Calorimeter Shower Superresolution with Conditional Normalizing Flows: Implementation and Statistical Evaluation

ArXi:2603.26813v1 Announce Type: cross In High Energy Physics, detailed calorimeter simulations and reconstructions are essential for accurate energy measurements and particle identification, but their high granularity makes them computationally expensive. Developing data-driven techniques capable of recovering fine-grained information from coarser readouts, a task known as calorimeter superresolution, offers a promising way to reduce both computational and hardware costs while preserving detector performance.