3-5 June 2020
Europe/Zurich timezone

Position reconstruction using machine learning algorithms applied to Resistive Silicon Detectors (RSD)

4 Jun 2020, 15:00


Federico Siviero (Universita e INFN Torino (IT))


RSDs (Resistive AC-Coupled Silicon Detectors) are n-in-p silicon sensors based on LGAD (Low-Gain Avalanche Diode) technology, featuring a continuous gain layer over the whole sensor area. The innovative feature of these sensors is that the signal induced by an ionizing particle spreads among several pixels, allowing position reconstruction techniques that combine the information of many read-out channels.
In this contribution, the first application of a machine learning technique to RSD devices is presented: using inputs from 3 or 4 pads, a Multi-Output regressor algorithm is trained and validated using laboratory data taken with a Transient Current Technique (TCT) setup; then it is applied to beam test data. RSD matrices having different pitch and pixel sizes have been tested, in order to assess the algorithm performances with different geometries.
As an example, an RSD with 200 μm pixel provided 5 μm position resolution, 10 times better than what is achievable with binary read-out (200μm / sqrt(12) ~ 55μm).

Primary author

Federico Siviero (Universita e INFN Torino (IT))


Roberta Arcidiacono (Universita e INFN Torino (IT)) Nicolo Cartiglia (INFN Torino (IT)) marco costa (University of Torino) Marco Ferrero (Universita e INFN Torino (IT)) Marco Mandurrino (INFN) Valentina Sola (Universita e INFN Torino (IT)) Amedeo Staiano (Universita e INFN Torino (IT)) Marta Tornago (Universita e INFN Torino (IT)) Artur Apresyan (Fermi National Accelerator Lab. (US)) Ryan Heller (Fermi National Accelerator Lab. (US)) Karri Folan Di Petrillo (Fermi National Accelerator Lab. (US)) Serguei Los (Fermi National Accelerator Laboratory (FNAL)) Giacomo Borghi (Fondazione Bruno Kessler) Maurizio Boscardin (FBK Trento) Gian-Franco Dalla Betta (INFN and University of Trento) Francesco Ficorella (Fondazione Bruno Kessler and INFN Trento) Lucio Pancheri (University of Trento) Giovanni Paternoster (Fondazione Bruno KEssler) Matteo Centis Vignali (FBK)

Presentation materials