| --- |
| language: |
| - en |
| license: apache-2.0 |
| pretty_name: ProbeBench classical reference selection |
| size_categories: |
| - 10K<n<100K |
| tags: |
| - optics |
| - wavefront-sensing |
| - scientific-computing |
| configs: |
| - config_name: default |
| data_files: |
| - split: public_tuning |
| path: data/*.parquet |
| --- |
| |
| # ProbeBench: classical reference selection |
|
|
| Measured focal-plane exposures from a simulated wavefront-control benchmark. Each record connects a detector image to the applied optical-path command, photon budget, episode identity, and exact signed detector array. |
|
|
| This release contains **30,912 exposures from 4,032 episodes**, covering **14 classical candidates and 12 independent base wavefronts**. It retains every candidate, including configurations that were not selected, and all optimizer diagnostics. The single split, `public_tuning`, supports inspection and reproduction of parameter selection. It does not provide held-out performance estimates. |
|
|
| [Code](https://github.com/noetherlabs/probebench) · [Methods and results](https://github.com/noetherlabs/probebench/blob/main/docs/parameter-selection-results.md) · [Native records](https://github.com/noetherlabs/probebench/releases/tag/classical-selection-v1-20261016) · [Measurement replay](https://github.com/noetherlabs/probebench/releases/tag/classical-selection-replay-v1-20261017) |
|
|
| ## Load an exposure |
|
|
| ```python |
| from datasets import load_dataset |
| |
| frames = load_dataset( |
| "noetherlabs/probebench", |
| split="public_tuning", |
| revision="classical-selection-v1", |
| streaming=True, |
| ) |
| frame = next(iter(frames)) |
| frame["image"] # PIL image; display rendering, not detector values |
| ``` |
|
|
| The images are embedded in Parquet shards. Streaming reads avoid creating a second complete dataset cache. The revision tag identifies this fixed release; record the resolved commit when reporting derived results. |
|
|
| ## Read the detector values |
|
|
| The `raw_archive` column identifies a ZIP shard. Its `raw_array` member contains the original NumPy file, including signed float64 values. Loading a member into memory requires no archive extraction. |
|
|
| ```python |
| import hashlib |
| import io |
| import zipfile |
| |
| import numpy as np |
| from huggingface_hub import hf_hub_download |
| |
| archive = hf_hub_download( |
| "noetherlabs/probebench", |
| filename=frame["raw_archive"], |
| repo_type="dataset", |
| revision="classical-selection-v1", |
| ) |
| with zipfile.ZipFile(archive) as z: |
| payload = z.read(frame["raw_array"]) |
| assert hashlib.sha256(payload).hexdigest() == frame["raw_array_sha256"] |
| electrons = np.load(io.BytesIO(payload), allow_pickle=False) |
| ``` |
|
|
| ## Record structure |
|
|
| | Fields | Meaning | |
| | --- | --- | |
| | `image`, `image_sha256` | Original PNG bytes and their SHA-256 digest. | |
| | `episode_id`, `exposure_index`, `file_name` | Identity and original image filename. | |
| | `applied_opd_nm`, `expected_photons`, `cumulative_expected_photons` | Applied command and acquired-exposure budgets. | |
| | `candidate_id`, `family`, `selected_reference` | Candidate identity and the global selection flag for each family. | |
| | `base_wavefront_id`, `member`, `stratum_id`, `replicate` | Dependence structure: base wavefront, conjugate member, RMS stratum, and detector replicate. | |
| | `raw_archive`, `raw_array`, `raw_array_sha256` | Archive, member path, and digest of the unchanged detector array. | |
| | `evaluator_wfe_nm`, `evaluator_strehl_peak_ratio` | Latent simulator labels for analysis. | |
|
|
| Evaluator labels, cohort identities, selection flags, and simulator seeds are **not controller observations**. `episodes.jsonl` preserves complete native episode records, including optimizer diagnostics, seeds, latent wavefronts, and final-command observation indices. A final command measured earlier is distinct from the last exposure or an unmeasured submission. |
|
|
| `selected-settings.json` records six globally selected family configurations. `configuration.json` specifies the experiment. `source-manifest.json` binds the original ImageFolder export; `source-metadata.jsonl` and `source-README.md` preserve its metadata and format description. `provenance.json` records the native archive and rendering provenance. The publication manifest describes the Parquet and ZIP layout. These source artifacts contain evaluator information and are intended for reproduction and analysis. |
|
|
| ## Model and interpretation |
|
|
| The simulator uses static, monochromatic scalar Fourier optics with six controlled modes, a matched estimator, and Poisson–Gaussian detector noise. Conjugate members, detector replicates, and shared budget prefixes are correlated; the experiment has **12 independent base wavefronts**, not 4,032 independent wavefronts. |
|
|
| PNGs display `log1p(max(electrons, 0)) / log1p(photons_per_exposure)` with fixed limits 0–1, the magma colormap, and lower image origin. The display clips negative values; the raw arrays preserve them. Every image corresponds to a retained exposure. No image is synthesized for an unmeasured command. |
|
|
| These data establish neither telescope performance nor language-model performance. Recorded decision times do not establish comparable algorithm latency or a real-time control deadline. Keep failed and nonselected candidates in analyses, and separate tuning results from any subsequent evaluation. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{noetherlabs2026probebenchselection, |
| title = {ProbeBench: Classical Reference Selection}, |
| author = {{Noether Labs}}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/noetherlabs/probebench} |
| } |
| ``` |
|
|
| Released under Apache-2.0. See [LICENSE](LICENSE) and [NOTICE](NOTICE). |
|
|
