Dev
Particle Calorimetry — Dev Tier
(5 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 |
|---|---|---|
| energy_scale_factor | 0.9928 – 1.0108 | - |
| position_resolution | -1.2 – 1.8 | mm |
| sampling_fraction | 0.0952 – 0.1072 | - |
| pile_up_fraction | -0.012 – 0.018 | - |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | CaloDiffusion + gradient | 0.617 | 23.58 | 0.753 | 0.9 | ✓ Certified | Mikuni & Nachman, PRD 2023 |
| 2 | GARFIELD++ + gradient | 0.596 | 23.15 | 0.737 | 0.85 | ✓ Certified | Veenhof, Nucl. Instr. Meth. 1998 |
| 3 | GravNet + gradient | 0.518 | 20.5 | 0.622 | 0.82 | ✓ Certified | Qasim et al., Eur. Phys. J. C 2019 |
| 4 | PandoraPFA + gradient | 0.458 | 18.07 | 0.503 | 0.88 | ✓ Certified | Thomson, JINST 2009 |
Visible Data Fields
y
H_ideal
spec_ranges
Dataset
Format: HDF5
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%