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20162024
most citedGround state preparation with shallow variational warm-start

3 citations · 6 across the 12 of their papers we have counts for

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5 papers · 1 filter

quant-ph2023

Quantum sequential scattering model for quantum state learning

Mingrui Jing, Geng Liu, Hongbin Ren +1

Learning probability distribution is an essential framework in classical learning theory. As a counterpart, quantum state learning has spurred the exploration of quantum machine le…

quant-ph20231 cited

Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks

Hao-kai Zhang, Chenghong Zhu, Mingrui Jing +1

Quantum neural networks (QNNs) have been a promising framework in pursuing near-term quantum advantage in various fields, where many applications can be viewed as learning a quantu…

quant-ph2023

Efficient information recovery from Pauli noise via classical shadow

Yifei Chen, Zhan Yu, Chenghong Zhu +1

The rapid advancement of quantum computing has led to an extensive demand for effective techniques to extract classical information from quantum systems, particularly in fields lik…

quant-ph20233 cited

Ground state preparation with shallow variational warm-start

Youle Wang, Chenghong Zhu, Mingrui Jing +1

Preparing the ground states of a many-body system is essential for evaluating physical quantities and determining the properties of materials. This work provides a quantum ground s…

quant-ph2016

Towards quantum entanglement of micromirrors via a two-level atom and radiation pressure

Zhi-Rong Zhong, Xin Wang, Wei Qin +3

We propose a method to entangle two distant vibrating microsize mirrors (i.e., mechanical oscillators) in a cavity optomechanical system. In this scheme, we discuss both the resona…