Multidimensional Reconciliation in Continuous-Variable QKD: Review, Coding Schemes, and Open Source Simulation
摘要
Continuous-variable quantum key distribution (CV-QKD) requires highly efficient reconciliation techniques to operate at low signal-to-noise ratios and long distances. Multidimensional reconciliation addresses this challenge by transforming the physical Gaussian quantum channel into a virtual binary-input additive white Gaussian noise (BIAWGN) channel, enabling the use of modern errorcorrecting codes. In this work, we review the principles of multidimensional reconciliation, with a particular focus on high-dimensional constructions beyond the algebraic dimensions 1, 2, 4, 8. We describe the construction of the virtual channel, discuss practical coding schemes for reverse reconciliation, and analyse their integration with linear error-correcting codes. We also present an opensource simulation framework, HDirac, implementing multidimensional reconciliation for arbitrary dimensions, and use it to evaluate state-of-the-art LDPC codes. The results highlight key trade-offs between dimension, reconciliation efficiency, and frame error rate, providing practical guidance for CV-QKD system design.
正文
Continuous-variable quantum key distribution (CV-QKD) requires highly efficient reconciliation techniques to operate at low signal-to-noise ratios and long distances. Multidimensional reconciliation addresses this challenge by transforming the physical Gaussian quantum channel into a virtual binary-input additive white Gaussian noise (BIAWGN) channel, enabling the use of modern errorcorrecting codes. In this work, we review the principles of multidimensional reconciliation, with a particular focus on high-dimensional constructions beyond the algebraic dimensions 1, 2, 4, 8. We describe the construction of the virtual channel, discuss practical coding schemes for reverse reconciliation, and analyse their integration with linear error-correcting codes. We also present an opensource simulation framework, HDirac, implementing multidimensional reconciliation for arbitrary dimensions, and use it to evaluate state-of-the-art LDPC codes. The results highlight key trade-offs between dimension, reconciliation efficiency, and frame error rate, providing practical guidance for CV-QKD system design. Authors: Martial Lucien, Rosio Alexis, Diamanti Eleni, Cassagne Adrien, Gouraud Baptiste Categories: cs.IT, cs.CR, quant-ph PDF: https://arxiv.org/pdf/2606.02323v1 Comment: 15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac
标签
- category:cs.cr
- category:cs.it
- category:quant-ph
- primary_category:cs.it
- source:arxiv
- type:paper
扩展字段
{
"arxiv_id": "2606.02323v1",
"authors": [
"Martial Lucien",
"Rosio Alexis",
"Diamanti Eleni",
"Cassagne Adrien",
"Gouraud Baptiste"
],
"categories": [
"cs.IT",
"cs.CR",
"quant-ph"
],
"comment": "15 pages, 8 figures. Link to the open-source project: https://github.com/aff3ct/HDirac",
"doi": null,
"entry_id": "https://arxiv.org/abs/2606.02323v1",
"pdf_url": "https://arxiv.org/pdf/2606.02323v1",
"primary_category": "cs.IT",
"search_query": "cat:cs.CR",
"updated_at": "2026-06-01T14:36:12+00:00"
}