Performance Analysis of Quantum Arithmetic Circuits on IBM Eagle Processor

Quantum computing is a transformative technology providing exponential speedup over classical computing for specific computational problems. At the foundation of computing lies arithmetic, with addition as a fundamental operation for subtraction, multiplication, division, and other operations. In this paper, we evaluate the performance of quantum arithmetic circuits – including half adders, full adders, Toffoli-based adders, Quantum Fourier Transform (QFT)-based adders, and quantum comparators – on IBM’s Eagle Processor, a 127-qubit superconducting Quantum Processing Unit (QPU) accessible through the IBM Quantum cloud platform. These circuits are implemented using IBM Qiskit and tested on both ideal and noisy simulators to validate their functionality before execution on quantum hardware. Experimental results show that the probabilities of accurate computations are notably low, even for smaller input sizes, due to hardware imperfections such as shorter qubit coherence times and limited qubit stability. A comparative analysis of Toffoli-based and QFT-based adders demonstrates that Toffoli-based adders have higher accuracy, making them more suitable for precise quantum arithmetic operations. These findings highlight the significant impact of quantum hardware imperfections on the reliability of arithmetic operations.