activity
20192021
most citedMachine Learning Topological Phases with a Solid-state Quantum Simulator

69 citations · 72 across the 2 of their papers we have counts for

collaborators

5 papers

quant-ph2021

Experimental demonstration of adversarial examples in learning topological phases

Huili Zhang, Si Jiang, Xin Wang +7

Classification and identification of different phases and the transitions between them is a central task in condensed matter physics. Machine learning, which has achieved dramatic…

quant-ph2020

Observation of non-Hermitian topology with non-unitary dynamics of solid-state spins

Wengang Zhang, Xiaolong Ouyang, Xianzhi Huang +7

Non-Hermitian topological phases exhibit a number of exotic features that have no Hermitian counterparts, including the skin effect and breakdown of the conventional bulk-boundary…

quant-ph2020★ 3 cited

Entangling Nuclear Spins by Dissipation in a Solid-state System

Xin Wang, Huili Zhang, Wengang Zhang +7

Entanglement is a fascinating feature of quantum mechanics and a key ingredient in most quantum information processing tasks. Yet the generation of entanglement is usually hampered…

quant-ph2019

Experimental Test of Leggett's Inequalities with Solid-State Spins

Xianzhi Huang, Xiaolong Ouyang, Wenqian Lian +9

Bell's theorem states that no local hidden variable model is compatible with quantum mechanics. Surprisingly, even if we release the locality constraint, certain nonlocal hidden va…

cond-mat.dis-nn2019★ 69 cited

Machine Learning Topological Phases with a Solid-state Quantum Simulator

Wenqian Lian, Sheng-Tao Wang, Sirui Lu +11

We report an experimental demonstration of a machine learning approach to identify exotic topological phases, with a focus on the three-dimensional chiral topological insulators. W…