Related Experiment Video
Updated: Nov 25, 2025
05:56
Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
Published on: October 27, 2023
1.4K
Asymmetric stochastic resetting: Modeling catastrophic events.
Carlos A Plata1, Deepak Gupta1, Sandro Azaele1
1Dipartimento di Fisica "G. Galilei," INFN, Università di Padova, Via Marzolo 8, 35131 Padova, Italy.
Physical Review. E
|December 17, 2020
Summary
This study introduces asymmetric stochastic resetting, where systems reset only above a threshold. This modification alters optimal resetting behaviors and provides new insights into nonequilibrium steady states.
Area of Science:
- Physics
- Statistical Mechanics
- Complex Systems
Background:
- Classical stochastic resetting involves symmetric resets to a preferred location.
- Real-world systems often exhibit directional or asymmetric resetting mechanisms, like catastrophic events.
Purpose of the Study:
- To investigate a continuous stochastic process with a threshold-dependent, asymmetric resetting mechanism.
- To derive exact solutions for the nonequilibrium steady state and mean first passage time.
- To analyze how asymmetric resetting modifies classical results, such as optimal resetting.
Main Methods:
- Developed an analytical approach to determine the exact nonequilibrium steady state.
- Calculated the mean first passage time to the origin.
- Derived explicit solutions for two distinct model systems.
Main Results:
- Introduced a novel asymmetric stochastic resetting model where resets occur only when the system exceeds a threshold.
- Demonstrated significant modifications to classical stochastic resetting outcomes, including optimal resetting.
- Obtained exact analytical solutions for the steady state and first passage time.
Conclusions:
- Asymmetric stochastic resetting fundamentally alters system dynamics compared to symmetric resetting.
- The findings provide a more realistic framework for modeling natural systems with directional reset behaviors.
- Numerical simulations confirm the accuracy of the derived analytical results.
Related Concept Videos
01:15Assumptions of Survival Analysis
259
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
259
03:33Genetic Drift
42.1K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
42.1K
01:25Multimachine Stability
307
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
307
00:59Propagation of Uncertainty from Random Error
1.5K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.5K
01:09Censoring Survival Data
372
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
372
01:18Steps in Outbreak Investigation
364
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
364