Relative entropy in quantum information theory
Benjamin Schumacher (Kenyon College), Michael D. Westmoreland, (Denison University)
TL;DR
This paper reviews the properties of quantum relative entropy and explores its applications in quantum information transfer, data compression, entanglement quantification, and manipulation.
Contribution
It provides a comprehensive overview of quantum relative entropy and discusses its diverse applications in quantum information theory.
Findings
Quantum relative entropy characterizes information transfer efficiency.
It serves as a tool for quantifying and manipulating quantum entanglement.
Applications include quantum data compression and entanglement analysis.
Abstract
We review the properties of the quantum relative entropy function and discuss its application to problems of classical and quantum information transfer and to quantum data compression. We then outline further uses of relative entropy to quantify quantum entanglement and analyze its manipulation.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStatistical Mechanics and Entropy · Computability, Logic, AI Algorithms · Quantum Computing Algorithms and Architecture