3 papers
quant-ph2026
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…
cs.LG2026
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…
quant-ph2026
Arbitrary Polynomial Separations in Trainable Quantum Machine Learning
Eric R. Anschuetz, Xun Gao
Recent theoretical results in quantum machine learning have demonstrated a general trade-off between the expressive power of quantum neural networks (QNNs) and their trainability;…