activity
20072023
most citedExperimental quantification of asymmetric Einstein-Podolsky-Rosen steering

206 citations · 1.1k across the 54 of their papers we have counts for

collaborators
Showing 2018Show all

7 papers · 1 filter

quant-ph2018★ 9 cited

An Efficient Algorithmic Way to Construct Boltzmann Machine Representations for Arbitrary Stabilizer Code

Yuan-Hang Zhang, Zhian Jia, Yu-Chun Wu +1

Restricted Boltzmann machines (RBMs) have demonstrated considerable success as variational quantum states; however, their representational power remains incompletely understood. In…

quant-ph2018★ 101 cited

Quantum Neural Network States: A Brief Review of Methods and Applications

Zhih-Ahn Jia, Biao Yi, Rui Zhai +3

One of the main challenges of quantum many-body physics is that the dimensionality of the Hilbert space grows exponentially with the system size, which makes it extremely difficult…

quant-ph2018★ 32 cited

Experimentally Robust Self-testing for Bipartite and Tripartite Entangled States

Wen-Hao Zhang, Geng Chen, Xing-Xiang Peng +9

Self-testing refers to a method with which a classical user can certify the state and measurements of quantum systems in a device-independent way. Especially, the self-testing of e…

quant-ph2018★ 6 cited

Entropic No-Disturbance as a Physical Principle

Zhih-Ahn Jia, Rui Zhai, Bai-Chu Yu +2

The celebrated Bell-Kochen-Specker no-go theorem asserts that quantum mechanics does not present the property of realism, the essence of the theorem is the lack of a joint probabil…

quant-ph2018★ 83 cited

Demonstration of Einstein-Podolsky-Rosen Steering with Enhanced Subchannel Discrimination

Kai Sun, Xiang-Jun Ye, Ya Xiao +6

Einstein-Podolsky-Rosen (EPR) steering describes a quantum nonlocal phenomenon in which one party can nonlocally affect the other's state through local measurements. It reveals an…

quant-ph2018★ 31 cited

Efficient Machine Learning Representations of Surface Code with Boundaries, Defects, Domain Walls and Twists

Zhih-Ahn Jia, Yuan-Hang Zhang, Yu-Chun Wu +3

Machine learning representations of many-body quantum states have recently been introduced as an ansatz to describe the ground states and unitary evolutions of many-body quantum sy…

quant-ph2018★ 5 cited

Experimentally detecting a quantum change point via Bayesian inference

Shang Yu, Chang-Jiang Huang, Jian-Shun Tang +15

Detecting a change point is a crucial task in statistics that has been recently extended to the quantum realm. A source state generator that emits a series of single photons in a d…