An ultra-efficient design of fault-tolerant 3-input majority gate (FTMG) with an error probability model based o quantum-dots

Dr. Seyed-Sajad Ahmadpour

Kadir Has University

Abstract: Quantum-dot cellular automata (QCA) has recently attracted significant notice thanks to their inherent ability to decrease energy dissipation and decreasing area, which is the primary need of digital circuits. However, the lack of resistance of QCA circuits under defects in previous works is a vital challenge affecting the stability of the circuit and output production. In addition, with the high defect rate in QCA, suggesting resistance and stable structures is critical. Furthermore, the 3-input majority gate is a fundamental component of QCA circuits; therefore, improving this essential gate would enable the development of fault-tolerant circuits. In this webinar, I will show a 3-input majority gate which is 100% fault-tolerant against single-cell omission defects. Moreover, the fundamental gates are introduced based on the proposed gate. In addition, an adder and a 1:2 decoder are also designed. Using QCADesigner 2.0.3 and QCAPro software, simulations of structures and analysis of power consumption are performed.

Speaker Biography: Seyed-Sajad Ahmadpour is a Postdoctoral Researcher in the Department of Computer Engineering, within the Faculty of Engineering and Natural Sciences at Kadir Has University, Istanbul, Türkiye. He has achieved significant recognition in his field, having been listed among the World’s Top 2% Scientists according to a 2022 study conducted by Stanford University in the United States. Dr. Ahmadpour’s research interests span several cutting-edge areas in computing and nanotechnology, including quantum-dot cellular automata, reversible logic, atomic silicon, and faulttolerance. His work in these areas contributes to the advancement of technology and provides valuable insights into quantum computing. His inclusion in the prestigious World’s Top 2% Scientists List underscores the impact and importance of his research contributions.

Meeting ID: 316 386 786 505

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