Overcoming the uplink limit of satellite-based quantum communication with deterministic quantum teleportation

Zuo, Zhiyue; Wang, Yijun; Liao, Qin; Guo, Ying

doi:10.1103/physreva.104.022615

Cited by 14 publications

(10 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The parameters for numerical simulation are shown in Table I. It is worth noting that the selection of relevant parameters is similar to our previous work [13], [31], [38].…”

Section: Machine Learning Assisted Prediction Schemementioning

confidence: 95%

Machine Learning Assisted Prediction for Free-Space Continuous Variable Quantum Teleportation

Mao

Chen

et al. 2022

IEEE Photonics J.

Self Cite

View full text Add to dashboard Cite

Satellite-based quantum communication is critical in establishing a global quantum network for its ability to achieve thousand-kilometer-level tasks without the requirement of quantum relay. The free-space channel, however, is affected by diffraction, regular refraction, and atmospheric turbulence, which induce random wandering and broadening of the transmitted beam, resulting in the transmittance of fluctuation. In such a scenario, the ability to predict the unknown situation has become a problem worth considering. In this paper, we suggest a machine learning (ML) assisted prediction of continuous-variable quantum teleportation (CVQT) over satellite-ground channel. We apply the prediction algorithm, which involves k-nearest neighbor (KNN) algorithm and decision tree (DT) algorithm, to the squeezing parameter and the satellite altitude. Numerical analysis shows that the predicted parameter can reflect the actual derivation and calculation under certain circumstances within the allowable range of error. Moreover, we apply the prediction algorithm to the case affected by the fluctuating parameter transmittance. The results show that the ML-assisted prediction results are consistent with the actual data when zenith angles, turbulence strengths, and wavelengths are taken into account. It demonstrates the high identifying accuracy without increasing the complexity of the system.

show abstract

“…The parameters for numerical simulation are shown in Table I. It is worth noting that the selection of relevant parameters is similar to our previous work [13], [31], [38].…”

Section: Machine Learning Assisted Prediction Schemementioning

confidence: 95%

Machine Learning Assisted Prediction for Free-Space Continuous Variable Quantum Teleportation

Mao

Chen

et al. 2022

IEEE Photonics J.

Self Cite

View full text Add to dashboard Cite

show abstract

“…We consider a collimated Gaussian beam with an initial radius W 0 transmitted onto a telescope with radius a, and illustrate the results of clear night-time. Note that CV protocol has the potential to reach an all-day communication [36,37], and the performance of the day-time situation can be derived by updating the atmospheric parameters, i.e., refraction index structure parameter C 2 n , and the mean number of scatterer particles n 0 .…”

Section: Performance Analysismentioning

confidence: 99%

Noiseless Attenuation for Continuous-Variable Quantum Key Distribution over Ground-Satellite Uplink

Yin

Wang

et al. 2021

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Satellite-based quantum key distribution (QKD) has lately received considerable attention due to its potential to establish a secure global network. Associated with its application is a turbulent atmosphere that sets a notable restriction to the transmission efficiency, which is especially challenging for ground-to-satellite uplink scenarios. Here, we propose a novel noiseless attenuation (NA) scheme involving a zero-photon catalysis operation for source preparation to improve the performance of continuous-variable (CV) QKD over uplink. Numerical analysis shows that the NA-based CV-QKD, under attenuation optimization, outperforms the traditional CV-QKD, which is embodied in extending the allowable zenith angle while improving the effective communication time. Attributing to characteristics of the attenuation optimization, we find that the NA-involved source preparation improves the security bound by relatively reducing the amount of information available to eavesdroppers. Taking the finite-size effect into account, we achieve a tighter bond of security, which is more practical compared with the asymptotic limit.

show abstract

“…The lossy channel of CVQT system has been gradually extended from the initial fiber channel [3,10,11] to the free-space atmosphere channel [12,13], which has been verified [14][15][16][17][18]. Since the attenuation of seawater is more serious than that of optical fiber and atmospheric channel, the practicability of seawater as a communication medium is reduced.…”

Section: Introductionmentioning

confidence: 98%

Performance Analysis of Continuous Variable Quantum Teleportation with Noiseless Linear Amplifier in Seawater Channel

Liu

Zhang

et al. 2022

Symmetry

Self Cite

View full text Add to dashboard Cite

Continuous variable quantum teleportation (CVQT) is one of the technologies currently explored to implement global quantum networks. Entanglement source is an indispensable resource to realize CVQT, and its distribution process has natural symmetry. Though there are many results for CVQT over optical fiber or atmospheric channel, little attention is paid to seawater channel. In this paper, a model based on seawater chlorophyll concentration is used to study the attenuation effect of seawater on light. In our scheme, a noiseless linear amplifier is utilized for enhancing the performance of CVQT under seawater channel. Simulation results show that the proposed scheme has an improvement in terms of fidelity and maximum transmission distance compared with the original scheme.

show abstract

Overcoming the uplink limit of satellite-based quantum communication with deterministic quantum teleportation

Cited by 14 publications

References 67 publications

Machine Learning Assisted Prediction for Free-Space Continuous Variable Quantum Teleportation

Machine Learning Assisted Prediction for Free-Space Continuous Variable Quantum Teleportation

Noiseless Attenuation for Continuous-Variable Quantum Key Distribution over Ground-Satellite Uplink

Performance Analysis of Continuous Variable Quantum Teleportation with Noiseless Linear Amplifier in Seawater Channel

Contact Info

Product

Resources

About