Predictive Error Suppression in Quantum Computing via Digital Twin Modeling — A Hybrid Classical–Quantum Architecture without Physical Redundancy —

This paper presents a predictive error suppression architecture for quantum computing that eliminates reliance on physical redundancy. By constructing a digital twin of the quantum processor, a classical system models and predicts noise as deviations from ideal quantum states in real time. The predicted noise is then used to correct measurement outcomes or apply compensatory operations, significantly improving computational accuracy on NISQ devices. This approach shifts the challenge of error correction from hardware scaling to computational modeling, enabling scalable, adaptive, and practical quantum computing systems.