A Novel Hybrid Quantum Framework for Assessing Noise Effects on Performance of Shor’s Algorithm

Abstract

This experimental study introduces a hybrid quantum-classical framework aiming to improve the noise robustness of Shor’s algorithm. By incorporating a novel hybrid logic gate into the modular exponentiation phase, the framework stabilizes qubit interactions and decreases decoherence in a noisy environment simulated by IBM Qiskit. Performance evaluation is accomplished by fidelity and entropy analysis across varied noise levels. Comparative benchmarking with conventional techniques, including Shor’s code, Bacon-Shor code, dynamical decoupling, and zero noise extrapolation, demonstrates that the proposed hybrid gate achieves higher fidelity (0.90) and lower entropy (0.33), while preserving minimal resource overhead. These findings highlight the framework’s effectiveness as a hardware-independent, scalable solution for Noisy Intermediate-Scale Quantum (NISQ) devices. Instead, the study offers an approach toward a scalable, error-resilient model to avoid exaggerating scalability. Despite its promising outcomes, study is presently limited to simulations and a single noise model. Future work will explore implementation on real quantum hardware and extend the framework to incorporate a broader range of noise profiles, contributing to the evolution of fault-tolerant quantum computation.