Improved bounds on quantum uncommon information

Abstract In classical information theory, channel capacity quantifies the maximum number of messages that can be reliably transmitted using shared information. An equivalent concept, termed uncommon information , represents the number of messages required to be exchanged to completely share all information in common. However, this equivalence does not extend to quantum information theory. Specifically, quantum uncommon information (QUI) is operationally defined as the minimal amount of entanglement required for the quantum communication task of quantum state exchange (QSE), where two parties exchange quantum states to share all quantum messages in common. Currently, an analytical closed-form expression for the QUI remains undetermined. In this work, by investigating underlying characterization of the QUI, we derive improved bounds on it. To obtain these bounds, we develop a subspace exchange strategy that leverages a common subspace of two parties to identify the unnecessary qubits for exchange. We also consider a referee-assisted exchange , wherein a referee aids two parties in efficiently performing the QSE. Our bounds provide more precise estimations for the QUI. Furthermore, we demonstrate that the subspace technique is a versatile tool for characterizing uncommon information not only in the bipartite scenario but also in various multi-partite ones.

Authors

Institutions

Publication Details

Journal
Journal of Physics A Mathematical and Theoretical
Published
2025-01-22
DOI
https://doi.org/10.1088/1751-8121/adad1f
Citations
1
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
2.48

Funders

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

Improved bounds on quantum uncommon information

Joonwoo Bae, Hayata Yamasaki, Yonghae Lee, Soojoon Lee
1 citations
Journal of Physics A Mathematical and Theoretical
Quantum Information and Cryptography
2.48
article

Improved bounds on quantum uncommon information

Joonwoo Bae, Hayata Yamasaki, Yonghae Lee, Soojoon Lee
article en
1 citations

Abstract

Abstract In classical information theory, channel capacity quantifies the maximum number of messages that can be reliably transmitted using shared information. An equivalent concept, termed uncommon information , represents the number of messages required to be exchanged to completely share all information in common. However, this equivalence does not extend to quantum information theory. Specifically, quantum uncommon information (QUI) is operationally defined as the minimal amount of entanglement required for the quantum communication task of quantum state exchange (QSE), where two parties exchange quantum states to share all quantum messages in common. Currently, an analytical closed-form expression for the QUI remains undetermined. In this work, by investigating underlying characterization of the QUI, we derive improved bounds on it. To obtain these bounds, we develop a subspace exchange strategy that leverages a common subspace of two parties to identify the unnecessary qubits for exchange. We also consider a referee-assisted exchange , wherein a referee aids two parties in efficiently performing the QSE. Our bounds provide more precise estimations for the QUI. Furthermore, we demonstrate that the subspace technique is a versatile tool for characterizing uncommon information not only in the bipartite scenario but also in various multi-partite ones.

Journal of Physics A Mathematical and TheoreticalVol. 58(5)
Korea Advanced Institute of Science and Technology (KR), Kangwon National University (KR), Kyung Hee University (KR), Institute for Basic Science (KR), The University of Tokyo (JP)
Ministry of Education, Culture, Sports, Science and Technology, National Research Foundation of Korea, Japan Society for the Promotion of Science, Japan Science and Technology Agency, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 12%
Quantum Information and Cryptography
2.48
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.