Public
Gravitational Wave Detection — Public Tier
(5 scenes)Full-access development tier with all data visible.
What you get
Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.
How to use
Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.
What to submit
Reconstructed signals (x_hat) and corrected spec as HDF5.
Parameter Specifications
✓
True spec visible — use these exact values for Scenario III oracle reconstruction.
| Parameter | Spec Range | True Value | Unit |
|---|---|---|---|
| calibration_amplitude | 0.99 – 1.02 | 1.005 | - |
| phase_calibration | -0.01 – 0.02 | 0.005 | rad |
| power_spectral_density | -0.15 – 0.15 | 0.0 | 1/Hz |
| timing_offset | -0.15 – 0.15 | 0.0 | s |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
7.77 dB
SSIM 0.3772
Scenario II (Mismatch)
7.61 dB
SSIM 0.1940
Scenario III (Oracle)
15.93 dB
SSIM 0.4222
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 7.57 | 0.3615 | 7.48 | 0.1918 | 15.88 | 0.4337 |
| scene_01 | 7.70 | 0.3833 | 7.85 | 0.1983 | 15.89 | 0.4210 |
| scene_02 | 7.97 | 0.3846 | 7.45 | 0.1929 | 16.02 | 0.4175 |
| scene_03 | 7.84 | 0.3794 | 7.67 | 0.1931 | 15.94 | 0.4166 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | WaveFormer + gradient | 0.736 | 28.88 | 0.898 | 0.94 | ✓ Certified | GW detection transformer, 2024 |
| 2 | GW-CNN + gradient | 0.686 | 26.92 | 0.856 | 0.87 | ✓ Certified | George & Huerta, Phys. Rev. D 2018 |
| 3 | BayesWave + gradient | 0.611 | 23.01 | 0.731 | 0.94 | ✓ Certified | Cornish & Littenberg, CQG 2015 |
| 4 | Matched Filter + gradient | 0.434 | 17.06 | 0.453 | 0.91 | ✓ Certified | Allen et al., Phys. Rev. D 2012 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
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%