Dev
Event Horizon Telescope (EHT) Imaging — 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 |
|---|---|---|
| atmospheric_opacity_(tau) | 0.004 – 0.244 | nepers |
| station_gain_calibration | -2.4 – 3.6 | - |
| uv_coverage_sparsity | -0.15 – 0.15 | - |
| interstellar_scattering | -2.4 – 3.6 | uasbroadening |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | RadioFormer + gradient | 0.766 | 31.25 | 0.934 | 0.9 | ✓ Certified | Gheller & Vazza, MNRAS 2023 |
| 2 | DiffVLBI + gradient | 0.761 | 32.13 | 0.944 | 0.81 | ✓ Certified | Gao et al., NeurIPS 2024 |
| 3 | PhysVLBI + gradient | 0.730 | 29.08 | 0.902 | 0.89 | ✓ Certified | He et al., ApJ 2024 |
| 4 | TransVLBI + gradient | 0.685 | 27.41 | 0.868 | 0.82 | ✓ Certified | Feng et al., A&A 2023 |
| 5 | SMILI + gradient | 0.580 | 22.39 | 0.706 | 0.87 | ✓ Certified | Akiyama et al., ApJ 2017 |
| 6 | eht-imaging + gradient | 0.483 | 19.43 | 0.571 | 0.8 | ✓ Certified | Chael et al., ApJ 2018 |
| 7 | RESOLVE + gradient | 0.477 | 19.3 | 0.565 | 0.79 | ✓ Certified | Junklewitz et al., A&A 2016 |
| 8 | CLEAN-VLBI + gradient | 0.430 | 17.59 | 0.48 | 0.81 | ✓ Certified | Hogbom, A&AS 1974 |
| 9 | MEM-VLBI + gradient | 0.351 | 14.47 | 0.33 | 0.87 | ✓ Certified | Narayan & Nityananda, ARA&A 1986 |
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%