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Efficient designs of quantum-dot cellular automata multiplexer and RAM with physical proof along with power analysis

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Abstract

In this manuscript, we first suggest a single-layer 2:1 QCA MUX with an ultra-low number of cells and high speed. Unlike existing designs, the output of the proposed design does not comply with the Boolean regulation and is produced using the essential characteristics of quantum technology. Single-layer 4:1 and 8:1 QCA multiplexers have also been implemented. Moreover, using the proposed 2:1 QCA MUX, a novel and efficient QCA RAM memory cell with the set and reset abilities has been proposed. Forasmuch as the most significant challenge in quantum-dot cellular automata circuit design is the number of cell counts and occupied area. The proposed 2:1 QCA MUX includes 10 cells and an occupied area of 0.03. The unique advantage of the proposed design over all previous output generation tasks is based on cellular interactions. Our findings showed that the proposed 2:1 QCA MUX has a 16.66% and 60% improvement in terms of cell count and occupied area, respectively. In order to confirm the function of the proposed design, some physical proofs are presented. The software for implement of the circuits and their power analysis are QCADesigner 2.0.3 and QCAPro, respectively. The results of the comparisons indicate that the proposed structures are more efficient than the existing ones. The QCAPro power analysis tool has been used for analyzing the power consumption of the proposed designs.

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Authors and Affiliations

  1. Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

    Seyed-Sajad Ahmadpour & Mohammad Mosleh

  2. Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

    Saeed Rasouli Heikalabad

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  1. Seyed-Sajad Ahmadpour
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Correspondence to Mohammad Mosleh.

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Ahmadpour, SS., Mosleh, M. & Rasouli Heikalabad, S. Efficient designs of quantum-dot cellular automata multiplexer and RAM with physical proof along with power analysis. J Supercomput 78, 1672–1695 (2022). https://doi.org/10.1007/s11227-021-03913-2

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