Dev

Quantum Illumination — Dev Tier

(3 scenes)

Blind evaluation tier — no ground truth available.

What you get

Measurements (y), ideal forward operator (H), and spec ranges only.

How to use

Apply your pipeline from the Public tier. Use consistency as self-check.

What to submit

Reconstructed signals and corrected spec. Scored server-side.

Parameter Specifications

🔒

True spec hidden — estimate parameters from spec ranges below.

Parameter Spec Range Unit
entanglement_quality_(concurrence) 0.82 – 1.12 -
background_thermal_noise -24.0 – 36.0 -
detector_dark_count_rate -240.0 – 360.0 Hz
channel_loss -7.2 – 10.8 dB

Dev Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 QuantumFormer + gradient 0.570 21.8 0.681 0.9 ✓ Certified Quantum detection transformer, 2024
2 QI-Net + gradient 0.514 20.48 0.622 0.8 ✓ Certified Quantum illumination DL, 2023
3 FF-SFG + gradient 0.507 19.99 0.598 0.84 ✓ Certified Zhuang et al., PRL 2017
4 OPA Receiver + gradient 0.367 15.33 0.37 0.83 ✓ Certified Guha & Erkmen, PRA 2009

Visible Data Fields

y H_ideal spec_ranges

Dataset

Format: HDF5
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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