Restoring and non-restoring array divider designs in quantum-dot cellular automata

Sayedsalehi, Samira, Rahimi Azghadi, Mostafa, Angizi, Shaahin, and Navi, Keivan (2015) Restoring and non-restoring array divider designs in quantum-dot cellular automata. Information Sciences, 311. pp. 86-101.

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Abstract

Quantum-dot Cellular Automata (QCA) is a very high speed, extra low power and extremely dense technology for implementing computing architectures which encodes binary logics through configuration of charges amongst quantum dots. Several studies of adders and multipliers in QCA have been proposed, whereas QCA divider design and implementation is a rather unexplored research area. In this paper the earliest designs for QCA dividers, which explore the restoring and non-restoring array dividers, considered as the best possible dividers, are introduced. These designs use well-organized arithmetic components as their basic construction parts and take some design rules into consideration which make them reliable and more robust against noise. These dividers with their design considerations and constraints are introduced step by step. Moreover, these designs are probed in terms of complexity, clocking and latency. QCADesigner, a simulation tool for QCA circuits, is used to check circuits' layout and functionality.

Item ID: 45726
Item Type: Article (Research - C1)
ISSN: 1872-6291
Keywords: Quantum-dot Cellular Automata, array divider, restoring, non-restoring, full adder
Date Deposited: 06 Dec 2016 03:07
FoR Codes: 09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090601 Circuits and Systems @ 33%
10 TECHNOLOGY > 1007 Nanotechnology > 100705 Nanoelectronics @ 33%
09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090604 Microelectronics and Integrated Circuits @ 34%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 34%
97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 33%
97 EXPANDING KNOWLEDGE > 970110 Expanding Knowledge in Technology @ 33%
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