mlsanityData to 14 Oct 2026

The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider

arXiv 2105.14027 ↗First posted 28 May 2021hep-ph hep-ex physics.data-ancited by 29

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Abstract (arXiv)

We describe the outcome of a data challenge conducted as part of the Dark Machines Initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims at detecting signals of new physics at the LHC using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of >1 Billion simulated LHC events corresponding to 10~rmfb-1 of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.

Key facts. Cited by 29 papers in the map (data through 14 Oct 2026). Builds on 24 of its 116 references that are in the map. First posted on arXiv 28 May 2021.

Builds on

24 of 116 references.

References · 24

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12 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 7; 2022: 3; 2023: 10; 2024: 1; 2025: 5; 2026: 3.

29 papers.

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  1. 2021Machine Learning in the Search for New Fundamental Physicscited by 50
  2. 2023Machine Learning for Anomaly Detection in Particle Physicscited by 30
  3. 2023PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physicscited by 27
  4. 2022Learning new physics efficiently with nonparametric methodscited by 21
  5. 2023Quantum anomaly detection in the latent space of proton collision events at the LHCcited by 21
  6. 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
  7. 2021Challenges for Unsupervised Anomaly Detection in Particle Physicscited by 16
  8. 2021Online-compatible Unsupervised Non-resonant Anomaly Detectioncited by 15
  9. 2025Large Physics Models: Towards a collaborative approach with Large Language Models and Foundation Modelscited by 14
  10. 2023High-dimensional and Permutation Invariant Anomaly Detectioncited by 12
  11. 2023Anomalies, Representations, and Self-Supervisioncited by 11
  12. 2023CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimationcited by 10
17 more
  1. 2023Improving new physics searches with diffusion models for event observables and jet constituentscited by 10
  2. 2021Autoencoders for Semivisible Jet Detectioncited by 9
  3. 2023Unravelling physics beyond the standard model with classical and quantum anomaly detectioncited by 9
  4. 2021New Methods and Datasets for Group Anomaly Detection From Fundamental Physicscited by 6
  5. 2022Benchmarking energy consumption and latency for neuromorphic computing in condensed matter and particle physicscited by 5
  6. 2021Shared Data and Algorithms for Deep Learning in Fundamental Physicscited by 4
  7. 2021Funnels: Exact maximum likelihood with dimensionality reductioncited by 4
  8. 2022Resonant Anomaly Detection with Multiple Reference Datasetscited by 4
  9. 2024Universal New Physics Latent Spacecited by 3
  10. 2025ColliderML: The First Release of an OpenDataDetector High-Luminosity Physics Benchmark Datasetcited by 3
  11. 2026Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practicecited by 3
  12. 2023Decorrelation using Optimal Transportcited by 0
  13. 2025TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searchescited by 0
  14. 2025Generator Based Inference (GBI)cited by 0
  15. 2025SparsePixels: Efficient Convolution for Sparse Data on FPGAscited by 0
  16. 2026Contrastive Learning for Interpretable Anomaly Detection at Collider Experimentscited by 0
  17. 2026Local Diagnostics of Learned Event Representations for Anomaly Detection at the HL-LHCcited by 0