Title: Quantum-Enhanced Generative Modeling via Variational Circuits

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of quantum-enhanced generative modeling through the development of novel variational circuit-based models. We propose a new class of generative models that exploit quantum effects to improve sampling efficiency and feature extraction capabilities, moving beyond the limitations of classical generative techniques. The core mechanism centers on employing variational circuits to generate complex data, pushing the boundaries of what's currently achievable in generative modeling. The integration of quantum chemistry principles into variational circuit design allows for a pathway towards significantly enhanced data quality and representation. This work presents a theoretical framework and initial explorations demonstrating the potential of this approach, highlighting the advantages of quantum-enhanced generative modeling.

DOI: 10.5281/zenodo.22195204

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