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AI-Agent-HEP-HZZ-Case-Study

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test

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Cannot extract the features (columns) for the split 'test' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
m_z2_cut: int64
event_count: int64
I3_reference: double
I3_detector: double
I3_detector_stat: double
delta_reference_to_detector: double
delta_stat_paired: double
delta_over_sigma_paired: double
paper_I3: double
detector_minus_paper: double
detector_minus_paper_over_sample_stat: double
vs
variable: string
low: double
high: double
numerator: double
denominator: double
efficiency: double
bootstrap_std: double
low95: double
high95: double
undefined_replicas: int64
sparse: bool
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4645, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2866, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 606, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5012, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              m_z2_cut: int64
              event_count: int64
              I3_reference: double
              I3_detector: double
              I3_detector_stat: double
              delta_reference_to_detector: double
              delta_stat_paired: double
              delta_over_sigma_paired: double
              paper_I3: double
              detector_minus_paper: double
              detector_minus_paper_over_sample_stat: double
              vs
              variable: string
              low: double
              high: double
              numerator: double
              denominator: double
              efficiency: double
              bootstrap_std: double
              low95: double
              high95: double
              undefined_replicas: int64
              sparse: bool

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AI-Agent HEP HZZ Case Study

This private dataset repository contains the frozen data products associated with the study:

Towards AI-Agent-Accelerated Research in High-Energy Physics: A Case Study in Monte Carlo Analysis

The accompanying analysis code and workflow are available at:

https://github.com/AItutorialjrb/agentic_HZZ_case

`delphes/`

Final detector-level Delphes ROOT products used for the frozen 200,000-event analysis.

`derived/`

Machine-readable derived outputs used in the benchmark and open-ended diagnostic studies.

`publication/`

Numerical inputs and tables associated with the publication results.

`metadata/`

Random seeds, production manifests, provenance records, frozen commit information, and SHA256 checksums.

Reproducibility

The public release will support:

Reproduction of publication tables and figures from machine-readable outputs.
Recalculation of the Bell observable and bootstrap uncertainties from frozen analysis products.
Re-running extraction and analysis starting from final Delphes ROOT files.

Large intermediate LHE and HepMC files are not archived because they can be regenerated from the public configurations, seeds, and workflow definitions.

Physics process

e+ e- -> ZH Z -> q qbar H -> ZZ* -> 4 mu

at sqrt(s) = 250 GeV.

The frozen production contains 200 random seeds with 1000 generated events per seed, corresponding to 200,000 generated events.

Software

MadGraph5_aMC@NLO 3.7.1
PYTHIA 8.317
Delphes 3.5.1
FastJet 3.5.1
Python 3.9.25
ROOT 6.40.02
HTCondor 24.12.16

Integrity

Checksums are stored in:

metadata/SHA256SUMS

and can be verified with:

sha256sum -c metadata/SHA256SUMS

Availability

This repository is private during manuscript preparation and will be made public when the manuscript is submitted.

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Total file size:

215 MB

AI-Agent HEP HZZ Case Study

Contents

delphes/

derived/

publication/

metadata/