Development of quantum circuits with a focus on squraring, multiplying devices for low power VLSI circuits using Quantum Dot Cellular Automata theory

This paper explores the use of Quantum-dot Cellular Automata (QCA) technology for developing high-performance, low-power arithmetic circuits, with a focus on multipliers and square circuits. QCA is an emerging nano-electronics technology that offers significant advantages over traditional CMOS (Complementary Metal-Oxide-Semiconductor) technology, including reduced power consumption, faster operational speeds, and better integration potential. These properties make QCA a promising candidate to replace CMOS in various applications, particularly in systems requiring efficient processing of mathematical computations. The research focuses on designing QCA-based multipliers and square circuits, which are crucial for digital signal processing and mathematical computations. These components directly influence system throughput and power efficiency. The research involves the development of a QCA based Multiplier utilizing binary adders and AND gates, which are then compared to conventional CMOS technology. Important parameters such as Cell Count, Area and Power Dissipation have been estimated for the QCA circuits using the QCA Designer tool, as an evaluation of the efficiencies achieved from using QCA technology as against the normal CMOS designs. The results so obtained show that the QCA based designs have better performance over CMOS technology in order to enhance performance as well as reduction in power dissipation and of reduced area requirements as compared to CMOS technology. This elucidates the applicability of QCA technology for improving the efficiencies and integration of important components of digital systems and gives the approach of transformation its direction in the field of nano–electronics. It shows clearly the possibility of using QCA technology for improvement of performance and power efficiency of arithmetic circuits, which would pave the way for a better era of future developments in low power, high performance computing.