Quantum separability criteria based on symmetric measurements

We propose experimentally feasible separability criteria for bipartite systems based on local symmetric measurements. Through detailed examples, we demonstrate that our criteria can detect entanglement more effectively compared to existing counterparts. Furthermore, we demonstrate the potential for our results to be generalized to general multipartite systems.

Authors

Institutions

Publication Details

Journal
Physical review. A/Physical review, A
Published
2025-11-24
DOI
https://doi.org/10.1103/v9gs-6jvz
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum separability criteria based on symmetric measurements

Yu Lu, Zhi‐Xi Wang, Hongxing Wu, Shao-Ming Fei et al.
Physical review. A/Physical review, A
Quantum Information and Cryptography
article

Quantum separability criteria based on symmetric measurements

Yu Lu, Zhi‐Xi Wang, Hongxing Wu, Shao-Ming Fei, Wen Zhou, Meng Su
article en

Abstract

We propose experimentally feasible separability criteria for bipartite systems based on local symmetric measurements. Through detailed examples, we demonstrate that our criteria can detect entanglement more effectively compared to existing counterparts. Furthermore, we demonstrate the potential for our results to be generalized to general multipartite systems.

Physical review. A/Physical review, AVol. 112(6)
Shangrao Normal University (CN), Capital Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 79%
Quantum Information and Cryptography
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.