We describe the construction of end-to-end jet image classifiers based on
simulated low-level detector data to discriminate quark- vs. gluon-initiated
jets with high-fidelity simulated CMS Open Data. We highlight the importance of
precise spatial information and demonstrate competitive performance to existing
state-of-the-art jet classifiers. We further generalize the end-to-end approach
to event-level classification of quark vs. gluon di-jet QCD events. We compare
the fully end-to-end approach to using hand-engineered features and demonstrate
that the end-to-end algorithm is robust against the effects of underlying event
and pile-up.

使用高保真模拟的 CMS 开放数据，构建以低级检测器数据为基础的端到端喷注图像分类器，可以区分以夸克 vs. 胶子引发的喷注；并将端到端方法泛化到夸克 vs. 胶子二喷注 QCD 事件的事件级分类中，与使用手工特征的方法进行对比，结果表明端到端算法对事件和堆积的影响具有很强的鲁棒性。