We show that the well-known linear Langevin equation, modeling the Brownian motion and leading to a Gaussian stationary distribution of the corresponding Fokker-Planck equation, is changed by the smallest multiplicative noise. This leads to a power-law tail of the distribution for sufficiently large momenta. At finite ratio of the correlation strength for the multiplicative and the additive noises the stationary energy distribution becomes exactly the Tsallis distribution.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevLett.94.132302DOI Listing

Publication Analysis

Top Keywords

multiplicative noise
8
power-law tails
4
tails multiplicative
4
noise well-known
4
well-known linear
4
linear langevin
4
langevin equation
4
equation modeling
4
modeling brownian
4
brownian motion
4

Similar Publications

A comparative analysis of perceptual noise in lateral and depth motion: Evidence from eye tracking.

J Vis

January 2025

Vision and Control of Action (VISCA) Group, Department of Cognition, Development and Psychology of Education, Institut de Neurociències, Universitat de Barcelona, Barcelona, Catalonia, Spain.

The characterization of how precisely we perceive visual speed has traditionally relied on psychophysical judgments in discrimination tasks. Such tasks are often considered laborious and susceptible to biases, particularly without the involvement of highly trained participants. Additionally, thresholds for motion-in-depth perception are frequently reported as higher compared to lateral motion, a discrepancy that contrasts with everyday visuomotor tasks.

View Article and Find Full Text PDF

Stochastic Filtering of the Attitude Quaternion.

Sensors (Basel)

December 2024

Mechanical Engineering Department, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel.

Several stochastic H∞ filters for estimating the attitude of a rigid body from line-of-sight measurements and rate gyro readings are developed. The measurements are corrupted by white noise with unknown variances. Our approach consists of estimating the quaternion while attenuating the transmission gain from the unknown variances and initial errors to the current estimation error.

View Article and Find Full Text PDF

In this paper, the unified approach is used in acquiring some new results to the coupled Maccari system (MS) in Itô sense with multiplicative noise. The MS is a nonlinear model used in hydrodynamics, plasma physics, and nonlinear optics to represent isolated waves in a restricted region. We provide new results with complicated structures to this model, including hyperbolic, trigonometric and rational function solutions.

View Article and Find Full Text PDF

Study on the effect of occupational exposure on hypertension of steelworkers based on Lasso-Logistic regression model.

Public Health

December 2024

Department of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China; Hebei Key Laboratory of Coal Health and Safety, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China. Electronic address:

Objectives: This study aimed to use a stable and predictive method: Lasso regression model to analyze hypertension's influencing factors and explore the interactions between occupational exposures.

Study Design: This has been a nested case-control study.

Methods: The case group consisted of 959 patients with high blood pressure found during the study.

View Article and Find Full Text PDF

The Kuramoto model has provided deep insights into synchronization phenomena and remains an important paradigm to study the dynamics of coupled oscillators. Yet, despite its success, the asynchronous regime in the Kuramoto model has received limited attention. Here, we adapt and enhance the mean-field approach originally proposed by Stiller and Radons [Phys.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!