Learning Quantum Distributions with Variational Diffusion Models

• DOI: 10.1016/j.ifacol.2023.10.095
• Publication Date: 2023-11-22T10:58:45Z
• Authors: Yong Wang; Shuming Cheng; Li Li; Jie Chen
• Keywords: High fidelity

It is challenging to identify the state of many-body quantum systems, as recovering density matrices underlying typically requires computational resources scale exponentially system size. In this work, we introduce variational diffusion model (VDM) efficiently learn high-dimensional distributions with high fidelity, which essential realize fast reconstruction states. We build up VDM suitable for dealing samples, and then perform numerical experiments test our other autoregressive models, including recurrent neural network transformer. found that can achieve a modest better performance fewest parameters than two distribution desired. Our results pave way applying models solve hard problems in domain.