activity
20082023
most citedMeasure of genuine multipartite entanglement with computable lower bounds

312 citations · 696 across the 27 of their papers we have counts for

collaborators
Showing quant-phShow all

27 papers · 1 filter

quant-ph2023★ 17 cited

Entanglement Verification with Deep Semi-supervised Machine Learning

Lifeng Zhang, Zhihua Chen, Shao-Ming Fei

Quantum entanglement lies at the heart in quantum information processing tasks. Although many criteria have been proposed, efficient and scalable methods to detect the entanglement…

quant-ph2022★ 4 cited

Detecting Tripartite Steering via Quantum Entanglement

Zhihua Chen, Shao-Ming Fei

Einstein-Podolsky-Rosen steering is a kind of powerful nonlocal quantum resource in quantum information processing such as quantum cryptography and quantum communication. Many crit…

quant-ph2018★ 22 cited

Improved quantum entropic uncertainty relations

Zhihua Chen, Zhihao Ma, Yunlong Xiao +1

We study entropic uncertainty relations by using stepwise linear functions and quadratic functions. Two kinds of improved uncertainty lower bounds are constructed: the state-indepe…

quant-ph2017

Detection and measure of genuine tripartite entanglement with partial transposition and realignment of density matrices

Ming Li, Jing Wang, Shuqian Shen +2

It is challenging task to detect and measure genuine multipartite entanglement. We investigate the problem by considering the average based positive partial transposition(PPT) crit…

quant-ph2017

Quantum steerability based on joint measurability

Zhihua Chen, Xiangjun Ye, Shaoming Fei

Occupying a position between entanglement and Bell nonlocality, Einstein-Podolsky-Rosen (EPR) steering has attracted increasing attention in recent years. Many criteria have been p…

quant-ph2017

Uncertainty conservation relations: theory and experiment

Hengyan Wang, Zhihao Ma, Shengjun Wu +8

As a very fundamental principle in quantum physics, uncertainty principle has been studied intensively via various uncertainty inequalities. Based on the information measure introd…