直接优化粒子物理信号显著性，提升对撞机搜索灵敏度。
Loss function to optimise signal significance in particle physics
- 用代理损失函数直接优化信号显著性指标。
- 相同显著性下，信号效率比交叉熵更高。
- 适合需要高灵敏度的粒子物理探测任务。
我们构建了一个代理损失函数，用于直接优化粒子物理中使用的显著性度量。在使用线性模型的简单事件分类任务中评估该损失函数，结果表明其决策边界会随过程截面变化而调整。与采用交叉熵损失训练的模型相比，新损失训练出的模型在相似的估计显著性水平下具有更高的信号效率，显示出提升对撞机粒子物理搜寻灵敏度的潜力。
原文摘要 · Abstract (English)
We construct a surrogate loss to directly optimise the significance metric used in particle physics. We evaluate our loss function for a simple event classification task using a linear model and show that it produces decision boundaries that change according to the cross sections of the processes involved. We find that the models trained with the new loss have higher signal efficiency for similar values of estimated signal significance compared to ones trained with a cross-entropy loss, showing promise to improve sensitivity of particle physics searches at colliders.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。