Datasets:
license: apache-2.0
task_categories:
- other
tags:
- quantum-error-correction
- surface-code
- willow
pretty_name: Willow Surface-Code Detection Events
configs:
- config_name: default
data_files: data/*.parquet
Willow Surface-Code Detection Events (ingested)
Detection events and logical-observable flips derived from Google's Willow below-threshold surface-code dataset (Zenodo 10.5281/zenodo.13273331), rotated surface code at distances 3, 5, 7 in X and Z memory.
Each row is one experimental shot. Detection events are derived from the raw
device measurement records with Stim's measurement-to-detector converter, using
the per-shot sweep bits, and validated to reproduce the dataset's shipped
detection_events.b8 / obs_flips_actual.b8 byte-for-byte for all
420 configurations.
Columns
| column | type | meaning |
|---|---|---|
distance |
int16 | code distance d (3, 5, 7) |
basis |
string | X or Z memory |
rounds |
int16 | number of QEC cycles |
orientation |
string | patch location label on the chip (e.g. q4_5) |
shot |
int32 | shot index within the configuration |
detectors |
list<bool> | which detectors fired (length num_detectors, = 2 * rounds * (d^2-1)/2) |
observable |
bool | ground-truth logical flip the decoder must predict |
One Parquet shard per (distance, orientation, basis, rounds) configuration under
data/. The decoder sees only detectors; observable is the held-out answer key.
Decoding bundle
Alongside the detection events, each config ships the inputs a decoder panel needs,
keyed by the same <stem> (d{D}_at_{orient}__{basis}__r{rounds:03d}):
circuits/<stem>.stim— the ideal (noiseless) annotated circuit.dems/<stem>.si1000.dem.gz— shipped SI1000 detector error model (gzipped).dems/<stem>.rl.dem.gz— shipped RL-optimized detector error model (gzipped).
With these, the whole evaluation runs off this dataset with no local copy of the 12 GB Willow tree.
Load
from datasets import load_dataset
ds = load_dataset("ShayManor/willow-surface-code-detection-events", split="train") # detection events