Title: Quantum-Enhanced Neural Network Architecture

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum-enhanced neural networks (QNNs) represent a promising area of research aiming to surpass classical neural networks in complex pattern recognition tasks. This paper explores a novel QNN architecture utilizing quantum properties like superposition and entanglement to improve learning capabilities. We present a detailed design of this architecture, outlining the key quantum gates and their integration into the network's structure. The core claim is that incorporating these quantum elements will significantly enhance the network's ability to model intricate relationships within data, leading to improved performance in tasks requiring complex pattern detection.

DOI: 10.5281/zenodo.22329341

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