mlsanityData to 7 Oct 2026

Quantum Diffusion Model for Quark and Gluon Jet Generation

arXiv 2412.21082 ↗First posted 30 Dec 2024quant-ph cs.LG hep-phcited by 1

On the map: Diffusion models → Diffusion foundations and sampling

Abstract (arXiv)

Diffusion models have demonstrated remarkable success in image generation, but they are computationally intensive and time-consuming to train. In this paper, we introduce a novel diffusion model that benefits from quantum computing techniques in order to mitigate computational challenges and enhance generative performance within high energy physics data. The fully quantum diffusion model replaces Gaussian noise with random unitary matrices in the forward process and incorporates a variational quantum circuit within the U-Net in the denoising architecture. We run evaluations on the structurally complex quark and gluon jets dataset from the Large Hadron Collider. The results demonstrate that the fully quantum and hybrid models are competitive with a similar classical model for jet generation, highlighting the potential of using quantum techniques for machine learning problems.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 17 of its 29 references that are in the map. First posted on arXiv 30 Dec 2024.

Builds on

17 of 29 references.

Closest ancestors · 8

Same direction, newest first

  1. 2023Generative quantum machine learning via denoising diffusion probabilistic models9 Oct
  2. 2023Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds4 Apr
  3. 2022A Survey on Generative Diffusion Model6 Sep
  4. 2022Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise19 Aug
  5. 2021Diffusion Models Beat GANs on Image Synthesis11 May
  6. 2021Improved Denoising Diffusion Probabilistic Models18 Feb
  7. 2020Denoising Diffusion Implicit Models6 Oct
  8. 2020Denoising Diffusion Probabilistic Models19 Jun

Other references · 9

  1. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  2. 2022Denoising Diffusion Restoration Modelscited by 951
  3. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  4. 2023Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generationcited by 142
  5. 2017Quantum machine learning: a classical perspectivecited by 95
  6. 2023Graph Denoising Diffusion for Inverse Protein Foldingcited by 44
  7. 2019End-to-End Jet Classification of Quarks and Gluons with the CMS Open Datacited by 11
  8. 2024Quantum Vision Transformers for Quark-Gluon Classificationcited by 7
  9. 2024Variational Quantum Circuits Enhanced Generative Adversarial Networkcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Local-Time Riemannian Score Matching on the Quantum Pure-State Manifoldcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Jet Image Generation in High Energy Physics Using Diffusion Models
  2. 2023Quantum-Noise-Driven Generative Diffusion Models
  3. 2024Quantum Denoising Diffusion Models
  4. 2026An Hybrid Quantum-Classical Diffusion Model for Image Generation
  5. 2023Quantum circuit synthesis with diffusion models
  6. 2023PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
  7. 2025Physics-inspired Generative AI models via real hardware-based noisy quantum diffusion
  8. 2025Leveraging Diffusion Models for Parameterized Quantum Circuit Generation