Bit erasure analysis of binary adders in quantum-dot cellular automata

As a post-CMOS technology, the incipient Quantum-dot Cellular Automata technology has various advantages. A key aspect which makes it highly desirable is low power dissipation. One method that is used to analyse power dissipation in QCA circuits is bit erasure analysis. This method has been applied to analyse previously proposed QCA binary adders. However, a number of improved QCA adders have been proposed more recently that have only been evaluated in terms of area and speed. As the three key performance metrics for QCA circuits are speed, area and power, in this paper, a bit erasure analysis of these adders will be presented to determine their power dissipation. The adders to be analysed are the Carry Flow Adder (CFA), Brent-Kung Adder (B-K), Ladner-Fischer Adder (L-F) and a more recently developed area-delay efficient adder. This research will allow for a more comprehensive comparison between the different QCA adder proposals. To the best of the authors' knowledge, this is the first time power dissipation analysis has been carried out on these adders.

A First Step Towards Cost Functions for Quantum-dot Cellular Automata Designs

Quantum-dot cellular automata (QCA) is potentially a very attractive alternative to CMOS for future digital designs. Circuit designs in QCA have been extensively studied. However, how to properly evaluate the QCA circuits has not been carefully considered. To date, metrics and area-delay cost functions directly mapped from CMOS technology have been used to compare QCA designs, which is inappropriate due to the differences between these two technologies. In this paper, several cost metrics specifically aimed at QCA circuits are studied. It is found that delay, the number of QCA logic gates, and the number and type of crossovers, are important metrics that should be considered when comparing QCA designs. A family of new cost functions for QCA circuits is proposed. As fundamental components in QCA computing arithmetic, QCA adders are reviewed and evaluated with the proposed cost functions. By taking the new cost metrics into account, previous best adders become unattractive and it has been shown that different optimization goals lead to different “best” adders.

Cost-Efficient Decimal Adder Design in Quantum-dot Cellular Automata

Applications that cannot tolerate the loss of accuracy that results from binary arithmetic demand hardware decimal arithmetic designs. Binary arithmetic in Quantum-dot cellular automata (QCA) technology has been extensively investigated in recent years. However, only limited attention has been paid to QCA decimal arithmetic. In this paper, two cost-efficient binary-coded decimal (BCD) adders are presented. One is based on the carry flow adder (CFA) using a conventional correction method. The other uses the carry look ahead (CLA) algorithm which is the first QCA CLA decimal adder proposed to date. Compared with previous designs, both decimal adders achieve better performance in terms of latency and overall cost. The proposed CFA-based BCD adder has the smallest area with the least number of cells. The proposed CLA-based BCD adder is the fastest with an increase in speed of over 60% when compared with the previous fastest decimal QCA adder. It also has the lowest overall cost with a reduction of over 90% when compared with the previous most cost-efficient design.

Response curves of deterministic and probabilistic cellular automata in one and two dimensions

One of the most important problems in the theory of cellular automata (CA) is determining the proportion of cells in a specific state after a given number of time iterations. We approach this problem using patterns in preimage sets - that is, the set of blocks which iterate to the desired output. This allows us to construct a response curve - a relationship between the proportion of cells in state 1 after niterations as a function of the initial proportion. We derive response curve formulae for many two-dimensional deterministic CA rules with L-neighbourhood. For all remaining rules, we find experimental response curves. We also use preimage sets to classify surjective rules. In the last part of the thesis, we consider a special class of one-dimensional probabilistic CA rules. We find response surface formula for these rules and experimental response surfaces for all remaining rules.

Simulation of dynamic recrystallization using random grid cellular automata

Computer simulation is a powerful tool to predict microstructure and its evolution in dynamic and post-dynamic recrystallization. CAFE proposed as an appropriate approach by combining finite element (FE) method and cellular automata (CA) for recrystallization simulation. In the current study, a random grid cellular automaton (CA), as micro-scale model, based on finite element (FE), as macro-scale method, has been used to study initial and evolving microstructural features; including nuclei densities, dislocation densities, grain size and grain boundary movement during dynamic recrystallization in a C-Mn steel. An optimized relation has been established between mechanical variables and evolving microstructure features during recrystallization and grain growth. In this model, the microstructure is defined as cells located within grains and grain boundaries while dislocations are randomly dispersed throughout microstructure. Changes of dislocation density during deformation are described considering hardening, recovery and recrystallization. Recrystallization is assumed to initiate near grain boundaries and nucleation rate was considered constant (site-saturated condition). The model produced a mathematical formulation which captured the initial and evolving microstructural entities and linked their effects to measurable macroscopic variables (e.g. stress).

Microstructural modeling of dynamic recrystallization using irregular cellular automata

Cellular automaton (CA) was used to simulate dynamic recrystallization (DRX) during thermomechanical deformation. Initial grain size, initial grain orientation and dislocation density were used as input data to the CA model. Flow curve, dislocation density, final grain size and orientation, and DRX volume fraction were the output data which were compared with experimental data to validate the model. The model proposed in this work considered the thermomechanical parameters (e.g., temperature and strain rate) and their role on the nucleation and growth kinetics during DRX. It was shown that the CA model can predict the final microstructure and flow curve to a high degree of accuracy and was able to successfully simulate the volume fraction of DRX as a function of strain for a wide range of deformation conditions.

Simulating urban growth in a developing nation's region using a cellular automata-based model

Urbanization is one of the most evident global changes. Research in the field of urban growth modelling has generated models that explore for drivers and components of the urban growth dynamics. Cellular automata (CA) modeling is one of the recent advances, and a number of CA-based models of urban growth have produced satisfactory simulations of spatial urban expansion over time. Most application and test of CA-based models of urban growth which provide likely and reliable simulations has been developed in urban regions of developed nations; urban regions in the United States, in particular. This is because most of the models were developed in universities and research centers of developed nations, and these regions have the required data, which is extensive. Most of the population growth in the world, however, occurs in the developing world. While some European countries show signs of stabilization of their population, in less developed countries, such as India, population still grows exponentially. And this growth is normally uncoordinated, which results in serious environmental and social problems in urban areas. Therefore, the use of existing dynamic–spatial models of urban growth in regions of developing nations could be a means to assist planners and decision makers of these regions to understand and simulate the process of urban growth and test the results of different development strategies. The pattern of growth of urban regions of developing nations, however, seems to be different of the pattern of developed countries. The former use to be more dense and centralized, normally expanding outwards from consolidated urban areas; while the second is normally more fragmented and sparse. The present paper aims to investigate to how extent existing CA-based urban growth models tested in developed nations can also be applied to a developing country urban area. The urban growth model was applied to Porto Alegre City, Brazil. An expected contiguous expansion from existing urban areas has been obtained as following the historical trends of growth of the region. Moreover, the model was sensitive and able to portray different pattern of growth in the study area by changing the value of its parameters.

Evolutionary modeling of larval dispersal in blowflies using non-uniform cellular automata

When the food supply flnishes, or when the larvae of blowflies complete their development and migrate prior to the total removal of the larval substrate, they disperse to find adequate places for pupation, a process known as post-feeding larval dispersal. Based on experimental data of the Initial and final configuration of the dispersion, the reproduction of such spatio-temporal behavior is achieved here by means of the evolutionary search for cellular automata with a distinct transition rule associated with each cell, also known as a nonuniform cellular automata, and with two states per cell in the lattice. Two-dimensional regular lattices and multivalued states will be considered and a practical question is the necessity of discovering a proper set of transition rules. Given that the number of rules is related to the number of cells in the lattice, the search space is very large and an evolution strategy is then considered to optimize the parameters of the transition rules, with two transition rules per cell. As the parameters to be optimized admit a physical interpretation, the obtained computational model can be analyzed to raise some hypothetical explanation of the observed spatiotemporal behavior. © 2006 IEEE.

Modelling fungus dispersal scenarios using cellular automata

This study focused on representing spatio-temporal patterns of fungal dispersal using cellular automata. Square lattices were used, with each site representing a host for a hypothetical fungus population. Four possible host states were allowed: resistant, permissive, latent or infectious. In this model, the probability of infection for each of the healthy states (permissive or resistant) in a time step was determined as a function of the host's susceptibility, seasonality, and the number of infectious sites and the distance between them. It was also assumed that infected sites become infectious after a pre-specified latency period, and that recovery is not possible. Several scenarios were simulated to understand the contribution of the model's parameters and the spatial structure on the dynamic behaviour of the modelling system. The model showed good capability for representing the spatio-temporal pattern of fungus dispersal over planar surfaces. With a specific problem in mind, the model can be easily modified and used to describe field behaviour, which can contribute to the conservation and development of management strategies for both natural and agricultural systems. © 2012 Elsevier B.V.

Cellular automata-based spatial dynamic modeling for analyzing urban land use change

This paper analyzes land use change in Rio Claro City and its surroundings, located in the southeastern state of Sao Paulo, in the period from 1988 to 1995, using air-borne digital imagery and a cellular automata model. The simulation experiment was carried out in the Dinamica EGO platform and the results revealed a constrained urban sprawl, resulting from both the densification of residential areas implemented in previous years and the economic recession that led to an internal financial crisis in Brazil during the early 1990s. The simulation outputs were validated using a multi-resolution procedure based on a fuzzy similarity index and showed a satisfactory fitness in relation to the historical reference data. © 2013 IEEE.

Chaotic encryption method based on life-like cellular automata

A chaotic encryption algorithm is proposed based on the "Life-like" cellular automata (CA), which acts as a pseudo-random generator (PRNG). The paper main focus is to use chaos theory to cryptography. Thus, CA was explored to look for this "chaos" property. This way, the manuscript is more concerning on tests like: Lyapunov exponent, Entropy and Hamming distance to measure the chaos in CA, as well as statistic analysis like DIEHARD and ENT suites. Our results achieved higher randomness quality than others ciphers in literature. These results reinforce the supposition of a strong relationship between chaos and the randomness quality. Thus, the "chaos" property of CA is a good reason to be employed in cryptography, furthermore, for its simplicity, low cost of implementation and respectable encryption power. (C) 2012 Elsevier Ltd. All rights reserved.