Hidden

Quantum Illumination — Hidden Tier

(3 scenes)

Fully blind server-side evaluation — no data download.

What you get

No data downloadable. Algorithm runs server-side on hidden measurements.

How to use

Package algorithm as Docker container / Python script. Submit via link.

What to submit

Containerized algorithm accepting y + H, outputting x_hat + corrected spec.

Parameter Specifications

🔒

True spec hidden — blind evaluation, only ranges available.

Parameter Spec Range Unit
entanglement_quality_(concurrence) 0.77 – 1.07 -
background_thermal_noise -14.0 – 46.0 -
detector_dark_count_rate -140.0 – 460.0 Hz
channel_loss -4.2 – 13.8 dB

Hidden Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 QI-Net + gradient 0.493 19.66 0.582 0.82 ✓ Certified Quantum illumination DL, 2023
2 QuantumFormer + gradient 0.488 19.15 0.557 0.87 ✓ Certified Quantum detection transformer, 2024
3 FF-SFG + gradient 0.461 18.18 0.509 0.88 ✓ Certified Zhuang et al., PRL 2017
4 OPA Receiver + gradient 0.312 13.78 0.301 0.77 ✓ Certified Guha & Erkmen, PRA 2009

Dataset

Scenes: 3

Scoring Formula

0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)

PSNR: 40% SSIM: 40% Consistency: 20%
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