activity
20072022
most citedMachine learning meets quantum physics

157 citations · 364 across the 17 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

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

Markovian Quantum Neuroevolution for Machine Learning

Zhide Lu, Pei-Xin Shen, Dong-Ling Deng

Neuroevolution, a field that draws inspiration from the evolution of brains in nature, harnesses evolutionary algorithms to construct artificial neural networks. It bears a number…

quant-ph20205 cited

Solving Quantum Master Equations with Deep Quantum Neural Networks

Zidu Liu, L. -M. Duan, Dong-Ling Deng

Deep quantum neural networks may provide a promising way to achieve quantum learning advantage with noisy intermediate scale quantum devices. Here, we use deep quantum feedforward…

quant-ph20203 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-ph2020

Topological Quantum Compiling with Reinforcement Learning

Yuan-Hang Zhang, Pei-Lin Zheng, Yi Zhang +1

Quantum compiling, a process that decomposes the quantum algorithm into a series of hardware-compatible commands or elementary gates, is of fundamental importance for quantum compu…