407 citations · 3.9k across the 91 of their papers we have counts for
8 papers · 1 filter
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…
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…
Unsupervised Learning of Non-Hermitian Topological Phases
Li-Wei Yu, Dong-Ling Deng
Non-Hermitian topological phases bear a number of exotic properties, such as the non-Hermitian skin effect and the breakdown of conventional bulk-boundary correspondence. In this p…
Realizing a quantum generative adversarial network using a programmable superconducting processor
Kaixuan Huang, Zheng-An Wang, Chao Song +11
Generative adversarial networks are an emerging technique with wide applications in machine learning, which have achieved dramatic success in a number of challenging tasks includin…
Solving the Liouvillian Gap with Artificial Neural Networks
Dong Yuan, He-Ran Wang, Zhong Wang +1
We propose a machine-learning inspired variational method to obtain the Liouvillian gap, which plays a crucial role in characterizing the relaxation time and dissipative phase tran…
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…
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…
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…