Abstract

Evaluating quantum key distributions in edge power grids.

Introduction

The evolution of academic analytics has been fundamentally tied to the capabilities of classical machine learning. However, as the volume and dimensionality of educational data grow, classical architectures face diminishing returns in terms of predictive reliability and computational cost...

Figure 1: Hybrid QNN Schematic for Student Dataset Processing

Our methodology focuses on the implementation of a 12-qubit system that pre-processes categorical academic inputs into quantum states before feeding them into a classical dense layer structure. This hybrid approach ensures compatibility with current hardware while providing the quantum advantage in feature extraction...