November 29, 2021 to December 3, 2021
Virtual and IBS Science Culture Center, Daejeon, South Korea
Asia/Seoul timezone

Reconstruction and Particle Identification with CYGNO Experiment

contribution ID 669
Dec 3, 2021, 4:10 PM
Auditorium (Virtual and IBS Science Culture Center, Daejeon, South Korea)


Virtual and IBS Science Culture Center, Daejeon, South Korea

55 EXPO-ro Yuseong-gu Daejeon, South Korea email: +82 42 878 8299
Poster Track 2: Data Analysis - Algorithms and Tools Lightning talks session


Atul Prajapati (Gran Sasso Science Institute)


CYGNO is developing a gaseous Time Projection Chamber (TPC) for directional dark matter searches, to be hosted at Laboratori Nazionali del Gran Sasso (LNGS), Italy. CYGNO uses He:CF4 gas mixture at atmospheric pressure and relies on Gas Electron Multipliers (GEMs) stack for the charge amplification. Light is produced by the electrons avalanche thanks to the CF4 scintillation properties and is then optically read out by a high-resolution scientific CMOS Camera (sCMOS) and Photo-Multiplier Tubes (PMT). sCMOS are designed for low readout noise, uniformity, and linearity and are therefore capable to track particles down to O(keV) energies. These high-resolution images (2D event projection) are combined with the PMT signal (relative z coordinate information) to obtain 3D reconstruction, with the aim of particle identification and to determine track direction of arrival.

sCMOS images are very well suited to be analysed with Machine Learning techniques (using Convolutional Neural Networks) because of their high granularity and low noise. We will present the CYGNO features and achieved experimental performance, and then focus on the MonteCarlo sCMOS images simulation, reconstruction algorithms to identify and track particles, and the use of Convolutional Neural Networks to classify them into different energy classes of Electron and Nuclear recoils.

Speaker time zone Compatible with Asia

Primary author

Atul Prajapati (Gran Sasso Science Institute)

Presentation materials