mlsanityData to 14 Oct 2026

CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation

arXiv 2309.05704 ↗First posted 11 Sep 2023physics.ins-det cs.LG hep-excited by 20

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Abstract (arXiv)

Fast simulation of the energy depositions in high-granular detectors is needed for future collider experiments with ever-increasing luminosities. Generative machine learning (ML) models have been shown to speed up and augment the traditional simulation chain in physics analysis. However, the majority of previous efforts were limited to models relying on fixed, regular detector readout geometries. A major advancement is the recently introduced CaloClouds model, a geometry-independent diffusion model, which generates calorimeter showers as point clouds for the electromagnetic calorimeter of the envisioned International Large Detector (ILD). In this work, we introduce CaloClouds II which features a number of key improvements. This includes continuous time score-based modelling, which allows for a 25-step sampling with comparable fidelity to CaloClouds while yielding a 6× speed-up over Geant4 on a single CPU (5× over CaloClouds). We further distill the diffusion model into a consistency model allowing for accurate sampling in a single step and resulting in a 46× (37× over CaloClouds) speed-up. This constitutes the first application of consistency distillation for the generation of calorimeter showers.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 52 of its 104 references that are in the map. First posted on arXiv 11 Sep 2023.

Builds on

52 of 104 references.

References · 52

  1. 2017Attention Is All You Needcited by 60,361
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38 more
  1. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,979
  2. 2023Consistency Modelscited by 1,822
  3. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,043
  4. 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 938
  5. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 735
  6. 2016Improving Variational Inference with Inverse Autoregressive Flowcited by 640
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  8. 2022Fast Sampling of Diffusion Models with Exponential Integratorcited by 532
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  11. 2022Fast Sampling of Diffusion Models via Operator Learningcited by 175
  12. 2023TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillationcited by 116
  13. 2017CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networkscited by 78
  14. 2017Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeterscited by 55
  15. 2022Score-based Generative Models for Calorimeter Shower Simulationcited by 52
  16. 2017Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesiscited by 46
  17. 2021CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flowscited by 46
  18. 2021Particle Cloud Generation with Message Passing Generative Adversarial Networkscited by 46
  19. 2019Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physicscited by 42
  20. 2021CaloFlow II: Even Faster and Still Accurate Generation of Calorimeter Showers with Normalizing Flowscited by 34
  21. 2023CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulationcited by 33
  22. 2022Evaluating generative models in high energy physicscited by 31
  23. 2020GANplifying Event Samplescited by 28
  24. 2022CaloMan: Fast generation of calorimeter showers with density estimation on learned manifoldscited by 28
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  30. 2023Inductive Simulation of Calorimeter Showers with Normalizing Flowscited by 22
  31. 2021Generative Networks for Precision Enthusiastscited by 21
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  37. 2022CaloFlow for CaloChallenge Dataset 1cited by 14
  38. 2023Attention to Mean-Fields for Particle Cloud Generationcited by 12

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 8; 2025: 5; 2026: 4.

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  1. 2024OmniJet-α: The first cross-task foundation model for particle physicscited by 43
  2. 2024A Lorentz-Equivariant Transformer for All of the LHCcited by 28
  3. 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
  4. 2023EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusioncited by 17
  5. 2025OmniJet-αC: Learning point cloud calorimeter simulations using generative transformerscited by 14
  6. 2024Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flowscited by 13
  7. 2025Foundation models for high-energy physicscited by 10
  8. 2024Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusioncited by 8
  9. 2025CaloHadronic: a diffusion model for the generation of hadronic showerscited by 8
  10. 2023Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Informationcited by 7
  11. 2024A Comprehensive Evaluation of Generative Models in Calorimeter Shower Simulationcited by 5
  12. 2024Calibrating Bayesian Generative Machine Learning for Bayesiamplificationcited by 5
8 more
  1. 2024BUFF: Boosted Decision Tree based Ultra-Fast Flow matchingcited by 3
  2. 2024Physics Instrument Design with Reinforcement Learningcited by 3
  3. 2026AllShowers: One model for all calorimeter showerscited by 3
  4. 2026Generalizable Foundation Models for Calorimetry via Mixtures-of-Experts and Parameter Efficient Fine Tuningcited by 3
  5. 2025A First Full Physics Benchmark for Highly Granular Calorimeter Surrogatescited by 2
  6. 2026Generative Models and Statistical Validationcited by 2
  7. 2026CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeterscited by 1
  8. 2025Jet Image Generation in High Energy Physics Using Diffusion Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation
  2. 2026Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation
  3. 2025Even Faster Simulations with Flow Matching: A Study of Zero Degree Calorimeter Responses
  4. 2024Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN
  5. 2024CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
  6. 2025Inverse Autoregressive Flows for Zero Degree Calorimeter fast simulation
  7. 2024Scaling Up Diffusion and Flow-based XGBoost Models
  8. 2021Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case