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REVIEW 2 major objections 4 minor 79 references

Analysis of untrusted-node quantum key distribution from a geostationary satellite

T0 review · 2 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read A single geostationary satellite carrying two 50 cm telescopes could support untrusted-node quantum key distribution with terrestrial stations of 20 cm to 1 m aperture, achieving secret-key rates of a few hundred bits per second with…

desk verdict First serious rate estimates for GEO untrusted-node TF/MP-QKD; results hinge on simulated MMSE gain and optimistic detector assumptions, but the paper is careful and deserves peer review. read the letter →

arxiv 2507.23466 v1 pith:RUPSFLOZ submitted 2025-07-31 quant-ph

classification quant-ph
keywords quantumkeydistributiontwin-fieldQKDmode-pairingmeasurement-device-independentgeostationarysatelliteadaptiveopticsuplinkprecompensationfree-spaceopticalturbulenceuntrusted-nodenetwork
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Quantum key distribution over continental distances usually forces a choice between trusting intermediate relay nodes or building very large telescopes. This paper argues that a single geostationary satellite acting as an untrusted measurement node, equipped with two 50 cm telescopes and talking to ground stations with apertures from 20 cm to 1 m, can avoid both costs by using two loss-resilient protocols, twin-field and mode-pairing QKD. In the best case with realistic detectors, the simulated secret-key rates reach roughly 260 bit/s for TF-QKD and 180 bit/s for MP-QKD at 1 m ground apertures, and positive rates appear even at 20 cm once detector performance matches ground-based superconducting detectors. The result matters because such a node would serve roughly a third of the planet's surface without trusted relays and without requiring meter-class ground infrastructure.

What carries the argument

The carrying mechanism is a reciprocity identity: the coupling efficiency of the precompensated uplink into the satellite receiver equals the coupling of the satellite receiver mode back-propagated to the ground and coupled to the transmitter mode, evaluated at the point-ahead angle. This turns the GEO uplink with adaptive-optics correction into a downlink problem solvable with known phase and log-amplitude statistics, with a numerical overlap integral as the final step. The paper compares a standard on-axis phase correction with an MMSE estimator that reconstructs the phase at the point-ahead angle from downlink phase and amplitude measurements. The resulting per-channel efficiency distributions are convolved with satellite-jitter losses and fixed losses to form the probability distribution of transmission efficiency $\tau$, which is then fed into square-root-scaling secret-key-rate models for sending-or-not-sending TF-QKD and MP-QKD; a Gaussian phase-drift model with standard deviation $\sigma_{\mathrm{fs}}=150$ rad/s sets the phase-locking requirement for TF-QKD and the optimal maximal pairing length $L_{\mathrm{max}}$ for MP-QKD.

What would settle it

Measure the uplink coupling efficiency of a 1 m ground station with MMSE precompensation to a GEO terminal at 30° elevation and 1550 nm under turbulence comparable to the model's ($r_0=25$ cm, $\theta_0=8.51\ \mu$rad). If the mean turbulence coupling falls below the simulated value of about $0.56$ or the mean one-way channel attenuation stays above roughly $60$ dB, the predicted few-hundred-bit/s rates would not survive; a free-space phase drift several times larger than the assumed $150$ rad/s would likewise break the TF-QKD phase-locking and MP-QKD pairing assumptions.

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Extended reading notes

Core claim

The paper's central claim is that a GEO satellite carrying two 50 cm telescopes can act as an untrusted measurement node for TF-QKD and MP-QKD with practical ground stations. Using the simulated channel model with MMSE adaptive-optics precompensation, the optimum secret-key rate at 1 m ground apertures is about $260$ bit/s for TF-QKD and $180$ bit/s for MP-QKD when detectors have 70% efficiency and dark-count probability $10^{-8}$; with detector parameters matching ground-based superconducting nanowire detectors (90% efficiency, dark-count probability $4\times10^{-10}$), both protocols give positive rates down to 20 cm apertures, reaching $822$ bit/s for TF-QKD and $280$ bit/s for MP-QKD at 1 m. With currently demonstrated space-qualified detector parameters (50% efficiency, 100 Hz dark count), only MP-QKD with 1 m ground stations gives a positive rate, $17$ bit/s. The authors conclude that detector performance and advanced adaptive-optics correction, rather than telescope size, set the feasibility boundary for a scalable GEO untrusted-node QKD service.

Load-bearing premise

The load-bearing premise is that the advanced MMSE adaptive-optics precompensation achieves in a real GEO uplink the coupling efficiencies the simulation assigns to it; with only standard correction the model predicts no positive key rate at any studied aperture.

Editorial extensions

If this is right

  • With 1 m ground stations and MMSE precompensation, the predicted maximum rates are ~260 bit/s for TF-QKD and ~180 bit/s for MP-QKD under the optimistic realistic detector scenario (70% efficiency, dark-count probability $10^{-8}$).
  • Under the currently demonstrated space-detector parameters (50% efficiency, 100 Hz dark count), the model still yields 17 bit/s for MP-QKD with two 1 m stations, so a positive-rate GEO link is within reach of present hardware.
  • If space detectors reach ground-commercial performance (90% efficiency, 1 Hz dark count), both protocols give positive rates down to 20 cm ground apertures, with rates of 822 bit/s (TF-QKD) and 280 bit/s (MP-QKD) at 1 m.
  • With standard, non-MMSE adaptive-optics correction, the model finds no positive key rate at any studied aperture, making the advanced precompensation a necessary ingredient of the predicted performance.
  • MP-QKD achieves the same order of magnitude of key rate as TF-QKD without global phase locking, which the paper identifies as a practical advantage for space deployment.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A consequence the paper leaves implicit is network-level: the same per-link rates, combined with GEO coverage geometry, imply a single satellite could act as a key-distribution hub for many small ground stations, with total throughput set by detector dark counts and scheduling rather than by telescope size.
  • The detector comparison sets a concrete technology target: space-qualified SNSPDs with dark-count probability below about $10^{-8}$ and efficiency above about 70% would make the 20 cm terminal viable, a threshold that a dedicated space-demonstration mission could test before committing to a full QKD service.
  • The assumed free-space phase-drift standard deviation of $150$ rad/s implies TF-QKD phase locking over GEO needs only millisecond-scale feedback; an experimental measurement of the drift on a real GEO uplink would settle whether phase locking is a modest engineering task or a dominant cost.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 4 minor

Summary. The paper analyzes the feasibility of untrusted-node satellite QKD using twin-field (TF) and mode-pairing (MP) protocols with a geostationary satellite as the central untrusted node. It develops an end-to-end channel model that includes atmospheric turbulence with adaptive optics (SoA and MMSE pre-compensation), satellite pointing jitter, geometrical/absorption/system losses, and detector dark counts and efficiency. The authors simulate the probability distribution of the end-to-end transmission efficiency and compute asymptotic secret key rates for TF-QKD and MP-QKD for ground telescope apertures from 20 cm to 1 m, under three detector scenarios (optimistic, pessimistic/space-demonstrated, and idealized). They find, in the optimistic scenario, maximum rates around 260 bit/s (TF) and 180 bit/s (MP) at 1 m apertures, and positive rates at 20 cm only for the idealized detector parameters; with only state-of-the-art AO correction no positive key rate is found for any aperture.

Significance. This is one of the first detailed end-to-end simulations of an untrusted-node GEO satellite QKD architecture with small-aperture ground telescopes. The work is thorough in its channel modeling: it uses the reciprocity principle for pre-compensated uplinks, a pseudo-analytical turbulence model, a realistic jitter model, and the established asymmetric TF and MP-QKD security formulas. It also compares multiple detector scenarios, which is useful for assessing technology roadmaps. The key-rate predictions are quantitative and falsifiable. However, the central feasibility claim is conditional on the MMSE adaptive-optics model (not independently validated here) and on the optimistic detector scenario for the headline numbers; these conditions must be clearly communicated.

major comments (2)
  1. [Abstract and Section IV C 3] The abstract's central claim of 'a few hundred bit/s for both TF and MP-QKD' 'considering realistic detectors' is not supported by the detector scenario that corresponds to currently demonstrated space technology. With the space-qualified detector parameters from [49] (pd=4e-8, etaD=50%), the paper reports positive rates only for MP-QKD with a 1 m OGS aperture, at 17 bit/s (Section IV C 3), and no positive rate for TF-QKD. The few-hundred-bit/s figures are obtained for the 'optimistic' scenario (pd=1e-8, etaD=70%), which the paper itself labels as not yet demonstrated in space, and for 20 cm apertures only the 'idealized' scenario (pd=4e-10, etaD=90%) yields positive rates. Please either present the demonstrated-technology rates as the headline or explicitly label the optimistic/idealized assumptions as future-technology projections in the abstract.
  2. [Section IV C 1 and Appendix A] Every positive key rate in the paper relies on the MMSE pre-compensation model: the paper states in Section IV C 1 that with SoA correction 'we did not obtain a positive key rate for any aperture diameter under these conditions.' The MMSE model is taken from the authors' previous work [32,62] and is not validated against an independent experiment or simulation in this manuscript. The residual covariance model in Eqs. (A14)-(A15) assumes known phase/amplitude statistics, no wavefront-sensor noise, no temporal error, and an exact point-ahead covariance; deviations from these idealizations would reduce the achieved coupling. Because the key rate is a threshold function of the tail of the PDTE, a modest overestimate of the MMSE gain (the mean coupling gain is only ~1.5 dB at 1 m, Table II) could eliminate the claimed positive rates. Please add a sensitivity analysis of the final key rates to the assumed MMSE residual variance (e.g., by scaling the covariance or adding uncorrected wavefront-sensor noise), and discuss how the results would degrade if MMSE performance fell between the SoA and ideal cases.
minor comments (4)
  1. [Appendix C, Eq. (C3)] The free-space phase-drift term e^{-sigma_fs^2 Delta t^2/2} is inconsistent with the text stating sigma_fs is the per-channel drift. For two independent uplink channels, the difference Delta theta_fs,b - Delta theta_fs,a has variance 2 sigma_fs^2, so the exponent should be -sigma_fs^2 Delta t^2. As written, the phase error is underestimated by a factor of sqrt(2) in the standard deviation. The numerical impact is small for the parameters used here (sigma_fs Delta t << 1), but the formula and text should be reconciled.
  2. [Text before Eq. (C3)] The sentence 'the linewidth effect follows a Gaussian distribution with a standard deviation of sqrt(2) sigma_nu' is ambiguous: the sqrt(2) factor arises from the difference between Alice's and Bob's laser frequencies, not from the round index. Please rephrase to clarify which difference is being considered.
  3. [Section IV] The simulated key rates are point estimates from Monte Carlo sampling of the turbulence and jitter distributions, but the number of samples and the statistical uncertainty are not reported. Given that the 20 cm aperture cases lie near threshold, provide confidence intervals or at least state the number of Monte Carlo draws.
  4. [Section I] The claim that the GEO satellite coverage is 'approximately one-third of the planet's surface' is not quantified with a source; consider adding a reference or a clarifying calculation.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the QKD rates are computed from external protocol formulas and a prior AO channel model, with no target result assumed as an input.

full rationale

The paper's derivation chain is a forward simulation: Section II builds a channel model (Eq. 1) from independent loss factors; Eqs. (A3)-(A15) implement a reciprocity-based turbulence model whose MMSE reconstructor is taken from Ref. [32]; the QKD secret-key rates are computed with security models from Refs. [20,46] (Appendix B), decoy-state bounds, and phase-drift formulas from Refs. [17,51] (Appendix C). No equation in the paper defines a quantity in terms of the final key rate, and no fitted parameter is relabeled as a prediction: the parameters tau_abs, theta_jitter, p_d, eta_D, and sigma_fs are inputs with stated sources, and the intensity mu is optimized. The main caveat, namely that positive rates require the MMSE pre-compensation model and that with state-of-the-art correction no positive rate is obtained, is a robustness or validation issue rather than a circularity: the MMSE model was developed and published in prior work (Ref. [32]) by overlapping authors, but it does not assume the QKD rates derived here, and the present paper re-implements the published model instead of using the target result as an input. Similarly, Refs. [25,34,35,62] are self-citations that supply channel statistics and AO tools, but they are independent prior results that do not contain the present QKD-rate claim. No uniqueness theorem is invoked to forbid alternatives, and no known result is renamed as a new unification. The conditional dependence on simulated AO performance should be assessed as a scientific risk, not as circular reasoning.

Assumptions & free parameters 9 free parameters · 6 assumptions · 0 invented entities

The central key-rate estimates rest on a large set of hand-chosen or externally sourced simulation parameters and on the validity of previously published security and turbulence models. The most fragile are the MMSE pre-compensation performance, the free-space phase drift model, and the detector scenarios, none of which are independently validated in this paper.

free parameters (9)
  • free-space phase drift standard deviation sigma_fs = 150 rad/s per uplink channel
    Extracted from the VERTIGO simulation dataset for a severe turbulence profile (Section III C, Fig 4); used in the MP-QKD phase error model and strongly influences the maximal pairing length and key rate.
  • optimistic detector scenario (dark count probability pd, detection efficiency etaD) = pd=1e-8 (Y0=25 Hz), etaD=70%
    Adopted for the main results in Table I and Section IV C; labeled 'optimistic' in Section III C, corresponding to ground-based SNSPD performance not yet demonstrated in space.
  • pessimistic space detector scenario = pd=4e-8 (Y0=100 Hz), etaD=50%
    Based on demonstrated space SNSPD from Ref [49]; used for the 17 bit/s current-technology estimate.
  • idealized space detector scenario = pd=4e-10 (Y0=1 Hz), etaD=90%
    Assumes ground state-of-the-art detectors are brought to space; required for positive key rates with 20 cm telescopes.
  • point-ahead angle alpha_PAA = 18.5 murad
    Taken from Refs [32,52] for the GEO geometry; sets the anisoplanatic error in the AO correction model.
  • OGS static misalignment Delta_alpha = 0.2 murad
    Chosen value from Ref [21]; modeled as a static tip-tilt phase term.
  • satellite residual tracking jitter theta_jitter = 0.07 murad
    Value from Ref [58]; used in the Weibull jitter loss model.
  • system fixed loss tau_syst = 2.8 dB
    Fixed optical system attenuation assumed in Table I.
  • atmospheric turbulence scenario = r0=25 cm, theta0=8.51 murad, sigma_chi^2=0.03 at 1550 nm, 30 deg elevation
    Nighttime 25-percentile MOSPAR profile from Refs [35,53,54]; defines the turbulence strength, isoplanatic angle, and scintillation used throughout.
assumptions (6)
  • domain assumption Total channel loss factorizes into independent turbulence, jitter, absorption, system, and geometric losses (Eq 1).
    Invoked in Section II A. Standard for free-space links, but ignores correlations between loss mechanisms.
  • domain assumption Reciprocity principle maps the AO-pre-compensated uplink coupling to a downlink coupling at the point-ahead angle (Eq A3).
    Invoked in Appendix A. Requires the turbulent medium to be frozen during propagation and the uplink/downlink corrections to be equivalent.
  • domain assumption Both OGS channels are statistically identical and asymmetries can be symmetrized by adding loss at Charlie or adjusting intensities (Section III).
    Used to justify the symmetric-channel key-rate formulas; assumes probing the instantaneous transmission adds no noise.
  • standard math Asymptotic decoy-state security models for TF-QKD (Ref [46]) and MP-QKD (Ref [20]) are valid.
    The key rate formulas in Appendix B rely on these published security analyses; finite-size effects are neglected.
  • domain assumption MMSE estimator performance from Ref [32] transfers to the GEO QKD geometry and turbulence conditions.
    The MMSE correction is essential to obtain positive key rates; without it, SoA correction yields zero under the assumed parameters (Section IV C 1).
  • domain assumption Free-space phase drift is zero-mean Gaussian with sigma_fs=150 rad/s per channel, approximated from VERTIGO data (Fig 4).
    Used in the MP-QKD phase error model, Eq (C3); there is a potential inconsistency between the per-channel definition and the variance used in the equation.

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Pith. "Pith review of Analysis of untrusted-node quantum key distribution from a geostationary satellite." pith.science (2026). https://pith.science/paper/RUPSFLOZ

@misc{pith2026250723466,
  author       = {Pith},
  title        = {Pith review of: Analysis of untrusted-node quantum key distribution from a geostationary satellite},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RUPSFLOZ}},
  note         = {Machine review of arXiv:2507.23466}
}
read the original abstract

In pursuit of a global quantum key distribution (QKD) network, a service based on untrusted nodes on geostationary satellites could offer wide coverage, continuous operation, and enhanced security compared to the trusted node alternative. Although this scenario has been studied for entanglement-based protocols, such an approach would require large-area telescopes both on the ground and in space. In this work, we analyze the performance of two QKD protocols well adapted to this scenario, namely twin-field (TF) and mode-pairing (MP) QKD, which exhibit high resilience to high-loss channels. Leveraging an in-depth simulation of communication channels corrected with adaptive optics, we assess the expected secret key rates for both protocols in a configuration involving two 50 cm telescopes on board the satellite and ground-based telescopes ranging from 20 cm to 1 m in aperture. Our results show that, in the best case and considering realistic detectors, it is possible to achieve secret key rates on the order of a few hundred bit/s for both TF and MP-QKD. We show, notably, that secret key generation is potentially feasible even with 20 cm ground telescopes, highlighting the high scalability potential of such a configuration.

Figures

Figures reproduced from arXiv: 2507.23466 by the authors.

Figure 1
Figure 1. FIG. 1. Three examples of coverage of a GEO satellite at 30 degree elevation with different longitudes. A few examples of [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Sketch of the OGS-GEO bidirectional untrusted-node [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Cumulative density function of the coupling efficiency [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: FIG. 4. Probability density function (PDF) of the free-space [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5. PDF of [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. PDTE comparison for one channel with AO pre [PITH_FULL_IMAGE:figures/full_fig_p008_6.png]
Figure 9
Figure 9. Figure 9: FIG. 9. MP-QKD secret key rate performance for [PITH_FULL_IMAGE:figures/full_fig_p008_9.png]
Figure 11
Figure 11. Figure 11: FIG. 11. TF-QKD maximal key rate evolution as a function [PITH_FULL_IMAGE:figures/full_fig_p009_11.png]
Figure 10
Figure 10. Figure 10: FIG. 10. MP-QKD maximal secret key rate reached for each [PITH_FULL_IMAGE:figures/full_fig_p009_10.png]
Figure 12
Figure 12. Figure 12: FIG. 12. MP-QKD maximal key rate evolution as a function [PITH_FULL_IMAGE:figures/full_fig_p009_12.png]
Figure 13
Figure 13. Figure 13: FIG. 13. On the left, distribution of the log-amplitude in [PITH_FULL_IMAGE:figures/full_fig_p012_13.png]
Figure 14
Figure 14. Figure 14: FIG. 14. MP-QKD [PITH_FULL_IMAGE:figures/full_fig_p015_14.png]
Figure 15
Figure 15. Figure 15: FIG. 15. MP-QKD key rate performance with respect to [PITH_FULL_IMAGE:figures/full_fig_p015_15.png]

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Reference graph

Works this paper leans on

79 extracted references · 77 canonical work pages

  1. [49]

    Liu, W.-J

    Y. Liu, W.-J. Zhang, C. Jiang, J.-P. Chen, C. Zhang, W.-X. Pan, D. Ma, H. Dong, J.-M. Xiong, C.-J. Zhang, et al. , Physical Review Letters 130, 210801 (2023)

  2. [1]

    Turbulence effects and beam pre-compensation A crucial element in determining the end-to-end trans- mission efficiency of a free-space communication system is the divergence of the beam and the spatial fluctua- tions of the optical pattern in the far-field plane. Al- though divergence close to the diffraction limit can be achieved by optical telescopes, t...

  3. [2]

    compen- sated

    Satellite jitter model Next, we also model the fluctuating losses caused by the satellite pointing jitter by applying the reciprocity principle. This allows us to use tools from the litera- ture [33, 34] that apply to downlink scenarios. In a downlink scenario, the satellite jitter induces a random beam displacement around the ground station telescope ape...

  4. [3]

    We observe an increasing impact of the MMSE esti- mator on the quality of the coupling efficiency as the OGS aperture diameter increases

    The numerical comparison between the two correction schemes is given in Table II. We observe an increasing impact of the MMSE esti- mator on the quality of the coupling efficiency as the OGS aperture diameter increases. This can be explained by two factors. First, the MMSE estimator is a phase estimator and is therefore more efficient when the phase contr...

  5. [4]

    7 for DOGS = 100 cm

    Twin-field QKD The evolution of the performance of TF-QKD, with re- spect to the average intensity used per pulse, is shown in Fig. 7 for DOGS = 100 cm. In this scenario, for the best (compensated + MMSE) case, the secret key rate reaches 8 FIG. 6. PDTE comparison for one channel with AO pre- compensation, considering the MMSE or the SoA correction, for d...

  6. [5]

    Mode-pairing QKD FIG. 9. MP-QKD secret key rate performance for DOGS = 100 cm. Other parameters are pd = 10−8, ηD = 70%, Lmin =

  7. [6]

    Elkouss, J

    D. Elkouss, J. Martinez-Mateo, A. Ciurana, and V. Mar- tin, Journal of Optical Communications and Networking 5, 316 (2013)

  8. [7]

    An overall comparison for TF-QKD is given in Fig

    Comparison with different SNSPD scenarios We further analyze the secret key rate performance as a function of the single-photon detector parameters using the values discussed in Section III C. An overall comparison for TF-QKD is given in Fig. 11 and for MP- QKD in Fig. 12. Considering the technology that is currently being de- veloped for space applicatio...

Show all 79 references
  1. [8]

    Bedington, J

    R. Bedington, J. M. Arrazola, and A. Ling, npj Quantum Information 3, 30 (2017)

  2. [9]

    Liao, W.-Q

    S.-K. Liao, W.-Q. Cai, W.-Y. Liu, L. Zhang, Y. Li, J.-G. Ren, J. Yin, Q. Shen, Y. Cao, Z.-P. Li, et al. , Nature 549, 43 (2017)

  3. [10]

    Lee and T

    O. Lee and T. Vergoossen, arXiv preprint arXiv:1909.13061 (2019)

  4. [11]

    H. Dai, Q. Shen, C.-Z. Wang, S.-L. Li, W.-Y. Liu, W.-Q. Cai, S.-K. Liao, J.-G. Ren, J. Yin, Y.-A. Chen, et al. , Nature Physics 16, 848 (2020)

  5. [12]

    Salvail, M

    L. Salvail, M. Peev, E. Diamanti, R. All´ eaume, N. L¨ utkenhaus, and T. L¨ anger, Journal of Computer Se- curity 18, 61 (2010)

  6. [13]

    Liu, Z.-W

    Y. Liu, Z.-W. Yu, W. Zhang, J.-Y. Guan, J.-P. Chen, C. Zhang, X.-L. Hu, H. Li, C. Jiang, J. Lin, et al., Phys- ical Review Letters 123, 100505 (2019)

  7. [14]

    Huttner, R

    B. Huttner, R. All´ eaume, E. Diamanti, F. Fr¨ owis, P. Grangier, H. H¨ ubel, V. Martin, A. Poppe, J. A. Slater, T. Spiller, et al., npj Quantum Information 8, 108 (2022)

  8. [15]

    Fan-Yuan, F.-Y

    G.-J. Fan-Yuan, F.-Y. Lu, S. Wang, Z.-Q. Yin, D.-Y. He, Z. Zhou, J. Teng, W. Chen, G.-C. Guo, and Z.-F. Han, Photonics Research 9, 1881 (2021)

  9. [16]

    Y. Cao, Y. Zhao, J. Li, R. Lin, J. Zhang, and J. Chen, IEEE Journal on Selected Areas in Communications 39, 2701 (2021)

  10. [17]

    G¨ unthner, I

    K. G¨ unthner, I. Khan, D. Elser, B. Stiller,¨O. Bayraktar, C. R. M¨ uller, K. Saucke, D. Tr¨ ondle, F. Heine, S. Seel, et al. , Optica 4, 611 (2017)

  11. [18]

    Wille, H

    E. Wille, H. Hauschildt, C. Heese, J. Huesing, B. G. Gutierrez, Z. Sodnik, and C. Elia, in Free-Space Laser Communications XXXII , Vol. 11272 (SPIE, 2020) pp. 140–148

  12. [19]

    Dirks, I

    B. Dirks, I. Ferrario, A. Le Pera, D. V. Finocchiaro, M. Desmons, D. de Lange, H. de Man, A. J. Meskers, J. Morits, N. M. Neumann, et al. , in International Con- ference on Space Optics—ICSO 2020 , Vol. 11852 (SPIE,

  13. [20]

    Z. Lu, G. Wang, C. Li, and Z. Cao, Physical Review A 109, 012401 (2024)

  14. [21]

    Wang, Z.-W

    X.-B. Wang, Z.-W. Yu, and X.-L. Hu, Physical Review A 98, 062323 (2018)

  15. [22]

    Wang, Z.-Q

    S. Wang, Z.-Q. Yin, D.-Y. He, W. Chen, R.-Q. Wang, P. Ye, Y. Zhou, G.-J. Fan-Yuan, F.-X. Wang, W. Chen, et al. , Nature photonics 16, 154 (2022)

  16. [23]

    P. Zeng, H. Zhou, W. Wu, and X. Ma, Nature Commu- nications 13, 3903 (2022)

  17. [24]

    H.-T. Zhu, Y. Huang, H. Liu, P. Zeng, M. Zou, Y. Dai, S. Tang, H. Li, L. You, Z. Wang, et al., Physical Review Letters 130, 030801 (2023)

  18. [25]

    Minder, M

    M. Minder, M. Pittaluga, G. L. Roberts, M. Lucamarini, J. F. Dynes, Z. Yuan, and A. J. Shields, Nature Photonics 13, 334 (2019)

  19. [26]

    J.-P. Chen, C. Zhang, Y. Liu, C. Jiang, W. Zhang, X.-L. Hu, J.-Y. Guan, Z.-W. Yu, H. Xu, J. Lin, et al., Physical review letters 124, 070501 (2020)

  20. [27]

    R. R. Parenti, J. M. Roth, J. H. Shapiro, F. G. Walther, and J. A. Greco, Optics express 20, 21635 (2012)

  21. [28]

    Vedrenne, C

    N. Vedrenne, C. Petit, A. Montmerle-Bonnefois, C. Lim, J.-M. Conan, L. Paillier, M.-T. Velluet, K. Caillault, F. Gustave, A. Durecu, et al. , in International Confer- ence on Space Optics—ICSO 2020 , Vol. 11852 (SPIE, 11

  22. [29]

    Montmerle-Bonnefois, M.-T

    A. Montmerle-Bonnefois, M.-T. Velluet, M. Ciss´ e, C. B. Lim, J.-M. Conan, C. Petit, J.-F. Sauvage, S. Meimon, P. Perrault, J. Montri, et al. , Optics Express 30, 47179 (2022)

  23. [30]

    I. R. Hristovski, A. R. Campelo, B. Femen ´ ıa-Castella, E. Doensdorf-Sternal, A. O. Duliu, S. Haeusler, J. F. Holzman, K. Klemich, D. J. Laidlaw, T. Marynowski, et al., in Free-Space Laser Communications XXXVI, Vol. 12877 (SPIE, 2024) pp. 328–336

  24. [31]

    V´ edrenne, A

    N. V´ edrenne, A. Montmerle-Bonnefois, C. Petit, E. Cha- lali, Y. Lai-Tim, L. Krafft, J. Henrion, J. Houy, F. Gus- tave, K. Caillault, et al. , in ICSO 2024 (2024)

  25. [32]

    Lognon´ e, Optimization of High Data Rate Ground to Satellite Links Pre-compensated by Adaptive Optics , Ph.D

    P. Lognon´ e, Optimization of High Data Rate Ground to Satellite Links Pre-compensated by Adaptive Optics , Ph.D. thesis, Institut Polytechnique de Paris (2023)

  26. [33]

    J. H. Shapiro and A. L. Puryear, Journal of Optical Com- munications and Networking 4, 947 (2012)

  27. [34]

    V. M. Acosta, D. Dequal, M. Schiavon, A. Montmerle- Bonnefois, C. B. Lim, J.-M. Conan, and E. Diamanti, arXiv preprint arXiv:2411.09564 (2024)

  28. [35]

    H. Yao, C. Chen, X. Ni, S. Tong, B. Li, P. Chidike, Z. Liu, Y. Zhao, and H. Jiang, Optics express 27, 25000 (2019)

  29. [36]

    Lognon´ e, A

    P. Lognon´ e, A. M. Bonnefois, J.-M. Conan, L. Paillier, C. Petit, C. B. Lim, S. Meimon, J. Montri, J.-F. Sauvage, and N. V´ edrenne, in 2022 IEEE International Confer- ence on Space Optical Systems and Applications (ICSOS) (IEEE, 2022) pp. 261–266

  30. [37]

    Robert, J.-M

    C. Robert, J.-M. Conan, and P. Wolf, Phys. Rev. A 93, 033860 (2016)

  31. [38]

    O. J. D. Farley, M. J. Townson, and J. Osborn, Opt. Express 30, 10.1364/OE.458659 (2022)

  32. [39]

    Lognon´ e, J.-M

    P. Lognon´ e, J.-M. Conan, G. Rekaya, and N. V´ edrenne, Optics Express 31, 3441 (2023)

  33. [40]

    D. Y. Vasylyev, A. Semenov, and W. Vogel, Physical re- view letters 108, 220501 (2012)

  34. [41]

    Lucamarini, Z

    M. Lucamarini, Z. L. Yuan, J. F. Dynes, and A. J. Shields, Nature 557, 400 (2018)

  35. [42]

    V. M. Acosta, D. Dequal, M. Schiavon, A. Montmerle- Bonnefois, C. B. Lim, J.-M. Conan, and E. Diamanti, New Journal of Physics 26, 023039 (2024)

  36. [43]

    Zhong, J

    X. Zhong, J. Hu, M. Curty, L. Qian, and H.-K. Lo, Phys- ical Review Letters 123, 100506 (2019)

  37. [44]

    Zhong, W

    X. Zhong, W. Wang, L. Qian, and H.-K. Lo, npj Quan- tum Information 7, 8 (2021)

  38. [45]

    Z. Li, T. Dou, M. Cheng, Y. Liu, and J. Tang, Optics Letters 49, 6609 (2024)

  39. [46]

    Zhang, W

    L. Zhang, W. Li, J. Pan, Y. Lu, W. Li, Z.-P. Li, Y. Huang, X. Ma, F. Xu, and J.-W. Pan, Physical Review X 15, 021037 (2025)

  40. [47]

    Zhou, C.-H

    X.-Y. Zhou, C.-H. Zhang, C.-M. Zhang, and Q. Wang, Physical Review A 99, 062316 (2019)

  41. [48]

    J.-P. Chen, F. Zhou, C. Zhang, C. Jiang, F.-X. Chen, J. Huang, H. Li, L.-X. You, X.-B. Wang, Y. Liu, et al. , Physical Review Letters 132, 260802 (2024)

  42. [50]

    Y.-H. Li, T. Zeng, M.-Y. Wang, C. Jiang, J. Lin, H.-B. Fu, X.-Y. Zheng, J.-P. Chen, Z.-S. Lin, C.-L. Li, et al. , arXiv preprint arXiv:2503.17744 (2025)

  43. [51]

    Takenaka, A

    H. Takenaka, A. Carrasco-Casado, M. Fujiwara, M. Ki- tamura, M. Sasaki, and M. Toyoshima, Nature photonics 11, 502 (2017)

  44. [52]

    J. Yin, Y. Cao, Y.-H. Li, S.-K. Liao, L. Zhang, J.-G. Ren, W.-Q. Cai, W.-Y. Liu, B. Li, H. Dai, et al., Science 356, 1140 (2017)

  45. [53]

    Wang and H.-K

    W. Wang and H.-K. Lo, New Journal of Physics 22, 013020 (2020)

  46. [54]

    H.-T. Zhu, Y. Huang, W.-X. Pan, C.-W. Zhou, J. Tang, H. He, M. Cheng, X. Jin, M. Zou, S. Tang, et al., Optica 11, 883 (2024)

  47. [55]

    Beesley, R

    L. Beesley, R. Griffiths, K. Hartley, O. Farley, F. Qua- tresooz, A. Rodriguez-Gomez, A. Comeron, M. Town- son, D. Alaluf, and J. Osborn, Optics Express 33, 10140 (2025)

  48. [56]

    L. You, J. Quan, Y. Wang, Y. Ma, X. Yang, Y. Liu, H. Li, J. Li, J. Wang, J. Liang, et al. , Optics Express 26, 2965 (2018)

  49. [57]

    Le Kernec, L

    A. Le Kernec, L. Canuet, A. Maho, M. Sotom, D. Mat- ter, L. Francou, J. Edmunds, M. Welch, E. Kehayas, N. Perlot, et al. , in International Conference on Space Optics—ICSO 2020 , Vol. 11852 (SPIE, 2021) pp. 508– 519

  50. [58]

    Zhou, J.-R

    X.-Y. Zhou, J.-R. Hu, C.-H. Zhang, and Q. Wang, Optics Letters 50, 249 (2025)

  51. [59]

    Mengali, C

    A. Mengali, C. I. Kourogiorgas, N. K. Lyras, B. Shankar Mysore Rama Rao, F. Kayhan, A. D. Panagopoulos, T. B¨ aumer, and K. Liolis, International Journal of Satel- lite Communications and Networking (2020)

  52. [60]

    Osborn, R

    J. Osborn, R. W. Wilson, M. Sarazin, T. But- terley, A. Chac´ on, F. Derie, O. J. D. Farley, X. Haubois, D. Laidlaw, M. LeLouarn, E. Masci- adri, J. Milli, J. Navarrete, and M. J. Townson, Monthly Notices of the Royal Astronomical Society 478, 825 (2018), https://academic.oup....

  53. [61]

    Sprung and E

    D. Sprung and E. Sucher, in Remote Sensing of Clouds and the Atmosphere XVIII; and Optics in Atmospheric Propagation and Adaptive Systems XVI, Vol. 8890 (SPIE,

  54. [62]

    Lognon´ e, J.-M

    P. Lognon´ e, J.-M. Conan, L. Paillier, N. V´ edrenne, and G. Rekaya, in Signal Processing in Photonic Communi- cations (Optica Publishing Group, 2022) pp. SpTu3G–3. 12

  55. [63]

    Conan, A

    J.-M. Conan, A. Montmerle-Bonnefois, N. V´ edrenne, C. B. Lim, C. Petit, V. Michau, M.-T. Velluet, J.-F. Sauvage, S. Meimon, C. Robert, et al. , in COAT-2019- workshop (Communications and Observations through Atmospheric Turbulence: characterization and mitiga- tion) (2019)

  56. [64]

    A. Berk, P. Conforti, R. Kennett, T. Perkins, F. Hawes, and J. Van Den Bosch, in 2014 6th Workshop on Hyper- spectral Image and Signal Processing: Evolution in Re- mote Sensing (WHISPERS) (IEEE, 2014) pp. 1–4

  57. [65]

    Cantore, D

    C. Cantore, D. Monopoli, A. Altamura, A. Mengali, M. Grande, and A. D’Orazio, Scientific Reports 14, 8579 (2024)

  58. [66]

    Xu, Z.-W

    H. Xu, Z.-W. Yu, C. Jiang, X.-L. Hu, and X.-B. Wang, Physical Review A 101, 042330 (2020)

  59. [67]

    F. Mah´ e, Application d’un mod` ele atmosph´ erique ` a l’´ etude des fluctuations d’indice de r´ efraction dans la couche limite : influence de la scintillation sur l’analyse de front d’onde , Ph.D. thesis (2000)

  60. [68]

    Chassat, Journal of Optics 20, 10.1088/0150- 536x/20/1/002 (1989)

    F. Chassat, Journal of Optics 20, 10.1088/0150- 536x/20/1/002 (1989)

  61. [70]

    Canuet, N

    L. Canuet, N. V´ edrenne, J.-M. Conan, C. Petit, G. Ar- taud, A. Rissons, and J. Lacan, JOSA A 35, 148 (2018)

  62. [71]

    R. J. Sasiela, in Electromagnetic Wave Propagation in Turbulence (Springer, 1994) pp. 19–46

  63. [72]

    D. L. Fried, JOSA 57, 169 (1967)

  64. [73]

    Conan, Etude de la correction partielle en optique adaptative, Ph.D

    J.-M. Conan, Etude de la correction partielle en optique adaptative, Ph.D. thesis, Paris 11 (1994)

  65. [74]

    Roddier, Adaptive Optics in Astronomy (Cambridge University, 1999)

    F. Roddier, Adaptive Optics in Astronomy (Cambridge University, 1999). Appendix A: Atmospheric turbulence induced losses model To simulate the turbulence impact on the optical link, we use a pseudo-analytical model - pseudo-analytical as we consider the phase and amplitude spa...

  66. [75]

    Reciprocal uplink losses To model the uplink turbulence-induced losses, we adopt a reciprocal formalism. The reciprocity principle states that the coupling efficiency of an emitted mode, propagated and coupled to a receiver mode, is equal to the coupling efficiency of this rec...

  67. [76]

    Log-amplitude induced losses We assume the aperture averaged scintillation to dom- inate the log-amplitude contribution ρχ. Therefore, ρχ is expressed as [62, 63]: ρχ = e−σ2 χ e−2χAp , (A5) where e−σ2 χ is a static penalty term to account for the spa- tial log-amplitude fluctu...

  68. [77]

    T urbulent phase induced losses a. General expression The phase contribution to the coupling ρΦ is derived as the overlap integral of the complex field, neglecting the log-amplitude fluctuation, to the Gaussian mode M0(r), therefore expressed as: ρΦ = exp −σ2 super-fitting Z Z...

  69. [78]

    Security model for asymmetric twin-field QKD The model used was proposed in [46]. To compensate for asymmetry, the protocol suggests adjusting the signal intensities such that the arriving intensities at Charlie’s side are balanced, satisfying the condition: γA = α2 AηA, γ B =...

  70. [79]

    Security model for asymmetric mode-pairing QKD The model used was proposed in [20]. The key rate R, in the asymptotic case, is expressed as: R = rp(p, Lmax)rs q(1,1) 1 − H(e(1,1)) − fECH(eZ) , (B7) where rp(p, Lmax) is the pairing rate with p the successful click probability i...

  71. [100]

    For MP-QKD, it is also necessary to optimize the maximal pairing length Lmax

    Lmin is the minimal pairing length introduced to account for the detector dead time; see Appendix B 2. For MP-QKD, it is also necessary to optimize the maximal pairing length Lmax. For each OGS aper- ture diameter, we scan the best key rate reached for Lmax ∈ [103, 106] and th...

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