aiqbench analysis

This research demonstrates that structural motifs from quantum mechanics, such as angle encoding and Hilbert space representations, can be effectively translated into scalable classical tensor operations for image recognition. By leveraging these quantum-inspired principles on standard hardware, the QiT architecture achieves competitive ImageNet accuracy with significantly lower computational costs than simulated quantum alternatives. This approach validates a pathway to enhance AI models using theoretical quantum concepts without requiring unstable or expensive quantum processors.