Learning to Trigger: Reinforcement Learning at the Large Hadron Collider
Paper • 2606.23993 • Published • 3
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: OSError
Message: Can't synchronously read data (can't open directory (/usr/local/lib/plugin). Please verify its existence)
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 87, in _generate_tables
pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 275, in _recursive_load_arrays
arr = _load_array(dset, path, start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 242, in _load_array
arr = dset[start:end]
~~~~^^^^^^^^^^^
File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "/usr/local/lib/python3.14/site-packages/h5py/_hl/dataset.py", line 872, in __getitem__
return self._fast_reader.read(args)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^
File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py/_selector.pyx", line 393, in h5py._selector.Reader.read
OSError: Can't synchronously read data (can't open directory (/usr/local/lib/plugin). Please verify its existence)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Datasets for Self-Driving Trigger Study at L1
Mirror of Zenodo record 10.5281/zenodo.17399948 — datasets for Learning to Trigger: Reinforcement Learning at the Large Hadron Collider (arXiv:2606.23993).
Derived from CMS 2016 Open Data for Level-1 (L1) hadronic objects (jets). Each file contains reconstructed jet features and the number of primary vertices (N_PV) per event.
Files
| File | Size |
|---|---|
HToAATo4B.h5 |
70.9 MB |
MinBias_1.h5 |
354.0 MB |
MinBias_2.h5 |
368.1 MB |
TT_1.h5 |
175.7 MB |
Trigger_food_Data.h5 |
79.8 MB |
Trigger_food_MC.h5 |
210.1 MB |
data_Run_2016_283408_longest.h5 |
173.1 MB |
data_Run_2016_283876.h5 |
55.4 MB |
MinBias_1.h5— min-bias MC background (AD autoencoder training).MinBias_2.h5— alternate min-bias MC background (control-algorithm studies).TT_1.h5— Standard Model t-tbar hadronic signal.HToAATo4B.h5— BSM H→AA→4b signal.data_Run_2016_283876.h5— real CMS 2016 run (AD training, real background).data_Run_2016_283408_longest.h5— longest CMS 2016 run (control-algorithm testing).Trigger_food_MC.h5— precomputed control variables (anomaly score, HT, N_PV) for MC.Trigger_food_Data.h5— precomputed control variables for real data (matched by N_PV).
Loading
import h5py
from huggingface_hub import hf_hub_download
path = hf_hub_download(repo_id="zixinding/CMS-trigger-l1", filename="Trigger_food_MC.h5",
repo_type="dataset")
with h5py.File(path, "r") as f:
print(list(f.keys()))
Citation
@misc{ding2026learning,
title = {Learning to Trigger: Reinforcement Learning at the Large Hadron Collider},
author = {Ding, Zixin and Emami, Shaghayegh and Salvi, Giovanna and Tosciri, Cecilia and Gandrakota, Abhijith and Ngadiuba, Jennifer and Tran, Nhan and Herwig, Christian and Miller, David W. and Chen, Yuxin},
year = {2026},
eprint = {2606.23993},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2606.23993}
}
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