Workbench tool

CV-QKD teaching estimator

Estimate transmittance, SNR, covariance-style observables, and a cautious secret-key-rate proxy for a continuous-variable QKD teaching link.

Shareable URL state

Keep the current calculator inputs in the URL so this teaching setup can be reopened or shared without exporting files.

Only model inputs are stored in the link. No keys or telemetry are added.

PresetDetection modeHeterodyne adds an extra vacuum-noise unit in this teaching model but reports both quadratures per use.Receiver trustThis toggles whether receiver electronics are counted inside the Eve-information proxy or treated as trusted calibration noise.DistancekmFiber attenuationdB/kmExcess insertion lossdBSymbol rateHzModulation varianceSNUGaussian modulation variance relative to shot-noise units.Reconciliation efficiencyTeaching proxy for beta in reverse-reconciliation style formulas.Excess noiseSNUInput-referred channel excess noise above the unavoidable vacuum-loss contribution.Preparation noiseSNUTrusted source-side variance penalty for imperfect modulation and calibration.Detector efficiencyElectronic noiseSNUPhase recovery efficiencyBundles pilot-tone, phase-tracking, and coherent-reference quality into one observable correlation penalty.Usable symbol fractionReserves room for pilot symbols, calibration slots, or discarded training data.

Total loss

7dB

Channel transmittance

0.19953

SNR

0.1586

Secret-key-rate proxy

0Hz

Mutual information

0.10621

bits per use

Holevo proxy

1.6768

bits per use

Covariance proxy

2.197SNU

Correlation coefficient

37%

Noise accounting in shot-noise units

Line noise

4.0269SNU

Receiver-added noise

0.044643SNU

Trusted noise slice

0.044643SNU

Untrusted noise slice

4.0269SNU

Total noise

4.0715SNU

Received quadrature variance

5.876SNU

Distance vs secret-key-rate proxy

distanceKm spans 0.00 to 65.0 while secretKeyRateHz spans 0.00 to 0.00. Midpoint sample: distanceKm 32.5, secretKeyRateHz 0.00.

Distance vs SNR

distanceKm spans 0.00 to 65.0 while snr spans 0.00402 to 1.55. Midpoint sample: distanceKm 32.5, snr 0.0798.

Distance vs Eve-information proxy

distanceKm spans 0.00 to 65.0 while holevoProxy spans 1.17 to 2.61. Midpoint sample: distanceKm 32.5, holevoProxy 1.82.

Warnings and cautions

info: This CV-QKD output uses a covariance-style teaching proxy and does not replace calibrated covariance-matrix security analysis.
info: Receiver electronics are treated as trusted noise here, which reduces the Eve-information proxy but adds a hardware-trust assumption.
warning: Signal-to-noise ratio is very low, so reconciliation and parameter-estimation fragility would dominate a more realistic CV-QKD analysis.
info: Current loss, trust, and noise assumptions leave no positive CV-QKD teaching key margin.

Formulas and assumptions

This CV-QKD slice is a teaching estimator for Gaussian-modulated coherent-state links with scalar noise and reconciliation knobs.
Shot-noise calibration, covariance estimation, finite-size composable security, local-oscillator architecture, and detector saturation are compressed into simple SNU noise terms and trust labels.
The Eve information term is a lower-fidelity Holevo-style proxy, not a full symplectic-eigenvalue or covariance-matrix proof.
Outputs are educational estimates for protocol comparison and parameter intuition, not deployment-grade CV-QKD certification.
Channel transmittance uses eta = 10^(-loss_dB / 10) with excess insertion loss separated from fiber attenuation.
Total receiver efficiency multiplies channel transmittance, detector efficiency, and phase-recovery efficiency into one observable correlation term.
Line noise is reported in shot-noise units (SNU) and combines vacuum loss, excess noise, and preparation noise into an input-referred teaching term.
Receiver-added noise includes electronic-noise calibration and the extra heterodyne vacuum unit when heterodyne detection is selected.
The key-rate proxy uses R = R_src u max(0, beta I_AB - chi_BE,proxy), where I_AB and chi_BE,proxy are cautious teaching approximations.

References

Grosshans and Grangier continuous-variable QKD.
Weedbrook et al. review for Gaussian-modulated CV-QKD assumptions and noise terminology.

Tools

Engineering and research workbench

Loading the selected calculator, defaults, and scientific caution notes.

Preparing tool

Loading workbench view

Preparing calibrated controls, default presets, and explanatory notes.

Workbench tool

CV-QKD teaching estimator

Estimate transmittance, SNR, covariance-style observables, and a cautious secret-key-rate proxy for a continuous-variable QKD teaching link.

Shareable URL state

Keep the current calculator inputs in the URL so this teaching setup can be reopened or shared without exporting files.

Only model inputs are stored in the link. No keys or telemetry are added.

Total loss

7dB

Channel transmittance

0.19953

SNR

0.1586

Secret-key-rate proxy

0Hz

Mutual information

0.10621

bits per use

Holevo proxy

1.6768

bits per use

Covariance proxy

2.197SNU

Correlation coefficient

37%

Noise accounting in shot-noise units

Line noise

4.0269SNU

Receiver-added noise

0.044643SNU

Trusted noise slice

0.044643SNU

Untrusted noise slice

4.0269SNU

Total noise

4.0715SNU

Received quadrature variance

5.876SNU

Distance vs secret-key-rate proxy

distanceKm spans 0.00 to 65.0 while secretKeyRateHz spans 0.00 to 0.00. Midpoint sample: distanceKm 32.5, secretKeyRateHz 0.00.

Distance vs SNR

distanceKm spans 0.00 to 65.0 while snr spans 0.00402 to 1.55. Midpoint sample: distanceKm 32.5, snr 0.0798.

Distance vs Eve-information proxy

distanceKm spans 0.00 to 65.0 while holevoProxy spans 1.17 to 2.61. Midpoint sample: distanceKm 32.5, holevoProxy 1.82.

Warnings and cautions

info: This CV-QKD output uses a covariance-style teaching proxy and does not replace calibrated covariance-matrix security analysis.
info: Receiver electronics are treated as trusted noise here, which reduces the Eve-information proxy but adds a hardware-trust assumption.
warning: Signal-to-noise ratio is very low, so reconciliation and parameter-estimation fragility would dominate a more realistic CV-QKD analysis.
info: Current loss, trust, and noise assumptions leave no positive CV-QKD teaching key margin.

Formulas and assumptions

This CV-QKD slice is a teaching estimator for Gaussian-modulated coherent-state links with scalar noise and reconciliation knobs.
Shot-noise calibration, covariance estimation, finite-size composable security, local-oscillator architecture, and detector saturation are compressed into simple SNU noise terms and trust labels.
The Eve information term is a lower-fidelity Holevo-style proxy, not a full symplectic-eigenvalue or covariance-matrix proof.
Outputs are educational estimates for protocol comparison and parameter intuition, not deployment-grade CV-QKD certification.
Channel transmittance uses eta = 10^(-loss_dB / 10) with excess insertion loss separated from fiber attenuation.
Total receiver efficiency multiplies channel transmittance, detector efficiency, and phase-recovery efficiency into one observable correlation term.
Line noise is reported in shot-noise units (SNU) and combines vacuum loss, excess noise, and preparation noise into an input-referred teaching term.
Receiver-added noise includes electronic-noise calibration and the extra heterodyne vacuum unit when heterodyne detection is selected.
The key-rate proxy uses R = R_src u max(0, beta I_AB - chi_BE,proxy), where I_AB and chi_BE,proxy are cautious teaching approximations.

References

Grosshans and Grangier continuous-variable QKD.
Weedbrook et al. review for Gaussian-modulated CV-QKD assumptions and noise terminology.