39 citations · 72 across the 6 of their papers we have counts for
6 papers
Neural quantum embedding via deterministic quantum computation with one qubit
Hongfeng Liu, Tak Hur, Shitao Zhang +10
Quantum computing is expected to provide exponential speedup in machine learning. However, optimizing the data loading process, commonly referred to as quantum data embedding, to m…
Self-Consistent Determination of Single-Impurity Anderson Model Using Hybrid Quantum-Classical Approach on a Spin Quantum Simulator
Xinfang Nie, Xuanran Zhu, Yu-ang Fan +9
The accurate determination of the electronic structure of strongly correlated materials using first principle methods is of paramount importance in condensed matter physics, comput…
Experimental sample-efficient quantum state tomography via parallel measurements
Chang-Kang Hu, Chao Wei, Chilong Liu +11
Quantum state tomography (QST) via local measurements on reduced density matrices (LQST) is a promising approach but becomes impractical for large systems. To tackle this challenge…
Practical quantum simulation of small-scale non-Hermitian dynamics
Hongfeng Liu, Xiaodong Yang, Kai Tang +5
Non-Hermitian quantum systems have recently attracted considerable attention due to their exotic properties. Though many experimental realizations of non-Hermitian systems have bee…
Measuring Quantum Entanglement from Local Information by Machine Learning
Yulei Huang, Liangyu Che, Chao Wei +5
Entanglement is a key property in the development of quantum technologies and in the study of quantum many-body simulations. However, entanglement measurement typically requires qu…
Learning Quantum Hamiltonians from Single-qubit Measurements
Liangyu Che, Chao Wei, Yulei Huang +6
It is natural to measure the observables from the Hamiltonian-based quantum dynamics, and its inverse process that Hamiltonians are estimated from the measured data also is a vital…