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The critical behavior at the frozen/active transition in the Domany-Kinzel stochastic cellular automaton (DKCA) is studied {\it via} a surface growth process in (1+1) dimensions. At criticality, this process presents a kinetic roughening…

Statistical Mechanics · Physics 2015-06-24 A. P. F. Atman , Ronald Dickman , J. G. Moreira

We consider a discrete-time system of n coupled random vectors, a.k.a. interacting particles. The dynamics involve a vanishing step size, some random centered perturbations, and a mean vector field which induces the coupling between the…

Probability · Mathematics 2025-06-09 Pascal Bianchi , Walid Hachem , Victor Priser

Stochastic optimal control problems have a long tradition in applied probability, with the questions addressed being of high relevance in a multitude of fields. Even though theoretical solutions are well understood in many scenarios, their…

Statistics Theory · Mathematics 2024-05-28 Sören Christensen , Claudia Strauch , Lukas Trottner

Detecting L\'evy flights of cells has been a challenging problem in experiments. The challenge lies in accessing data in spatiotemporal scales across orders of magnitude, which is necessary for reliably extracting a power-law scaling.…

Soft Condensed Matter · Physics 2026-05-07 Mingyang Li , Yu'an Li , H. P. Zhang , Yongfeng Zhao

The growing demand for robots to operate effectively in diverse environments necessitates the need for robust real-time anomaly detection techniques during robotic operations. However, deep learning-based models in robotics face significant…

Robotics · Computer Science 2025-06-24 Taewook Kang , Bum-Jae You , Juyoun Park , Yisoo Lee

Thorough analysis of local droplet-level interactions is crucial to better understand the microphysical processes in clouds and their effect on the global climate. High-accuracy simulations of relevant droplet size distributions from Large…

Modern generative models are usually designed to match target distributions directly in the data space, where the intrinsic dimension of data can be much lower than the ambient dimension. We argue that this discrepancy may contribute to the…

Machine Learning · Computer Science 2020-07-02 Zijun Zhang , Ruixiang Zhang , Zongpeng Li , Yoshua Bengio , Liam Paull

We study a lattice model where the coupling stochastically switches between repulsive (subtractive) and attractive (additive) at each site with probability p at every time instance. We observe that such kind of coupling stabilizes the local…

Chaotic Dynamics · Physics 2011-04-01 Abhijeet R. Sonawane

Abridged abstract: Inert interactions between randomly moving entities and spatial disorder play a crucial role in quantifying the diffusive properties of a system. These interactions affect only the movement of the entities, and examples…

Statistical Mechanics · Physics 2022-09-20 Seeralan Sarvaharman , Luca Giuggioli

We introduce a model for the spreading of epidemics by long-range infections and investigate the critical behaviour at the spreading transition. The model generalizes directed bond percolation and is characterized by a probability…

Statistical Mechanics · Physics 2009-10-31 Haye Hinrichsen , Martin Howard

Recently, the quantum contact process, in which branching and coagulation processes occur both coherently and incoherently, was theoretically and experimentally investigated in driven open quantum spin systems. In the semi-classical…

Statistical Mechanics · Physics 2020-02-21 Minjae Jo , B. Kahng

We present a numerical method to learn an accurate predictive model for an unknown stochastic dynamical system from its trajectory data. The method seeks to approximate the unknown flow map of the underlying system. It employs the idea of…

Machine Learning · Computer Science 2024-12-24 Zhongshu Xu , Yuan Chen , Qifan Chen , Dongbin Xiu

The long-time dynamics of the 1D contact process suddenly brought out of an uncorrelated initial state is studied through a light-cone transfer-matrix renormalisation group approach. At criticality, the system undergoes ageing which is…

Statistical Mechanics · Physics 2007-05-23 Tilman Enss , Malte Henkel , Alan Picone , Ulrich Schollwöck

The kinetics of encounter-controlled processes in growing domains is markedly different from that in a static domain. Here, we consider the specific example of diffusion limited coalescence and annihilation reactions in one-dimensional…

Statistical Mechanics · Physics 2018-10-22 F. Le Vot , C. Escudero , E. Abad , S. B. Yuste

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that…

Machine Learning · Statistics 2018-04-04 Christoph Wehmeyer , Frank Noé

We investigate the application of deep learning techniques employing the conditional variational autoencoders for semi-supervised learning of latent parameters to describe phase transition in the two-dimensional (2D) ferromagnetic Ising…

Statistical Mechanics · Physics 2023-06-30 Adwait Naravane , Nilmani Mathur

We employ deep learning techniques to investigate the critical properties of the continuous phase transition in the majority vote model. In addition to deep learning, principal component analysis is utilized to analyze the transition. For…

We consider the directed percolation process as a prototype of systems displaying a nonequilibrium phase transition into an absorbing state. The model is in a critical state when the activation probability is adjusted at some precise value…

Statistical Mechanics · Physics 2012-10-30 François Landes , E. A. Jagla , Alberto Rosso

Explosive percolation (EP) has received significant research attention due to its rich and anomalous phenomena near criticality. In our recent study [Phys. Rev. Lett. 130, 147101 (2023)], we demonstrated that the correct critical behaviors…

Statistical Mechanics · Physics 2024-09-20 Ming Li , Junfeng Wang , Youjin Deng

We numerically study bootstrap percolation on Kleinberg's spatial networks, in which the probability density function of a node to have a long-range link at distance $r$ scales as $P(r)\sim r^{\alpha}$. Setting the ratio of the size of the…

Physics and Society · Physics 2014-08-07 Jian Gao , Tao Zhou , Yanqing Hu
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