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Simulation for the search of dark matter with CRESST

Simulation for the search of dark matter with CRESST

Jochen Schieck (ORCID: 0000-0002-1058-8093)
  • Grant DOI 10.55776/I5420
  • Funding program Principal Investigator Projects International
  • Status ended
  • Start December 1, 2021
  • End November 30, 2025
  • Funding amount € 319,998

DACH: Österreich - Deutschland - Schweiz

Disciplines

Computer Sciences (20%); Physics, Astronomy (80%)

Keywords

    Dark Matter, Simulation, Cryogenic Detectors

Abstract Final report

Over 80% of all matter in the universe is not visible, the so-called dark matter. This dark matter could be explained by introducing a new particle, which interacts weakly only with ordinary matter. However, to observe it, the interaction has to be stronger than the gravitational one. The predictions for the mass of this weakly interacting particle spans over several orders of magnitude. Recently, models with a mass range for dark matter particles between a few MeV and a few GeV have generated much interest. The CRESST experiment, which is currently being carried out at the Gran Sasso laboratory in Italy, is optimized for dark matter by searching for dark matter particles scattering with conventional matter. The energy of the scattering process is converted into lattice excitations of the detector crystal, the so-called phonons, and then read out with a sensor at the transition temperature. With the data collected so far by CRESST, no signal has been observed, however, the exclusion limits for dark matter candidates with a mass of less than 2 GeV are the best limit among the experiments for the direct search for dark matter. In the first funding period, the detection threshold for the recoil energy could be lowered down to 30 eV, an improvement of an order of magnitude compared to previous CRESST detectors and one of the lowest thresholds of all experiments. At recoil energies below 200 eV, however, the event rate rises sharply, and the origin of these energy deposits is not yet understood. Studies to identify these energy deposits are a central part of the project. These studies are based on detailed simulations studies and the analysis of experimental data. In addition to decoding this unknown background, different detector materials for the crystals, e.g., sapphire, are to be used in addition to the previously used detector material, calcium tungstate. These crystals and their properties must also be simulated to make full use of the data.

The mystery of dark matter is one of the great unsolved questions of modern physics. One possible solution is the existence of massive particles that do not interact electromagnetically and thus elude most detection methods. The CRESST experiment, which is being conducted at the Gran Sasso underground laboratory in Italy, is searching for these particles using cryogenic detectors and quantum sensors. Due to the low interaction of dark matter with the detector, background processes from rare radioactive decays can mimic signal events and thus influence the result. It is therefore important to estimate the number of background events as accurately as possible. As part of the project, several methods were developed using Geant4 simulation software to estimate background processes due to radioactive decays for the CRESST experiment. Two methods were used to estimate the contributions from radioactive decays. The first method used information from radioactive decay chains, which allows measurements of alpha decays at higher energies to be linked to beta decays in the signal region. In the second method, the simulated decay spectra of various possible radioactive decays were fitted to the entire measured decay spectrum. The information from the decay chains was used as input parameters. In addition to the active cryogenic detectors, the experimental setup in which they are operated was also simulated and possible external background contributions were estimated. A database was created for the results of different detector materials and geometries. In addition to the direct measurements, information from external precision measurements of the radioactivity of the passive detector material was also collected and used for the simulation. The results were compiled in a database. The studies revealed that the nature of the crystal surface influences the contribution of radioactive background processes. Various detector surfaces were simulated and the influence on the measurement was quantified. The search for dark matter with CRESST did not find any evidence of its existence. In order to set a limit on the sensitivity of the interaction rate and mass of hypothetical dark matter particles, an adjustment was made to an astrophysical model, taking into account the estimation of radioactive background processes.

Research institution(s)
  • Österreichische Akademie der Wissenschaften - 100%
International project participants
  • Federica Petricca, Max Planck-Institut München - Germany
  • Stefan Schönert, Technische Universität München - Germany

Research Output

  • 20 Citations
  • 24 Publications
  • 9 Artistic Creations
  • 3 Datasets & models
  • 1 Software
  • 11 Disseminations
  • 1 Fundings
Publications
  • 2023
    Title Secular equilibrium assessment in a CaWO4 target crystal from the dark matter experiment CRESST using Bayesian likelihood normalisation.
    DOI 10.1016/j.apradiso.2023.110670
    Type Journal Article
    Author Angloher G
    Journal Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
    Pages 110670
  • 2023
    Title Observation of a low energy nuclear recoil peak in the neutron calibration data of the CRESST-III Experiment
    DOI 10.48550/arxiv.2303.15315
    Type Other
    Author Angloher G
    Link Publication
  • 2023
    Title High-Dimensional Bayesian Likelihood Normalisation for CRESST's Background Model
    DOI 10.48550/arxiv.2307.12991
    Type Other
    Author Angloher G
    Link Publication
  • 2024
    Title Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.
    DOI 10.1007/s41781-024-00119-y
    Type Journal Article
    Author Angloher G
    Journal Computing and software for big science
    Pages 10
  • 2023
    Title Optimal operation of cryogenic calorimeters through deep reinforcement learning
    DOI 10.48550/arxiv.2311.15147
    Type Other
    Author Angloher G
    Link Publication
  • 2023
    Title Results on sub-GeV dark matter from a 10eV threshold CRESST-III silicon detector
    DOI 10.1103/physrevd.107.122003
    Type Journal Article
    Author Angloher G
    Journal Physical Review D
  • 2023
    Title Observation of a low energy nuclear recoil peak in the neutron calibration data of the CRESST-III experiment
    DOI 10.1103/physrevd.108.022005
    Type Journal Article
    Author Angloher G
    Journal Physical Review D
  • 2022
    Title Testing spin-dependent dark matter interactions with lithium aluminate targets in CRESST-III
    DOI 10.48550/arxiv.2207.07640
    Type Preprint
    Author Angloher G
  • 2022
    Title Latest observations on the low energy excess in CRESST-III
    DOI 10.48550/arxiv.2207.09375
    Type Preprint
    Author Angloher G
  • 2022
    Title Secular Equilibrium Assessment in a $\mathrm{CaWO}_4$ Target Crystal from the Dark Matter Experiment CRESST using Bayesian Likelihood Normalisation
    DOI 10.48550/arxiv.2209.00461
    Type Preprint
    Author Angloher G
  • 2024
    Title Background modeling and simulation of the calibration source for the CRESST dark matter search experiment
    DOI 10.22323/1.441.0071
    Type Conference Proceeding Abstract
    Author Banik S
    Pages 071
  • 2024
    Title Geant4 simulations of the influence of contamination and roughness of the detector surface on background spectra in CRESST
    DOI 10.22323/1.441.0092
    Type Conference Proceeding Abstract
    Author Angloher G
    Pages 092
  • 2024
    Title First observation of single photons in a CRESST detector and new dark matter exclusion limits
    DOI 10.48550/arxiv.2405.06527
    Type Preprint
    Author Angloher G
    Link Publication
  • 2024
    Title First observation of single photons in a CRESST detector and new dark matter exclusion limits
    DOI 10.3929/ethz-b-000704261
    Type Other
    Author Angloher
    Link Publication
  • 2024
    Title DoubleTES detectors to investigate the CRESST low energy background: results from above-ground prototypes
    DOI 10.3929/ethz-b-000699637
    Type Other
    Author Angloher
    Link Publication
  • 2024
    Title Rare event searches with cryogenic detectors.
    DOI 10.1098/rsta.2023.0091
    Type Journal Article
    Author Mokina V
    Journal Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
    Pages 20230091
    Link Publication
  • 2022
    Title EXCESS workshop: Descriptions of rising low-energy spectra
    DOI 10.48550/arxiv.2202.05097
    Type Other
    Author Adari P
    Link Publication
  • 2022
    Title EXCESS workshop: Descriptions of rising low-energy spectra
    DOI 10.21468/scipostphysproc.9.001
    Type Journal Article
    Author Adari P
    Journal SciPost Physics Proceedings
  • 2022
    Title EXCESS workshop: Descriptions of rising low-energy spectra
    DOI 10.5167/uzh-225638
    Type Other
    Author Adari
    Link Publication
  • 2022
    Title Results on sub-GeV Dark Matter from a 10 eV Threshold CRESST-III Silicon Detector
    DOI 10.48550/arxiv.2212.12513
    Type Preprint
    Author Cresst Collaboration
  • 2022
    Title Towards an automated data cleaning with deep learning in CRESST
    DOI 10.48550/arxiv.2211.00564
    Type Preprint
    Author Angloher G
  • 2022
    Title Testing spin-dependent dark matter interactions with lithium aluminate targets in CRESST-III
    DOI 10.1103/physrevd.106.092008
    Type Journal Article
    Author Angloher G
    Journal Physical Review D
    Pages 092008
    Link Publication
  • 2023
    Title Towards an automated data cleaning with deep learning in CRESST.
    DOI 10.1140/epjp/s13360-023-03674-2
    Type Journal Article
    Author Angloher G
    Journal European physical journal plus
    Pages 100
  • 2023
    Title Latest observations on the low energy excess in CRESST-III
    DOI 10.21468/scipostphysproc.12.013
    Type Journal Article
    Author Angloher G
    Journal SciPost Physics Proceedings
Artistic Creations
  • 2025 Link
    Title Lecture for Ukrainian Students
    Type Artefact (including digital)
    Link Link
  • 2025 Link
    Title Dark Matter Day 2025
    Type Artefact (including digital)
    Link Link
  • 2024 Link
    Title Lecture for Ukrainian Students
    Type Artefact (including digital)
    Link Link
  • 2024 Link
    Title Lange Nacht der Forschung 2024
    Type Artefact (including digital)
    Link Link
  • 2024 Link
    Title Dark Matter Day 2024
    Type Artefact (including digital)
    Link Link
  • 2023 Link
    Title An article in a journal "Wie Forscher im All und tief im Berg Dunkle Materie suchen"
    Type Artefact (including digital)
    Link Link
  • 2023 Link
    Title Dark Matter Day 2023
    Type Artefact (including digital)
    Link Link
  • 2023 Link
    Title Pint of Science 2023
    Type Artefact (including digital)
    Link Link
  • 2022 Link
    Title Dark Matter Day 2022
    Type Artefact (including digital)
    Link Link
Datasets & models
  • 2019 Link
    Title Description of CRESST-III Data
    DOI 10.48550/arxiv.1905.07335
    Type Database/Collection of data
    Public Access
    Link Link
  • 2017 Link
    Title Description of CRESST-II data
    DOI 10.48550/arxiv.1701.08157
    Type Database/Collection of data
    Public Access
    Link Link
  • 2025 Link
    Title CRESST-III lithium aluminate data
    Type Database/Collection of data
    Public Access
    Link Link
Software
  • 2025 Link
    Title SCoRe4 library
    DOI 10.5281/zenodo.17648567
    Link Link
Disseminations
  • 2023 Link
    Title Pint of Science 2024
    Type A talk or presentation
    Link Link
  • 2023 Link
    Title Participation in HEPHY Outreach Program
    Type A talk or presentation
    Link Link
  • 2025 Link
    Title Lecture for Ukrainian Studentes
    Type A talk or presentation
    Link Link
  • 2025 Link
    Title Dark Matter Day 2025
    Type A talk or presentation
    Link Link
  • 2024 Link
    Title Dark Matter Day 2024
    Type A talk or presentation
    Link Link
  • 2017 Link
    Title Participation in HEPHY Outreach Programme
    Type A talk or presentation
    Link Link
  • 2024 Link
    Title Lecture for Ukrainian Students
    Type A talk or presentation
    Link Link
  • 2023 Link
    Title Dark Matter Day 2023
    Type A talk or presentation
    Link Link
  • 2024 Link
    Title Lange Nacht der Forschung 2024
    Type A talk or presentation
    Link Link
  • 2023 Link
    Title An article in a journal "Wie Forscher im All und tief im Berg Dunkle Materie suchen
    Type A magazine, newsletter or online publication
    Link Link
  • 2022 Link
    Title Dark Matter Day 2022
    Type A talk or presentation
    Link Link
Fundings
  • 2021
    Title ELOISE: Reliable background simulation at sub-keV energies
    Type Research grant (including intramural programme)
    Start of Funding 2021
    Funder Austrian Science Fund (FWF)

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