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Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC
A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, Mark Adamowski, D. L. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Zahid Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. K. Allison, S. Alonso Monsalve, M. Alrashed, C. Alt, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, Н. Анфимов, Artur M. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, Stefan Antusch, Alfredo Aranda, L. Arellano, L. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Lara, M. Ayala-Torres, F. Azfar, H.O. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, Pierre Baldi, B. Baller, Bindu A. Bambah, F. Barão, Gabriela Barenboim, Pablo Barham Alzás, Gareth J. Barker, Wayne Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, E. Batista das Chagas, James Battat, Francesca De Battisti, F. Bay, M. C. Q. Bazetto, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, C. Beigbeder, L. Bellantoni, G. Bellettini, Vincenzo Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. J. Bevan, Y. Bezawada, T. J. C. Bezerra, Ashutosh Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. M. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. d. M. Blaszczyk, G. Blazey, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, M. Bongrand, Cesar Bonilla, F. Bonini, Andrew Booth, Fatma Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, C. Bourgeois, D. Boyden, J. Braciník, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, D. Breton, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. J. Brooke, A. Bross, G. Brunetti, M. B. Brunetti, N. J. Buchanan, H. S. Budd, Ilya Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Cãlin, S. Calvez, E. Calvo, A. Caminata, M. Campanelli, D. Caratelli, D. Carber, Juan Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, Timothy J. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, Gabriele Cavallaro, F. Cavanna, S. Centro, G. B. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, Etienne Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. S. S. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C.Y. Chi, S. Childress, R. Chirco, A. Chiriacescu, G. Chisnall, K. Cho, S. Choate, D. Chokheli, P.S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, М. Chung, E. Church, V. Cicero, Peter Clarke, G. Cline, T. E. Coan, A.G. Cocco, J. A. B. Coelho, N. Colton, E. Conley, R. Conley, J. M. Conrad, M. R. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, Ryan Cross, A. Cudd, C. Cuesta, Yanou Cui, D. Cussans, Olivia Dalager, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. P. Decowski, André de Gouvêa, P. C. de Holanda, I. L. De Icaza Astiz, A. Deisting, S. J. de Jong, A. Delbart, D. Delépine, M. Delgado, A. Dell’Acqua, Nicola Delmonte, P. De Lurgio, D. M. DeMuth, C. Densham, G. Deptuch, A. De Roeck, Valentina De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, F. Díaz, J. S. Díaz, S. Di Domizio, L. Di Giulio, P. F. Ding, L. Di Noto, G. Dirkx, C. Distefano, Z. Djurcic, M. Diwan, Z. Djurčić, D. Doering, S. Dolan, F. Dolek, M. J. Dolinski, L. Domine, Yann Donon, D. Douglas, Delphine Douillet, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, Hongyue Duyang, O. Dvornikov, D. A. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, Kevin Fahey, A. Falcone, C. Farnese, Yasaman Farzan, Dmitry Fedoseev, J. Félix, Y. Feng, E. Fernández-Martínez, M. Fernandez Morales, F. Ferraro, L. Fields, P. Filip, F. Filthaut, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, F. Fuentes Robayo, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. M. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, Raj Gandhi, R. P. Gandrajula, F. Gao, S. Gao, D. García-Gámez, Miguel García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. 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Mora Lepin, Shirley Weishi Li, Y. Li, H. Liao, C. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, Jun Liu, Yisu Liu, S. Lockwitz, T. Loew, M. Lokajı́ček, I. Lomidze, K. Long, T. Lord, J. M. LoSecco, W. C. Louis, X.-G. Lu, X.-G. Lu, B. Lunday, X. Luo, E. Luppi, T. Lux, V.P. Luzio, J. Maalmi, D. B. MacFarlane, A.A. Machado, P. Machado, C. T. Macias, J.R. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, Arkady Major, J.A. Maloney, G. Mandrioli, R. C. Mandujano, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, Venkata Narasimha Manyam, L. Manzanillas, M. Marchan, A. Marchionni, W. Marciano, Danny Marfatia, C. Mariani, J. Maricic, Rodolphe Marie, F. Marinho, A. D. Marino, D. Marsden, Marvin L. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martín-Albo, N. Lorenzo Martinez, D. A. Martínez Caicedo, Pablo Martínez-Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. 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Bibliographic record
VenueThe European Physical Journal C · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsUniversity of TorontoYork University
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsFermilabLaboratori Nazionali del Gran SassoInstitut National de Physique Nucléaire et de Physique des ParticulesInstituto Nazionale di Fisica NucleareRussian Academy of SciencesFundação para a Ciência e a TecnologiaNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilHorizon 2020 Framework ProgrammeInstitut de Física d'Altes EnergiesUK Research and InnovationIdaho State UniversityIstituto Nazionale di Fisica NucleareMinisterio de Ciencia e InnovaciónFundação de Amparo à Pesquisa do Estado de GoiásIndian Institute of Technology GuwahatiJunta de AndalucíaUniversidad de GuanajuatoUniversidade de LisboaFundação Amazônia Paraense de Amparo à PesquisaUniversità degli Studi dell'InsubriaIowa State UniversityUniversidad de GranadaUniversità degli Studi di GenovaGran Sasso Science InstituteTürkiye Bilimsel ve Teknolojik Araştırma KurumuNational Research FoundationCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaMinisterstvo Školství, Mládeže a TělovýchovyUniversitat de ValènciaXunta de GaliciaU.S. Department of EnergyFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoCanada Foundation for InnovationEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloIstituto Nazionale di Fisica Nucleare Sezione di PadovaHarvard UniversityInstituto Superior TécnicoNederlandse Organisatie voor Wetenschappelijk OnderzoekComunidad de MadridCERNHarish-Chandra Research InstituteNational Energy Research Scientific Computing CenterRoyal Society“la Caixa” FoundationOffice of ScienceUniversity of HyderabadNational Science FoundationEuropean Regional Development FundCentre National de la Recherche ScientifiqueImperial College LondonInstitute for Research in Fundamental Sciences
KeywordsPhysicsScintillationNeutrinoMuonPhotomultiplierArgonTime projection chamberNuclear physicsAnalytical Chemistry (journal)DetectorOpticsAtomic physicsChemistry
Abstract
Abstract DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $$\times $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>×</mml:mo> </mml:math> 6 $$\times $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>×</mml:mo> </mml:math> 6 m $$^3$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mn>3</mml:mn> </mml:msup> </mml:math> liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.772
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.020
GPT teacher head0.304
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations19
Published2022
Admission routes2
Has abstractyes