Speaker
Ayodele Ore
Description
Correcting measurements for detector effects is a pressing inverse problem in LHC physics. Current methods solve this problem by relying on iterative refinement, minimax optimization, or a surrogate forward mapping. In this talk, I present Adversary-free Unfolding SanS Iteration or Emulation (AUSSIE), which dispenses with these mechanisms while remaining asymptotically correct. AUSSIE unfolds by reweighting a reference simulator in similar fashion to OmniFold. However, its new kernel-based loss function yields one-shot solutions with minimal bias toward the reference distribution. I show results for AUSSIE applied to a range of unfolding tasks, from low-dimensional examples to full-phase-space jet substructure.