ColliderML

About the Data

The ColliderML dataset is the largest-yet source of full-detail simulation in a virtual detector experiment.

Why virtual? The simulation choices are not tied to a construction timeline, there are no budget limitations, no politics. The only goals are to produce the most realistic physics on a detailed detector geometry, with significant computating challenges, in an ML-friendly structure.

The ColliderML dataset provides comprehensive simulation data for machine learning applications in high-energy physics, with detailed detector responses and physics object reconstructions.

Get the Data

Download data with the colliderml CLI, then load it in Python with Polars. The dataset is also on HuggingFace if you prefer the datasets library.

Quick Start

1. Install and download:

pip install colliderml
colliderml download --channels ttbar --pileup pu0 --objects particles,tracker_hits,calo_hits,tracks --max-events 200

2. Load in Python (same config as the download):

from colliderml.core import load_tables, collect_tables

cfg = {
    "dataset_id": "CERN/ColliderML-Release-1",
    "channels": "ttbar",
    "pileup": "pu0",
    "objects": ["particles", "tracker_hits", "calo_hits", "tracks"],
    "split": "train",
    "lazy": False,
    "max_events": 200,
}
tables = load_tables(cfg)
frames = collect_tables(tables)  # dict[str, pl.DataFrame]
# e.g. frames["particles"], frames["tracker_hits"]

For more (exploding tables, pileup subsampling, calibration), see the library docs and the exploration notebook.

Interactive Configuration

Use the configurator below to customize your dataset selection and generate the corresponding code:

Dataset Configuration

Loading available datasets from HuggingFace...

Download command

colliderml download --channels ttbar --pileup pu0 --objects particles,tracker_hits,calo_hits,tracks --max-events 1000

Then load the data in Python with load_tables; see the library docs or the exploration notebook.

If there are errors or unexpected behavior, please open an issue on the GitHub repository.

Dataset Changelog (latest 5)

• (0.2.0 — 2025-11-07) - Datasets now hosted on HuggingFace Hub for easier access and distribution.
• (0.2.0 — 2025-11-07) - Support for standard HuggingFace datasets library for data loading.
• (0.2.0 — 2025-11-07) - Migrated from NERSC manifest-based distribution to HuggingFace datasets.
• (0.2.0 — 2025-11-07) - Data now stored in Parquet format with improved compression and accessibility.
• (0.1.0 — 2025-09-08) - Initial release of ColliderML dataset with ttbar and ggf physics processes. See the full changelog: Changelog.