Further Improving the Decoy State Quantum Key Distribution Protocol with Advantage Distillation
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Quantum Physics arXiv:2601.02565 (quant-ph) [Submitted on 5 Jan 2026] Title:Further Improving the Decoy State Quantum Key Distribution Protocol with Advantage Distillation Authors:Walter O. Krawec View a PDF of the paper titled Further Improving the Decoy State Quantum Key Distribution Protocol with Advantage Distillation, by Walter O. Krawec View PDF HTML (experimental) Abstract:In this paper, we revisit the application of classical advantage distillation (CAD) to the decoy-state BB84 protocol. Prior work has shown that CAD can greatly improve maximal distances and noise tolerances of the practical decoy state protocol. However, past work in deriving key-rate bounds for this protocol with CAD have assumed a trivial bound on the quantum entropy, whenever Alice sends a vacuum state in a CAD block (i.e., the entropy of such blocks is taken to be zero). Since such rounds contribute, negatively, to the error correction leakage, this results in a correct, though sub-optimal bound. Here, we derive a new proof of security for CAD applied to the decoy state BB84 protocol, computing a bound on Eve's uncertainty in all possible single and vacuum photon events. We use this to derive a new asymptotic key-rate bound which, we show, outperforms prior work, allowing for increased distances and noise tolerances. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2601.02565 [quant-ph] (or arXiv:2601.02565v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2601.02565 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Walter Krawec [view email] [v1] Mon, 5 Jan 2026 21:35:31 UTC (250 KB) Full-text links: Access Paper: View a PDF of the paper titled Further Improving the Decoy State Quantum Key Distribution Protocol with Advantage Distillation, by Walter O. KrawecView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-01 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) Links to Code Toggle Papers with Code (What is Papers with Code?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)