Hidden
Event Horizon Telescope (EHT) Imaging — Hidden Tier
(3 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 |
|---|---|---|
| atmospheric_opacity_(tau) | 0.044 – 0.284 | nepers |
| station_gain_calibration | -1.4 – 4.6 | - |
| uv_coverage_sparsity | -0.15 – 0.15 | - |
| interstellar_scattering | -1.4 – 4.6 | uasbroadening |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffVLBI + gradient | 0.723 | 30.13 | 0.919 | 0.77 | ✓ Certified | Gao et al., NeurIPS 2024 |
| 2 | RadioFormer + gradient | 0.711 | 28.72 | 0.895 | 0.83 | ✓ Certified | Gheller & Vazza, MNRAS 2023 |
| 3 | PhysVLBI + gradient | 0.680 | 27.46 | 0.869 | 0.79 | ✓ Certified | He et al., ApJ 2024 |
| 4 | TransVLBI + gradient | 0.598 | 23.14 | 0.737 | 0.86 | ✓ Certified | Feng et al., A&A 2023 |
| 5 | SMILI + gradient | 0.522 | 20.23 | 0.61 | 0.88 | ✓ Certified | Akiyama et al., ApJ 2017 |
| 6 | RESOLVE + gradient | 0.445 | 18.25 | 0.512 | 0.79 | ✓ Certified | Junklewitz et al., A&A 2016 |
| 7 | eht-imaging + gradient | 0.443 | 18.04 | 0.502 | 0.81 | ✓ Certified | Chael et al., ApJ 2018 |
| 8 | CLEAN-VLBI + gradient | 0.424 | 17.28 | 0.464 | 0.83 | ✓ Certified | Hogbom, A&AS 1974 |
| 9 | MEM-VLBI + gradient | 0.299 | 13.28 | 0.28 | 0.77 | ✓ Certified | Narayan & Nityananda, ARA&A 1986 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%