Nonvanishing optimal noise in cellular automaton model of self-propelled particles

Du, Guangle; Ye, Fang-Fu

doi:10.1088/1674-1056/ac67c4

Cited by 4 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several papers have used the mean-field approximation to characterize CAs with gliders, but only for specific cases [23][24][25][26], in conjunction with other analysis tools [11] or limited to ECAs [27,28]. This paper aims to enrich the mean-field approach by identifying CAs with gliders in ECAs and automata with a larger number of states, making it a first attempt of its kind.…”

Section: Introductionmentioning

confidence: 99%

Mean-Field Analysis with Random Perturbations to Detect Gliders in Cellular Automata

Seck-Tuoh-Mora,

Medina-Marin,

Hernández-Romero

et al. 2023

Mathematics

View full text Add to dashboard Cite

Cellular automata are mathematical models that represent systems with complex behavior through simple interactions between their individual elements. These models can be used to study unconventional computational systems and complexity. One notable aspect of cellular automata is their ability to create structures known as gliders, which move in a regular pattern to represent the manipulation of information. This paper introduces the modification of mean-field theory applied to cellular automata, using random perturbations based on the system’s evolution rule. The original aspect of this approach is that the perturbation factor is tailored to the nature of the rule, altering the behavior of the mean-field polynomials. By combining the properties of both the original and perturbed polynomials, it is possible to detect when a cellular automaton is more likely to generate gliders without having to run evolutions of the system. This methodology is a useful approach to finding more examples of cellular automata that exhibit complex behavior. We start by examining elementary cellular automata, then move on to examples of automata that can generate gliders with more states. To illustrate the results of this methodology, we provide evolution examples of the detected automata.

show abstract

Section: Introductionmentioning

confidence: 99%

Mean-Field Analysis with Random Perturbations to Detect Gliders in Cellular Automata

Seck-Tuoh-Mora,

Medina-Marin,

Hernández-Romero

et al. 2023

Mathematics

View full text Add to dashboard Cite

show abstract

Noise-induced phase transition in the Vicsek model through eigen microstate methodology

Jia 贾,

Han 韩,

Li 李

2024

Chinese Phys. B

View full text Add to dashboard Cite

This paper presents a comprehensive framework for analyzing phase transitions in collective models like the Vicsek model under various noise types. The Vicsek model, focuses on understanding the collective behaviors of social animals, is known for its discontinuous phase transitions under vector noise. However, its behavior under scalar noise remains less conclusive. Renowned for its efficacy in the analysis of complex systems under both equilibrium and non-equilibrium state, the eigen microstate method is employed here for a quantitative examination of the phase transitions in the Vicsek model under both vector and scalar noise. The study finds that the Vicsek model exhibits discontinuous phase transitions regardless of noise type. Furthermore, the dichotomy method is utilized to identify the critical points for these phase transitions. A significant finding is the observed increase in the critical point for discontinuous phase transitions with the escalation of population density.

show abstract

Impacts of bus holding strategy on the performance and pollutant emissions of a two-lane mixed traffic system

Qiao 乔,

Yao 姚,

Pan 潘

et al. 2024

Chinese Phys. B

View full text Add to dashboard Cite

This paper investigates the impacts of a bus holding strategy on the mutual interference between buses and passenger cars in a non-dedicated bus route, as well as the impacts on the characteristics of pollutant emissions of passenger cars. The dynamic behaviors of these two types of vehicles are described using cellular automata (CA) models under open boundary conditions. Numerical simulations are carried out to obtain the phase diagrams of the bus system and the trajectories of buses and passenger cars before and after the implementation of the bus holding strategy under different probabilities of passenger cars entering a two-lane mixed traffic system. Then, we analyze the flow rate, satisfaction rate and pollutant emission rates of passenger cars together with the performance of a mixed traffic system. The results show that: the bus holding strategy can effectively alleviate bus bunching, whereas it has no significant impact on the flow rate and pollutant emission rates of passenger cars; the flow rate, satisfaction rate and pollutant emission rates of passenger cars for either the traffic system or for each lane are influenced by the bus departure interval and the number of passengers arriving at bus stops.

show abstract

Nonvanishing optimal noise in cellular automaton model of self-propelled particles

Cited by 4 publications

References 27 publications

Mean-Field Analysis with Random Perturbations to Detect Gliders in Cellular Automata

Mean-Field Analysis with Random Perturbations to Detect Gliders in Cellular Automata

Noise-induced phase transition in the Vicsek model through eigen microstate methodology

Impacts of bus holding strategy on the performance and pollutant emissions of a two-lane mixed traffic system

Contact Info

Product

Resources

About