Representação Esparsa Aplicada a Estimação Online de Energia para um Calorímetro Submetido a uma Alta Taxa de Eventos

This work presents a study about channel equalization techniques, applied to the online energy reconstruction in ATLAS (A Toroidal LHC ApparatuS) calorimeters. The high event rate environment, predicted to occur in the next few years on the LHC (Large Hadron Collider) particle collider, increases the likelihood of adjacent collisions occurring, producing the signal stacking effect. The algorithm currently used for the reconstruction is not robust to this effect. Deconvolution techniques have already been proposed in other works and methods based on FIR (Finite Impulse Response) filters obtained higher results than the current technique. This paper proposes the use of a technique, which is based on sparse representations, where results indicate improvement in the estimation regarding the use of FIR filters.