Quantum-device-oriented multiple-valued logic system based on a super pass gate

Xiaowei Deng, Takahiro Hanyu, Michitaka Kameyama

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The investigation of device functions required from the systems point of view will be important for the development of the next generation of VLSI devices and systems. In this paper, a super pass transistor (SPT) model is presented as a quantum device candidate for future VLSI systems based on multiple-valued logic. A possible quantum device structure for the SPT model is also described, which employs the concepts of a lateral-resonant-tunneling quantum-dot transistor and a heterostructure field-effect transistor. Since it has the powerful capability of detecting multiple signal levels, the SPT will be useful for the implementation of highly compact multiple-valued VLSI systems. To exploit the functionality of the SPT, a super pass gate (SP-gate) corresponding to a single SPT is proposed as a multiple-valued universal logic module. The mathematical properties of the SP-gate are discussed. A design method for a multiple-valued SP-gate network is presented. An application of SP-gates to a multiple-valued image processing system is also demonstrated. The SP-gate network for the multiple-valued image processing system is evaluated in comparison with the corresponding NMOS implementation in terms of the number of transistors, interconnections and cascaded transistor stages. The size of a generalized series-parallel SP-gate network is also evaluated in comparison with a functionally equivalent multiple-valued series-parallel MOS pass transistor network. The results show that highly compact multiple-valued VLSI systems can be achieved if the SPT-model can be realized by an actual quantum device.

Original languageEnglish
Pages (from-to)951-958
Number of pages8
JournalIEICE Transactions on Information and Systems
VolumeE78-D
Issue number8
Publication statusPublished - 1995 Aug 1

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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