Publish classical reference selection exposures and detector arrays

30,912 acquired exposures across 4,032 public parameter-selection episodes. Includes exact raw arrays, native episode records and source manifests.

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NOTICE

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+ProbeBench
+Copyright 2026 Noether Labs contributors

README.md

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+---
+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).

configuration.json

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