Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

European Signal Processing Conference (EUSIPCO)

Performance evaluation of scalar reconciliation for Continuous-Variable Quantum Key Distribution

Albert Mráz, Sándor Imre, László Gyöngyösi

Published Aug 1, 2016• 3 citations
Publisher

Abstract

The existing robust technique, Scalar Reconciliation combined with a Continuous-Variable Quantum Key Distribution is investigated in this paper with the help of simulations in terms of the symbol error rate. The solution contains efficient logical layer-based reconciliation for Continuous-Variable Quantum Key Distribution techniques, which extract the binary information from correlated Gaussian variables. The algorithm has been extended by different assumptions related to the raw data generation method and the segmentation of the key symbols to be transmitted. The performance of the extended algorithm has been investigated in terms of the symbol error ratio.

DOI
10.1109/eusipco.2016.7760298

Related papers

Scalar Reconciliation for Gaussian Modulation of Two-Way Continuous-Variable Quantum Key Distribution.

László Gyöngyösi

The two-way continuous-variable quantum key distribution (CVQKD) systems allow higher key rates and improved transmission distances over standard telecommunication networks in comparison to the one-way CVQKD protocols. To exploit the real potential of two-way CVQKD systems a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of a two-way CVQKD system. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we propose an efficient logical layer-based reconciliation method for two-way CVQKD to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the scalar space and the reconciliation can be extended to arbitrary high dimensions. We prove that the error probability of scalar reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow to significantly improve the currently available key rates and transmission distances of two-way CVQKD. The proposed scalar reconciliation can also be applied in one-way systems as well, to replace the existing reconciliation schemes.

•Aug 6, 2013•11 citations

Long-distance continuous-variable quantum key distribution with advanced reconciliation of a Gaussian modulation

László Gyöngyösi, Sándor Imre

The two-way continuous-variable quantum key distribution (CVQKD) systems allow higher key rates and improved transmission distances over standard telecommunication networks in comparison to the one-way CVQKD protocols. To exploit the real potential of two-way CVQKD systems a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of a two-way CVQKD system. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we propose an efficient logical layer-based reconciliation method for two-way CVQKD to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the scalar space and the reconciliation can be extended to arbitrary high dimensions. We prove that the error probability of scalar reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow to significantly improve the currently available key rates and transmission distances of two-way CVQKD. The proposed scalar reconciliation can also be applied in oneway systems as well, to replace the existing reconciliation schemes.

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE•Feb 19, 2014•20 citations

Low-Dimensional Reconciliation for Continuous-Variable Quantum Key Distribution

László Gyöngyösi, Sándor Imre

We propose an efficient logical layer-based reconciliation method for continuous-variable quantum key distribution (CVQKD) to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the low-dimensional (scalar) space, and the reconciliation can be extended to arbitrary dimensions. The CVQKD systems allow an unconditionally secret communication over standard telecommunication networks. To exploit the real potential of CVQKD a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of the CVQKD protocols. The reconciliation is a post-processing step separated from the transmission of quantum states, which is aimed to derive the secret key from the raw data. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we define the low-dimensional reconciliation. We prove that the error probability of one-dimensional reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow for significantly improving the currently available key rates and transmission distances of CVQKD.

arXiv:1308.1391•Applied Sciences•Jan 9, 2018•0 citations

Improved reconciliation for continuous-variable quantum key distribution

László Gyöngyösi, Sándor Imre

The performance of a continuous-variable quantum key distribution (CVQKD) protocol depends on the efficiency of the post-processing of measurement results. The post-processing methods extract statistical information from the raw data, establish the mutual knowledge between the parties, and produce a final key that provides absolute security. Here we define an optimization method for post-processing in continuous-variable quantum key distribution. The optimization framework allows significant performance improvements in the post-processing phase compared to other existing reconciliation approaches.

Advances in Photonics of Quantum Computing, Memory, and Communication•Mar 4, 2019•1 citation

Information Reconciliation for Continuous-Variable Quantum Key Distribution using Non-Binary Low-Density Parity-Check Codes

Christoph Pacher, Jesús Martínez-Mateo, Jörg Duhme +2 more

An information reconciliation method for continuous-variable quantum key distribution with Gaussian modulation that is based on non-binary low-density parity-check (LDPC) codes is presented. Sets of regular and irregular LDPC codes with different code rates over the Galois fields $GF(8)$, $GF(16)$, $GF(32)$, and $GF(64)$ have been constructed. We have performed simulations to analyze the efficiency and the frame error rate using the sum-product algorithm. The proposed method achieves an efficiency between $0.94$ and $0.98$ if the signal-to-noise ratio is between $4$ dB and $24$ dB.

arXiv:1602.09140•Feb 29, 2016•4 citations

Post-processing optimization for continuous-variable quantum key distribution

László Gyöngyösi

The performance of a continuous-variable quantum key distribution (CVQKD) protocol depends on the efficiency of the post-processing of measurement results. The post-processing methods extract statistical information from the raw data, establish the mutual knowledge between the parties, and produce a final key that provides absolute security. The post-processing phase is a bottleneck in CVQKD with crucial importance to the efficiency and protocol attributes. Post-processing uses the raw data of the parties generated by the quantum-level transmission and a classical authenticated channel to generate a secret key between the parties. The current reconciliation procedures require high-complexity coding with moderate resulting efficiency. Here we define an optimization method for post-processing in continuous-variable quantum key distribution. The reconciliation method achieves additive Gaussian noise on the random secret for arbitrarily low dimensional blocks. The model consumes all information from the raw data blocks to provide maximal efficiency and security via standard operations. The results can be realized by generic Gaussian coding schemes, allowing an easily implementation for experimental CVQKD protocols.

Theoretical Computer Science•Sep 1, 2021•8 citations
The existing robust technique, Scalar Reconciliation combined with a Continuous-Variable Quantum Key Distribution is investigated in this paper with the help of simulations in terms of the symbol error rate. The solution contains efficient logical layer-based reconciliation for Continuous-Variable Quantum Key Distribution techniques, which extract the binary information from correlated Gaussian variables. The algorithm has been extended by different assumptions related to the raw data generation method and the segmentation of the key symbols to be transmitted. The performance of the extended algorithm has been investigated in terms of the symbol error ratio.
The two-way continuous-variable quantum key distribution (CVQKD) systems allow higher key rates and improved transmission distances over standard telecommunication networks in comparison to the one-way CVQKD protocols. To exploit the real potential of two-way CVQKD systems a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of a two-way CVQKD system. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we propose an efficient logical layer-based reconciliation method for two-way CVQKD to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the scalar space and the reconciliation can be extended to arbitrary high dimensions. We prove that the error probability of scalar reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow to significantly improve the currently available key rates and transmission distances of two-way CVQKD. The proposed scalar reconciliation can also be applied in one-way systems as well, to replace the existing reconciliation schemes.
The two-way continuous-variable quantum key distribution (CVQKD) systems allow higher key rates and improved transmission distances over standard telecommunication networks in comparison to the one-way CVQKD protocols. To exploit the real potential of two-way CVQKD systems a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of a two-way CVQKD system. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we propose an efficient logical layer-based reconciliation method for two-way CVQKD to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the scalar space and the reconciliation can be extended to arbitrary high dimensions. We prove that the error probability of scalar reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow to significantly improve the currently available key rates and transmission distances of two-way CVQKD. The proposed scalar reconciliation can also be applied in oneway systems as well, to replace the existing reconciliation schemes.
We propose an efficient logical layer-based reconciliation method for continuous-variable quantum key distribution (CVQKD) to extract binary information from correlated Gaussian variables. We demonstrate that by operating on the raw-data level, the noise of the quantum channel can be corrected in the low-dimensional (scalar) space, and the reconciliation can be extended to arbitrary dimensions. The CVQKD systems allow an unconditionally secret communication over standard telecommunication networks. To exploit the real potential of CVQKD a robust reconciliation technique is needed. It is currently unavailable, which makes it impossible to reach the real performance of the CVQKD protocols. The reconciliation is a post-processing step separated from the transmission of quantum states, which is aimed to derive the secret key from the raw data. The reconciliation process of correlated Gaussian variables is a complex problem that requires either tomography in the physical layer that is intractable in a practical scenario, or high-cost calculations in the multidimensional spherical space with strict dimensional limitations. To avoid these issues, we define the low-dimensional reconciliation. We prove that the error probability of one-dimensional reconciliation is zero in any practical CVQKD scenario, and provides unconditional security. The results allow for significantly improving the currently available key rates and transmission distances of CVQKD.
The performance of a continuous-variable quantum key distribution (CVQKD) protocol depends on the efficiency of the post-processing of measurement results. The post-processing methods extract statistical information from the raw data, establish the mutual knowledge between the parties, and produce a final key that provides absolute security. Here we define an optimization method for post-processing in continuous-variable quantum key distribution. The optimization framework allows significant performance improvements in the post-processing phase compared to other existing reconciliation approaches.
An information reconciliation method for continuous-variable quantum key distribution with Gaussian modulation that is based on non-binary low-density parity-check (LDPC) codes is presented. Sets of regular and irregular LDPC codes with different code rates over the Galois fields GF(8)GF(8)GF(8), GF(16)GF(16)GF(16), GF(32)GF(32)GF(32), and GF(64)GF(64)GF(64) have been constructed. We have performed simulations to analyze the efficiency and the frame error rate using the sum-product algorithm. The proposed method achieves an efficiency between 0.940.940.94 and 0.980.980.98 if the signal-to-noise ratio is between 444 dB and 242424 dB.
The performance of a continuous-variable quantum key distribution (CVQKD) protocol depends on the efficiency of the post-processing of measurement results. The post-processing methods extract statistical information from the raw data, establish the mutual knowledge between the parties, and produce a final key that provides absolute security. The post-processing phase is a bottleneck in CVQKD with crucial importance to the efficiency and protocol attributes. Post-processing uses the raw data of the parties generated by the quantum-level transmission and a classical authenticated channel to generate a secret key between the parties. The current reconciliation procedures require high-complexity coding with moderate resulting efficiency. Here we define an optimization method for post-processing in continuous-variable quantum key distribution. The reconciliation method achieves additive Gaussian noise on the random secret for arbitrarily low dimensional blocks. The model consumes all information from the raw data blocks to provide maximal efficiency and security via standard operations. The results can be realized by generic Gaussian coding schemes, allowing an easily implementation for experimental CVQKD protocols.