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  1. Article ; Online: Secular equilibrium assessment in a CaWO

    Angloher, G / Banik, S / Benato, G / Bento, A / Bertolini, A / Breier, R / Bucci, C / Burkhart, J / Canonica, L / D'Addabbo, A / Di Lorenzo, S / Einfalt, L / Erb, A / Feilitzsch, F V / Ferreiro Iachellini, N / Fichtinger, S / Fuchs, D / Fuss, A / Garai, A /
    Ghete, V M / Gorla, P / Gupta, S / Hauff, D / Ješkovský, M / Jochum, J / Kaznacheeva, M / Kinast, A / Kluck, H / Kraus, H / Langenkämper, A / Mancuso, M / Marini, L / Mokina, V / Nilima, A / Olmi, M / Ortmann, T / Pagliarone, C / Pattavina, L / Petricca, F / Potzel, W / Povinec, P / Pröbst, F / Pucci, F / Reindl, F / Rothe, J / Schäffner, K / Schieck, J / Schmiedmayer, D / Schönert, S / Schwertner, C / Stahlberg, M / Stodolsky, L / Strandhagen, C / Strauss, R / Usherov, I / Wagner, F / Willers, M / Zema, V / Ferella, F / Laubenstein, M / Nisi, S

    Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine

    2023  Volume 194, Page(s) 110670

    Abstract: CRESST is a leading direct detection sub- ... ...

    Abstract CRESST is a leading direct detection sub-GeVc
    Language English
    Publishing date 2023-01-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 1142596-9
    ISSN 1872-9800 ; 0883-2889 ; 0969-8043
    ISSN (online) 1872-9800
    ISSN 0883-2889 ; 0969-8043
    DOI 10.1016/j.apradiso.2023.110670
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Observation of a Nuclear Recoil Peak at the 100 eV Scale Induced by Neutron Capture.

    Abele, H / Angloher, G / Bento, A / Canonica, L / Cappella, F / Cardani, L / Casali, N / Cerulli, R / Chalil, A / Chebboubi, A / Colantoni, I / Crocombette, J-P / Cruciani, A / Del Castello, G / Del Gallo Roccagiovine, M / Desforge, D / Doblhammer, A / Dumonteil, E / Dorer, S /
    Erhart, A / Fuss, A / Friedl, M / Garai, A / Ghete, V M / Giuliani, A / Goupy, C / Gunsing, F / Hauff, D / Jeanneau, F / Jericha, E / Kaznacheeva, M / Kinast, A / Kluck, H / Langenkämper, A / Lasserre, T / Letourneau, A / Lhuillier, D / Litaize, O / Mancuso, M / de Marcillac, P / Marnieros, S / Materna, T / Mauri, B / Mazzolari, A / Mazzucato, E / Neyrial, H / Nones, C / Oberauer, L / Ortmann, T / Ouzriat, A / Pattavina, L / Peters, L / Petricca, F / Poda, D V / Potzel, W / Pröbst, F / Reindl, F / Rogly, R / Romagnoni, M / Rothe, J / Schermer, N / Schieck, J / Schönert, S / Schwertner, C / Scola, L / Serot, O / Soum-Sidikov, G / Stodolsky, L / Strauss, R / Tamisari, M / Thulliez, L / Tomei, C / Vignati, M / Vivier, M / Wagner, V / Wex, A

    Physical review letters

    2023  Volume 130, Issue 21, Page(s) 211802

    Abstract: Coherent elastic neutrino-nucleus scattering and low-mass dark matter detectors rely crucially on the understanding of their response to nuclear recoils. We report the first observation of a nuclear recoil peak at around 112 eV induced by neutron capture. ...

    Abstract Coherent elastic neutrino-nucleus scattering and low-mass dark matter detectors rely crucially on the understanding of their response to nuclear recoils. We report the first observation of a nuclear recoil peak at around 112 eV induced by neutron capture. The measurement was performed with a CaWO_{4} cryogenic detector from the NUCLEUS experiment exposed to a ^{252}Cf source placed in a compact moderator. We identify the expected peak structure from the single-γ de-excitation of ^{183}W with 3σ and its origin by neutron capture with 6σ significance. This result demonstrates a new method for precise, in situ, and nonintrusive calibration of low-threshold experiments.
    MeSH term(s) Cell Nucleus ; Neutrons ; Californium ; Monte Carlo Method
    Chemical Substances Californium (975X05H15A)
    Language English
    Publishing date 2023-05-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 208853-8
    ISSN 1079-7114 ; 0031-9007
    ISSN (online) 1079-7114
    ISSN 0031-9007
    DOI 10.1103/PhysRevLett.130.211802
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Towards an automated data cleaning with deep learning in CRESST.

    Angloher, G / Banik, S / Bartolot, D / Benato, G / Bento, A / Bertolini, A / Breier, R / Bucci, C / Burkhart, J / Canonica, L / D'Addabbo, A / Di Lorenzo, S / Einfalt, L / Erb, A / Feilitzsch, F V / Iachellini, N Ferreiro / Fichtinger, S / Fuchs, D / Fuss, A /
    Garai, A / Ghete, V M / Gerster, S / Gorla, P / Guillaumon, P V / Gupta, S / Hauff, D / Ješkovský, M / Jochum, J / Kaznacheeva, M / Kinast, A / Kluck, H / Kraus, H / Lackner, M / Langenkämper, A / Mancuso, M / Marini, L / Meyer, L / Mokina, V / Nilima, A / Olmi, M / Ortmann, T / Pagliarone, C / Pattavina, L / Petricca, F / Potzel, W / Povinec, P / Pröbst, F / Pucci, F / Reindl, F / Rizvanovic, D / Rothe, J / Schäffner, K / Schieck, J / Schmiedmayer, D / Schönert, S / Schwertner, C / Stahlberg, M / Stodolsky, L / Strandhagen, C / Strauss, R / Usherov, I / Wagner, F / Willers, M / Zema, V / Waltenberger, W

    European physical journal plus

    2023  Volume 138, Issue 1, Page(s) 100

    Abstract: The CRESST experiment employs cryogenic calorimeters for the sensitive measurement of nuclear recoils induced by dark matter particles. The recorded signals need to undergo a careful cleaning process to avoid wrongly reconstructed recoil energies caused ... ...

    Abstract The CRESST experiment employs cryogenic calorimeters for the sensitive measurement of nuclear recoils induced by dark matter particles. The recorded signals need to undergo a careful cleaning process to avoid wrongly reconstructed recoil energies caused by pile-up and read-out artefacts. We frame this process as a time series classification task and propose to automate it with neural networks. With a data set of over one million labeled records from 68 detectors, recorded between 2013 and 2019 by CRESST, we test the capability of four commonly used neural network architectures to learn the data cleaning task. Our best performing model achieves a balanced accuracy of 0.932 on our test set. We show on an exemplary detector that about half of the wrongly predicted events are in fact wrongly labeled events, and a large share of the remaining ones have a context-dependent ground truth. We furthermore evaluate the recall and selectivity of our classifiers with simulated data. The results confirm that the trained classifiers are well suited for the data cleaning task.
    Language English
    Publishing date 2023-01-30
    Publishing country Germany
    Document type Journal Article
    ISSN 2190-5444
    ISSN (online) 2190-5444
    DOI 10.1140/epjp/s13360-023-03674-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Geant4-based electromagnetic background model for the CRESST dark matter experiment.

    Abdelhameed, A H / Angloher, G / Bauer, P / Bento, A / Bertoldo, E / Breier, R / Bucci, C / Canonica, L / D'Addabbo, A / Lorenzo, S Di / Erb, A / Feilitzsch, F V / Iachellini, N Ferreiro / Fichtinger, S / Fuss, A / Gorla, P / Hauff, D / Jes Kovský, M / Jochum, J /
    Kaizer, J / Kinast, A / Kluck, H / Kraus, H / Langenkämper, A / Mancuso, M / Mokina, V / Mondragón, E / Olmi, M / Ortmann, T / Pagliarone, C / Palus Ová, V / Pattavina, L / Petricca, F / Potzel, W / Povinec, P / Pröbst, F / Reindl, F / Rothe, J / Schäffner, K / Schieck, J / Schipperges, V / Schmiedmayer, D / Schönert, S / Schwertner, C / Stahlberg, M / Stodolsky, L / Strandhagen, C / Strauss, R / Türkoğlu, C / Usherov, I / Willers, M / Zema, V / Zeman, J

    The European physical journal. C, Particles and fields

    2019  Volume 79, Issue 10, Page(s) 881

    Abstract: The CRESST (Cryogenic Rare Event Search with Superconducting Thermometers) dark matter search experiment aims for the detection of dark matter particles via elastic scattering off nuclei ... ...

    Abstract The CRESST (Cryogenic Rare Event Search with Superconducting Thermometers) dark matter search experiment aims for the detection of dark matter particles via elastic scattering off nuclei in
    Language English
    Publishing date 2019-10-26
    Publishing country France
    Document type Journal Article
    ZDB-ID 1459069-4
    ISSN 1434-6052 ; 1434-6044
    ISSN (online) 1434-6052
    ISSN 1434-6044
    DOI 10.1140/epjc/s10052-019-7385-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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