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Two MET-LDPC Codes Designed for Long-Distance CV-QKD Hossein Mani , Bernhard ¨ Omer * , Ulrik Lund Andersen , Tobias Gehring , Christoph Pacher * Center of Macroscopic Quantum States, bigQ, Department of Physics, Fysikvej 307, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark * Center for Digital Safety & Security, AIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria Two MET-LDPC Codes Designed for Long-Distance CV-QKD Hossein Mani , Bernhard ¨ Omer * , Ulrik Lund Andersen , Tobias Gehring , Christoph Pacher * Center of Macroscopic Quantum States, bigQ, Department of Physics, Fysikvej 307, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark * Center for Digital Safety & Security, AIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria Summary We propose two new highly efficient MET-LDPC codes for the post processing of CV-QKD The first code is a MET-LDPC code of rate 0.02 with code efficiency of 99.2% obtained by Density Evolution The second code is a MET-LDPC code of rate 0.01 with code efficiency of 98.7% obtained by Density Evolution. Why do we need highly efficient codes? The secret key rate equation for CV-QKD is K = n N (1 - FER) [ βI A,B -X E,B - Δ(n) ] N : Total number of symbols exchanged by Alice and Bob n : Total number of symbols used for key extraction FER : Frame error rate of the reconciliation process β : Efficiency of the reconciliation process I A,B : Classical mutual information between Alice and Bob X E,B : Upper bound on the information that Eve can obtain from Bob Δ(n) : Finite-size correction factor Figure 1 Effective finite secure key rate against collective attack on Gaussian modu- lated CV-QKD with multidimensional reconciliation. The reconciliation efficiency β = {0.7, 0.8, 0.9, 0.95, 1.00}. The parameters used in the calculations are V mod =8.5, ξ ch =0.015 (excess noise), η =0.6 (detector efficiency), v el =0.041 (trusted electronic noise), N =2 * 10 10 , n = 10 10 , security = 10 -10 , and the fiber loss is assumed to be 0.2 dB/km. References [1] Paul Jouguet, et al. Long-distance continuous-variable quantum key distribution with a Gaussian modulation, Phys. Rev. A, vol. 84, p. 062317, Dec 2011. [Online]. Available: https://link.aps.org/doi/10.1103/PhysRevA.84.062317 [2] Hossein Mani, et al. Reconciliation of Weakly Correlated Information Sources Utilizing Generalized EXIT Chart.arXiv preprint arXiv:1812.05867 (2018). [Online]. Available: https: //arxiv.org/abs/1812.05867 Results: Optimized code structures ν bd b d μ d d 0.02 0.02 0.96 [0 1] 2 51 0 3 60 0 0 0 1 0.016 0.004 0.30 0.66 4 0 0 9 0 0 0 3 1 0 2 1 σ * Sh =5.96 σ * DE =5.94 β DE = 99.2% Table I Structure of optimized MET-LDPC code of rate 0.02 with 3 edge types. Detailed description can be found in [2]. ν bd b d μ d d 0.01 0.01 0.98 [0 1] 2 103 0 3 125 0 0 0 1 0.008 0.002 0.32 0.66 400 900 031 021 σ * Sh =8.46 σ * DE =8.41 β DE = 98.7% Table II Structure of optimized MET-LDPC code of rate 0.01 with 3 edge types: Edge 1 Edge 2 Edge 3 0.02 N 0.02 N 0.96 N 0.016 N 0.004 N 0.30 N 0.66 N 2 51 4 9 3 60 1 1 1 3 2 Figure 2 Graphical representation of the MET-LDPC code of rate 0.02. Detailed description can be found in [2]. Contact info H. M [email protected] B. ¨ O [email protected] U. L. A [email protected] T. G [email protected] C. P * [email protected] Results: Performance comparison Figure 3 (Upper) Frame error rate vs SNR for rate 0.02 MET-LDPC code. Dashed blue and red vertical lines show thresholds calculated by density evolution. Solid curves show values obtained from LDPC decoding. (Lower) Efficiency vs frame error rate obtained from LDPC decoding. Acknowledgments This project has received funding from the European Union’s Horizon 2020 research and inno- vation programme under grant agreement No 820466 (CiViQ) and grant agreement No 820474 (UNIQORN). The authors thank the Quantum Innovation Center Qubiz funded by the Innovation Fund Denmark for support. H.M., T.G., and U.L.A. acknowledge support from the Danish National Research Foundation, Center for Macroscopic Quantum States (bigQ, DNRF142).

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Page 1: N Two MET-LDPC Codes Designed for Long-Distance CV ...Two MET-LDPC Codes Designed for Long-Distance CV-QKD Hossein Maniy, Bernhard O mer, Ulrik Lund Anderseny, Tobias Gehringy, Christoph

Two MET-LDPC Codes Designed for Long-Distance CV-QKD

Hossein Mani†, Bernhard Omer∗, Ulrik Lund Andersen†, Tobias Gehring†, Christoph Pacher∗

† Center of Macroscopic Quantum States, bigQ, Department of Physics, Fysikvej 307, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark

∗ Center for Digital Safety & Security, AIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria

Two MET-LDPC Codes Designed for Long-Distance CV-QKD

Hossein Mani†, Bernhard Omer∗, Ulrik Lund Andersen†, Tobias Gehring†, Christoph Pacher∗

† Center of Macroscopic Quantum States, bigQ, Department of Physics, Fysikvej 307, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark

∗ Center for Digital Safety & Security, AIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria

Summary

We propose two new highly efficient MET-LDPC codes for the post processingof CV-QKD

• The first code is a MET-LDPC code of rate 0.02 with code efficiency of 99.2% obtained byDensity Evolution

• The second code is a MET-LDPC code of rate 0.01 with code efficiency of 98.7% obtainedby Density Evolution.

Why do we need highly efficient codes?

The secret key rate equation for CV-QKD is

K =n

N(1− FER) [β IA,B −XE,B −∆(n)]

N : Total number of symbols exchanged by Alice and Bobn : Total number of symbols used for key extractionFER : Frame error rate of the reconciliation processβ : Efficiency of the reconciliation processIA,B : Classical mutual information between Alice and BobXE,B : Upper bound on the information that Eve can obtain from Bob

∆(n) : Finite-size correction factor

Figure 1 Effective finite secure key rate against collective attack on Gaussian modu-lated CV-QKD with multidimensional reconciliation. The reconciliation efficiency β ={0.7, 0.8, 0.9, 0.95, 1.00}. The parameters used in the calculations are Vmod = 8.5 , ξch = 0.015(excess noise), η = 0.6 (detector efficiency), vel = 0.041 (trusted electronic noise), N = 2 ∗ 1010,n = 1010, εsecurity = 10−10, and the fiber loss is assumed to be 0.2 dB/km.

References

[1] Paul Jouguet, et al. “Long-distance continuous-variable quantum key distribution with aGaussian modulation, ”Phys. Rev. A, vol. 84, p. 062317, Dec 2011. [Online]. Available:https://link.aps.org/doi/10.1103/PhysRevA.84.062317

[2] Hossein Mani, et al. ”Reconciliation of Weakly Correlated Information Sources UtilizingGeneralized EXIT Chart.”arXiv preprint arXiv:1812.05867 (2018). [Online]. Available: https://arxiv.org/abs/1812.05867

Results: Optimized code structures

νbd b d µd d

0.020.020.96

[0 1]2 51 03 60 00 0 1

0.0160.0040.300.66

4 0 09 0 00 3 10 2 1

σ∗Sh

= 5.96 σ∗DE

= 5.94 βDE

= 99.2%

Table I Structure of optimized MET-LDPC code of rate 0.02 with 3 edge types. Detailed description canbe found in [2].

νbd b d µd d

0.010.010.98

[0 1]2 103 03 125 00 0 1

0.0080.0020.320.66

4 0 09 0 00 3 10 2 1

σ∗Sh

= 8.46 σ∗DE

= 8.41 βDE

= 98.7%

Table II Structure of optimized MET-LDPC code of rate 0.01 with 3 edge types:

Edge 1

Edge 2

Edge 3

0.02 N

0.02 N

0.96 N

0.016 N

0.004 N

0.30 N

0.66 N

2

51

4

93

60

1

1

1

3

2

Figure 2 Graphical representation of the MET-LDPC code of rate 0.02. Detailed description can be foundin [2].

Contact info

H. M [email protected]

B. O [email protected]

U. L. A [email protected]

T. G † [email protected]. P ∗ [email protected]

Results: Performance comparison

Figure 3 (Upper) Frame error rate vs SNR for rate 0.02 MET-LDPC code. Dashed blue andred vertical lines show thresholds calculated by density evolution. Solid curves show valuesobtained from LDPC decoding. (Lower) Efficiency vs frame error rate obtained from LDPCdecoding.

Acknowledgments

This project has received funding from the European Union’s Horizon 2020 research and inno-vation programme under grant agreement No 820466 (CiViQ) and grant agreement No 820474(UNIQORN).The authors thank the Quantum Innovation Center Qubiz funded by the Innovation FundDenmark for support. H.M., T.G., and U.L.A. acknowledge support from the Danish NationalResearch Foundation, Center for Macroscopic Quantum States (bigQ, DNRF142).