Hidden

Neutron Diffraction — Hidden Tier

(5 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
wavelength_calibration -0.014 – 0.046 -
absorption_correction -1.4 – 4.6 -
texture/preferred_orientation -2.8 – 9.2 -
tof_frame_overlap -0.7 – 2.3 -

Hidden Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 DiffFormer + gradient 0.621 24.99 0.802 0.75 ✓ Certified Diffraction pattern transformer, 2024
2 Le Bail Fit + gradient 0.580 23.31 0.743 0.75 ✓ Certified Le Bail et al., Mater. Res. Bull. 1988
3 NeutronNet + gradient 0.575 22.12 0.695 0.88 ✓ Certified Neutron diffraction DL, 2023
4 Rietveld-GSAS + gradient 0.443 18.45 0.522 0.75 ✓ Certified Rietveld, J. Appl. Cryst. 1969

Dataset

Scenes: 5

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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