4 papers
Learning and Generating Mixed States Prepared by Shallow Channel Circuits
Fangjun Hu, Christian Kokail, Milan KornjaÄa +5
Learning quantum states from measurement data is a central problem in quantum information and computational complexity. In this work, we study the problem of learning to generate m…
Concurrence of Symmetry Breaking and Nonlocality Phase Transitions in Diffusion Models
Yifan F. Zhang, Fangjun Hu, Guangkuo Liu +2
Diffusion models undergo a phase transition in a critical time window during generation dynamics, with two complementary diagnoses of criticality. The symmetry breaking picture vie…
Local Diffusion Models and Phases of Data Distributions
Fangjun Hu, Guangkuo Liu, Yifan F. Zhang +1
As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance in synthesizing complicated data…
Generalization Error in Quantum Machine Learning in the Presence of Sampling Noise
Fangjun Hu, Xun Gao
Tackling output sampling noise due to finite shots of quantum measurement is an unavoidable challenge when extracting information in machine learning with physical systems. A techn…