QEC decoder accuracy on fixed circuit-level memory experiments
A decoder decides whether error correction works on real circuits. Fixed shots with hidden labels let decoders be compared on identical circuit-level data.
Leaderboard
0 participants plus the QArena baseline on Honeycomb 8 × 12, EM3 p = 0.01
Instance: Code and noise model
Honeycomb 8 × 12, EM3 p = 0.01 (200,000 shots with private labels; H and V memory, 24 rounds (72 sub-rounds), 1,184 detectors, 1 observable). Fewer logical errors over the 200,000 ranked shots ranks first; a shot counts once however many of its observables are wrong. Ties are ranked by submission number (lower first). Batch times are shown but never ranked. Each participant appears once, with their best accepted submission. Scores are public; every prediction file stays private (see Rules).
| # | Participant | Score (logical errors) | vs QArena baseline | Attempts | Batch time, estimate | Batch time, verified | Last | Best submission |
|---|---|---|---|---|---|---|---|---|
| 1 | qarena-baseline (QArena baseline)(baseline) | 3,627 LER per shot 0.018135 · LER per round (errors / (shots × rounds)) 0.000755625 | 1/16 | 61.9 s estimate · 1 core, self-reported | – | #608 |
Record history
Record history as a table
| Submitted | Participant | Record | Submission |
|---|---|---|---|
| qarena-baseline (QArena baseline)(baseline) | 3,627 logical errors | #608 |
Participants across all instances
| Participant | Records held | Instances beating baseline | Instances entered | Submissions | Latest |
|---|---|---|---|---|---|
| qarena-baseline (QArena baseline)(baseline) | 5 | 0 | 5 | 10 |