Novel Design for Quantum Dots Cellular Automata to Obtain Fault-Tolerant Majority Gate

Razieh Farazkish,Samira Sayedsalehi,Keivan Navi

doi:10.1155/2012/943406

Abstract

Quantum-dot Cellular Automata (QCA) is one of the most attractive technologies for computing at nanoscale. The principle element in QCA is majority gate. In this paper, fault-tolerance properties of the majority gate is analyzed. This component is suitable for designing fault-tolerant QCA circuits. We analyze fault-tolerance properties of three-input majority gate in terms of misalignment, missing, and dislocation cells. In order to verify the functionality of the proposed component some physical proofs using kink energy (the difference in electrostatic energy between the two polarization states) and computer simulations using QCA Designer tool are provided. Our results clearly demonstrate that the redundant version of the majority gate is more robust than the standard style for this gate.

Highlights

Current CMOS technology is going to approach a scaling limitation in deep nanometer technologies
Quantum-dot cellular automata (QCA) is one of the promising new technologies for future generation ICs that overcome the limitation of CMOS [1,2,3]
The fundamental unit of QCA-based design is majority gate; efficient construction of QCA circuits using majority gates has attracted a lot of attention [4,5,6,7,8,9]

Summary

Introduction

Current CMOS technology is going to approach a scaling limitation in deep nanometer technologies. The CMOS technology in nanoscales experienced some problems due to increase in amounts of variation in every aspect of a nanometer design. Quantum-dot cellular automata (QCA) is one of the promising new technologies for future generation ICs that overcome the limitation of CMOS [1,2,3]. The fundamental unit of QCA-based design is majority gate; efficient construction of QCA circuits using majority gates has attracted a lot of attention [4,5,6,7,8,9]. Efficiently constructing an inverter in QCA is of great importance [10,11,12]

Methods

Results

Conclusion