تقرير
DeepTreeGAN: Fast Generation of High Dimensional Point Clouds
| العنوان: | DeepTreeGAN: Fast Generation of High Dimensional Point Clouds |
|---|---|
| المؤلفون: | Scham, Moritz Alfons Wilhelm, Krücker, Dirk, Käch, Benno, Borras, Kerstin |
| سنة النشر: | 2023 |
| المجموعة: | High Energy Physics - Experiment Physics (Other) |
| مصطلحات موضوعية: | High Energy Physics - Experiment, Physics - Computational Physics |
| الوصف: | In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the complex dependencies between the particles must be correctly modelled. Particle showers are inherently tree-based processes, as each particle is produced by the decay or detector interaction of a particle of the previous generation. In this work, we present a novel Graph Neural Network model (DeepTreeGAN) that is able to generate such point clouds in a tree-based manner. We show that this model can reproduce complex distributions, and we evaluate its performance on the public JetNet dataset. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2311.12616 |
| رقم الأكسشن: | edsarx.2311.12616 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |