4 papers
Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning
Chuangtao Chen, Qinglin Zhao, MengChu Zhou +3
Discrete diffusion models represent a significant advance in generative modeling, demonstrating remarkable success in synthesizing complex, high-quality discrete data. However, to…
Continuous-variable Quantum Diffusion Model for State Generation and Restoration
Haitao Huang, Chuangtao Chen, Qinglin Zhao
The generation and preservation of complex quantum states against environmental noise are paramount challenges in advancing continuous-variable (CV) quantum information processing.…
Quantum Mixed-State Self-Attention Network
Fu Chen, Qinglin Zhao, Li Feng +3
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Q…
Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemble
Chuangtao Chen, Qinglin Zhao, MengChu Zhou +3
Mixed quantum states are the native description of many physically important quantum systems, making their generation a fundamental task in quantum information processing. However,…