mlsanityData to 7 Oct 2026

PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics

arXiv 2303.05376 ↗First posted 9 Mar 2023hep-ph cs.LG hep-excited by 27

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Abstract (arXiv)

In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with transformers which are well suited to the task of generating jets as particle clouds due to their permutation equivariance. PC-JeDi achieves competitive performance with current state-of-the-art methods across several metrics that evaluate the quality of the generated jets. Although slower than other models, due to the large number of forward passes required by diffusion models, it is still substantially faster than traditional detailed simulation. Furthermore, PC-JeDi uses conditional generation to produce jets with a desired mass and transverse momentum for two different particles, top quarks and gluons.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 42 of its 92 references that are in the map. First posted on arXiv 9 Mar 2023.

Builds on

42 of 92 references.

References · 42

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30 more
  1. 2017Deep Setscited by 1,394
  2. 2018Relational inductive biases, deep learning, and graph networkscited by 1,341
  3. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  4. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
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  6. 2021Gotta Go Fast When Generating Data with Score-Based Modelscited by 218
  7. 2022Particle Transformer for Jet Taggingcited by 95
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 14; 2024: 6; 2025: 3; 2026: 4.

27 papers.

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  1. 2023CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulationcited by 33
  2. 2023End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physicscited by 22
  3. 2023CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulationcited by 20
  4. 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
  5. 2023EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusioncited by 17
  6. 2023Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulationcited by 16
  7. 2024Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flowscited by 13
  8. 2023Attention to Mean-Fields for Particle Cloud Generationcited by 12
  9. 2023High-dimensional and Permutation Invariant Anomaly Detectioncited by 12
  10. 2023PC-Droid: Faster diffusion and improved quality for particle cloud generationcited by 8
  11. 2024Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusioncited by 8
  12. 2025CaloHadronic: a diffusion model for the generation of hadronic showerscited by 8
15 more
  1. 2023Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Informationcited by 7
  2. 2024PIPPIN: Generating variable length full events from partonscited by 6
  3. 2023Generalizing to new geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulationcited by 5
  4. 2023Induced Generative Adversarial Particle Transformerscited by 3
  5. 2024BUFF: Boosted Decision Tree based Ultra-Fast Flow matchingcited by 3
  6. 2023DeepTreeGANv2: Iterative Pooling of Point Cloudscited by 2
  7. 2026Generative Models and Statistical Validationcited by 2
  8. 2023The Optimal use of Segmentation for Sampling Calorimeterscited by 1
  9. 2024Variational inference for pile-up removal at hadron colliders with diffusion modelscited by 1
  10. 2025BitHEP -- The Limits of Low-Precision ML in HEPcited by 1
  11. 2026CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeterscited by 1
  12. 2024Enhancing generalization in high energy physics using white-box adversarial attackscited by 0
  13. 2025Jet Image Generation in High Energy Physics Using Diffusion Modelscited by 0
  14. 2026Generative models on phase spacecited by 0
  15. 2026Learning Standard Model structure from LHC data with Riemannian flow matchingcited by 0

Similar, not cited

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  3. 2025Multimodal Generative Flows for LHC Jets
  4. 2023Improving new physics searches with diffusion models for event observables and jet constituents
  5. 2024Particle physics DL-simulation with control over generated data properties
  6. 2026Permutation-Symmetrized Diffusion for Unconditional Molecular Generation
  7. 2025Generative Monte Carlo Sampling for Constant-Cost Particle Transport
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