20 citations · 60 across the 11 of their papers we have counts for
11 papers
Machine learning reveals common features of unconventional superconductors with high transition temperatures
Haosheng Xu, Dongheng Qian, Yijun Yu +1
Superconductors with high critical temperatures that emerges beyond the phonon-mediated regime are usually considered unconventional in nature, yet unlike conventional superconduct…
Enhancing Neural-Network Variational Monte Carlo through Basis Transformation
Zhixuan Liu, Dongheng Qian, Jing Wang
Neural-network variational Monte Carlo (NNVMC) has emerged as a powerful tool for solving quantum many-body problems, yet systematic pathways for improving its accuracy remain larg…
Data-Driven Learnability Transition of Measurement-Induced Entanglement
Dongheng Qian, Jing Wang
Measurement-induced entanglement (MIE) captures how local measurements generate long-range quantum correlations and drive dynamical phase transitions in many-body systems. Yet esti…
Design Topological Materials by Reinforcement Fine-Tuned Generative Model
Haosheng Xu, Dongheng Qian, Zhixuan Liu +2
Topological insulators (TIs) and topological crystalline insulators (TCIs) are materials with unconventional electronic properties, making their discovery highly valuable for pract…
Revealing Superconducting Chiral Edge Modes via Resistance Distributions
Linghao Huang, Dongheng Qian, Jing Wang
Inducing superconducting correlations in quantum anomalous Hall (QAH) states offers a promising route to realize topological superconductivity with chiral Majorana edge modes. Howe…
Quantum Non-Local Nonstabilizerness
Dongheng Qian, Jing Wang
Quantum entanglement and quantum nonstabilizerness are fundamental resources that characterize distinct aspects of a quantum state: entanglement reflects non-local correlations, wh…
Intrinsic Quantum Mpemba Effect in Markovian Systems and Quantum Circuits
Dongheng Qian, Huan Wang, Jing Wang
The quantum Mpemba effect (QME) describes the counterintuitive phenomenon in which a system farther from equilibrium reaches steady state faster than one closer to equilibrium. How…
Coherent Information Phase Transition in a Noisy Quantum Circuit
Dongheng Qian, Jing Wang
Coherent information quantifies the transmittable quantum information through a channel and is directly linked to the channel's quantum capacity. In a monitored quantum circuit, re…
Protect Measurement-Induced Phase Transition from Noise
Dongheng Qian, Jing Wang
Scrambling dynamics induced by random unitary gates can protect information from low-rate measurements, which underpins the phenomenon known as the measurement-induced phase transi…
Predicting Many Crystal Properties via an Adaptive Transformer-based Framework
Haosheng Xu, Dongheng Qian, Jing Wang
Machine learning has revolutionized many fields, including materials science. However, predicting properties of crystalline materials using machine learning faces challenges in inp…
Steering-induced phase transition in measurement-only quantum circuits
Dongheng Qian, Jing Wang
Competing measurements alone can give rise to distinct phases characterized by entanglement entropy$\unicode{x2013}$such as the volume law phase, symmetry-breaking (SB) phase, and…