M.V. Stepanov - Research Scientist, Moscow Technological University (MIREA). Е-mail: nanocompiler000@yandex.ru A.A. Evdokimov - Dr.Sc. (Chem.), Рrofessor, Moscow Technological University (MIREA). Е-mail: evdokimov@mirea.ru

On the basis of neural network approach the algorithm of modeling of self-organization of the polarization state of quantum cellular automata (QCA) in nanoscale circuit. The neural network algorithm shows convergence to steady state with a minimum value of the total energy error - minimizes the functional of the energy error, which is determined by the structure of the task. This status must be sustainable - most energetically favorable state of polarization of the QCA in Nanocircuit. The resulting algorithm for computer-aided design (CAD) for nanoscale functional systems and nano. This algorithm was used in a specially developed by the author for modeling of nano-based QCA. These programs can be used as an integral part of the future of CAD for the design of nano and nano - nanocompiler - CAD for design, development of systems of nanosystems. Association, silicon compiler with neural network algorithm for calculating the topology of the nano on the basis of the QCA will allow you to play on the basis of the QCA circuitry, which is currently performed on the basis of CMOS. Thus, on the one hand, be able to maintain the investment in the architecture and software of the processors and memory modules on the basis of CMOS; on the other hand, it is possible to circumvent the fundamental limits of miniaturization of CMOS, due to the quantum size effects (QSE) at subnanometric the size of the drain, source, gate MOSFETs.

 

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