Speaker
Description
Physically-grounded anomaly detection requires reconstruction pipelines that preserve, rather than obscure, detector information. I introduce a two-stage strategy that inserts a synthetic, detector-aware representation (S) between the raw calorimeter readout (D) and low-dimensional truth (T). I demonstrate the concept in full simulation of a segmented dual-readout crystal ECAL for future colliders, where S is built from images of scintillation and Cerenkov photon tracks inside the detector. These features encode the physics of the conventional dual-readout correction but are inaccessible in real data. A first U-Net implementation on D -> S -> T reproduces the principles of dual-readout correction, giving the network an interpretable physical anchor. Because outliers are expressed in terms of concrete detector processes, this approach makes possible more reliable, explainable anomaly detection than purely latent-space methods. I will present the first qualtitative results and outline next steps, setting the stage for detector-aware AD at future colliders.
