52 citations · 212 across the 10 of their papers we have counts for
10 papers
Quantum error correction at ultra-low overhead
Zhide Lu, Weikang Li, Dong-Ling Deng
Suppressing errors is the central challenge for useful large-scale quantum computing. While quantum error correction promises a viable solution to this challenge, existing codes ty…
Machine learning the arrow of time in solid-state spins
Xiang-Qian Meng, Zhide Lu, Ya-Nan Lu +9
Understanding the emergence of the thermodynamic arrow of time in microscopic systems is of fundamental importance, particularly given that unitary evolution preserves time-reversa…
Quantum continual learning on a programmable superconducting processor
Chuanyu Zhang, Zhide Lu, Liangtian Zhao +32
Quantum computers may outperform classical computers on machine learning tasks. In recent years, a variety of quantum algorithms promising unparalleled potential to enhance, speed…
Experimental demonstration of reconstructing quantum states with generative models
Xuegang Li, Wenjie Jiang, Ziyue Hua +9
Quantum state tomography, a process that reconstructs a quantum state from measurements on an ensemble of identically prepared copies, plays a crucial role in benchmarking quantum…
Non-Hermitian Fermi-Dirac Distribution in Persistent Current Transport
Pei-Xin Shen, Zhide Lu, Jose L. Lado +1
Persistent currents circulate continuously without requiring external power sources. Here, we extend their theory to include dissipation within the framework of non-Hermitian quant…
Expressibility-induced Concentration of Quantum Neural Tangent Kernels
Li-Wei Yu, Weikang Li, Qi Ye +3
Quantum tangent kernel methods provide an efficient approach to analyzing the performance of quantum machine learning models in the infinite-width limit, which is of crucial import…
Deep quantum neural networks equipped with backpropagation on a superconducting processor
Xiaoxuan Pan, Zhide Lu, Weiting Wang +10
Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of…
Quantum Neural Network Classifiers: A Tutorial
Weikang Li, Zhide Lu, Dong-Ling Deng
Machine learning has achieved dramatic success over the past decade, with applications ranging from face recognition to natural language processing. Meanwhile, rapid progress has b…
Quantum Continual Learning Overcoming Catastrophic Forgetting
Wenjie Jiang, Zhide Lu, Dong-Ling Deng
Catastrophic forgetting describes the fact that machine learning models will likely forget the knowledge of previously learned tasks after the learning process of a new one. It is…
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…