Issue |
EPL
Volume 137, Number 6, March 2022
|
|
---|---|---|
Article Number | 61002 | |
Number of page(s) | 5 | |
Section | Statistical physics and networks | |
DOI | https://doi.org/10.1209/0295-5075/ac5fd0 | |
Published online | 07 May 2022 |
Nonlinear mapping between continuous- and discrete-time dynamics
1 School of Physics, Northwest University - Xi'an 710069, China
2 Shaanxi Key Laboratory for Theoretical Physics Frontiers - Xi'an 710069, China
3 School of Physics and Electronic-Electrical Engineering, Ningxia University - Yinchuan 750021, China
4 School of Science, East China University of Technology - Nanchang, Jiangxi 330013, China
5 Yangtze Delta Region Institute of University of Electronic Science and Technology of China Huzhou, Zhejiang 313000, China
6 Institute of Computational Physics and Complex Systems, Lanzhou University - Lanzhou, Gansu 730000, China
(a) ccr@nwu.edu.cn (corresponding author)
Received: 22 January 2022
Accepted: 22 March 2022
Linear mapping is widely used in dynamic modeling and empirical data analysis, but it suffers from the serious shortcoming that it does not work in the common case of time intervals being large. The fundamental cause of the failure is that the linear mapping does not take into account the coupling effects of multiple events within a discrete time interval. Here, we develop a theoretical framework to provide a nonlinear mapping between continuous- and discrete-time dynamics by accounting for the coupling effect. We have verified the effectiveness of our mapping by exploring classical susceptible-infected-susceptible and susceptible-infected-recovered models. In particular, we give a quantitative criterion that the sum of two transition probabilities —from one state to the other and vice versa— must be strictly less than 1 for binary-state dynamics.
© 2022 EPLA
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.