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.

翻译：本文提出了一种名为PC-JeDi的高能物理喷注生成新方法。该方法利用基于分数的扩散模型与Transformer架构相结合，由于Transformer具有排列等变性，特别适合生成粒子云形式的喷注。PC-JeDi在多个评估生成喷注质量的指标上，与当前最先进的方法相比均展现出具有竞争力的性能。尽管由于扩散模型需要大量前向传播而使其速度慢于其他模型，但依然显著快于传统精细模拟。此外，PC-JeDi通过条件生成为顶夸克和胶子两种不同粒子生成具有指定质量与横向动量的喷注。