On the Computational Power of DNA Annealing and Ligation

In [20] it was shown that the DNA primitives of Separate, Merge, and Amplify were not sufficiently powerful to invert functions defined by circuits in linear time. Dan Boneh et al [4] show that the addition of a ligation primitive, Append, provides the missing power. The question becomes, "How powerful is ligation? Are Separate, Merge, and Amplify necessary at all?" This paper proposes to informally explore the power of annealing and ligation for DNA computation. We conclude, in fact, that annealing and ligation alone are theoretically capable of universal computation

A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

Magnetic Cellular Nonlinear Network with Spin Wave Bus for Image Processing

We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film - spin wave bus. The magneto-electric cell is an artificial two-phase multiferroic structure comprising piezoelectric and ferromagnetic materials. A bit of information is assigned to the cell's magnetic polarization, which can be controlled by the applied voltage. The information exchange among the cells is via the spin waves propagating in the spin wave bus. Each cell changes its state as a combined effect of two: the magneto-electric coupling and the interaction with the spin waves. The distinct feature of the network with spin wave bus is the ability to control the inter-cell communication by an external global parameter - magnetic field. The latter makes possible to realize different image processing functions on the same template without rewiring or reconfiguration. We present the results of numerical simulations illustrating image filtering, erosion, dilation, horizontal and vertical line detection, inversion and edge detection accomplished on one template by the proper choice of the strength and direction of the external magnetic field. We also present numerical assets on the major network parameters such as cell density, power dissipation and functional throughput, and compare them with the parameters projected for other nano-architectures such as CMOL-CrossNet, Quantum Dot Cellular Automata, and Quantum Dot Image Processor. Potentially, the utilization of spin waves phenomena at the nanometer scale may provide a route to low-power consuming and functional logic circuits for special task data processing

Electron Spin for Classical Information Processing: A Brief Survey of Spin-Based Logic Devices, Gates and Circuits

In electronics, information has been traditionally stored, processed and communicated using an electron's charge. This paradigm is increasingly turning out to be energy-inefficient, because movement of charge within an information-processing device invariably causes current flow and an associated dissipation. Replacing charge with the "spin" of an electron to encode information may eliminate much of this dissipation and lead to more energy-efficient "green electronics". This realization has spurred significant research in spintronic devices and circuits where spin either directly acts as the physical variable for hosting information or augments the role of charge. In this review article, we discuss and elucidate some of these ideas, and highlight their strengths and weaknesses. Many of them can potentially reduce energy dissipation significantly, but unfortunately are error-prone and unreliable. Moreover, there are serious obstacles to their technological implementation that may be difficult to overcome in the near term. This review addresses three constructs: (1) single devices or binary switches that can be constituents of Boolean logic gates for digital information processing, (2) complete gates that are capable of performing specific Boolean logic operations, and (3) combinational circuits or architectures (equivalent to many gates working in unison) that are capable of performing universal computation.Comment: Topical Revie

Towards a Holistic CAD Platform for Nanotechnologies

Silicon-based CMOS technologies are predicted to reach their ultimate limits by the middle of the next decade. Research on nanotechnologies is actively conducted, in a world-wide effort to develop new technologies able to maintain the Moore's law. They promise revolutionizing the computing systems by integrating tremendous numbers of devices at low cost. These trends will have a profound impact on the architectures of computing systems and will require a new paradigm of CAD. The paper presents a work in progress on this direction. It is aimed at fitting requirements and constraints of nanotechnologies, in an effort to achieve efficient use of the huge computing power promised by them. To achieve this goal we are developing CAD tools able to exploit efficiently these huge computing capabilities promised by nanotechnologies in the domain of simulation of complex systems composed by huge numbers of relatively simple elements.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Convergence analysis of hybrid cellular automata for topology optimization

The hybrid cellular automaton (HCA) algorithm was inspired by the structural adaptation of bones to their ever changing mechanical environment. This methodology has been shown to be an effective topology synthesis tool. In previous work, it has been observed that the convergence of the HCA methodology is affected by parameters of the algorithm. As a result, questions have been raised regarding the conditions by which HCA converges to an optimal design. The objective of this investigation is to examine the conditions that guarantee convergence to a Karush-Kuhn-Tucker (KKT) point. In this paper, it is shown that the HCA algorithm is a fixed point iterative scheme and the previously reported KKT optimality conditions are corrected. To demonstrate the convergence properties of the HCA algorithm, a simple cantilevered beam example is utilized. Plots of the spectral radius for projections of the design space are used to show regions of guaranteed convergence

Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

Molecular quantum cellular automata cell design trade-offs: latching vs. power dissipation.

The use of molecules to enact quantum cellular automata (QCA) cells has been proposed as a new way for performing electronic logic operations at sub-nm dimensions. A key question that arises concerns whether chemical or physical processes are to be exploited. The use of chemical reactions allows the state of a switch element to be latched in molecular form, making the output of a cell independent of its inputs, but costs energy to do the reaction. Alternatively, if purely electronic polarization is manipulated then no internal latching occurs, but no power is dissipated provided the fields from the inputs change slowly compared to the molecular response times. How these scenarios pan out is discussed by considering calculated properties of the 1,4-diallylbutane cation, a species often used as a paradigm for molecular electronic switching. Utilized are results from different calculation approaches that depict the ion either as a charge-localized mixed-valence compound functioning as a bistable switch, or else as an extremely polarizable molecule with a delocalized electronic structure. Practical schemes for using molecular cells in QCA and other devices emerge