The property of sensitive dependence on intial conditions is the basis of a rigorous mathematical construction of local maximum Lyapunov exponents for cellular automata. The maximum Lyapunov exponent is given by the fastest average velocity of either the left or right propagating damage fronts. Deviations from the long term behavior of the finite time Lyapunov exponents due to generation of information are quantified and could be used for the characterization of the space time complexity of cellular automata. (c) 1997 American Institute of Physics.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1063/1.166266 | DOI Listing |
Sci Rep
January 2025
Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.
According to recent research, with the ever-increasing use of Internet of Things (IoT) devices, there has arisen an ever-growing need for high-performance yet low-power circuits that can efficiently process information. Quantum-dot Cellular Automata (QCA) has emerged as a promising alternative to conventional complementary metal-oxide-semiconductor (CMOS) technology due to its great potential in digital design at nanoscale levels on account of very low power consumption and very high processing speed. However, QCA circuits are inherently prone to faults due to variations in manufacturing processes and due to the influence of environmental factors.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
The increasing trend in land surface temperature (LST) and the formation of urban heat islands (UHIs) has emerged as a persistent challenge for urban planners and decision-makers. The current research was carried out to study the land use and land cover (LULC) changes and associated LST patterns in the planned city (Kabul) and the unplanned city (Jalalabad), Afghanistan, using Support Vector Machine (SVM) and Landsat data from 1998 to 2018. Future changes in LULC and LST were predicted for 2028 and 2038 using Cellular Automata-Markov (CA-Markov) and Artificial Neural Network (ANN) models.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Mathematical and Physical Sciences, Macquarie University, Sydney, NSW 2109, Australia.
The density classification (DC) task, a computation which maps global density information to local density, is studied using one-dimensional non-unitary quantum cellular automata (QCAs). Two approaches are considered: one that preserves the number density and one that performs majority voting. For number-preserving DC, two QCAs are introduced that reach the fixed-point solution in a time scaling quadratically with the system size.
View Article and Find Full Text PDFChaos
January 2025
Department of Civil Engineering, The University of Hong Kong, HKSAR 999077, China.
Porous earth materials exhibit large-scale deformation patterns, such as deformation bands, which emerge from complex small-scale interactions. This paper introduces a cross-diffusion framework designed to capture these multiscale, multiphysics phenomena, inspired by the study of multi-species chemical systems. A microphysics-enriched continuum approach is developed to accurately predict the formation and evolution of these patterns.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
Department of Anatomy, Kanazawa Medical University, Uchinada, Ishikawa 9200293, Japan.
Acute myeloid leukaemia (AML) is a haematologic malignancy with high relapse rates in both adults and children. Leukaemic stem cells (LSCs) are central to leukaemopoiesis, treatment response and relapse and frequently associated with measurable residual disease (MRD). However, the dynamics of LSCs within the AML microenvironment is not fully understood.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!