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aryaraeesi/BEvAn-data

BEvAn — COSI activation simulations MEGAlib simulation files backing cosi-betadecay/BEvAn, a physics-based likelihood classifier that tags each simulated COSI event as a β⁺ / positron-annihilation signal (back-to-back 511 keV photons) or background from its Compton kinematics. All events come from a cosima activation simulation (BeamType Activation, DecayMode ActivationBuildup): cosmic-ray protons irradiate the instrument, the activated isotopes decay, and the β⁺ emitters among… See the full description on the dataset page: https://huggingface.co/datasets/aryaraeesi/BEvAn-data.

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BEvAn — COSI activation simulations

MEGAlib simulation files backing `cosi-betadecay/BEvAn`, a physics-based likelihood classifier that tags each simulated COSI event as a β⁺ / positron-annihilation signal (back-to-back 511 keV photons) or background from its Compton kinematics.

All events come from a cosima activation simulation (BeamType Activation, DecayMode ActivationBuildup): cosmic-ray protons irradiate the instrument, the activated isotopes decay, and the β⁺ emitters among them produce the 511 keV annihilation signal the classifier is trained to find. The three-step cosima source files that generate this are in the GitHub repo under `data/cosima/` and are not duplicated here. Produced with MEGAlib 4.00.00.

Datasets

One folder per detector geometry. The geometries ship with MEGAlib under $MEGALIB/resource/examples/geomega/:

Folder	Geometry (`.geo.setup`)	Size
`SPILike/`	`special/SPILike`	382 MB
`NCT/`	`special/Simple_Ge_NCT_try1_040721`	848 MB
`Max/`	`special/Max`	1.2 GB
`GeACT/`	`special/GeACT`	3.8 GB
`COSIBalloon_9det/`	`cosiballoon/COSIBalloon.9Detector`	1.0 GB
`COSIBalloon_10det/`	`cosiballoon/COSIBalloon.10Detector`	980 MB
`COSIBalloon_12det/`	`cosiballoon/COSIBalloon.12Detector`	1.1 GB

Files in each folder

For a dataset {name}:

File	What it is
`{name}.sim`	Concatenation file written by `mcosima` — it holds no events. It is a short header plus `IN {name}.incN.id1.sim.gz` lines pointing at the chunks below. This is the path you pass to the pipeline; MEGAlib follows the pointers.
`{name}.incN.id1.sim.gz`	The actual simulated events, one chunk per parallel `mcosima` thread (N = 1…4). Required — `{name}.sim` is useless without them.
`{name}.tra`	Compton-reconstructed events (`revan` output) for `{name}.sim`.
`{name}_P1.`, `{name}_P2.`	Two dedicated prior simulations against the same geometry, each a full `.sim` (+ `.tra`) set of its own. Their ANNI-labeled events, counted per hit-multiplicity bucket, form the classifier's class priors. The training split is never used for the prior, which is why these are separate runs. Passed via `--prior-sim`. `_P1` files are self-contained `.sim` files from an earlier run; `_P2` files use the same `mcosima` concatenation layout as above.

The COSIBalloon_* folders additionally carry a crossections/ directory — MEGAlib-generated cross-section tables. They are regenerated on demand by MEGAlib and are included only so the folders are a byte-exact mirror.

Results

results/ holds the outputs of the ablation study over the datasets above — a mirror of ablations/results/ in the GitHub repo (which remains the source of truth; these are generated files, published here so the figures and numbers are citable alongside the inputs they came from). 25 MB total.

One folder per run, named by timestamp:

Run	Contents
`2026-07-14_09-33-32/`	includes a `no_calibration` ablation, since removed
`2026-07-15_00-45-23/`
`2026-07-15_05-06-29/`	most recent; adds `deployment` and `label_window`

Each run folder has:

—tables/ — one CSV per ablation (factor_contributions, learned_weights, no_ckd_order, gt_tolerance / label_window, …) plus a summary.csv. deployment.csv is the champion deployed per dataset at the dedicated-prior operating point.
—figures/ — one PNG per ablation at the top level, plus a per-dataset subfolder (SPILike/, NCT/, Max/, GeACT/, COSIBalloon_*/) of the per-run plots for that geometry.

Regenerate with python ablations/main.py from the GitHub repo.

Download

bash

hf download aryaraeesi/BEvAn-data --repo-type dataset --local-dir data/

Note this pulls results/ into data/ too. For just the simulation inputs, or a single dataset (remember to take its .inc* chunks along with the .sim):

bash

hf download aryaraeesi/BEvAn-data --repo-type dataset \
  --include "SPILike/*" --local-dir data/

Or just the results, without the multi-GB simulations:

bash

hf download aryaraeesi/BEvAn-data --repo-type dataset \
  --include "results/*" --local-dir .

Gotcha: the geometry path is absolute

The Geometry line inside every .sim header is an absolute path from the machine that ran the simulation (/home/arya/Documents/megalib/...). MEGAlib will not find the geometry on your machine unless you either point that line at your own $MEGALIB checkout or pass the geometry explicitly — which is what the BEvAn entry scripts do via --geo-file:

bash

python src/BEvAn/analysis.py \
  --geo-file $MEGALIB/resource/examples/geomega/special/SPILike.geo.setup \
  --sim-file data/SPILike/SPILike.sim \
  --tra-file data/SPILike/SPILike.tra \
  --prior-sim data/SPILike/SPILike_P1.sim data/SPILike/SPILike_P2.sim

License

Apache-2.0, matching the BEvAn repository.