Hidden
Particle Calorimetry — 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 |
|---|---|---|
| energy_scale_factor | 0.9958 – 1.0138 | - |
| position_resolution | -0.7 – 2.3 | mm |
| sampling_fraction | 0.0972 – 0.1092 | - |
| pile_up_fraction | -0.007 – 0.023 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | CaloDiffusion + gradient | 0.587 | 23.09 | 0.735 | 0.81 | ✓ Certified | Mikuni & Nachman, PRD 2023 |
| 2 | GARFIELD++ + gradient | 0.526 | 20.45 | 0.62 | 0.87 | ✓ Certified | Veenhof, Nucl. Instr. Meth. 1998 |
| 3 | GravNet + gradient | 0.443 | 18.22 | 0.511 | 0.78 | ✓ Certified | Qasim et al., Eur. Phys. J. C 2019 |
| 4 | PandoraPFA + gradient | 0.402 | 16.44 | 0.423 | 0.84 | ✓ Certified | Thomson, JINST 2009 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%