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We study the Ising model under a time-varying, but spatially homogeneous, Gaussian random magnetic field. In the Monte Carlo simulations, we go beyond the standard analysis of the order parameter by measuring the magnetization probability…

统计力学 · 物理学 2026-03-30 Sara Oliver-Bonafoux , Raul Toral , Amitabha Chakrabarti

Experimental, analytical, and numerical results suggest that the mechanism by which a uniaxial single-domain ferromagnet switches after sudden field reversal depends on the field magnitude and the system size. Here we report new results on…

凝聚态物理 · 物理学 2009-10-28 S. W. Sides , R. A. Ramos , P. A. Rikvold , M. A. Novotny

We study hysteresis for a two-dimensional, spin-1/2, nearest-neighbor, kinetic Ising ferromagnet in an oscillating field, using Monte Carlo simulations and analytical theory. Attention is focused on small systems and weak field amplitudes…

材料科学 · 物理学 2009-10-30 S. W. Sides , P. A. Rikvold , M. A. Novotny

We study, using Monte Carlo dynamics, the time ($t$) dependent average magnetization per spin $m(t)$ behavior of 2-D kinetic Ising model under a binary ($\pm h_0$) stochastic field $h(t)$. The time dependence of the stochastic field is such…

统计力学 · 物理学 2013-12-02 Asim Ghosh , Bikas K. Chakrabarti

We study a one-dimensional Ising model with a magnetic field and show that tilting the field induces a transition to quantum chaos. We explore the stationary states of this Hamiltonian to show the intimate connection between entanglement…

量子物理 · 物理学 2009-11-13 J. Karthik , Auditya Sharma , Arul Lakshminarayan

Stochastic dynamical systems allow modelling of transitions induced by disturbances, in particular from an attracting equilibrium and crossing the stable manifold of a saddle. In the small-noise limit, the probability of such transitions is…

统计力学 · 物理学 2025-09-05 Jiayao Shao , Tobias Grafke , Robert S. MacKay

We consider particles that are conditioned to initial and final states. The trajectory of these particles is uniquely shaped by the intricate interplay of internal and external sources of randomness. The internal randomness is aptly…

最优化与控制 · 数学 2023-09-13 Daniel Owusu Adu , Yongxin Chen

In this paper we develop a perturbation method to predict the rate of occurrence of rare events for singularly perturbed stochastic systems using a probability density function approach. In contrast to a stochastic normal form approach, we…

动力系统 · 数学 2015-06-16 Christoffer R. Heckman , Ira B. Schwartz

In a recent letter [Phys.Rev.Lett. {\bf 30}, 3269 (1995), chao-dyn/9510011], we reported that a macroscopic chaotic determinism emerges in a multistable system: the unidirectional motion of a dissipative particle subject to an apparently…

chao-dyn · 物理学 2009-10-28 Tsuyoshi Hondou , Yasuji Sawada

We investigate how a quenched random field influences the damage spreading transition in kinetic Ising models. To this end we generalize a recent master equation approach and derive an effective field theory for damage spreading in random…

统计力学 · 物理学 2009-10-30 Thomas Vojta

To probe the connection between the dynamic phase transition and stochastic resonance, we study the mean-field kinetic Ising model and the two-dimensional Josephson-junction array in the presence of appropriate oscillating magnetic fields.…

统计力学 · 物理学 2007-05-23 Beom Jun Kim , Petter Minnhagen , Hyun Jin Kim , M. Y. Choi , Gun Sang Jeon

It seems that a stochastic system must be a nonlinear one to observe the phenomenon, noise induced transition. But in the present paper, we have demonstrated that the phenomenon may be observed even in a linear stochastic process where both…

统计力学 · 物理学 2022-01-04 Shrabani Mondal , L. R. Rahul Biswas , Mousumi Biswas , Bidhan Chandra Bag

Diverse complex dynamical systems are known to exhibit abrupt regime shifts at bifurcation points of the saddle-node type. The dynamics of most of these systems, however, have a stochastic component resulting in noise driven regime shifts…

统计力学 · 物理学 2013-10-29 Sayantari Ghosh , Amit Kumar Pal , Indrani Bose

We investigate the stochastic resonance phenomena in the field-driven Ising model on small-world networks. The response of the magnetization to an oscillating magnetic field is examined by means of Monte Carlo dynamic simulations, with the…

无序系统与神经网络 · 物理学 2009-11-07 H. Hong , Beom Jun Kim , M. Y. Choi

This paper considers the state transition of the stochastic Morris-Lecar neuronal model driven by symmetric $\alpha$-stable L\'evy noise. The considered system is bistable: a stable fixed point (resting state) and a stable limit cycle…

动力系统 · 数学 2019-06-19 Rui Cai , Yancai Liu , Jinqiao Duan , Almaz Tesfay Abebe

We consider the transport statistics of classical bistable systems driven by noise. The stochastic path integral formalism is used to investigate the dynamics and distribution of transmitted charge. Switching rates between the two stable…

统计力学 · 物理学 2007-05-23 Andrew N. Jordan , Eugene V. Sukhorukov

We study long-range interacting systems driven by external stochastic forces that act collectively on all the particles constituting the system. Such a scenario is frequently encountered in the context of plasmas, self-gravitating systems,…

统计力学 · 物理学 2013-12-03 Cesare Nardini , Shamik Gupta , Stefano Ruffo , Thierry Dauxois , Freddy Bouchet

Many complex real world phenomena exhibit abrupt, intermittent or jumping behaviors, which are more suitable to be described by stochastic differential equations under non-Gaussian L\'evy noise. Among these complex phenomena, the most…

数值分析 · 数学 2023-09-15 Wei Wei , Ting Gao , Jinqiao Duan , Xiaoli Chen

We analyse biased ensembles of trajectories for the random-field Ising model on a fully-connected lattice, which is described exactly by mean-field theory. By coupling the activity of the system to a dynamical biasing field, we find a range…

统计力学 · 物理学 2021-10-27 Jules Guioth , Robert L. Jack

This paper considers the problem of steering the state distribution of a nonlinear stochastic system from an initial Gaussian to a terminal distribution with a specified mean and covariance, subject to probabilistic path constraints. An…

最优化与控制 · 数学 2019-09-16 Jack Ridderhof , Kazuhide Okamoto , Panagiotis Tsiotras
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