Apr 22 – 27, 2024
Europe/Vienna timezone

GEANT4 simulations within the ANAIS-112 experiment data analysis procedures

Apr 27, 2024, 9:40 AM
20m

Speaker

Mrs Tamara Pardo Yanguas (CAPA, University of Zaragoza, Spain)

Description

ANAIS is a direct dark matter detection experiment whose goal is to confirm or refute in a model independent way the positive annual modulation signal reported by DAMA/LIBRA. ANAIS-112, consisting of 112.5 kg of NaI(Tl) scintillators, is taking data at the Canfranc Underground Laboratory in Spain since August 2017. Results corresponding to the analysis of three years of data show no modulation and are incompatible with DAMA/LIBRA. A 3-year data reanalysis based on a new filtering protocol improves both the selection efficiency and the background of the experiment, thus enabling a first direct test of DAMA/LIBRA at three sigma level. However, testing this signal relies on the knowledge of the scintillation quenching factors (QF) for the conversion of nuclear recoil energy depositions with respect to the same energy deposited by electrons. Previous measurements of the QF in NaI(Tl) show a large dispersion, which introduces a systematic uncertainty in the comparison between different experiments using NaI(Tl). Consequently, in order to fully understand the response of the ANAIS-112 detectors to nuclear recoils, a specific neutron calibration program is being developed. This program combines two different approaches: on the one hand, QF measurements across several NaI(Tl) crystals similar to those used in ANAIS-112 were carried out in a monoenergetic neutron beam; on the other hand, the study presented here aims at the evaluation of the QF by exposing directly the large ANAIS-112 crystals to neutrons from 252Cf sources. Comparison between these onsite calibrations and detailed GEANT4 simulations allows testing different QF models. Some results will be discussed. In addition, the GEANT4 model of the full ANAIS-112 experiment is currently under revision and upgrading. Present status will be reported in this talk, focusing in particular in the optical simulations of the ANAIS-112 detectors, which allow to produce synthetic signals that can be used for training machine-learning procedures for noise discrimination.

Primary author

Mrs Tamara Pardo Yanguas (CAPA, University of Zaragoza, Spain)

Co-authors

Alfonso Ortiz de Solórzano Dr Ana Salinas (CAPA, University of Zaragoza) Mr David Cintas González (Universidad de Zaragoza) Dr Eduardo García (CAPA, University of Zaragoza) Iván Coarasa Casas (CAPA, University of Zaragoza, Spain) Mr Jaime Apilluelo (CAPA, University of Zaragoza) Jorge Puimedon (Universidad de Zaragoza) Dr Julio Amaré (CAPA, University of Zaragoza) Maria Martinez María Luisa Sarsa (University of Zaragoza) Dr Miguel Ángel Oliván (Universidad de Zaragoza) Dr Patricia Villlar (CAPA, University of Zaragoza) Susana Cebrian Guajardo (Universidad de Zaragoza (ES)) Dr Ysrael Ortigoza (CAPA, University of Zaragoza)

Presentation materials