Building on the success of PC-JeDi we introduce PC-Droid, a substantially improved diffusion model for the generation of jet particle clouds. By leveraging a new diffusion formulation, studying more recent integration solvers, and training on all jet types simultaneously, we are able to achieve state-of-the-art performance for all types of jets across all evaluation metrics. We study the trade-off between generation speed and quality by comparing two attention based architectures, as well as the potential of consistency distillation to reduce the number of diffusion steps. Both the faster architecture and consistency models demonstrate performance surpassing many competing models, with generation time up to two orders of magnitude faster than PC-JeDi.

翻译：在PC-JeDi成功的基础上，我们提出了PC-Droid——一种用于喷注粒子云生成的大幅改进的扩散模型。通过采用新的扩散公式、研究更先进的积分求解器，并同时对所有喷注类型进行训练，我们能够在所有评价指标上实现各类喷注的最优性能。我们通过比较两种基于注意力的架构以及一致性蒸馏减少扩散步骤的潜力，研究了生成速度与质量之间的权衡。更快的架构和一致性模型均展现出超越众多竞争模型的性能，其生成时间比PC-JeDi快两个数量级。