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Related papers: Predicting catastrophic shifts

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What are the signatures of the onset of catastrophe? Here we present the rich system physics characterizing the transition from homeostasis to stochasticity driven breakdown in an experimentally motivated minimal model. Recent…

Statistical Mechanics · Physics 2025-07-09 Rudro R. Biswas , Charles S. Wright , Kunaal Joshi , Srividya Iyer-Biswas

Synchronization transitions are investigated in coupled chaotic maps. Depending on the relative weight of linear versus nonlinear instability mechanisms associated to the single map two different scenarios for the transition may occur. When…

Chaotic Dynamics · Physics 2009-11-11 Massimo Cencini , Alessandro Torcini

This paper proposes an early detection method for cluster structural changes. Cluster structure refers to discrete structural characteristics, such as the number of clusters, when data are represented using finite mixture models, such as…

Machine Learning · Statistics 2024-03-28 Kento Urano , Ryo Yuki , Kenji Yamanishi

A reliable understanding of the Earth system is essential for the life quality of modern society. Natural hazards are the cause of most life and resource losses. The ability to define the conditions for a sustainable development of…

Chaotic Dynamics · Physics 2025-04-08 Jürgen Kurths , Ankit Agarwal , Ugur Öztürk , Shubham Sharma , Norbert Marwan , Deniz Eroglu

We propose that catastrophic events are "outliers" with statistically different properties than the rest of the population and result from mechanisms involving amplifying critical cascades. Applications and the potential for prediction are…

Statistical Mechanics · Physics 2009-11-07 D. Sornette

The study of chaos has long relied on computationally intensive methods to quantify unpredictability and design control strategies. Recent advances in machine learning, from convolutional neural networks to transformer architectures,…

Chaotic Dynamics · Physics 2026-01-30 David Valle , Alexandre Wagemakers , Miguel A. F. Sanjuán

Unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering…

Computational Physics · Physics 2018-12-06 Nicholas Walker , Ka-Ming Tam , Brian Novak , M. Jarrell

Interacting many-particle systems can self-organize into a rich variety of crystalline structures. While symmetry provides a powerful framework for predicting whether transitions between crystal states are continuous or discontinuous,…

Atomic Physics · Physics 2026-03-20 Akhil Ayyadevara , Anand Prakash , Shovan Dutta , Arun Paramekanti , S. A. Rangwala

Graphs are commonly used to represent and visualize causal relations. For a small number of variables, this approach provides a succinct and clear view of the scenario at hand. As the number of variables under study increases, the graphical…

Machine Learning · Statistics 2023-08-16 Santtu Tikka , Jouni Helske , Juha Karvanen

In a range of scientific coauthorship networks, transitions emerge in degree distributions, correlations between degrees and local clustering coefficients, etc. The existence of those transitions could be regarded as a result of the…

Physics and Society · Physics 2018-06-19 Zheng Xie , Enming Dong , Dongyun Yi , Ouyang Zhenzheng , Jianping Li

We introduce a model to study the impact of catastrophes on evolutionary paths. If we do not allow catastrophes the number of changes in the maximum fitness of a population grows logarithmically with respect to time. Allowing catastrophes…

Populations and Evolution · Quantitative Biology 2021-11-16 Rinaldo B. Schinazi

The percolation phase transition in complex network systems attracts much attention and has numerous applications in various research fields. Finite size effects smooth the transition and make it difficult to predict the critical point of…

Disordered Systems and Neural Networks · Physics 2026-02-11 A. V. Goltsev , S. N. Dorogovtsev

Whereas the importance of transient dynamics to the functionality and management of complex systems has been increasingly recognized, most of the studies are based on models. Yet in realistic situations the models are often unknown and what…

Adaptation and Self-Organizing Systems · Physics 2021-10-25 Huawei Fan , Liang Wang , Yao Du , Yafeng Wang , Jinghua Xiao , Xingang Wang

Bistable biological regulatory systems need to cope with stochastic noise to fine-tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative…

Adaptation and Self-Organizing Systems · Physics 2025-08-04 Daniele Proverbio , Arthur N. Montanari , Alexander Skupin , Jorge Gonçalves

Detecting critical transitions in complex, noisy time-series data is a fundamental challenge across science and engineering. Such transitions may be anticipated by the emergence of a low-dimensional order parameter, whose signature is often…

Machine Learning · Computer Science 2025-12-16 Wenqi Fang , Ye Li

The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states.…

Populations and Evolution · Quantitative Biology 2018-02-07 Haim Weissmann , Rafi Kent , Yaron Michael , Nadav M. Shnerb

The world surrounding us is subject to constant change. These changes, frequently described as concept drift, influence many industrial and technical processes. As they can lead to malfunctions and other anomalous behavior, which may be…

Machine Learning · Computer Science 2023-10-25 Fabian Hinder , Valerie Vaquet , Barbara Hammer

Species or population that proliferate faster than others become dominant in numbers. Catalysis allows catalytic sets within a molecular reaction network to dominate the non catalytic parts of the network by processing most of the available…

Cell Behavior · Quantitative Biology 2016-08-31 Rudolf Hanel

Determining the reachable set for a given nonlinear control system is crucial for system control and planning. However, computing such a set is impossible if the system's dynamics are not fully known. This paper is motivated by a scenario…

Optimization and Control · Mathematics 2021-08-26 Taha Shafa , Melkior Ornik

Safety assurance is critical in the planning and control of robotic systems. For robots operating in the real world, the safety-critical design often needs to explicitly address uncertainties and the pre-computed guarantees often rely on…

Robotics · Computer Science 2024-07-09 Hao Zhou , Yanze Zhang , Wenhao Luo
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