High-performance continuous-variable quantum secret sharing using a state-discrimination detector

Abstract Continuous-variable quantum secret sharing (CVQSS) is a promising approach to ensuring multi-party information security. While CVQSS offers practical ease of implementation, its present performance remains limited. In this paper, we propose a novel CVQSS protocol integrated with a state-discrimination detector (SDD), dubbed SDD-CVQSS. In particular, we first develop the detailed procedure of SDD-CVQSS, which replaces the traditional coherent detector with an SDD and eliminates the long-standing necessary step of establishing multiple point-to-point quantum key distribution links between all users and the dealer. We then elaborate on the principle of the specifically designed SDD, which can efficiently discriminate interfered states with a much lower error probability. Finally, we construct a security model for SDD-CVQSS and derive its security bound against both eavesdroppers and dishonest users. Numerical simulations show that SDD-CVQSS outperforms conventional CVQSS in terms of both maximum transmission distance and secret key rate, and its performance is even superior to the PLOB bound. Additionally, we find that the performance degradation of SDD-CVQSS in long-distance transmission scenarios can be effectively compensated for using a post-selection scheme, providing a feasible way to achieve high-performance CVQSS.

Authors

Publication Details

Journal
npj Quantum Information
Published
2026-05-14
DOI
https://doi.org/10.1038/s41534-026-01260-9
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High-performance continuous-variable quantum secret sharing using a state-discrimination detector

Lingjin Zhu, Qingquan Peng, Chao Ding, Chong Tang et al.
npj Quantum Information
Quantum Information and Cryptography
article

High-performance continuous-variable quantum secret sharing using a state-discrimination detector

Lingjin Zhu, Qingquan Peng, Chao Ding, Chong Tang, Yijun Wang, Yiyu Mao, Xiquan Fu, Qin Liao
article en

Abstract

Abstract Continuous-variable quantum secret sharing (CVQSS) is a promising approach to ensuring multi-party information security. While CVQSS offers practical ease of implementation, its present performance remains limited. In this paper, we propose a novel CVQSS protocol integrated with a state-discrimination detector (SDD), dubbed SDD-CVQSS. In particular, we first develop the detailed procedure of SDD-CVQSS, which replaces the traditional coherent detector with an SDD and eliminates the long-standing necessary step of establishing multiple point-to-point quantum key distribution links between all users and the dealer. We then elaborate on the principle of the specifically designed SDD, which can efficiently discriminate interfered states with a much lower error probability. Finally, we construct a security model for SDD-CVQSS and derive its security bound against both eavesdroppers and dishonest users. Numerical simulations show that SDD-CVQSS outperforms conventional CVQSS in terms of both maximum transmission distance and secret key rate, and its performance is even superior to the PLOB bound. Additionally, we find that the performance degradation of SDD-CVQSS in long-distance transmission scenarios can be effectively compensated for using a post-selection scheme, providing a feasible way to achieve high-performance CVQSS.

npj Quantum Information
Reduced inequalities
Openalex Percentile: Top 3%
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.