HIGH-PERFORMANCE DISTRIBUTED QUANTUM MULTIPLICATION USING RESIDUE NUMBER SYSTEM FOR OPTIMIZED QUANTUM ARITHMETIC

Quantum arithmetic operations play a vital role in modern quantum computing applications such as cryptography, signal processing, and large-scale scientific computation. However, conventional quantum multiplication architectures often suffer from high computational complexity, increased Toffoli depth, and excessive T gate consumption, which limit their practical implementation on scalable quantum hardware. This paper presents an optimized distributed quantum multiplication framework based on the Residue Number System (RNS) to improve computational efficiency and scalability. The proposed approach divides large multiplication tasks into multiple modular arithmetic operations that are executed independently across distributed quantum processing units. A Quantum Diminished-1 Modulo (2ⁿ+1) multiplier is incorporated as the fundamental computational block to achieve faster modular multiplication with reduced gate complexity. Performance analysis is carried out for quantum outputs ranging from 6 to 16 qubits and compared with traditional quantum multiplication methods. Experimental results demonstrate significant improvements in resource optimization, including reduced Toffoli depth, minimized T gate utilization, and enhanced execution speed. The proposed framework provides a scalable and efficient solution for next-generation distributed quantum arithmetic systems and supports the development of practical large-scale quantum computing architectures.