Abstract

The semiconductor industry is facing a twofold challenge at sub-nanometer level; first, the high power dissipation in irreversible computing architectures due to information loss and second, inability to handle large data due to sequential information processing. These issues create obstacles in producing the presumed low-power complex computing outcomes. The heat dissipation can be reduced by utilizing the complementary metal–oxide–semiconductor-based reversible computing architectures. However, these architectures fail to enhance the performance owing to inability to process large data. Quantum computing (QC) can circumvent these problems due to its fundamental ineffaceable characteristics of quantum mechanics-based reversible computing and parallelism. Spin-torque-based physical realization is the most suitable platform for reversible computing due to the electron spin analogous to the qubit. However, optimal quantum circuits are required to physically realize the complex Boolean logic due to spin-qubit decoherence and reduce the number of transistor switching activities for the spin generation and injection required for the spin-qubit rotation. Therefore, in this paper, optimal quantum circuit decompositions are presented with the help of developed elementary quantum library { $R_{y}^{(\theta)}$ , $R_{z}^{(\theta)}$ , $\sqrt {\text {SWAP}}$ } for the spin-torque-based QC architecture. The reversible Boolean logic performance is analyzed and compared for the conventional, reduced, and optimal decompositions on the first- and second-order transmission coefficient matrix-based spin-torque QC architecture. The results encourage to set a path toward QC-based reconfigurable complex computing systems in near future.

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