics Education · Physics 2025-09-15 Luiz Antonio Barreiro

Many stars, active galactic nuclei, accretion discs etc. are affected by the stochastic variations of temperature, turbulent gas motions, magnetic fields, number densities of atoms and dust grains. These stochastic variations influence on…

Solar and Stellar Astrophysics · Physics 2017-12-20 N. A. Silant'ev , G. A. Alekseeva , V. V. Novikov

We derive the stochastic master equations which describe the evolution of open quantum systems in contact with a heat bath and undergoing indirect measurements. These equations are obtained as a limit of a quantum repeated measurement model…

Mathematical Physics · Physics 2010-04-21 S Attal , C Pellegrini

We study the diffusion process in a Heisenberg chain with correlated spatial disorder, with a power spectrum in the momentum space behaving as $k^{-\beta}$, using a stochastic description. It establishes a direct connection between the…

Statistical Mechanics · Physics 2007-05-23 M. H. Vainstein , R. Morgado , F. A. Oliveira , F. A. B. F. de Moura , M. D. Coutinho-Filho

Diffusion models have recently been increasingly applied to temporal data such as video, fluid mechanics simulations, or climate data. These methods generally treat subsequent frames equally regarding the amount of noise in the diffusion…

Machine Learning · Computer Science 2024-09-10 David Ruhe , Jonathan Heek , Tim Salimans , Emiel Hoogeboom
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