Optimal first-arrival times in Lévy flights with resetting.

Phys Rev E Stat Nonlin Soft Matter Phys

Marian Smoluchowski Institute of Physics, Jagiellonian University, ul. Łojasiewicza 11, 30-348 Kraków, Poland and Mark Kac Complex Systems Research Center, Jagiellonian University, Kraków, Poland.

Published: November 2015

We consider the diffusive motion of a particle performing a random walk with Lévy distributed jump lengths and subject to a resetting mechanism, bringing the walker to an initial position at uniformly distributed times. In the limit of an infinite number of steps and for long times, the process converges to superdiffusive motion with replenishment. We derive a formula for the mean first arrival time (MFAT) to a predefined target position reached by a meandering particle and we analyze the efficiency of the proposed searching strategy by investigating criteria for an optimal (a shortest possible) MFAT.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevE.92.052127DOI Listing

Publication Analysis

Top Keywords

optimal first-arrival
4
first-arrival times
4
times lévy
4
lévy flights
4
flights resetting
4
resetting consider
4
consider diffusive
4
diffusive motion
4
motion particle
4
particle performing
4

Similar Publications

Through this paper, a three-dimensional molecular communication (MC) inside a cuboid container is considered. Instead of normal diffusion phenomenon, the anomalous diffusion phenomenon is incorporated which enhances the practicability of the model. The Fick's law is re-defined for the considering rectangular coordinate system in which information carrying molecules (ICMs) diffuse anomalously in the environment.

View Article and Find Full Text PDF

Effect of stochastic resettings on the counting of level crossings for inertial random processes.

Phys Rev E

July 2024

Department of Condensed Matter Physics and Institute of Complex Systems (UBICS), University of Barcelona, Catalonia 08028, Spain.

We study the counting of level crossings for inertial random processes exposed to stochastic resetting events. We develop the general approach of stochastic resetting for inertial processes with sudden changes in the state characterized by position and velocity. We obtain the level-crossing intensity in terms of that of underlying reset-free process for resetting events with Poissonian statistics.

View Article and Find Full Text PDF

Intermittent random walks under stochastic resetting.

Phys Rev E

March 2024

Grupo de Física Estadística, Departament de Física, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.

We analyze a one-dimensional intermittent random walk on an unbounded domain in the presence of stochastic resetting. In this process, the walker alternates between local intensive search, diffusion, and rapid ballistic relocations in which it does not react to the target. We demonstrate that Poissonian resetting leads to the existence of a non-equilibrium steady state.

View Article and Find Full Text PDF

A microseismic localization algorithm that combines global search and local optimization is proposed. The Fewer Conditions Trigger Difference (FCTD) objective function of global search and local optimization is constructed, the execution process of the algorithm is described by numerical simulation, and the global search and local optimization microseismic localization algorithm is verified and applied by field data analysis. The results show that: (1) the global search and local optimization methods have fast search speed in the global range, high convergence accuracy and stable localization results in the local range, and high localization accuracy and stability without relying on the velocity model and initial values in the process of search.

View Article and Find Full Text PDF

Image segmentation is important in improving the diagnostic capability of ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT), as it can be included in the image reconstruction process to improve image quality and quantification abilities. Segmenting the imaged object out of the background using image domain methods is easily complicated by low contrast, noise, and artifacts in the reconstructed image. Here, we introduce a new signal domain object segmentation method for USCT and PACT which does not require image reconstruction beforehand and is automatic, robust, computationally efficient, accurate, and straightforward.

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!