Eur. Phys. J. C (2022) 82:618 https://doi.org/10.1140/epjc/s10052-022-10549-w Regular Article - Experimental Physics Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC DUNE Collaboration A. Abed Abud36,127 , B. Abi154 , R. Acciarri67 , M. A. Acero11 , M. R. Adames190 , G. Adamov72 , M. Adamowski67 , D. Adams21 , M. Adinolfi20 , A. Aduszkiewicz81 , J. Aguilar125 , Z. Ahmad201 , J. Ahmed204 , B. Aimard53 , B. Ali-Mohammadzadeh32,93 , T. Alion188 , K. Allison44 , S. Alonso Monsalve36,60 , M. AlRashed117 , C. Alt60 , A. Alton12 , R. Alvarez40 , P. Amedo86 , J. Anderson7 , C. Andreopoulos127,175 , M. Andreotti68,94 , M. Andrews67 , F. Andrianala5 , S. Andringa126 , N. Anfimov115 , A. Ankowski180 , M. Antoniassi190 , M. Antonova85 , A. Antoshkin115 , S. Antusch14 , A. Aranda-Fernandez43 , L. Arellano133 , L. O. Arnold46 , M. A. Arroyave59 , J. Asaadi193 , L. Asquith188 , A. Aurisano41 , V. Aushev123 , D. Autiero108 , V. Ayala Lara103 , M. Ayala-Torres42 , F. Azfar154 , A. Back91 , H. Back155 , J. J. Back204 , C. Backhouse199 , I. Bagaturia72 , L. Bagby67 , N. Balashov115 , S. Balasubramanian67 , P. Baldi25 , B. Baller67 , B. Bambah82 , F. Barao110,126 , G. Barenboim85 , P. Barham Alzas36 , G. Barker204 , W. Barkhouse147 , C. Barnes137 , G. Barr154 , J. Barranco Monarca77 , A. Barros190 , N. Barros61,126 , J. L. Barrow134 , A. Basharina-Freshville199 , A. Bashyal7 , V. Basque133 , C. Batchelor58 , E. Batista das Chagas31 , J. B. R. Battat205 , F. Battisti154 , F. Bay4 , M. C. Q. Bazetto31 , J. L. L. Bazo Alba167 , J. F. Beacom152 , E. Bechetoille108 , B. Behera45 , C. Beigbeder158 , L. Bellantoni67 , G. Bellettini165 , V. Bellini32,93 , O. Beltramello36 , N. Benekos36 , C. Benitez Montiel9 , F. Bento Neves126 , J. Berger45 , S. Berkman67 , P. Bernardini96,176 , R. M. Berner15 , A. Bersani95 , S. Bertolucci18,92 , M. Betancourt67 , A. Betancur Rodríguez59 , A. Bevan170 , Y. Bezawada24 , T. J. C. Bezerra188 , A. Bhardwaj129 , V. Bhatnagar157 , M. Bhattacharjee89 , D. Bhattarai143 , S. Bhuller20 , B. Bhuyan89 , S. Biagi102 , J. Bian25 , M. Biassoni97 , K. Biery67 , B. Bilki16,106 , M. Bishai21 , A. Bitadze133 , A. Blake124 , F. Blaszczyk67 , G. C. Blazey148 , E. Blucher38 , J. Boissevain128 , S. Bolognesi35 , T. Bolton117 , L. Bomben97,105 , M. Bonesini97,139 , M. Bongrand158 , C. Bonilla-Diaz33 , F. Bonini21 , A. Booth170 , F. Boran16 , S. Bordoni36 , A. Borkum188 , N. Bostan150 , P. Bour50 , C. Bourgeois158 , D. Boyden148 , J. Bracinik17 , D. Braga67 , D. Brailsford124 , A. Branca97 , A. Brandt193 , J. Bremer36 , D. Breton158 , C. Brew175 , S. J. Brice67 , C. Brizzolari97,139 , C. Bromberg138 , J. Brooke20 , A. Bross67 , G. Brunetti97,139 , M. Brunetti204 , N. Buchanan45 , H. Budd172 , I. Butorov115 , I. Cagnoli18,92 , T. Cai211 , D. Caiulo108 , R. Calabrese68,94 , P. Calafiura125 , J. Calcutt153 , M. Calin22 , S. Calvez45 , E. Calvo40 , A. Caminata95 , M. Campanelli199 , D. Caratelli67 , D. Carber45 , J. C. Carceller199 , G. Carini21 , B. Carlus108 , M. F. Carneiro21 , P. Carniti97 , I. Caro Terrazas45 , H. Carranza193 , T. Carroll208 , J. F. Castaño Forero6 , A. Castillo178 , C. Castromonte103 , E. Catano-Mur207 , C. Cattadori97 , F. Cavalier158 , G. Cavallaro97 , F. Cavanna67 , S. Centro100,156 , G. Cerati67 , A. Cervelli92 , A. Cervera Villanueva85 , M. Chalifour36 , A. Chappell204 , E. Chardonnet159 , N. Charitonidis36 , A. Chatterjee166 , S. Chattopadhyay201 , M. S. S. Chavarry Neyra103 , H. Chen21 , M. Chen25 , Y. Chen15 , Z. Chen185 , Z. Chen-Wishart173 , Y. Cheon198 , D. Cherdack81 , C. Chi46 , S. Childress67 , R. Chirco87 , A. Chiriacescu22 , G. Chisnall188 , K. Cho120 , S. Choate148 , D. Chokheli72 , P. S. Chong162 , A. Christensen45 , D. Christian67 , G. Christodoulou36 , A. Chukanov115 , M. Chung198 , E. Church155 , V. Cicero18,92 , P. Clarke58 , G. Cline125 , T. E. Coan184 , A. G. Cocco99 , J. A. B. Coelho159 , N. Colton45 , E. Conley56 , R. Conley180 , J. Conrad134 , M. Convery180 , S. Copello95 , P. Cova98,160 , L. Cremaldi143 , L. Cremonesi170 , J. I. Crespo-Anadón40 , M. Crisler67 , E. Cristaldo9 , J. Crnkovic143 , R. Cross124 , A. Cudd44 , C. Cuesta40,a , Y. Cui27 , D. Cussans20 , O. Dalager25 , H. da Motta34 , L. Da Silva Peres66 , C. David67,211 , Q. David108 , G. S. Davies143 , S. Davini95 , J. Dawson159 , K. De193 , S. De2 , P. Debbins106 , I. De Bonis53 , M. P. Decowski3,146 , A. De Gouvêa149 , P. C. De Holanda31 , I. L. De Icaza Astiz188 , A. Deisting173 , P. De Jong3,146 , A. Delbart35 , D. Delepine77 , M. Delgado97,139 , A. Dell’Acqua36 , N. Delmonte98,160 , P. De Lurgio7 , J. R. T. de Mello Neto66 , D. M. DeMuth200 , S. Dennis30 , C. Densham175 , G. W. Deptuch21 , A. De Roeck36 , V. De Romeri85 , G. De Souza31 , R. Devi112 , R. Dharmapalan80 , M. Dias197 , F. Diaz167 , J. S. Díaz91 , S. Di Domizio71,95 , L. Di Giulio36 , P. Ding67 , L. Di Noto71,95 , G. Dirkx88 , C. Distefano102 , R. Diurba142 , M. Diwan21 , Z. Djurcic7 , D. Doering180 , S. Dolan36 , F. Dolek16 , M. Dolinski55 , L. Domine180 , Y. Donon36 , D. Douglas138 , D. Douillet158 , A. Dragone180 , G. Drake67 , F. Drielsma180 , L. Duarte197 , D. Duchesneau53 , K. Duffy67 , P. Dunne88 , B. Dutta191 , H. Duyang181 , O. Dvornikov80 , 0123456789().: V,-vol 123 618 Page 2 of 29 Eur. Phys. J. C (2022) 82:618 D. Dwyer125 , A. Dyshkant148 , M. Eads148 , A. Earle188 , D. Edmunds138 , J. Eisch67 , L. Emberger133,135 , S. Emery35 , P. Englezos174 , A. Ereditato209 , T. Erjavec24 , C. Escobar67 , G. Eurin35 , J. J. Evans133 , E. Ewart91 , A. C. Ezeribe179 , K. Fahey67 , A. Falcone97,139 , M. Fani’128 , C. Farnese100 , Y. Farzan109 , D. Fedoseev115 , J. Felix77 , Y. Feng107 , E. Fernandez-Martinez131 , P. Fernandez Menendez85 , M. Fernandez Morales86 , F. Ferraro71,95 , L. Fields150 , P. Filip49 , F. Filthaut146,171 , M. Fiorini68,94 , V. Fischer107 , R. S. Fitzpatrick137 , W. Flanagan52 , B. Fleming209 , R. Flight172 , S. Fogarty45 , W. Foreman87 , J. Fowler56 , W. Fox91 , J. Franc50 , K. Francis148 , D. Franco209 , J. Freeman67 , J. Freestone133 , J. Fried21 , A. Friedland180 , F. Fuentes Robayo20 , S. Fuess67 , I. K. Furic69 , K. Furman170 , A. P. Furmanski142 , A. Gabrielli92 , A. Gago167 , H. Gallagher196 , A. Gallas158 , A. Gallego-Ros40 , N. Gallice98,140 , V. Galymov108 , E. Gamberini36 , T. Gamble179 , F. Ganacim190 , R. Gandhi78 , R. Gandrajula138 , F. Gao166 , S. Gao21 , D. Garcia-Gamez73 , M. Á. García-Peris85 , S. Gardiner67 , D. Gastler19 , J. Gauvreau151 , G. Ge46 , N. Geffroy53 , B. Gelli31 , A. Gendotti60 , S. Gent183 , Z. Ghorbani-Moghaddam95 , P. Giammaria31 , T. Giammaria68,94 , N. Giangiacomi195 , D. Gibin100,156 , I. Gil-Botella40 , S. Gilligan153 , C. Girerd108 , A. K. Giri90 , D. Gnani125 , O. Gogota123 , M. Gold144 , S. Gollapinni128 , K. Gollwitzer67 , R. A. Gomes63 , L. V. Gomez Bermeo178 , L. S. Gomez Fajardo178 , F. Gonnella17 , D. Gonzalez-Diaz86 , M. Gonzalez-Lopez131 , M. C. Goodman7 , O. Goodwin133 , S. Goswami164 , C. Gotti97 , E. Goudzovski17 , C. Grace125 , R. Gran141 , E. Granados77 , P. Granger35 , A. Grant54 , C. Grant19 , D. Gratieri70 , P. Green133 , L. Greenler208 , J. Greer20 , J. Grenard36 , W. C. Griffith188 , M. Groh45 , J. Grudzinski7 , K. Grzelak203 , W. Gu21 , E. Guardincerri128 , V. Guarino7 , M. Guarise68,94 , R. Guenette79 , E. Guerard158 , M. Guerzoni92 , D. Guffanti98 , A. Guglielmi100 , B. Guo181 , A. Gupta180 , V. Gupta146 , K. K. Guthikonda121 , R. Gutierrez6 , P. Guzowski133 , M. M. Guzzo31 , S. Gwon39 , C. Ha39 , K. Haaf67 , A. Habig141 , H. Hadavand193 , R. Haenni15 , A. Hahn67 , J. Haiston182 , P. Hamacher-Baumann154 , T. Hamernik67 , P. Hamilton88 , J. Han166 , D. A. Harris67,211 , J. Hartnell188 , T. Hartnett175 , J. Harton45 , T. Hasegawa119 , C. Hasnip154 , R. Hatcher67 , K. W. Hatfield25 , A. Hatzikoutelis177 , C. Hayes91 , K. Hayrapetyan170 , J. Hays170 , E. Hazen19 , M. He81 , A. Heavey67 , K. M. Heeger209 , J. Heise187 , S. Henry172 , M. A. Hernandez Morquecho87 , K. Herner67 , J. Hewes41 , C. Hilgenberg142 , T. Hill83 , S. J. Hillier17 , A. Himmel67 , E. Hinkle38 , L. R. Hirsch190 , J. Ho79 , J. Hoff67 , A. Holin175 , E. Hoppe155 , G. A. Horton-Smith117 , M. Hostert142 , A. Hourlier134 , B. Howard67 , R. Howell172 , J. Hoyos136 , I. Hristova175 , M. S. Hronek67 , J. Huang24 , Z. Hulcher180 , G. Iles88 , N. Ilic195 , A. M. Iliescu92 , R. Illingworth67 , G. Ingratta18,92 , A. Ioannisian210 , B. Irwin142 , L. Isenhower1 , R. Itay180 , C. M. Jackson155 , V. Jain2 , E. James67 , W. Jang193 , B. Jargowsky25 , F. Jediny50 , D. Jena67 , Y. S. Jeong39,106 , C. Jesús-Valls84 , X. Ji21 , L. Jiang202 , S. Jiménez40 , A. Jipa22 , R. Johnson41 , W. Johnson182 , N. Johnston91 , B. Jones193 , S. Jones199 , M. Judah166 , C. K. Jung185 , T. Junk67 , Y. Jwa46 , M. Kabirnezhad154 , A. Kaboth173,175 , I. Kadenko123 , I. Kakorin115 , A. Kalitkina115 , D. Kalra46 , F. Kamiya65 , N. Kaneshige28 , D. M. Kaplan87 , G. Karagiorgi46 , G. Karaman106 , A. Karcher125 , M. Karolak35 , Y. Karyotakis53 , S. Kasai122 , S. P. Kasetti129 , L. Kashur45 , N. Kazaryan210 , E. Kearns19 , P. Keener162 , K. J. Kelly36 , E. Kemp31 , O. Kemularia72 , W. Ketchum67 , S. H. Kettell21 , M. Khabibullin104 , A. Khotjantsev104 , A. Khvedelidze72 , D. Kim191 , B. King67 , B. Kirby46 , M. Kirby67 , J. Klein162 , A. Klustova88 , T. Kobilarcik67 , K. Koehler208 , L. W. Koerner81 , D. H. Koh180 , S. Kohn23,125 , P. P. Koller15 , L. Kolupaeva115 , D. Korablev115 , M. Kordosky207 , T. Kosc76 , U. Kose36 , V. A. Kostelecký91 , K. Kothekar20 , R. Kralik188 , L. Kreczko20 , F. Krennrich107 , I. Kreslo15 , W. Kropp25 , T. Kroupova162 , S. Kubota79 , Y. Kudenko104 , V. A. Kudryavtsev179 , S. Kulagin104 , J. Kumar80 , P. Kumar179 , P. Kunze53 , N. Kurita180 , C. Kuruppu181 , V. Kus50 , T. Kutter129 , J. Kvasnicka49 , D. Kwak198 , A. Lambert125 , B. Land162 , C. E. Lane55 , K. Lang194 , T. Langford209 , M. Langstaff133 , J. Larkin21 , P. Lasorak188 , D. Last162 , A. Laundrie208 , G. Laurenti92 , A. Lawrence125 , I. Lazanu22 , R. LaZur45 , M. Lazzaroni98,140 , T. Le196 , S. Leardini86 , J. Learned80 , P. LeBrun108 , T. LeCompte180 , C. Lee67 , S. Y. Lee114 , G. Lehmann Miotto36 , R. Lehnert91 , M. A. Leigui de Oliveira65 , M. Leitner125 , L. M. Lepin133 , S. W. Li180 , Y. Li21 , H. Liao117 , C. S. Lin125 , Q. Lin180 , S. Lin129 , R. A. Lineros33 , J. Ling186 , A. Lister208 , B. R. Littlejohn87 , J. Liu25 , Y. Liu38 , S. Lockwitz67 , T. Loew125 , M. Lokajicek49 , I. Lomidze72 , K. Long88 , T. Lord204 , J. M. LoSecco150 , W. C. Louis128 , X.-G. Lu204 , K. B. Luk23,125 , B. Lunday162 , X. Luo28 , E. Luppi68,94 , T. Lux84 , V. P. Luzio65 , J. Maalmi158 , D. MacFarlane180 , A. A. Machado31 , P. Machado67 , C. T. Macias91 , J. R. Macier67 , A. Maddalena75 , A. Madera36 , P. Madigan23,125 , S. Magill7 , K. Mahn138 , A. Maio61,126 , A. Major56 , J. A. Maloney51 , G. Mandrioli92 , R. C. Mandujano25 , J. Maneira61,126 , L. Manenti199 , S. Manly172 , A. Mann196 , K. Manolopoulos175 , M. Manrique Plata91 , V. N. Manyam21 , L. Manzanillas158 , M. Marchan67 , A. Marchionni67 , W. Marciano21 , D. Marfatia80 , C. Mariani202 , J. Maricic80 , R. Marie158 , F. Marinho64 , A. D. Marino44 , D. Marsden133 , M. Marshak142 , C. Marshall172 , J. Marshall204 , J. Marteau108 , J. Martín-Albo85 , N. Martinez117 , D. A. Martinez Caicedo182 , P. Martínez Miravé85 , S. Martynenko185 , V. Mascagna97,105 , K. Mason196 , A. Mastbaum174 , F. Matichard125 , S. Matsuno80 , J. Matthews129 , C. Mauger162 , N. Mauri18,92 , K. Mavrokoridis127 , 123 Eur. Phys. J. C (2022) 82:618 Page 3 of 29 618 I. Mawby204 , R. Mazza97 , A. Mazzacane67 , E. Mazzucato35 , T. McAskill205 , E. McCluskey67 , N. McConkey133 , K. S. McFarland172 , C. McGrew185 , A. McNab133 , A. Mefodiev104 , P. Mehta113 , P. Melas10 , O. Mena85 , H. Mendez168 , P. Mendez36 , D. P. Méndez21 , A. Menegolli101,161 , G. Meng100 , M. D. Messier91 , W. Metcalf129 , T. Mettler15 , M. Mewes91 , H. Meyer206 , T. Miao67 , G. Michna183 , T. Miedema146,171 , V. Mikola199 , R. Milincic80 , G. Miller133 , W. Miller142 , J. Mills196 , O. Mineev104 , A. Minotti98,139 , O. G. Miranda42 , S. Miryala21 , C. S. Mishra67 , S. R. Mishra181 , A. Mislivec142 , M. Mitchell129 , D. Mladenov36 , I. Mocioiu163 , K. Moffat57 , N. Moggi18,92 , R. Mohanta82 , T. A. Mohayai67 , N. Mokhov67 , J. Molina9 , L. Molina Bueno85 , E. Montagna18,92 , A. Montanari92 , C. Montanari67,101,161 , D. Montanari67 , L. M. Montañno Zetina42 , S. H. Moon198 , M. Mooney45 , A. F. Moor30 , D. Moreno6 , D. Moretti97 , C. Morris81 , C. Mossey67 , M. Mote129 , E. Motuk199 , C. A. Moura65 , J. Mousseau137 , G. Mouster124 , W. Mu67 , L. Mualem29 , J. Mueller45 , M. Muether206 , S. Mufson91 , F. Muheim58 , A. Muir54 , M. Mulhearn24 , D. Munford81 , H. Muramatsu142 , S. Murphy60 , J. Musser91 , J. Nachtman106 , S. Nagu130 , M. Nalbandyan210 , R. Nandakumar175 , D. Naples166 , S. Narita111 , A. Nath89 , A. Navrer-Agasson133 , N. Nayak25 , M. Nebot-Guinot58 , K. Negishi111 , J. K. Nelson207 , J. Nesbit208 , M. Nessi36 , D. Newbold175 , M. Newcomer162 , H. Newton54 , R. Nichol199 , F. Nicolas-Arnaldos73 , A. Nikolica162 , E. Niner67 , K. Nishimura80 , A. Norman67 , A. Norrick67 , R. Northrop38 , P. Novella85 , J. A. Nowak124 , M. Oberling7 , J. Ochoa-Ricoux25 , A. Olivier172 , A. Olshevskiy115 , Y. Onel106 , Y. Onishchuk123 , J. Ott25 , L. Pagani24 , G. Palacio59 , O. Palamara67 , S. Palestini36 , J. M. Paley67 , M. Pallavicini71,95 , C. Palomares40 , W. Panduro Vazquez173 , E. Pantic24 , V. Paolone166 , V. Papadimitriou67 , R. Papaleo102 , A. Papanestis175 , S. Paramesvaran20 , S. Parke67 , E. Parozzi97,139 , Z. Parsa21 , M. Parvu22 , S. Pascoli18,57 , L. Pasqualini18,92 , J. Pasternak88 , J. Pater133 , C. Patrick199 , L. Patrizii92 , R. B. Patterson29 , S. J. Patton125 , T. Patzak159 , A. Paudel67 , B. Paulos208 , L. Paulucci65 , Z. Pavlovic67 , G. Pawloski142 , D. Payne127 , V. Pec49 , S. J. M. Peeters188 , A. Pena Perez180 , E. Pennacchio108 , A. Penzo106 , O. L. G. Peres31 , J. Perry58 , D. Pershey56 , G. Pessina97 , G. Petrillo180 , C. Petta32,93 , R. Petti181 , V. Pia18,92 , F. Piastra15 , L. Pickering138 , F. Pietropaolo36,100 , V. L. Pimentel31,47 , G. Pinaroli21 , K. Plows154 , R. Plunkett67 , R. Poling142 , F. Pompa85 , X. Pons36 , N. Poonthottathil107 , F. Poppi18,92 , S. Pordes67 , J. Porter188 , M. Potekhin21 , R. Potenza32,93 , B. V. K. S. Potukuchi112 , J. Pozimski88 , M. Pozzato18,92 , S. Prakash31 , T. Prakash125 , M. Prest97 , S. Prince79 , F. Psihas67 , D. Pugnere108 , X. Qian21 , J. L. Raaf67 , V. Radeka21 , J. Rademacker20 , B. Radics60 , A. Rafique7 , E. Raguzin21 , M. Rai204 , M. Rajaoalisoa41 , I. Rakhno67 , A. Rakotonandrasana5 , L. Rakotondravohitra5 , R. Rameika67 , M. A. Ramirez Delgado162 , B. Ramson67 , A. Rappoldi101,161 , G. Raselli101,161 , P. Ratoff124 , S. Raut185 , R. F. Razakamiandra5 , E. M. Rea142 , J. S. Real76 , B. Rebel67,208 , R. Rechenmacher67 , M. Reggiani-Guzzo133 , J. Reichenbacher182 , S. D. Reitzner67 , H. Rejeb Sfar36 , A. Renshaw81 , S. Rescia21 , F. Resnati36 , M. Ribas190 , S. Riboldi98 , C. Riccio185 , G. Riccobene102 , L. C. J. Rice166 , J. S. Ricol76 , A. Rigamonti36 , Y. Rigaut60 , E. V. Rincón59 , H. Ritchie-Yates173 , D. Rivera128 , A. Robert76 , L. Rochester180 , M. Roda127 , P. Rodrigues154 , M. J. Rodriguez Alonso36 , E. Rodriguez Bonilla6 , J. Rodriguez Rondon182 , S. Rosauro-Alcaraz131 , M. Rosenberg166 , P. Rosier158 , B. Roskovec25 , M. Rossella101,161 , M. Rossi36 , J. Rout113 , P. Roy206 , A. Rubbia60 , C. Rubbia74 , B. Russell125 , D. Ruterbories172 , A. Rybnikov115 , A. Saa-Hernandez86 , R. Saakyan199 , S. Sacerdoti159 , T. Safford138 , N. Sahu90 , K. Sakashita119 , P. Sala36,98 , N. Samios21 , O. Samoylov115 , M. C. Sanchez107 , V. Sandberg128 , D. A. Sanders143 , D. Sankey175 , S. Santana168 , M. Santos-Maldonado168 , N. Saoulidou10 , P. Sapienza102 , C. Sarasty41 , I. Sarcevic8 , G. Savage67 , V. Savinov166 , A. Scaramelli101 , A. Scarff179 , A. Scarpelli21 , T. Schefke129 , H. Schellman67,153 , S. Schifano68,94 , P. Schlabach67 , D. Schmitz38 , A. W. Schneider134 , K. Scholberg56 , A. Schukraft67 , E. Segreto31 , A. Selyunin115 , C. R. Senise Jr.197 , J. Sensenig162 , A. Sergi17 , D. Sgalaberna60 , M. H. Shaevitz46 , S. Shafaq113 , F. Shaker211 , M. Shamma27 , R. Sharankova196 , H. R. Sharma112 , R. Sharma21 , R. K. Sharma169 , T. Shaw67 , K. Shchablo108 , C. Shepherd-Themistocleous175 , A. Sheshukov115 , S. Shin114 , I. Shoemaker202 , D. Shooltz138 , R. Shrock185 , H. Siegel46 , L. Simard158 , J. Sinclair180 , G. Sinev182 , J. Singh130 , J. Singh130 , L. Singh48 , P. Singh170 , V. Singh13,48 , R. Sipos36 , F. W. Sippach46 , G. Sirri92 , A. Sitraka182 , K. Siyeon39 , K. Skarpaas180 , A. Smith30 , E. Smith91 , P. Smith91 , J. Smolik50 , M. Smy25 , E. Snider67 , P. Snopok87 , D. Snowden-Ifft151 , M. Soares Nunes189 , H. Sobel25 , M. Soderberg189 , S. Sokolov115 , C. J. Solano Salinas103 , S. Söldner-Rembold133 , S. R. Soleti125 , N. Solomey206 , V. Solovov126 , W. E. Sondheim128 , M. Sorel85 , A. Sotnikov115 , J. Soto-Oton40 , F. A. Soto Ugaldi103 , A. Sousa41 , K. Soustruznik37 , F. Spagliardi154 , M. Spanu97,139 , J. Spitz137 , N. J. C. Spooner179 , K. Spurgeon189 , M. Stancari67 , L. Stanco100,156 , C. Stanford79 , R. Stein20 , H. M. Steiner125 , A. F. Steklain Lisbôa190 , J. Stewart21 , B. Stillwell38 , J. Stock182 , F. Stocker36 , T. Stokes129 , M. Strait142 , T. Strauss67 , L. Strigari191 , A. Stuart43 , J. G. Suarez59 , J. M. Suárez Sunción103 , H. Sullivan193 , D. Summers143 , A. Surdo96 , V. Susic14 , L. Suter67 , C. M. Sutera32,93 , R. Svoboda24 , B. Szczerbinska192 , A. M. Szelc58 , H. Tanaka180 , S. Tang21 , A. Tapia136 , B. Tapia Oregui194 , A. Tapper88 , S. Tariq67 , E. Tarpara21 , N. Tata79 , E. Tatar83 , R. Tayloe91 , 123 618 Page 4 of 29 Eur. Phys. J. C (2022) 82:618 A. M. Teklu185 , P. Tennessen4,125 , M. Tenti92 , K. Terao180 , C. A. Ternes85 , F. Terranova97,139 , G. Testera95 , T. Thakore41 , A. Thea175 , J. L. Thompson179 , C. Thorn21 , S. C. Timm67 , V. Tishchenko21 , L. Tomassetti68,94 , A. Tonazzo159 , D. Torbunov142 , M. Torti97,139 , M. Tortola85 , F. Tortorici32,93 , N. Tosi92 , D. Totani28 , M. Toups67 , C. Touramanis127 , R. Travaglini92 , J. Trevor29 , S. Trilov20 , W. H. Trzaska116 , Y. Tsai25 , Y.-T. Tsai180 , Z. Tsamalaidze72 , K. V. Tsang180 , N. Tsverava72 , S. Tufanli36 , C. Tull125 , E. Tyley179 , M. Tzanov129 , L. Uboldi36 , M. A. Uchida30 , J. Urheim91 , T. Usher180 , S. Uzunyan148 , M. R. Vagins118 , P. Vahle207 , S. Valder188 , G. D. A. Valdiviesso62 , E. Valencia77 , R. Valentim197 , Z. Vallari29 , E. Vallazza97 , J. W. F. Valle85 , S. Vallecorsa36 , R. Van Berg162 , R. G. Van de Water128 , D. Vanegas Forero136 , D. Vannerom134 , F. Varanini100 , D. Vargas Oliva84 , G. Varner80 , J. Vasel91 , S. Vasina115 , G. Vasseur35 , N. Vaughan153 , K. Vaziri67 , S. Ventura100 , A. Verdugo40 , S. Vergani30 , M. A. Vermeulen146 , M. Verzocchi67 , M. Vicenzi71,95 , H. Vieira de Souza159 , C. Vignoli75 , C. Vilela36 , B. Viren21 , T. Vrba50 , T. Wachala145 , A. V. Waldron88 , M. Wallbank41 , C. Wallis45 , H. Wang26 , J. Wang182 , L. Wang125 , M. H. L. S. Wang67 , X. Wang67 , Y. Wang26 , Y. Wang185 , K. Warburton107 , D. Warner45 , M. O. Wascko88 , D. Waters199 , A. Watson17 , K. Wawrowska175,188 , P. Weatherly55 , A. Weber67,132 , M. Weber15 , H. Wei21 , A. Weinstein107 , D. Wenman208 , M. Wetstein107 , A. White193 , L. H. Whitehead30 , D. Whittington189 , M. J. Wilking185 , A. Wilkinson199 , C. Wilkinson125 , Z. Williams193 , F. Wilson175 , R. J. Wilson45 , W. Wisniewski180 , J. Wolcott196 , T. Wongjirad196 , A. Wood81 , K. Wood125 , E. Worcester21 , M. Worcester21 , K. Wresilo30 , C. Wret172 , W. Wu67 , W. Wu25 , Y. Xiao25 , F. Xie188 , B. Yaeggy41 , E. Yandel28 , G. Yang185 , K. Yang154 , T. Yang67 , A. Yankelevich25 , N. Yershov104 , K. Yonehara67 , Y. S. Yoon39 , T. Young147 , B. Yu21 , H. Yu21 , H. Yu186 , J. Yu193 , Y. Yu87 , W. Yuan58 , R. Zaki211 , J. Zalesak49 , L. Zambelli53 , B. Zamorano73 , A. Zani98 , L. Zazueta207 , G. P. Zeller67 , J. Zennamo67 , K. Zeug208 , C. Zhang21 , S. Zhang91 , Y. Zhang166 , M. Zhao21 , E. Zhivun21 , G. Zhu152 , E. D. Zimmerman44 , S. Zucchelli18,92 , J. Zuklin49 , V. Zutshi148 , R. Zwaska67 1 Abilene Christian University, Abilene, TX 79601, USA 2 University of Albany, SUNY, Albany, NY 12222, USA 3 University of Amsterdam, 1098 XG Amsterdam, The Netherlands 4 Antalya Bilim University, 07190 Döşemealti/Antalya, Turkey 5 University of Antananarivo, 101 Antananarivo, Madagascar 6 Universidad Antonio Nariño, Bogotá, Colombia 7 Argonne National Laboratory, Argonne, IL 60439, USA 8 University of Arizona, Tucson, AZ 85721, USA 9 Universidad Nacional de Asunción, San Lorenzo, Paraguay 10 University of Athens, 157 84 Zografou, Greece 11 Universidad del Atlántico, Barranquilla, Atlántico, Colombia 12 Augustana University, Sioux Falls, SD 57197, USA 13 Banaras Hindu University, Varanasi 221 005, India 14 University of Basel, 4056 Basel, Switzerland 15 University of Bern, 3012 Bern, Switzerland 16 Beykent University, Istanbul, Turkey 17 University of Birmingham, Birmingham B15 2TT, UK 18 Università del Bologna, 40127 Bologna, Italy 19 Boston University, Boston, MA 02215, USA 20 University of Bristol, Bristol BS8 1TL, UK 21 Brookhaven National Laboratory, Upton, NY 11973, USA 22 University of Bucharest, Bucharest, Romania 23 University of California Berkeley, Berkeley, CA 94720, USA 24 University of California Davis, Davis, CA 95616, USA 25 University of California Irvine, Irvine, CA 92697, USA 26 University of California Los Angeles, Los Angeles, CA 90095, USA 27 University of California Riverside, Riverside, CA 92521, USA 28 University of California Santa Barbara, Santa Barbara, CA 93106, USA 29 California Institute of Technology, Pasadena, CA 91125, USA 30 University of Cambridge, Cambridge CB3 0HE, UK 31 Universidade Estadual de Campinas, Campinas, SP 13083-970, Brazil 32 Università di Catania, 2, 95131 Catania, Italy 33 Universidad Católica del Norte, Antofagasta, Chile 34 Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, RJ 22290-180, Brazil 35 IRFU, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France 36 CERN, The European Organization for Nuclear Research, 1211 Meyrin, Switzerland 37 Institute of Particle and Nuclear Physics of the Faculty of Mathematics and Physics of the Charles University, 180 00 Prague 8, Czech Republic 38 University of Chicago, Chicago, IL 60637, USA 123 Eur. Phys. J. C (2022) 82:618 Page 5 of 29 618 39 Chung-Ang University, Seoul 06974, South Korea 40 CIEMAT, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain 41 University of Cincinnati, Cincinnati, OH 45221, USA 42 Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Mexico City, Mexico 43 Universidad de Colima, Colima, Mexico 44 University of Colorado Boulder, Boulder, CO 80309, USA 45 Colorado State University, Fort Collins, CO 80523, USA 46 Columbia University, New York, NY 10027, USA 47 Centro de Tecnologia da Informacao Renato Archer, Amarais, Campinas, SP CEP 13069-901, Brazil 48 Central University of South Bihar, Gaya 824236, India 49 Institute of Physics, Czech Academy of Sciences, 182 00 Prague 8, Czech Republic 50 Czech Technical University, 115 19 Prague 1, Czech Republic 51 Dakota State University, Madison, SD 57042, USA 52 University of Dallas, Irving, TX 75062-4736, USA 53 Laboratoire d’Annecy de Physique des Particules, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LAPP-IN2P3, 74000 Annecy, France 54 Daresbury Laboratory, Cheshire WA4 4AD, UK 55 Drexel University, Philadelphia, PA 19104, USA 56 Duke University, Durham, NC 27708, USA 57 Durham University, Durham DH1 3LE, UK 58 University of Edinburgh, Edinburgh EH8 9YL, UK 59 Universidad EIA, Envigado, Antioquia, Colombia 60 ETH Zurich, Zurich, Switzerland 61 Faculdade de Ciências da Universidade de Lisboa-FCUL, 1749-016 Lisbon, Portugal 62 Universidade Federal de Alfenas, Poços de Caldas, MG 37715-400, Brazil 63 Universidade Federal de Goias, Goiania, GO 74690-900, Brazil 64 Universidade Federal de São Carlos, Araras, SP 13604-900, Brazil 65 Universidade Federal do ABC, Santo André, SP 09210-580, Brazil 66 Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21941-901, Brazil 67 Fermi National Accelerator Laboratory, Batavia, IL 60510, USA 68 University of Ferrara, Ferrara, Italy 69 University of Florida, Gainesville, FL 32611-8440, USA 70 Fluminense Federal University, 9 Icaraí, Niterói, RJ 24220-900, Brazil 71 Università degli Studi di Genova, Genoa, Italy 72 Georgian Technical University, Tbilisi, Georgia 73 University of Granada & CAFPE, 18002 Granada, Spain 74 Gran Sasso Science Institute, L’Aquila, Italy 75 Laboratori Nazionali del Gran Sasso, L’Aquila, AQ, Italy 76 University Grenoble Alpes, CNRS, Grenoble INP, LPSC-IN2P3, 38000 Grenoble, France 77 Universidad de Guanajuato, C.P. 37000 Guanajuato, Mexico 78 Harish-Chandra Research Institute, Jhunsi, Allahabad 211 019, India 79 Harvard University, Cambridge, MA 02138, USA 80 University of Hawaii, Honolulu, HI 96822, USA 81 University of Houston, Houston, TX 77204, USA 82 University of Hyderabad, Gachibowli, Hyderabad 500 046, India 83 Idaho State University, Pocatello, ID 83209, USA 84 Institut de Física d’Altes Energies (IFAE)-Barcelona Institute of Science and Technology (BIST), Barcelona, Spain 85 Instituto de Física Corpuscular, CSIC and Universitat de València, 46980 Paterna, Valencia, Spain 86 Instituto Galego de Fisica de Altas Enerxias, A Coruña, Spain 87 Illinois Institute of Technology, Chicago, IL 60616, USA 88 Imperial College of Science Technology and Medicine, London SW7 2BZ, UK 89 Indian Institute of Technology Guwahati, Guwahati 781 039, India 90 Indian Institute of Technology Hyderabad, Hyderabad 502285, India 91 Indiana University, Bloomington, IN 47405, USA 92 Istituto Nazionale di Fisica Nucleare Sezione di Bologna, 40127 Bologna, BO, Italy 93 Istituto Nazionale di Fisica Nucleare Sezione di Catania, 95123 Catania, Italy 94 Istituto Nazionale di Fisica Nucleare Sezione di Ferrara, 44122 Ferrara, Italy 95 Istituto Nazionale di Fisica Nucleare Sezione di Genova, 16146 Genoa, GE, Italy 96 Istituto Nazionale di Fisica Nucleare Sezione di Lecce, 73100 Lecce, Italy 97 Istituto Nazionale di Fisica Nucleare Sezione di Milano Bicocca, 3, 20126 Milan, Italy 98 Istituto Nazionale di Fisica Nucleare Sezione di Milano, 20133 Milan, Italy 99 Istituto Nazionale di Fisica Nucleare Sezione di Napoli, 80126 Naples, Italy 100 Istituto Nazionale di Fisica Nucleare Sezione di Padova, 35131 Padua, Italy 101 Istituto Nazionale di Fisica Nucleare Sezione di Pavia, 27100 Pavia, Italy 102 Istituto Nazionale di Fisica Nucleare Laboratori Nazionali del Sud, 95123 Catania, Italy 103 Universidad Nacional de Ingeniería, Lima 25, Peru 123 618 Page 6 of 29 Eur. Phys. J. C (2022) 82:618 104 Institute for Nuclear Research of the Russian Academy of Sciences, Moscow 117312, Russia 105 University of Insubria, Via Ravasi, 2, 21100 Varese, VA, Italy 106 University of Iowa, Iowa City, IA 52242, USA 107 Iowa State University, Ames, IA 50011, USA 108 Institut de Physique des 2 Infinis de Lyon, 69622 Villeurbanne, France 109 Institute for Research in Fundamental Sciences, Tehran, Iran 110 Instituto Superior Técnico-IST, Universidade de Lisboa, 1049-001 Lisbon, Portugal 111 Iwate University, Morioka, Iwate 020-8551, Japan 112 University of Jammu, Jammu 180006, India 113 Jawaharlal Nehru University, New Delhi 110067, India 114 Jeonbuk National University, Jeonrabuk-do 54896, South Korea 115 Joint Institute for Nuclear Research, Dzhelepov Laboratory of Nuclear Problems 6 Joliot-Curie, Dubna, Moscow Region 141980, Russia 116 University of Jyvaskyla, 40014 Jyvaskyla, Finland 117 Kansas State University, Manhattan, KS 66506, USA 118 Kavli Institute for the Physics and Mathematics of the Universe, Kashiwa, Chiba 277-8583, Japan 119 High Energy Accelerator Research Organization (KEK), Ibaraki 305-0801, Japan 120 Korea Institute of Science and Technology Information, Daejeon 34141, South Korea 121 K L University, Vaddeswaram, Andhra Pradesh 522502, India 122 National Institute of Technology, Kure College, Hiroshima 737-8506, Japan 123 Taras Shevchenko National University of Kyiv, Kyiv 01601, Ukraine 124 Lancaster University, Lancaster LA1 4YB, UK 125 Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA 126 Laboratório de Instrumentação e Física Experimental de Partículas, 1649-003 Lisboa, 3004-516 Coimbra, Portugal 127 University of Liverpool, Liverpool L69 7ZE, UK 128 Los Alamos National Laboratory, Los Alamos, NM 87545, USA 129 Louisiana State University, Baton Rouge, LA 70803, USA 130 University of Lucknow, Lucknow, Uttar Pradesh 226007, India 131 Madrid Autonoma University and IFT UAM/CSIC, 28049 Madrid, Spain 132 Johannes Gutenberg-Universität Mainz, 55122 Mainz, Germany 133 University of Manchester, Manchester M13 9PL, UK 134 Massachusetts Institute of Technology, Cambridge, MA 02139, USA 135 Max-Planck-Institut, 80805 Munich, Germany 136 University of Medellín, Medellín 050026, Colombia 137 University of Michigan, Ann Arbor, MI 48109, USA 138 Michigan State University, East Lansing, MI 48824, USA 139 Università del Milano-Bicocca, 20126 Milan, Italy 140 Università degli Studi di Milano, 20133 Milan, Italy 141 University of Minnesota Duluth, Duluth, MN 55812, USA 142 University of Minnesota Twin Cities, Minneapolis, MN 55455, USA 143 University of Mississippi, University, MS 38677, USA 144 University of New Mexico, Albuquerque, NM 87131, USA 145 H. Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences, Kraków, Poland 146 Nikhef National Institute of Subatomic Physics, 1098 XG Amsterdam, The Netherlands 147 University of North Dakota, Grand Forks, ND 58202-8357, USA 148 Northern Illinois University, DeKalb, IL 60115, USA 149 Northwestern University, Evanston, IL 60208, USA 150 University of Notre Dame, Notre Dame, IN 46556, USA 151 Occidental College, Los Angeles, CA 90041, USA 152 Ohio State University, Columbus, OH 43210, USA 153 Oregon State University, Corvallis, OR 97331, USA 154 University of Oxford, Oxford OX1 3RH, UK 155 Pacific Northwest National Laboratory, Richland, WA 99352, USA 156 Universtà degli Studi di Padova, 35131 Padua, Italy 157 Panjab University, Chandigarh, U.T. 160014, India 158 Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France 159 Université de Paris, CNRS, Astroparticule et Cosmologie, 75006 Paris, France 160 University of Parma, 43121 Parma, PR, Italy 161 Università degli Studi di Pavia, 27100 Pavia, PV, Italy 162 University of Pennsylvania, Philadelphia, PA 19104, USA 163 Pennsylvania State University, University Park, PA 16802, USA 164 Physical Research Laboratory, Ahmedabad 380 009, India 165 Università di Pisa, 56127 Pisa, Italy 166 University of Pittsburgh, Pittsburgh, PA 15260, USA 167 Pontificia Universidad Católica del Perú, Lima, Peru 168 University of Puerto Rico, Mayaguez, PR 00681, USA 169 Punjab Agricultural University, Ludhiana 141004, India 123 Eur. Phys. J. C (2022) 82:618 Page 7 of 29 618 170 Queen Mary University of London, London E1 4NS, UK 171 Radboud University, 6525 AJ Nijmegen, The Netherlands 172 University of Rochester, Rochester, NY 14627, USA 173 Royal Holloway College, London TW20 0EX, UK 174 Rutgers University, Piscataway, NJ 08854, USA 175 STFC Rutherford Appleton Laboratory, Didcot OX11 0QX, UK 176 Università del Salento, 73100 Lecce, Italy 177 San Jose State University, San José, CA 95192-0106, USA 178 Universidad Sergio Arboleda, 11022 Bogotá, Colombia 179 University of Sheffield, Sheffield S3 7RH, UK 180 SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA 181 University of South Carolina, Columbia, SC 29208, USA 182 South Dakota School of Mines and Technology, Rapid City, SD 57701, USA 183 South Dakota State University, Brookings, SD 57007, USA 184 Southern Methodist University, Dallas, TX 75275, USA 185 Stony Brook University, SUNY, Stony Brook, NY 11794, USA 186 Sun Yat-Sen University, Guangzhou 510275, China 187 Sanford Underground Research Facility, Lead, SD 57754, USA 188 University of Sussex, Brighton BN1 9RH, UK 189 Syracuse University, Syracuse, NY 13244, USA 190 Universidade Tecnológica Federal do Paraná, Curitiba, Brazil 191 Texas A&M University, College Station 77840, USA 192 Texas A&M University-Corpus Christi, Corpus Christi, TX 78412, USA 193 University of Texas at Arlington, Arlington, TX 76019, USA 194 University of Texas at Austin, Austin, TX 78712, USA 195 University of Toronto, Toronto, ON M5S 1A1, Canada 196 Tufts University, Medford, MA 02155, USA 197 Universidade Federal de São Paulo, São Paulo 09913-030, Brazil 198 Ulsan National Institute of Science and Technology, Ulsan 689-798, South Korea 199 University College London, London WC1E 6BT, UK 200 Valley City State University, Valley City, ND 58072, USA 201 Variable Energy Cyclotron Centre, Kolkata, West Bengal 700 064, India 202 Virginia Tech, Blacksburg, VA 24060, USA 203 University of Warsaw, 02-093 Warsaw, Poland 204 University of Warwick, Coventry CV4 7AL, UK 205 Wellesley College, Wellesley, MA 02481, USA 206 Wichita State University, Wichita, KS 67260, USA 207 College of William and Mary, Williamsburg, VA 23187, USA 208 University of Wisconsin Madison, Madison, WI 53706, USA 209 Yale University, New Haven, CT 06520, USA 210 Yerevan Institute for Theoretical Physics and Modeling, Yerevan 0036, Armenia 211 York University, Toronto M3J 1P3, Canada Received: 31 March 2022 / Accepted: 24 June 2022 © The Author(s) 2022 Abstract DUNE is a dual-site experiment for long-baseline improves the calorimetry measurements. In ProtoDUNE-DP, neutrino oscillation studies, neutrino astrophysics and nucl- scintillation and electroluminescence light produced by cos- eon decay searches. ProtoDUNE Dual Phase (DP) is a mic muons in the LArTPC is collected by photomultiplier 6 × 6 × 6 m3 liquid argon time-projection-chamber (LArTPC) tubes placed up to 7 m away from the ionizing track. In this that recorded cosmic-muon data at the CERN Neutrino Plat- paper, the ProtoDUNE-DP photon detection system perfor- form in 2019–2020 as a prototype of the DUNE Far Detector. mance is evaluated with a particular focus on the different Charged particles propagating through the LArTPC produce wavelength shifters, such as PEN and TPB, and the use of ionization and scintillation light. The scintillation light sig- Xe-doped LAr, considering its future use in giant LArTPCs. nal in these detectors can provide the trigger for non-beam The scintillation light production and propagation processes events. In addition, it adds precise timing capabilities and are analyzed and a comparison of simulation to data is per- formed, improving understanding of the liquid argon prop- erties. a e-mail: clara.cuesta@ciemat.es (corresponding author) 123 618 Page 8 of 29 Eur. Phys. J. C (2022) 82:618 1 Introduction tion (∼ 3.125 × 3.125 × 0.64 mm3 ) [9] enabling the con- struction of large active volumes making efficient use of The Deep Underground Neutrino Experiment (DUNE) [1] the LAr volume. The CRP consists of the extraction grid aims to address key questions in neutrino physics such as which bounds the active volume, large electron multipliers measuring the CP violating phase and the neutrino mass (LEMs) to produce the charge avalanche, and the anode to ordering with an intense muon neutrino beam produced at collect the electrons. In ProtoDUNE-DP, two fully instru- Fermilab [2]. The physics program also addresses non-beam mented CRPs of 3 × 3 m2 , and two CRPs without LEMs are physics such as nucleon decay and beyond the Standard installed. The scintillation light signal is collected by a photon Model searches [3] and the detection and measurement of the detection system (PDS) constructed out of photo-multiplier electron neutrino flux from a potential core-collapse super- tubes (PMTs). The PDS goals are to provide a trigger and nova within our galaxy [4]. DUNE will consist of a near to determine precisely the event time, with capability to per- detector placed at Fermilab close to the production point of form calorimetric measurements and particle identification. the neutrino beam of the Long-Baseline Neutrino Facility Two Cosmic Ray Tagger (CRT) panels with eight scintilla- (LBNF) to measure the unoscillated neutrino interaction rate, tor bars (1.44 m × 0.12 m) per panel are placed on opposite and four 17-kt liquid-argon time-projection chambers (LArT- sides of the ProtoDUNE-DP cryostat to trigger on muon- PCs) as far detector in the Sanford Underground Research tracks passing through both CRTs. Figure 1 shows a diagram Facility (SURF) at 4300 m.w.e. depth at 1300 km from Fer- of ProtoDUNE-DP with the layout and dimensions of the milab [5,6] where the neutrino interaction will be measured CRPs, PMTs and CRTs. The PDS layout is optimized to after neutrinos have oscillated. maximize the collected light [10]. The ProtoDUNE Dual Phase (DP) detector [7,8] was oper- As charged particles pass through LAr, they create pairs ated from 2019 to 2020 at the CERN Neutrino Platform of positively charged argon ions (Ar+ ) and free electrons and to demonstrate the LArTPC DP technology at large scale also produce excited atoms (Ar∗ ). When ionized and excited as a prototype for one of the DUNE far detector modules. argon atoms couple to neutral Ar atoms, they produce the ProtoDUNE-DP has an active volume of 6×6×6 m3 corre- molecular states Ar+ ∗ 2 and Ar2 , respectively. The first one sponding to an active mass of 300 t (total LAr mass of 750 t), eventually recombines with an electron producing Ar∗2 . In being the largest DP LArTPC ever operated. In ProtoDUNE- both processes (recombination and excitation) the decay of DP the electric drift field is oriented in the vertical direction, the final state results in the emission of a vacuum ultraviolet causing the electrons to drift vertically towards the anode (VUV) photon within a wavelength centered at 127 ± 8 nm at the top. The ionization charge is then extracted, ampli- [11] constituting the primary scintillation light (S1) signal: fied, and detected in gaseous argon above the liquid sur- Rec. : Ar + + Ar → Ar + − ∗ 2 + e → Ar 2 → 2Ar + γ , (1) face by the charge readout planes (CRPs). The DP tech- ∗ nology allows a good signal to noise ratio (> 10 for 6- Exc. : Ar + Ar → Ar ∗2 → 2Ar + γ . (2) m drift at 500 V/cm drift field) and a fine spatial resolu- Top view Top-CRT Side view CRP2 CRP1 y (instrumented) (instrumented) CRP2 CRP1 (instrumented) (instrumented) 281 81 x Bottom-CRT 135 135 Top-CRT 1 2 3 4 z 300 5 6 7 8 CRT-triggered RT-triggered 9 10 11 12 600 281 281 cosmic c rays 790 13 14 15 16 17 18 19 20 855 663 21 22 23 24 25 26 TPC Bottom-CRT Bot 27 28 29 30 active 300 volume 281 31 32 33 34 35 36 TPC PMT array Cathode & Ground grid active x volume 155 600 107 CRP3 CRP4 300 300 z 68 PMT array 38 Cryostat Cryostat 855 855 Fig. 1 Views of ProtoDUNE-DP. Dimensions and positions of the major elements are indicated (in units of centimeters). The drift direction corresponds to the y-axis. The PMTs are represented with circles and, in the top view, the empty circles correspond to PEN PMTs and the filled circles to TPB PMTs 123 Eur. Phys. J. C (2022) 82:618 Page 9 of 29 618 This paper describes the ProtoDUNE-DP PDS perfor- mance after 18 months of operation considering its future use in giant LArTPCs with a particular focus on the wavelength shifting techniques. A study of the LAr scintillation and elec- troluminescence light production and propagation over large distances is presented. In Sect. 2, the ProtoDUNE-DP oper- ation and collected light data are described. Section 3 details the performance of ProtoDUNE-DP PDS. In Sect. 4 the light simulation tools are detailed. The analyses of scintillation light propagation and production are discussed in Sect. 5 and the cosmic muon rate measured in ProtoDUNE-DP is described in Sect. 6. Studies using the electroluminescence Fig. 2 ProtoDUNE-DP PDS formed of 36 PMTs installed at the bot- light signal are summarized in Sect. 7. Finally the perfor- tom of the cryostat at CERN. The front left PMT has TPB coating and mance of the system using Xe-doped LAr is reviewed in the front right PMT has PEN sheet Sect. 8. In order for the recombination process to occur, an electron cloud surrounding the Ar+ 2 is needed. Hence the scintillation 2 ProtoDUNE-DP PDS operation at CERN light yield depends on the electric field. Ar∗2 has two possible states, a singlet and a triplet state. The singlet transition to ProtoDUNE-DP collected cosmic-ray data from June 2019 the ground state Ar2 has a short decay time τfast ∼6 ns, while until November 2020, operating with pure LAr and Xe-doped the triplet transition to the same ground state is allowed only LAr in different conditions of electric fields. Muons are the because of spin-orbit coupling and has a much longer lifetime most abundant charged particles in cosmic rays at surface, τslow ∼1.6 µs [12]. together with protons (∼1%), and electrons and positrons In addition, electroluminescence secondary scintillation (∼0.1%). No beam data were taken with ProtoDUNE-DP. light, called S2, is produced in the gas phase of the dual The ProtoDUNE-DP operation faced issues that impacted phase LArTPC when electrons, extracted from the liquid, are the electric field conditions. A short circuit between the high- accelerated in the electric field of the LEMs. The S2 signal voltage (HV) source and a field-cage ring at approximately also has 127 nm wavelength. The time difference between 1/3 the field-cage depth prevented reaching the nominal cath- the S1 and the S2 signals reflects the drift time of the original ode voltage (− 300 kV). The cathode HV was set at − 50 kV ionization in the liquid phase up to the gas phase, and the S2 and the drift field in the operation conditions was fairly uni- duration, which can be up to hundreds of microseconds, is form in the top part of the drift and away from the field directly related to the track topology and covers the span of cage walls. A COMSOL [18] simulation of the resulting drift the electron drift time. field is shown in Fig. 3. Additionally, CRP operation was not The PDS of ProtoDUNE-DP [13] is formed of 36 8-in. straightforward due to the presence of bubbles on the LAr cryogenic R5912-02MOD PMTs from Hamamatsu [14,15], surface causing LEM and grid discharges. Given these lim- placed below the cathode grid. As the PMTs are not sen- itations, data taken with the CRPs in combination with the sitive to VUV light, a wavelength shifter converts 127- PDS were very limited and the data presented in this paper nm photons into visible photons. Two different wavelength were taken with the PDS alone. The operation conditions of shifters were deployed. A sheet of polyethylene naphthalate ProtoDUNE-DP were 88 K with a thermal gradient present (PEN) is placed on top of 30 PMTs and the other 6 PMTs in the detector less than 20 mK and 1045 mbar. have tetraphenyl butadiene (TPB) directly coated on them. The PDS started its operation as soon as the detector was Figure 2 shows a picture of the PDS installed in ProtoDUNE- purged with argon gas in June 2019. ProtoDUNE-DP oper- DP. ated fully filled with LAr from August 2019 until May 2020. A light calibration system (LCS) was developed for In June 2020, an intervention on the HV extender was carried ProtoDUNE-DP to monitor the PMT performance and obtain out with the aim of fixing the short circuit although the issue an equalized PMT response [16]. The light source consists was not solved. In July 2020, the detector was re-filled using of 6 blue LEDs and a silicon photo-multiplier (SiPM) as ref- ∼230 ton of Xe-doped LAr from ProtoDUNE-SP [19] con- erence sensor. The LEDs use a Kapustinsky [17] circuit as taminated with N2 . In August 2020, operations were resumed LED driver, and have a wavelength of 465 nm that matches and two additional N2 injections took place to measure the the PMT maximum quantum efficiency. The calibration light effect of N2 contamination in the light attenuation length. is transmitted through a fiber system with a fiber-end pointing Table 1 summarizes the different doping concentrations in at each PMT photocathode. ProtoDUNE-DP. 123 618 Page 10 of 29 Eur. Phys. J. C (2022) 82:618 Individual PMT waveforms were recorded for analysis, so each event contains 36 waveforms. An example of a PMT self-trigger event is shown in Fig. 4 and an individual PMT waveform is shown in Fig. 5. In the off-line analysis, vari- ous properties of the waveform are evaluated: the integrated charge in a given time period (in photo-electron units, PE), the time when the waveform reaches the minimum value (t0 ), the amplitude of the event, and the baseline mean and stan- dard deviation (STD). The PDS system took data in three trigger modes: – PMT self-trigger: Provided by the PDS when a set num- ber of PMT signals (or more) over a given threshold are in coincidence. The trigger rate is in the Hz–kHz range depending on the customizable threshold and the num- ber of PMTs required to pass the threshold. In this trigger Fig. 3 Map of the drift field in ProtoDUNE-DP with cathode at − 50 kV simulated using COMSOL. A particular plane of the active volume mode, not only single tracks are collected, but also show- is shown (vertical plane at 130 cm from a field cage wall). The drift ers and multi-track. direction is along the y-axis and the color scale represents the electric – CRT trigger: In this case the PDS receives an external field strength. The discontinuity at y∼100 cm is due to the HV failure trigger signal from the CRT planes at an average rate of described in the text 0.3 Hz. The CRT trigger mode allows the recording of single tracks with known topology. Table 1 Summary of Xe and N2 doping concentrations in ProtoDUNE- – Calibration mode: An external trigger signal is received DP. Units are ppm in mass for Xe, and ppm in volume for N2 from the light calibration system at 1 kHz synchronized Situation [Xe] (ppmm) [N2 ] (ppmv) with the calibration light pulse sent to the PMTs. This mode also allows taking data with random trigger at a LAr + Xe + N2 5.8 2.4 configurable rate turning off the LEDs. 1st N2 injection 5.8 3.4 2nd N2 injection 5.8 5.3 A total of 130.7 million events were acquired during a live time of 675 h. Table 2 shows the summary of the data taken for the different trigger configurations. As shown in Table 3, The PDS took data on a daily basis during short time peri- most of the light data were acquired without electric drift ods (typically 1–2 h/day). PMT HVs had to be switched off field, and therefore contain only primary scintillation sig- during the operation of some monitoring systems that emit nals. Events with secondary light signals were collected for light, like the purity monitors or the cryogenic cameras, to different drift and amplification field conditions. An impor- avoid any damage to the PMTs. Especially at the beginning of tant sample of events was recorded during the commissioning the data taking period, this happened very often to survey the phase of the system with varying conditions (test mode). status of the liquid surface and charge readout planes. Longer time periods of PDS data taking (∼12 h) were allowed, typ- ically at night, proving the stability of the PDS. 3 ProtoDUNE-DP PDS performance A dedicated light data acquisition and calibration software was developed for ProtoDUNE-DP [20]. The software allows All 36 PMTs were operational throughout of data taking, the user to choose the acquisition trigger mode, control and allowing the validation of the basic performance of the PDS. define the acquisition settings (front-end and high-voltage), A coincident primary scintillation light signal (S1) detected and provides the graphical user interface. The light readout by all 36 PMTs is visible in Fig. 4. The time alignment among front-end electronics is based on the commercial ADC V1740 PMT signals has been measured for all channels to be better from CAEN [21]. This 12-bit VME digitizer has 64 analog than 16 ns. input channels with 2 Vpp dynamic range and a maximum The low noise in the baseline of the signals is notable, as sampling rate of 62.5 MS/s. All data presented in this paper the baseline presents very small fluctuation: 0.6 ± 0.1 ADC were taken with 16-ns sampling, and different time acquisi- (0.29 ± 0.05 mV). The error includes the differences among tion windows depending on the configuration (from 2 µs to PMTs and the stability along the time. In addition, the base- 4 ms). line stability with time is shown in Fig. 6. 123 Eur. Phys. J. C (2022) 82:618 Page 11 of 29 618 Fig. 4 Example of a PMT self-trigger event showing the waveforms The x-axis range is 0–16 µs for all PMTs while the y-axis range (in corresponding to the 36 PMTs according to their relative position in the ADC counts) varies for each PMT and is optimized to best display the detector. The PEN PMTs are shown in black and TPB PMTs in red. S1 signal With the aim of understanding the performance of the 3.1 Calibration PDS, the gain calibration results are shown in Sect. 3.1, the single photo-electron (SPE) is characterized in terms of The main goal of the LCS is to calibrate the PMT response amplitude and rate in Sect. 3.2, the relative performance of by determining the PMT gain during the operation of the PEN and TPB is evaluated in Sect. 3.3, and the scintillation detector. It is important to guarantee equalized PMT response time profile is studied in Sect. 3.4. and to measure the light collected in PE units. An accurate measurement of the collected light is essential for calorimetry 123 618 Page 12 of 29 Eur. Phys. J. C (2022) 82:618 Fig. 6 Baseline mean STD during ProtoDUNE-DP operation. A fit to Fig. 5 Example of a scintillation light event in a ProtoDUNE-DP PMT the mean value (0.6 ± 0.1 ADC) is shown in red and error bars represent at a gain of 107 in LAr without electric field the differences among the different PMTs Table 2 Summary of trigger conditions indicating the number of events and total time of data taken in the different trigger configurations The calibrations performed during the detector operation allow to monitor the PMT gain stability with time. Figure 7 Trigger # of events (M) Time (h) presents the gain evolution of all the PMTs during one year of PMT 85.3 96 regular operation of the LCS. It should be noted that the PMTs CRT panels 0.6 515 were switched on and off every day (sometimes several times Calibration 30 42 on the same day). Despite this, it can be seen that the PMT Random 14.7 21 gains are quite stable with time. In particular, the average Total 130.7 675 value of the gain STD at 1500 V for 36 PMTs is 9%. Table 3 Summary of the detector configurations indicating the number 3.2 Single photo-electron characterization of events and total time of data taken with different voltage across LEMs The capability of measuring low energy signals depends on Drift field LEMs voltage # of events (M) Time (h) the signal-to-noise ratio and on the SPE rate from various background sources. OFF – 85.1 342 The SPE amplitude is characterized as a function of the ON 0 kV 13.6 72 PMT gain using calibration data. The SPE amplitude spectra 2.5–3.6 kV 7.7 212 are fitted with a Gaussian function for each PMT in order to Test – 23.2 48 obtain the mean amplitude (μ) and its corresponding stan- Total – 130.7 675 dard deviation (σ ) as functions of the PMT gain. The corre- lation between mean amplitude and gain is shown in Fig. 8, which allows the average SPE amplitude at any gain to be and to estimate the detection efficiency of the PDS. The PMTs extracted. For instance, at a gain of 107 , the SPE amplitude is are typically operated at a gain in the range from 1 · 107 to 7 ADC counts, implying a signal-to-noise ratio greater than 5 · 107 as a compromise between maximizing the sensitivity 11 thanks to the small fluctuation of the baseline in the PMT to the SPE and minimizing ADC-saturated events. The LCS waveforms, while σ is 2 ADC counts. An example of a SPE illuminates the PMT photocathode at the SPE level in order pulse in a PMT waveform at a gain of 107 is shown in Fig. 9. to determine the PMT gain. The calibration light rate is kept The SPE pulses have a full width at half maximum (FWHM) to ∼kHz to avoid PMT fatigue [16]. of 1 time sample (59%, 16 ns) or 2 time samples (40%, 32 The gain calibration method, based on measuring the SPE ns). charge at a given voltage, is described in [16]. During oper- The SPE rate is computed by counting the SPE pulses ation, PMTs were biased at the HV required to achieve the in the data samples taken with the random trigger. Pulses target gain according to the calibration results. Calibrations with an amplitude within the expected range (μ ± 2σ ) are were carried out weekly and a gain correction based on the considered, ignoring the parts of the waveform affected by closest calibration in time is applied in the analysis. S1 signals larger than 1 PE. Without drift field, a SPE rate of 123 Eur. Phys. J. C (2022) 82:618 Page 13 of 29 618 Fig. 7 Gain (G) stability with time for the 36 PMTs (one color per PMT) evaluated at 1500 V represented with respect to the average gain < G > Fig. 8 Mean SPE amplitude from Gaussian fits as a function of the Fig. 9 Example of SPE pulse in a PMT waveform (107 gain) PMT gain, and linear fit. All PMTs are included but only data corre- sponding to gains that allow a proper fit are considered expectation from these sources. A study [24] suggests that Ar+2 drifting to the cathode could explain the high SPE rate ∼350 kHz is obtained for TPB PMTs, whereas PEN PMTs recently measured in several experiments as these molecules are less sensitive and a rate of ∼170 kHz is measured. recombine with electrons and neutralize with electronegative There are several light contributions at the SPE level to impurities producing photons. Unfortunately, this hypothesis the low-energy background detected by the PMTs. First, cannot be tested in our detector because of the non-uniform according to data analysis, cosmic muons are expected to be drift field. detected as SPE at ∼35 kHz. Second, according to a dedicated simulation, natural radioactivity, mainly from 1.01 Bq/kq 3.3 Wavelength-shifting materials: PEN and TPB 39 Ar [22], 115 mBq/kg 85 Kr [22] and 0.09 mBq/kg 42 Ar [23], is expected to contribute with ∼20 kHz. Lastly, it is known The LAr scintillation light is produced at 127 nm, a wave- that the PMT dark current contributes with a SPE rate of length which most photosensors are not sensitive to, and flu- ∼1.7 kHz [14]. However, the measured rate is higher than the orescent materials are introduced to shift the photon wave- 123 618 Page 14 of 29 Eur. Phys. J. C (2022) 82:618 length towards the visible range. ProtoDUNE-DP uses PMTs Table 4 First row: Value of the relative photon detection efficiency, either covered with polyethylene naphthalate (PEN) foils or N P E PEN /N P E TPB . The error represents the STD for all the PMT pairs. Second row: relative WLS efficiency of PEN and TPB, PEN /TPB directly coated with tetraphenyl butadiene (TPB). While TPB is broadly used, PEN is a novel material, never used before Parameter Value in such a large scale experiment and whose efficiency is not N P E PEN /N P E TPB 0.25 ± 0.03 well known. As TPB needs complex coating setups [25], the PEN /TPB 0.35 ± 0.09 potential benefit of PEN comes from its simple handling, because PEN foils are flexible plastic sheets easy to fabricate and install. The PEN sample used in ProtoDUNE-DP is trans- parent and biaxially oriented, manufactured by GoodFellow reported in Table 4. The error is the STD among PMT-pairs, [26]. It has been installed as round disks of 240 mm diame- which agrees with the expected error (0.03) due to the QE ter and 0.125 mm thickness placed over the top of the PMT variation between 3 PMTs measured by the manufacturer. glass surface, as shown in Fig. 2. TPB was deposited over On average, ProtoDUNE-DP TPB-coated PMTs detect four the PMT polished surface, using a dedicated evaporation sys- times more photons than PEN-foil PMTs. This ratio is com- tem developed by the ICARUS experiment [25]. The coating puted for a particular sample of muons; selecting events with density is 0.2 mg/cm2 , which corresponds to a coating thick- a different track topology would vary this ratio. ness around 0.2 m. Both PEN and TPB have a maximum of Additionally, a simple model is proposed to compute the re-emitted photons around a wavelength of 430 nm [27,28]. relative WLS efficiency of the two materials. The number of Photons produced after cosmic particles interact with detected photoelectrons is given by: the LAr will arrive at the wavelength-shifter (either PEN N P E = γ ·  · Δ · Q E, (3) or TPB) and will convert into visible light that can be detected by the PMTs. The relative photon detection effi- where γ is the number of VUV photons arriving to the wave- ciency of the PEN-foil PMTs versus the TPB-coated PMTs, length shifter,  is the WLS efficiency, Δ is the photon trans- N P E PEN /N P E TPB , is experimentally determined by com- port losses from the WLS to the PMT, and Q E is the PMT paring the amount of light (in PEs) detected by a pair of quantum efficiency. Then, the relative conversion efficiency PEN-TPB PMTs placed symmetrically with respect to the can be derived: detector and the light source. An homogeneous response for PEN N P E PEN γcoat Δcoat the whole photocathode is considered. = · · . (4) TPB N P E TPB γfoil Δfoil Dedicated data-sets were taken selecting events with a sig- nal amplitude larger than 13 PEs in the trigger PMT, a TPB- The ratio of photons arriving to the TPB coating over the coated PMT placed at the center of the detector (channel 16 PEN foil is, on average, γcoat /γfoil = 0.69 ± 0.16, as calcu- in Fig. 1). The PMT pairs are selected among PMTs symmet- lated using the cosmic-muon simulation described in Sect. 4. rically placed near the trigger PMT (for example, channels This factor depends on the selected sample, and the simula- 17 and 23). As the event position is not known, the number tion of a different event topology would vary its value. The of photons reaching the PMTs cannot be compared on an fact that the PEN foil receives 30% more photons than the event by event basis, but it can be assumed that the amount TPB coating can be explained as its two faces are exposed to of photons reaching both PMTs is on average the same. The LAr while the TPB only has one. cosmic-muon flux is assumed to be isotropic. Considering an isotropic re-emission of the TPB coating, The response of five PMT pairs is compared at different only 50% of the photons will reach the photocathode (Δcoat gains (107 , 2·107 , 5·107 and 108 ). The trigger configuration = 0.5). For the PEN foil, the transport losses are simulated was kept constant in all data-sets, with the same gain (5·106 ) considering an isotropic re-emission in the foil, and it is found and threshold (13 PEs in amplitude) in the trigger PMT in that Δfoil = 0.247, meaning that only 25% of the re-emitted order to study the same event sample at different gains. To photons will reach the photocathode due to the geometrical avoid saturation of the ADC and guarantee linear response of configuration of the foil with respect to the photocathode. the PMTs, events with a signal amplitude larger than ∼30 PEs As a result, considering the geometrical differences and on the trigger PMT are not included. This selection reduces the measured ratio N P E PEN /N P E TPB , the relative WLS the fraction of saturating events below 1% in all PMTs in all efficiency of both materials is estimated to be PEN /TPB = data-sets. 0.35 ± 0.09, as shown in Table 4. TPB produces three times The average light collected on the PMTs for the selected more visible photons than PEN, for the same amount of inci- events is ∼200 PEs on TPB-coated PMTs, and ∼50 PEs on dent VUV photons. This agrees with the value of 0.34 ± 0.01 PEN-foil PMTs. The N P E PEN /N P E TPB ratio is stable for reported in [29] for the same PEN sample. each pair at different gains and different ranges. An aver- To introduce the PMT response in the simulation, the age N P E PEN /N P E TPB ratio of 0.25 ± 0.03 is obtained, as effective PMT photon-detection efficiencies at 127 nm for 123 Eur. Phys. J. C (2022) 82:618 Page 15 of 29 618 TPB-coated PMTs (E TPB ) and for PEN-foil PMTs (E PEN ) are estimated. This effective efficiency provides the amount of photoelectrons detected per incident VUV photon, and it can be calculated by: E =  · Δ · QE . (5) The PMT quantum efficiency (QE) was measured by the manufacturer for three of the PMTs at room temperature. They measured a value of QE = 0.183 ± 0.013 at 430 nm, and it is assumed that the PMT QE is stable when going to cryogenic temperature [30,31]. Since the values of TPB efficiency at 127 nm reported in the literature show a large dispersion [32–34], a 100% TPB efficiency is assumed as in a previous work [35] (TPB =1). Then, assuming the PEN Fig. 10 Example of the average scintillation waveform of a PEN PMT efficiency obtained by the relative performance of both sys- (blue). The fit to Eq. 6 is shown in red. The corresponding parameters are shown in the legend tems in Table 4 (PEN = 0.35 ± 0.09), the corresponding effective efficiency for TPB-coated and PEN-foil PMTs are E TPB = 0.09 and E PEN = 0.016, making the TPB coated- PMT six times more efficient. However, positioning the PEN foil directly over the PMT glass, as the TPB coating, would double its effective efficiency. These efficiencies are used in the analyses presented in Sects. 5 and 6. 3.4 LAr scintillation time profile The scintillation light emission in LAr has a characteristic time dependence as mentioned in Sect. 1. To get the scintil- lation decay times from the PMT waveforms, signals from cosmic muons are selected by triggering on a TPB-coated PMT with a minimum amplitude of 25 PEs. The PMT gain is set at 5·106 to minimize the ADC saturation, and events saturating the PMT [36] are excluded. Eleven of the PMTs Fig. 11 Monitoring of the τslow component of the scintillation time profile during the detector operation. The error bars show the STD suffer this phenomenon more frequently and are excluded for of the measurements for the different PMT waveforms. Red line at this analysis. τslow = 1.46 µs shows the average from September 2019 when stable An average time profile is generated for each PMT. The operation began average waveform in the absence of drift field for one PMT is shown in Fig. 10. Waveforms are well described by Eq. (6): reflections at the flange feed-through appear ∼200 ns and    2A j σ2 t − t0 ∼400 ns after the maximum, affecting the sensitivity to the f (t) = exp − τint measurement. To mitigate this, the bins containing the τj 2τ 2j τj j=fast,slow,int reflections are excluded from the fit.    σ 2 − τ j (t − t0 ) Purity is critical in LArTPCs, since impurities can reduce × 1 − Erf √ (6) the signal by trapping the ionization electrons. The purity 2σ τ j can be monitored using the PDS by measuring the lifetime of a sum of three exponential functions convoluted with a Gaus- the triplet molecular argon excimers, τslow . Figure 11 shows sian function to represent the detector response. Although the the evolution of the average τslow during the operation of scintillation time profile should in principle have only two ProtoDUNE-DP. The purity improved when the LAr purifi- components, from the decay to ground state of singlet (τfast ) cation system was turned on, and remained stable during the and triplet (τslow ) argon excimers, an intermediate compo- whole operation. The value of τslow is 1.46 ± 0.02 µs, with nent (τint ) is added in order to improve the fit as reported the error corresponding to the STD among the PMT wave- also by other LAr experiments [35]. Given the 16-ns digiti- forms. This average value has a small variation over time zation sampling, the fit has a limited sensitivity to τfast and of just 0.004 µs. The absolute value indicates a high LAr this parameter is fixed to 6 ns [12]. Additionally, two signal purity at the ppb level. No significant difference is observed 123 618 Page 16 of 29 Eur. Phys. J. C (2022) 82:618 according to a Poisson distribution around the predicted aver- age number of primary cosmic rays for each source. The detector location (CERN), altitude and latitude, is used. The start time and spatial origin of the cascades of secondary par- ticles are chosen randomly, and time and space correlations of the particles within each shower are preserved. Muons crossing the CRT panels of ProtoDUNE-DP are also simulated. Single muons are generated with a defined ini- tial position, momentum, and momentum spread. The energy distribution of the muons is taken from CORSIKA for a more realistic outcome. The data-driven track entry/exit distribu- tions in the CRT panels are taken as inputs to define the track topology of the events. A topological selection is carried out Fig. 12 τint distribution obtained from the fit to the average waveform and only muons with a complete trajectory between the CRTs for PEN (blue) and TPB PMTs (red) are accepted, as deviations from the ideal straight trajectory can appear during the propagation through the detector and muons can decay along the track length. in τslow between PEN and TPB PMTs. On average, τslow is The cosmic muons simulated with the event generators 1.45 ± 0.02 µs on PEN PMTs and 1.46 ± 0.02 µs on TPB enter the LAr volume and deposit energy along their tracks PMTs. as they interact with LAr. An incident muon behaves as a min- Figure 12 shows the value of τint for PEN and TPB PMTs imum ionizing particle (MIP) and deposits about 2 MeV/cm. obtained from the fit of the average waveforms using data sets First, the simulation of the muon energy deposition is per- for which the purity was already stable, from September 2019 formed in Geant4. Then, the number of scintillation photons to May 2020. An average value of 50.3±1.7 ns is obtained for is computed by multiplying the deposited energy by a light the PEN PMTs, and a faster response of 43.6 ± 0.7 ns for the yield of 4·104 scintillation photons per MeV in the absence TPB PMTs. The clear difference between the two different of a drift field. The time profile is simulated with an expo- WLS points to a delayed emission time by the WLS material, nential fast decay of 6 ns for 30% of the photons, and an as proposed in [37,38]. exponential slow decay of 1590 ns for the other 70% of the photons. Simulations were carried out before obtaining the ProtoDUNE-DP results described in Sect. 3 and no inter- 4 Cosmic-muon light simulation mediate component is included. No drift field is assumed in this simulation to match the data taking conditions. Note also ProtoDUNE-DP light simulations are carried out using LAr- that only cosmic particles are simulated (only muons in the Soft [39], a physics software package designed for LAr neu- CRT case), and backgrounds from natural radioactivity are trino experiments, such as DUNE. not currently included in the simulation. The detailed geometry of the ProtoDUNE-DP detector has The photon propagation in LAr, from the production point been implemented in Geant4 [40] using geometry description to the PMT array, is performed with Geant4 in LArSoft. markup language (GDML) files. It includes the full cryostat The VUV-light attenuation due to absorption by impurities with its support structure, cathode, field cage, LEMs, PMTs in LAr is simulated (20-m absorption length, equivalent to and ground grid. 3 ppmv of nitrogen contamination in LAr [44]) as well as the The simulation of the cosmic-induced particles reaching Rayleigh scattering length (RSL) (99.9 cm as baseline value ProtoDUNE-DP is based on CORSIKA (COsmic Ray SIm- [45], but also a shorter length of 61.0 cm [46] is tested). A ulation for KAscade) [41], a Monte-Carlo (MC) simulation VUV reflectance of 26% in aluminum is taken (field cage) package. It is based on a multi-component model of primary [47], and the same VUV reflectance is assumed for stainless cosmic rays, the constant mass composition (CMC) model steel (SS) surfaces (cryostat walls, cathode and ground grid) [42], for a more complete modeling of the flux. CORSIKA [48]. Full absorption is considered for the rest of the materi- generates showers from each specific cosmic ray type (Fe, als. Table 5 summarizes the relevant parameters of the light He2 , Mg, proton) according to a power law distribution of the propagation used in the simulation. primary particle energy. The FLUKA model [43] describes The complete simulation of the propagation of all the the hadronic shower propagation. The LArSoft simulation photons produced by each particle crossing the detector draws from a random set of pre-generated air showers from would require an enormous amount of CPU time. Hence, a specific database created with CORSIKA. The number of pre-generated libraries are employed to simulate the light showers per event and per primary particle source is extracted propagation in an efficient way: a Geant4-driven simulation 123 Eur. Phys. J. C (2022) 82:618 Page 17 of 29 618 Table 5 Parameters of the light propagation simulation in ProtoDUNE- a photoelectron in the PMT photocathode. The WLS-PMT DP photon-detection efficiency includes the WLS efficiency, the Parameter Baseline value Alternative propagation of the visible light from the WLS towards the photocathode, and the PMT quantum efficiency. The values Absorption length 20 m – used in the light simulation are taken from studies presented RSL 99.9 cm 61.0 cm in Sect. 3.3: E TPB = 0.09 and E PEN = 0.016. VUV reflectance 26% in Al & SS, 0% for all Waveforms are produced by adding the SPE response for 0% for the rest each detected photon. The simulated PMT response is linear, Voxel size 0.34 × 0.32 × 0.34 m3 – and includes a dark current component of 1.7 kHz [16]). The waveform digitization considers a 16-ns sampling matching the data acquisition system. is generated and the results are stored and parametrized in the so-called photon libraries. The LAr volume is divided into 3D 5 Light production and propagation in LAr measured voxels and 108 photons per voxel are isotropically and uni- with cosmic muon data formly generated. A photon library contains, for each PMT- voxel combination: the visibility (photon detection probabil- The pure LAr of ProtoDUNE-DP is an optimal medium to ity), the minimum time for the light to reach the PMT (arrival study the scintillation light production, propagation and col- time), and the Landau-fit parameters of the propagation time lection in a LAr volume. The experiment provides valuable distribution. In order to mitigate the relatively large size of technical feedback for future light detection systems as well the voxels, 3D interpolations among them are used at each as results on the scintillation light mechanisms in LAr. In step of the track. this section, PMT data acquired with the CRT-trigger system Three different photon libraries are generated to study are analyzed to profit from the off-line reconstruction of the the impact of several parameters in ProtoDUNE-DP: (A) the track trajectory that such a trigger allows. Muon tracks cross- baseline photon library with 99.9-cm RSL and 26% VUV- ing the detector diagonally and in the downward direction are light surface reflectance, (B) a library with 61-cm RSL and selected. Information about the distance the light travels from 26% of surface reflectance, and (C) a library with 99.9-cm its production point in the LAr volume to the PMT detecting RSL and no reflection. The maps with the detected light per the signal is retrieved. deposited MeV across the volume for the baseline photon The analysis focuses on the 30 PEN PMTs because they library (A) are displayed in Fig. 13. allow exploring a wider track-PMT distance range than the The PMT response is simulated with a dedicated mod- TPB PMTs. Consistent results are obtained with the TPB ule that produces a waveform for each PMT. Each 127-nm PMTs. The S1 charge (number of PEs) of each triggered photon arriving to the WLS has a probability to produce signal is obtained by integrating the PMT waveform in a Fig. 13 Maps of the detected light (sum of PMT visibilities multiplied of RSL and 26% VUV reflections. The PMT positions are represented by efficiency, E TPB = 0.09 and E PEN = 0.016) per voxel for the base- with black dots and the active volume with a red rectangle line photon library in ProtoDUNE-DP: 4·104 photons per MeV, 99.9 cm 123 618 Page 18 of 29 Eur. Phys. J. C (2022) 82:618 Fig. 14 Normalized distributions of the collected S1 charge for CRT triggered light data and simulation 4-µs window. An event selection is made in both data and simulation to obtain comparable event samples: 1. Time of flight (data)/geometrical cut (MC): a data event is considered a good muon-candidate if the time of flight between the CRT panels (from top to bottom) is between 40 and 45 ns, and only one scintillating bar per panel is triggered. This cut contributes to the rejection of back- ground events like electrons, particle showers, muon bun- dles and fake triggers. In the simulation case, only CRT- trigger-like muons are kept by requiring that the muon- track trajectory crosses both CRTs. 2. Stable baseline before trigger: this cut intends to avoid the pile-up of signals. The waveform RMS is obtained in a 1-µs window before the signal trigger and the baseline is considered to be stable if the result is below 1 ADC Fig. 15 Collected S1 charge versus track-PMT distance for PEN PMTs: Light data (top) and MC sample (bottom). The color maps con- count. tain all the S1 signals detected by the PMTs and passing the event 3. No ADC saturation: data events with waveforms saturat- selection. A Gaussian fit of each charge-distribution every 10 cm is per- ing the ADC are excluded, both in data and MC. formed and the mean values are plotted in black over the map. The 4. Maximum charge: the charge per event must be below vertical error bars correspond to errors from the fits and a 5-cm distance uncertainty (horizontal error bars) is included 100 PE for PEN PMTs. This limit is applied to suppress high-energy events (vertical showers instead of diagonal muons) that affect the distribution of interest in data but tance, the correlation between charge and distance is lost not in the MC as they are not simulated, see Fig. 14. in data, presumably, because low-energy background (only present in data and contributing with up to 8-9 PE per integra- Since the propagation effects on the collected charge by tion window) prevails over the signal. The profile histogram the PMTs depend on their distance to the muon track, analy- superimposed on the 2D plot corresponds to a Gaussian fit ses shown in this section are mainly based on the correlation of the charge-distribution every 10 cm. In the case of the data between the S1 signal (S1 charge in PE units) and the min- samples, an additional systematic error of 4% (determined imum distance from the muon track to the detecting PMT by varying the PMT gain) is added in quadrature to the fit (simply referred to as track-PMT distance). Figure 15 shows error of the charge. the 2D distribution of theses variables for data and MC. A The top-view light detection maps (average S1 charge per good agreement is observed up to ∼5 m; beyond that dis- optical channel) for the PEN PMTs both for data and MC are 123 Eur. Phys. J. C (2022) 82:618 Page 19 of 29 618 Fig. 17 Top panel: Average S1 charge collected by the PEN PMTs as a function of the track-PMT distance without drift field (black) and with cathode at −50 kV (red). The larger error bars at short distance are due to a lack of statistics. Bottom panel: Ratio between the two distributions. The ratio is fitted to a constant value (result: 0.833 ± 0.007) Fig. 16 Average S1 charge per channel (in PE) in CRT-trigger mode: pared to roughly quantify the light yield decrease. Figure 17 top view of PEN-PMT array for data (top panel) and simulation (bottom shows the charge-distance distributions at the two cathode panel). Each color square represents one PMT channel at its position in the detector. The approximate positions of the CRT frames are indicated HVs and the corresponding ratios between them. The ratio with black lines as a function of the track-PMT distance is fitted to a constant to obtain the average ratio of 0.833 ± 0.007, which means that at least 17% of the scintillation light detected in the absence presented in Fig. 16. The obtained light detection patterns of a drift field comes from electron-ion recombination. reproduce the expected gradient: the PMTs which are closer The CRT-trigger muons cross different fields, which to the bottom CRT (top right corner in the top view) detect leads to a difficult quantification of the overall drift field more light than the rest. responsible for the light level reduction. An estimate of the effective electric field along the CRT-trigger muon tracks 5.1 Drift field effect on light production was made using the 3D simulation of the drift field in ProtoDUNE-DP corresponding to a cathode HV of − 50 kV, The reduction of the detected light with the increasing drift see Fig. 3. The average field value obtained for these tracks field is investigated. This reduction is due to the suppres- is 0.09+0.10 −0.02 kV/cm, where the errors are determined asym- sion of the electron-ion recombination by drift field, which metrically, as the RMS of the values above and below the reduces the primary scintillation light production. The elec- mean value separately. The reduction of the S1 signal for tric field in ProtoDUNE-DP is not uniform across the active this drift field is plotted in Fig. 18 and follows the empir- volume, which makes infeasible a complete understanding of ical Birks’ law. Despite the relatively large uncertainty of the drift field effect over the light production. Nonetheless, the ProtoDUNE-DP result, a fair agreement is found with the light levels detected with the PDS without drift field and the literature for both ground-level cosmic muons [35] and at the maximum operating cathode HV (− 50 kV) are com- MeV-electrons [49,50]. 123 618 Page 20 of 29 Eur. Phys. J. C (2022) 82:618 Fig. 19 Evolution of τslow with the cathode voltage for CRT-trigger events. The results are obtained averaging PEN PMTs and the error bars indicate the STD among them Fig. 18 Light yield reduction with drift field measured by various experiments (red triangles from [49], black squares from [50], blue inverted triangles from [35]), and the ProtoDUNE-DP result (orange circles) discussed in this section in experimental measurements. Modeling the dependence of the light attenuation from the track-PMT distance with a decaying exponential function allows the measurement of The scintillation time profile is also dependent on the drift the overall effective attenuation in data and MC and the eval- field. The two excited molecular states, singlet and triplet, uation of the agreement for the different simulated config- are formed either through recombination or excitation with urations. The track-PMT distance range studied is 4-5 m to different probability, in such a way that the normalization focus on the longer distances where the sensitivity to the RSL constants, Afast and Aslow of Eq. 6, are expected to change as effect is higher. a function of the drift field as the light emitted by electron- In Fig. 20, each S1 charge-distance correlation under study ion recombination is suppressed. According to [49] the ratio is fitted to an exponential and the data-MC ratios for the (Afast + Aint )/Aslow is expected to decrease but the recent two simulations are also presented. Looking at the distribu- measurement presented in [35] shows an increase of 34% at tion shape, the agreement between data and the 99.9-cm MC 500 V/cm. ProtoDUNE-DP has observed an increase of 28% sample is better than with the 61.0-cm value. The attenua- at -50 kV cathode voltage, corresponding to an average field tion length values obtained are presented in Table 6, and it value of 0.09+0.10 −0.02 kV/cm, which is consistent with the 23% is observed that the data value also agrees better with the measured in [35] at a similar electric field strength. 99.9-cm MC value. The attenuation length accounts for the A decrease of τslow with the drift field was reported for effective attenuation of the light in ProtoDUNE-DP, but it is the first time in [35] and is also observed in ProtoDUNE- not a physical property of the LAr as it depends, among other DP, see Fig. 19. A model is proposed in [51], taking into factors, on the topology of the selected tracks and detector account the quenching of the long-lived triplet states through geometry. The measured attenuation length is higher than the self-interaction with other triplet states or through the the RSL, so the light is expected to undergo Rayleigh scat- interaction with molecular Ar+ 2 ions. It successfully explains tering before being heavily attenuated due to, for example, the experimentally observed dependence of τslow with the absorption by LAr impurities or detector elements. This long intensity of the applied electric field. light path before absorption is achieved in ProtoDUNE-DP thanks to the excellent LAr purity and the large free LAr 5.2 Light propagation volume with no nearby components. By comparing MC samples generated with the photon The size of ProtoDUNE-DP, the longest drift-distance libraries (A) and (C), the impact of the VUV-photon reflec- LArTPC ever operated, allows for an unprecedented study of tions on the light reaching the PMT array can be evaluated. the light propagation. The Rayleigh scattering length (RSL) It is found that 11% of the light detected by PEN PMTs in can impact on the amount of light collected. An evaluation the baseline MC corresponds to VUV light reflected on the of the RSL value is carried out by comparing the measured field cage, cryostat walls, cathode and ground grid. light signals with the light predicted by the MC simulation Finally, the light detection is studied through the effec- testing two lengths (61.0 cm [46] and 99.9 cm [45]) obtained tive TPB and PEN PMT efficiencies described in Sect. 3.3. 123 Eur. Phys. J. C (2022) 82:618 Page 21 of 29 618 rate represents a perfect test bench to study the PDS capability for detecting muons and providing calorimetric information. The S1 rate and charge from cosmic muons crossing ProtoDUNE-DP as well as the muon flux are evaluated in Sect. 6.1. In addition, the observed light yield from muons is investigated for two different WLS methods in Sect. 6.2. In total, five data sets acquired over seven months with the random trigger are analyzed and compared with CORSIKA- based simulations. The cosmic-muon data sample allows the validation of the PDS simulation to demonstrate that the detector response is correctly modeled and understood. CRT- trigger data are also analyzed to evaluate the detected light yield for different muon samples. 6.1 Measurement of the cosmic muon flux The results shown in this section are based on the analysis of S1 signals from light data acquired in random-trigger mode. These data comprise varied signals as the light reaching the PMTs can be generated at any location within LAr volume and be associated with very different track topologies and energies. The muon S1 signals are identified in the PMT waveforms Fig. 20 Top panel: average S1 charge collected by the PEN PMTs as a function of the track-PMT distance. Two MC samples with differ- using a custom peak-finding algorithm which takes the fol- ent RSL values (61.0 cm and 99.9 cm) are compared to data. For each lowing aspects into account: distribution, an exponential fit is plotted as a solid line. Bottom panel: data-MC ratio for the two previous MC samples 1. Any pulse in the waveform with an amplitude larger than the expected SPE amplitude plus 2σ is considered a can- Table 6 Attenuation length values obtained from the exponential fits didate S1 signal. The amplitude threshold is based on shown in Fig. 20 the results of the average SPE amplitude presented in Sample λatt (cm) Sect. 3.2. The lack of τint in the simulated scintillation Data 180 ± 17 time profile (see Sect. 4) results in a different charge- amplitude correlation than in data and, hence, a correction MC (RSL 99.9 cm) 180 ± 10 of the amplitude is applied in the MC analysis in order MC (RSL 61.0 cm) 157 ± 8 to select events that correspond to the same deposited energy as in data. 2. After a candidate S1 signal, a veto time window of 4.8 µs The data-MC charge ratios obtained are 0.898 ± 0.002 and is applied. If another candidate S1 signal is detected dur- 1.150 ± 0.005 for PEN and TPB PMTs, respectively, in the ing that time, a new 4.8-µs veto window beginning at that selected track-PMT distance range. The result is that the point is imposed. simulation efficiency is validated within 10–15% of data. 3. An optical reconstruction to reject small and uncorrelated The simulation underestimates the light detected by the TPB signals is performed by requiring coincidences among PMTs, which may be because not all the reflected light is sim- PMTs. A coincidence occurs when at least two PMTs ulated, or the TPB WLS efficiency may be under-estimated. detect the candidate S1 signal within a time interval of However, the light detected by PEN PMTs in data is lower 112 ns. This cut is effective in rejecting candidate S1 sig- than in the simulations, which can be attributed to a PEN nals at low energy in data, where the background, which WLS efficiency over-estimation. is not considered in the MC, is dominant. About 40% and 10% of candidate S1 signals are rejected in data and MC, respectively. 6 Measurement of the cosmic muon rate and light yield The rate of S1 signals detected by each PMT is then com- The rate of cosmic particles crossing the detector is high puted. It should be noted that the obtained S1 rate is not because ProtoDUNE-DP is located on the surface. The high the overall cosmic muon rate in the detector but the aver- 123 618 Page 22 of 29 Eur. Phys. J. C (2022) 82:618 Table 7 Average S1 rate per PMT in random-trigger mode and data/MC ratio. The error of the S1 rate corresponds to the STD among PMTs PMT S1 rate per PMT (kHz) Data/MC ratio Data MC TPB 8.8 ± 0.5 10.2 ± 0.5 0.86 ± 0.09 PEN 5.5 ± 0.6 6.1 ± 0.4 0.90 ± 0.10 age muon rate per PMT. Results presented in Table 7 show a higher rate of simulated S1 signals induced by muons: around 16% (11%) higher S1 rates are detected by the TPB (PEN) PMTs in simulation than in data. Nevertheless, the muon flux with the model chosen within CORSIKA to generate the primary cosmic particles, the CMC model, is expected to be up to 20% above the one obtained with a model assum- ing only cosmic protons, as reported in [52], and the flux can be up to 25% lower with other particle generators. Thus, Fig. 21 Cosmic muon flux determined in ProtoDUNE-DP at CERN at 455 m above mean sea level (red square) compared to the measurements the observed data-MC deviation is within the discrepancy reported in [52] (filled black dots) and [53] (open black dot) between the cosmic-ray generator models. Finally, the atmospheric muon flux is assessed. Consider- Table 8 Total S1 charge per cosmic muon (sum of all PMTs detecting ing the surface covered by the PMT array and the fraction a S1 signal) and observed light yield (average value from events and of muons crossing such an effective area in the MC, the pre- maximum value reached in an event) for two trigger modes. All the dicted atmospheric muon flux at the Earth’s surface by COR- values obtained from data SIKA is 166 Hz/m2 . Then, the predicted flux is scaled by the Trigger PMTs S1 charge per Obs. light yield (PE/MeV) muon (PE) ratio between the data and MC rates given in Table 7. A cos- Avg. Max. mic muon flux of 148+8 2 −11 Hz/m is obtained in ProtoDUNE- DP at CERN (at 455 m altitude above mean sea level). The All 1830 2.3 21.4 systematic uncertainty on the flux is computed by varying Random 6 TPB 650 0.8 10.2 the threshold in amplitude for the S1 identification by ±20% 30 PEN 1180 1.5 13.1 (∼10-25 ADC) given the uncertainty in the MC waveform All 1320 0.7 2.1 simulation, and the PMT efficiency in the MC by ±10% as CRT 6 TPB 590 0.3 1.1 concluded in Sect. 5. The ProtoDUNE-DP cosmic muon flux 30 PEN 730 0.4 1.0 result is found to be consistent with other measurements at ground-level given in the literature, as can be seen in Fig. 21. the PDS per muon in data (1830 PE) and MC (1990 PE), see 6.2 Observed light yield from cosmic muons Fig. 22. In a similar way, the observed light yield is computed for S1 signals acquired with the CRT trigger, see Table 8. In The light yield for muon interactions observed by the PDS is this case, based on the average track length in LAr observed investigated considering the use of the system as a calorime- in data (9.4 m), an average deposited energy per muon of ter. The event selection of random-trigger data explained in 1880 MeV is obtained. Sect. 6.1 is applied. Good stability among data taken through- According to the values in Table 8, the complete PDS out seven months in terms of S1 rate and charge collection (2– of ProtoDUNE-DP (36 PMTs) detects about 2.3 PE/MeV 5% of STD among different sets in both cases) is observed, and 0.7 PE/MeV for random-trigger and CRT-trigger muon which indicates stable performance of the system. tracks, respectively. The latter case corresponds to an aver- Taking into account all the cosmic muon tracks across age track-PMT distance of 475 cm whereas the former com- the LAr volume, the average deposited energy per muon is prises muons crossing the detector at all distances from the determined with the CORSIKA cosmic-ray simulation to be PMTs (from close to distant tracks, up to 7 m away from the 813 MeV. Then, the observed light yield in random trigger PMTs). Since the scintillation photons from cosmic muons mode is calculated as the total S1 charge collected by all triggered with the CRTs are produced farther from the PMTs, PMTs normalized by the average deposited energy per muon. the light is expected to undergo more attenuation. It is worth The results can be seen in Table 8. This approach is validated commenting that the difference between the average and by the fair agreement between the total S1 charge collected by maximum observed light yields is wider for random trigger 123 Eur. Phys. J. C (2022) 82:618 Page 23 of 29 618 topology, as the more inclined the track is, the larger the S2 time spread is. The time difference between the S2 signal and the S1 peak corresponds to the drift time that takes to the electrons produced by the ionizing particles to the anode. In ProtoDUNE-DP, S2 electroluminescence signals are detected in all PMTs when extraction and amplification fields are on, corresponding to light originating about 7 m away from the PMTs. This detection is achieved thanks to the good LAr optical properties and purity and the high efficiency of the ProtoDUNE-DP PDS. In Fig. 23 an example event with S2 signal detected by all PMTs is shown. This is the first time light produced at such a large distance has been detected in a LArTPC. ProtoDUNE-DP operated on the surface and observed a high S1 rate, see Sect. 6. The S2 signals are mostly observed as an increase in SPE rate which increases from hundreds of kHz, see Sect. 3.2, up to several MHz (∼2.5 MHz for Fig. 22 Normalized distributions of the total S1 charge per cosmic muon event (sum of all detecting PMTs) in random trigger. Both data TPB PMTs and ∼1.1 MHz for PEN PMTs) when there is and MC (TPB and PEN) cases are displayed. The ADC saturation in S2 light production (DP operation mode). It is clear that the data that limits the charge range is fairly reproduced in the MC S2 signals are an important and continuous contribution to the low-energy background in the PMT waveform when the extraction field is on. (almost 10 times) than for CRT-trigger events (3 times) due As a result, not every S2 signal can be associated to its to the larger variety of events (energies and track topologies) previous S1. Only very energetic events produce S2 signals in the first case. that can be distinguished from the SPE background and asso- The light yield is also shown in Table 8 separately for the ciated to their previous S1. A dedicated algorithm was devel- two WLS groups in order to highlight the fact that the 6 TPB oped to select these events where the S2 signal can be dis- PMTs alone collect 1/3 of the total light. It can be concluded tinguished from the SPE background and evaluate them in that if the 36 PMTs had TPB coating (PEN foil), a detection relation to their previous S1 signal. of about 5 PE/MeV (2 PE/MeV) would be reached in ran- An individual PMT waveform of a very energetic event dom trigger, on average. Therefore, in this particular PDS selected by the algorithm can be seen in Fig. 24. In this case, configuration, the use of PEN as the only WLS option would a fast S1 signal can be seen followed by a S2 signal with a compromise the capability of the system as a calorimeter for duration of ∼2 ms. Other S1 signals from cosmic muons are low-energy particles. Considering TPB as the baseline WLS also visible. The S2 signals are observed to cause an over- would make the low-energy physics goals of the DUNE Far shoot in the waveforms as the amount of charge collected Detector, such as triggering on a supernova neutrino burst, in the PMT anode exceeds the discharging rate of the com- more feasible to accomplish. bined PMT and readout circuit (1/RC constant), effectively In conclusion, the better detection efficiency of the TPB- shifting the waveform baseline during the pulse. Waveforms coated PMTs together with their stable performance during are processed offline to correct for this effect, as described the detector operation confirm that TPB is a better WLS in [35]. In Fig. 24 the PMT waveform before and after the choice for future LArTPCs. However, the mechanical advan- overshooting correction is shown. tages of PEN make it a good candidate if the emission effi- Figure 25 shows the average waveform of the events pass- ciency is not critical. ing the algorithm. These are very energetic events corre- sponding mainly to vertical showers where the track passed through the liquid-gas interface, and the S2 maximum is pro- 7 Electroluminescence light detection duced right after the S1. In these events the average S1 charge detected per PMT is >700 PE and the S2 charge >30 kPE. The electrons extracted into the gas phase produce produces S2 signals last ∼2 ms. As illustrated in Fig. 3, vertical muons a secondary scintillation signal, called S2, which is propor- will traverse a field of ∼0.2 kV/cm along the first two meters tional to the drifted charge. The S2 signal provides infor- for which an electron drift velocity of ∼1 mm/µs is expected mation on the drifted electrons and the track topology. For [36]. This implies an expected S2 duration of ∼2 ms, which instance, the time spread of the S2 signal is related to the track is consistent with the observed time. 123 618 Page 24 of 29 Eur. Phys. J. C (2022) 82:618 Fig. 23 Example of an event with S1 and S2 signals showing the wave- The x-axis range is 0.8−3 ms for all PMTs while the y-axis range varies forms corresponding to the 36 PMTs according to their relative position for each PMT and is optimized to best display the S2 signal in the detector. PEN PMTs are shown in black and TPB PMTs in red. Fig. 24 Example of a scintillation light event in a ProtoDUNE-DP PMT at a gain of 107 in LAr with drift, amplification and extraction fields (S1 and S2 signal). The acquired waveform is shown in black and Fig. 25 Average waveform of PEN PMTs with a S2 signal identified. the resulting waveform after the overshooting correction in red The y-axis is zoomed to focus on the S2 signal 123 Eur. Phys. J. C (2022) 82:618 Page 25 of 29 618 8 Scintillation light in Xe-doped LAr quenching by N2 and Xe excimer formation are competing processes, the Xe atoms mitigate the light suppression due The use of Xe-doped LAr is a promising alternative to pure to the N2 . LAr for large-scale LArTPCs, since it mitigates the light sup- Additionally, the absorption of photons by N2 is expected pression due to some impurities and it also improves the to increase with the concentration, with a reported absorp- detection efficiency and uniformity. tion length for 127-nm photons of 28 m at 1.7 ppm, 20 m at In the presence of Xe, molecular Ar excimers in the triplet 2.7 ppm and 12 m at 4.7 ppm [44]. state live long enough to transfer their energy to the Xe atoms In the case of ProtoDUNE-DP, after the re-filling with creating Xe excimers that decay and produce photons with a ∼230 ton of Xe-doped liquid argon contaminated with N2 , longer wavelength than 127 nm [54]. Therefore, the scintilla- as described in Sect. 2, both N2 and Xe species were present tion light is no longer monochromatic and has three compo- in the LAr, altering the light production and propagation. nents: Ar light at 127 nm, and Xe light at 178 nm and 150 nm, The effect of the presence of Xe and N2 in the detected with significant contribution at 150 nm only at Xe concentra- light in ProtoDUNE-DP is studied using two types of muon- tions below 1 ppm [55]. Since molecular Ar excimers in the track signals: First, events triggered with a TPB-coated PMT singlet state decay too fast to transfer their energy, they pro- placed at the center of the detector with a minimum ampli- duce 127-nm photons only, while the late light is dominated tude of 25 PEs, for which the light is produced at a close by 150-nm and 178-nm photons. distance from the PMTs, and second, CRT-trigger events, for Xe doping also affects the photon propagation. On one which the PMT-track distance is in the range of 3−5 m. hand, it is reported that Xe acts as an impurity, suppressing Figure 26 shows the evolution of the total S1 charge part of the spectrum at 127 nm even at the concentration of detected by all PMTs as a function of time during the LAr 0.1 ppm [56]. This absorption reduces the fast component evaporation from 7.4 to 5.1 m of liquid level, re-filling and of the detected signal. On the other hand, photons at longer N2 injection steps. Around 12 kPEs are detected on average wavelengths (150 and 178 nm) are not absorbed [56], and per PMT-trigger event, compared to only 2 kPEs per CRT- have a longer RSL. RSL is ∼1 m for 127-nm photons while trigger event in LAr. The S1 signal is integrated over a long it is ∼3.5 m for 150 nm and ∼9 m for 178 nm photons [45]. A time window of 12 µs after the maximum. The reduction of longer RSL enhances the light detection at longer distances the collected light during the evaporation is visible for the with respect to pure LAr, since photons with a longer RSL CRT-trigger events, as part of the CRT-track is no longer scatter less and are able to travel further thereby improving in the liquid, while the collected light for the PMT-trigger the uniformity of detection. tracks is stable. After the filling with Xe-doped LAr, the col- The presence of nitrogen in LAr leads to the suppression lected light increases as expected due to the longer RSL, and of the light production due to a quenching process driven it decreases with the N2 injections due to the quenching. by two-body collisions of N2 impurities with excited argon To quantify the impact of the presence of Xe and N2 on excimers [57]. This quenching affects mainly the excimers in the S1 charge and amplitude with respect to their values in the triplet state as the singlet state decays much faster. Since pure LAr, data taken with the same liquid level are selected to Fig. 26 Evolution of the average S1 charge per event detected in all the PMTs for PMT(CRT)-trigger data in black (red) during the evaporation, filling and N2 injections. The processes are described in Sect. 2 123 618 Page 26 of 29 Eur. Phys. J. C (2022) 82:618 reduction is due to the absorption of the 127-nm photons by the Xe atoms as reported in [56]. Whilst a 16% decrease of the fast component (S1 amplitude) for the CRT-trigger data is expected when adding N2 according to [44], we observe the fast component remaining constant for the two N2 injec- tions. A possible explanation for this discrepancy is that the assumption of the fast component being monochromatic at 127 nm is not accurate, and an additional light contribution at a different wavelength, that is not absorbed by the N2 , is masking the expected absorption at 127 nm. The collected S1 charge increases 100% for the CRT-trigger data, while only 50% for the PMT-trigger data. This difference is understood as an improvement of the detection uniformity, since CRT- trigger muons are on average farther away from the PMTs, and the longer RSL of the Xe photons improves their collec- tion at large distances. The decrease of the S1 charge due to the presence of N2 is similar for both triggers (30%), meaning that there is no dependence of the detected light suppression on the PMT-track distance. This indicates that the reduction is mainly due to the quenching of the Ar excimers by N2 rather than photo-absorption. In order to evaluate the effect of the Xe-doping on the attenuation length (λatt ), a study of the dependence of the collected light per PMT with the track-PMT distance is per- formed for muon tracks crossing the CRT panels, see Fig. 28. The range of distances is given by the position of the PMTs with respect to the triggered track, which is always approxi- mately in the same position (see Sect. 1). The behavior is not purely exponential since light absorption by the field cage introduces a border effect. A shoulder shape is observed at around 4.3 m, which corresponds to the PMTs placed at the center of the detector, where this effect is reduced. This limi- tation is due to the fixed geometry of the triggered tracks. An exponential fit is performed to estimate the attenuation length Fig. 27 Ratio of the average S1 amplitude and S1 charge in the three doping concentrations relative to pure LAr. PMT-trigger data are shown in each detector condition, and the results are summarized in black, and CRT-trigger in red. Only a selection of PMTs is considered in Table 9. The effective attenuation length increases 60% for the average. Selected PMTs are marked as black (red) circles in the when adding Xe, as expected because of the longer RSL, small diagram for the PMT(CRT)-trigger data. A blue circle marks the and decreases 5% when adding 2.9 ppm of N2 . The lower trigger PMT in the PMT-trigger diagram. Errors show the STD among the selected PMTs. Xe and N2 concentrations for each situation are panel of Fig. 28 shows the ratios of the top panel curves. summarized in Table 1 The comparison between pure LAr and Xe-doped LAr in red shows the improved detection uniformity when adding Xe, with an increase of almost a factor of ∼3 on events at 5 m ensure the same optical conditions. Figure 27 shows the aver- age variation of the S1 amplitude and S1 charge for different detector conditions. Only PMTs placed near the trigger PMT Table 9 Measured attenuation lengths in the different doping concen- are considered for PMT-trigger data analysis, to have a simi- trations from the exponential fits shown in Fig. 28 lar track-PMT distance, while only channels placed below the Situation [Xe](ppm) [N2 ] (ppm) λatt (cm) CRT-track are selected for CRT-trigger data analysis, since the other PMTs are placed more than five meters away from LAr 0 0 209 ± 5 the track and for these distant PMTs the signal is dominated LAr + Xe + N2 5.8 2.4 338 ± 13 by background. The amplitude decreases 35% when adding 1st N2 inj. 5.8 3.4 332 ± 13 5.8 ppm of Xe and 2.4 ppm of N2 with respect to pure LAr for 2nd N2 inj. 5.8 5.3 321 ± 12 both trigger modes, being unaffected by the N2 addition. This 123 Eur. Phys. J. C (2022) 82:618 Page 27 of 29 618 Table 10 Time constants obtained from the fit of the average wave- forms at the different doping concentrations. Errors show the variation among PMTs Situation τtransfer (±0.01µs) τslow (±0.01µs) LAr N/A 1.43 LAr + Xe + N2 0.46 1.10 1st N2 injection 0.41 1.03 2nd N2 injection 0.35 0.91 Fig. 28 Top panel: average collected S1 charge per PMT as a function of the track-PMT distance for the different doping concentrations. For Fig. 29 PMT average waveform normalized to same amplitude in LAr each data-set, an exponential fit is performed (see results in Table 9). (black), LAr + Xe + N2 (red), after the 1st N2 injection (blue) and after Bottom panel: ratios between the data shown in the top panel. Each the 2nd N2 injection (magenta). Concentrations are described in Table 9 data-set is fitted with an exponential function (τtransfer ) and decay (τslow ) of the second bump from the Xe and a factor of ∼2 on events at 3 m. The extrapolation of this light. curve to short distances indicates an increase by a factor of The time constants obtained from the fits are shown in 1.5 at 2.2 m, as seen in Fig. 27 for the PMT-trigger muons, Table 10. No difference between PEN-foil and TPB-coated and no increase at 0 m, as expected due to the longer RSL. PMTs is found. The flat blue and magenta lines show that there is no depen- In summary, ProtoDUNE-DP data show that Xe doping is dence on the distance for the N2 injections, as seen also in a promising technique for large-scale detectors like DUNE Fig. 27. since it increases the collected light at large distances. With a The effect of xenon on the time profile of the waveforms small doping level of 5.8 ppm of Xe (and even with the pres- is also studied. Figure 29 shows the average waveforms for ence of 2.4 ppm of N2 ), an enhancement in the light detection a TPB-coated PMT in the different doping concentrations efficiency (100% increase for muons crossing at a distance described in Sect. 2 (pure LAr in black), normalized to the of 3–5 m from the PMTs) and a better uniformity (attenua- same amplitude. The average waveform is the result of adding tion length 50% longer) is measured. However, despite these waveforms for a PMT placed near the trigger PMT. The sec- advantages, it must be considered that the 35% amplitude ond bump in the red, blue and magenta waveforms (when Xe reduction observed in the fast signal could jeopardize the is present) is the late light at 150 nm and 178 nm, as explained efficiency of a light-based trigger. before. The profile of this second maximum changes with the N2 injections, as the energy transfer rate from argon to xenon 9 Conclusions atoms is altered due to the quenching by N2 . The average waveforms of Xe-doped LAr are fitted to the sum of three ProtoDUNE-DP is a 6×6×6 m3 LArTPC, operated at CERN exponential functions convolved with a Gaussian to account between 2019 and 2020 to demonstrate the dual-phase tech- for the PMT response, in a similar way as in Eq. (6). In nology at large scale for DUNE, a next generation long- this case, the first exponential describes the fast signal, and baseline neutrino experiment. The photon detection system the second and third exponential functions model the rise is composed of 36 8-inch cryogenic PMTs from Hamamatsu 123 618 Page 28 of 29 Eur. Phys. J. C (2022) 82:618 positioned at the bottom of the detector. The photon detection of N2 . However, it must be considered that the reduction system collected cosmic-ray data for 18 months in stable con- observed in the fast signal amplitude could compromise the ditions with all 36 PMTs in operation. The good performance performance of a light-based trigger. validates the photon detection system design for future long drift distance LArTPCs. Acknowledgements The ProtoDUNE-DP detector was constructed and operated on the CERN Neutrino Platform. We gratefully acknowl- ProtoDUNE-DP used PEN as a wavelength shifter for the edge the support of the CERN management, and the CERN EP, BE, first time in a large scale experiment and a comparison with TE, EN and IT Departments for NP04/ProtoDUNE-SP. This docu- the widely used TPB is carried out. TPB is estimated to be 3 ment was prepared by the DUNE collaboration using the resources of times more efficient than PEN. The observed light yield from the Fermi National Accelerator Laboratory (Fermilab), a U.S. Depart- ment of Energy, Office of Science, HEP User Facility. Fermilab is cosmic muons demonstrates that a system based exclusively managed by Fermi Research Alliance, LLC (FRA), acting under Con- on TPB as WLS would be needed to accomplish the DUNE tract No. DE-AC02-07CH11359. This work was supported by CNPq, low-energy physics program goals. Nonetheless, PEN can FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; be taken into account as an alternative when the detection CERN; MŠMT, Czech Republic; ERDF, H2020-EU and MSCA, Euro- pean Union; CNRS/IN2P3 and CEA, France; INFN, Italy; FCT, Por- efficiency is not critical compared to the benefits of easy tugal; NRF, South Korea; CAM, Fundación “La Caixa”, Junta de installation. Andalucía-FEDER, MICINN, and Xunta de Galicia, Spain; SERI In ProtoDUNE-DP, considering the field limitations, it is and SNSF, Switzerland; TÜBİTAK, Turkey; The Royal Society and found that at least 17% of the scintillation light detected in UKRI/STFC, United Kingdom; DOE and NSF, United States of Amer- ica. This research used resources of the National Energy Research the absence of a drift field comes from electron-ion recom- Scientific Computing Center (NERSC), a U.S. Department of Energy bination, verifying the expected trend from Birks’ law and Office of Science User Facility operated under Contract No. DE-AC02- in agreement with previous work. A decrease of τslow with 05CH11231. the drift field as reported in [35] is also observed. An expla- Data Availability Statement This manuscript has no associated data nation of this effect is provided in [51] taking into account or the data will not be deposited. [Authors’ comment: Data are stored the quenching of the long lived triplet states through the self- at CERN and Fermilab servers and could be provided upon request.] interaction with other triplet states or through the interactions with molecular argon ions. Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adaptation, The size of ProtoDUNE-DP allows for an unprecedented distribution and reproduction in any medium or format, as long as you study of the light propagation. An evaluation of the Rayleigh give appropriate credit to the original author(s) and the source, pro- scattering length is carried out by comparing the measured vide a link to the Creative Commons licence, and indicate if changes light signals with the light predicted by the MC simulation were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indi- testing two lengths (61.0 cm and 99.9 cm). The agreement cated otherwise in a credit line to the material. If material is not between data and the 99.9-cm MC sample is better than for included in the article’s Creative Commons licence and your intended the shorter scattering length. It is also concluded that at least use is not permitted by statutory regulation or exceeds the permit- 11% of the light detected by PMTs in the MC corresponds to ted use, you will need to obtain permission directly from the copy- right holder. To view a copy of this licence, visit http://creativecomm VUV-light reflected off the field cage, cryostat walls, cathode ons.org/licenses/by/4.0/. and ground grid. Funded by SCOAP3 . SCOAP3 supports the goals of the International The cosmic muon flux in ProtoDUNE-DP at ground level Year of Basic Sciences for Sustainable Development. is determined from the S1 signal rate detected by the PMTs and a cosmic-muon light simulation sample. The result, 148+8 2 −11 Hz/m , is consistent with other muon flux measure- ments in the literature [52,53]. References The electroluminescence light, S2, produced in the gas phase about 7 m away from the PMTs is observed in all 36 1. B. Abi et al., JINST 15(08), T08008 (2020). https://doi.org/10. 1088/1748-0221/15/08/T08008 PMTs implying a high efficiency for the ProtoDUNE-DP 2. B. Abi et al., Eur. Phys. J. C 80(10), 978 (2020). https://doi.org/ photon detection system. The detected SPE rate increases 10.1140/epjc/s10052-020-08456-z up to several MHz when there is S2 light production, clear 3. B. Abi et al., Eur. Phys. J. C 81(4), 322 (2021). https://doi.org/10. evidence that the S2 signals are an important and continu- 1140/epjc/s10052-021-09007-w 4. B. Abi et al., Eur. Phys. J. C 81(5), 423 (2021) ous contribution to the low-energy background in the PMT 5. B. Abi et al., JINST 15(08), T08010 (2020). https://doi.org/10. waveform. 1088/1748-0221/15/08/T08010 Finally, ProtoDUNE-DP data has demonstrated the impro- 6. B. Abi, et al., The DUNE Far Detector Interim Design Report, vement of the light detection efficiency and uniformity in Volume 3: Dual-Phase Module (2018). arXiv:1807.10340 7. L. Agostino, et al. LBNO-DEMO: Large-scale neutrino detector large LArTPCs, thanks to the Xe doping. A low doping level demonstrators for phased performance assesment in view of a long- of 5.8 ppm of Xe doubles the collected light at large distances baseline oscillation experiment, CERN-SPSC-2014-013, SPSC- (3–5 m from the PMTs) even with the presence of 2.4 ppm TDR-004 (2014). arXiv:1409.4405 123 Eur. Phys. J. C (2022) 82:618 Page 29 of 29 618 8. C. Cuesta, in 2019 European Physical Society Conference on High 36. C.F. Lastoria, Analysis of the scintillation light production and Energy Physics (2019). arXiv:1910.10115 propagation in the WA105 Dual-Phase demonstrator. Análisis de 9. B. Aimard et al., J. Instrum. 16(08), P08063 (2021). https://doi. la producción y propagación de la luz de centelleo en el detector org/10.1088/1748-0221/16/08/p08063 de doble-fase WA105 (2020). http://cds.cern.ch/record/2748990. 10. A. Chappuis, Study and simulation of the scintillation light pro- Presented 17 Dec 2020 duced and propagating in a dual phase liquid argon time projec- 37. E. Segreto, Phys. Rev. C 91(3), 035503 (2015). https://doi.org/10. tion chamber, in the context of the DUNE experiment. Theses, 1103/PhysRevC.91.035503 Université Grenoble Alpes (2018). https://tel.archives-ouvertes.fr/ 38. D. Whittington et al., JINST 11(05), P05016 (2016). https://doi. tel-02146587 org/10.1088/1748-0221/11/05/P05016 11. T. Heindl et al., EPL 91(6), 62002 (2010). https://doi.org/10.1209/ 39. E.L. Snider, G. Petrillo, J. Phys. Conf. Ser. 898(4), 042057 (2017). 0295-5075/91/62002 https://doi.org/10.1088/1742-6596/898/4/042057 12. A. Hitachi et al., Phys. Rev. B 27, 5279 (1983). https://doi.org/10. 40. S. Agostinelli et al., Nucl. Instrum. Methods A 506, 250 (2003). 1103/PhysRevB.27.5279 https://doi.org/10.1016/S0168-9002(03)01368-8 13. C. Cuesta et al., JINST 12, C12048 (2017). https://doi.org/10.1088/ 41. D. Heck, J. Knapp, J.N. Capdevielle, G. Schatz, T. Thouw (1998) 1748-0221/12/12/C12048 42. C. Forti, H. Bilokon, B. d’Ettorre Piazzoli, T.K. Gaisser, L. Satta, 14. D. Belver et al., JINST 13, T10006 (2018). (8/1748- T. Stanev, Phys. Rev. D 42, 3668 (1990). https://doi.org/10.1103/ 0221/13/10/T10006) PhysRevD.42.3668 15. D. Belver et al., JINST 15(09), P09023 (2020). https://doi.org/10. 43. T.T. Böhlen, F. Cerutti, M.P.W. Chin, A. Fassò, A. Ferrari, P.G. 1088/1748-0221/15/09/P09023 Ortega, A. Mairani, P.R. Sala, G. Smirnov, V. Vlachoudis, Nucl. 16. D. Belver et al., JINST 14(04), T04001 (2019). https://doi.org/10. Data Sheets 120, 211 (2014). https://doi.org/10.1016/j.nds.2014. 1088/1748-0221/14/04/T04001 07.049 17. J.S. Kapustinsky et al., NIMA 241, 612 (1985). https://doi.org/10. 44. B.J.P. Jones, C.S. Chiu, J.M. Conrad, C.M. Ignarra, T. Katori, 1016/0168-9002(85)90622-9 M. Toups, JINST 8, P07011 (2013). https://doi.org/10.1088/ 18. Comsol multiphysics® v. 5.4. www.comsol.com 1748-0221/8/07/P07011 (Erratum: JINST 8, E09001 (2013)) 19. B. Abi et al., JINST 15(12), P12004 (2020). https://doi.org/10. 45. M. Babicz et al., JINST 15(09), P09009 (2020). https://doi.org/10. 1088/1748-0221/15/12/P12004 1088/1748-0221/15/09/P09009 20. D. Belver et al., IEEE Trans. Nucl. Sci. 68(9), 2334 (2021). https:// 46. E. Grace, A. Butcher, J. Monroe, J.A. Nikkel, Nucl. Instrum. Meth- doi.org/10.1109/TNS.2021.3095355 ods Phys. Res. Sect. A Accel. Spectrom Detect. Assoc. Equip. 867, 21. V1740-64 channel 12 bit 62.5 ms/s digitizer-caen. https://www. 204 (2017). https://doi.org/10.1016/j.nima.2017.06.031 caen.it/products/v1740/. Accessed 05 Oct 2021 47. M. Antonello, et al., Technical Report ICARUS-TM/06-03 (2006) 22. P. Benetti et al., Nucl. Instrum. Methods A 574, 83 (2007). https:// 48. B. Zatschler, Attenuation of the scintillation light in liquid argon doi.org/10.1016/j.nima.2007.01.106 and investigation of the double beta decay of 76 Ge into excited 23. A.S. Barabash, R.R. Saakyan, V.I. Umatov, J. Phys. Conf. Ser. states of 76 Se in the GERDA experiment. Ph.D. thesis, Dresden, 718(6), 062004 (2016). https://doi.org/10.1088/1742-6596/718/6/ Tech. U., TU, Dresden (main) (2020) 062004 49. S. Kubota et al., Phys. Rev. B 20, 3486 (1979). https://doi.org/10. 24. X. Luo, F. Cavanna, JINST 15(03), C03034 (2020). https://doi.org/ 1103/PhysRevB.20.3486 10.1088/1748-0221/15/03/C03034 50. P. Agnes et al., Phys. Rev. D 97(11), 112005 (2018). https://doi. 25. M. Bonesini, T. Cervi, A. Falcone, U. Kose, R. Mazza, A. Mene- org/10.1103/PhysRevD.97.112005 golli, C. Montanari, M. Nessi, M. Prata, A. Rappoldi, G. Raselli, M. 51. E. Segreto, Phys. Rev. D 103(4), 043001 (2021). https://doi.org/ Rossella, M. Spanu, M. Torti, W. Vollenberg, A. Zani, J. Instrum. 10.1103/PhysRevD.103.043001 13(12), P12020 (2018). https://doi.org/10.1088/1748-0221/13/12/ 52. P. Abratenko et al., J. Instrum. 16(04), P04004 (2021). https://doi. p12020 org/10.1088/1748-0221/16/04/p04004 26. Polyethylene naphthalate (pen)-film-material information. http:// 53. B. Mitrica, R. Margineanu, S. Stoica, M. Petcu, I. Brancus, A. Jipa, www.goodfellow.com/E/Polyethylene-naphthalate-Film.html. I. Lazanu, O. Sima, A. Haungs, H. Rebel, M. Petre, G. Toma, A. Accessed 05 Oct 2021 Saftoiu, D. Stanca, A. Apostu, C. Gomoiu, Nucl. Instrum. Methods 27. D. Mary et al., J. Phys. D Appl. Phys. 30, 171 (1997). https://doi. Phys. Res. Sect. A Accel. Spectrom. Detect. Assoc. Equip. 654(1), org/10.1088/0022-3727/30/2/004 176 (2011) 28. R. Francini et al., JINST 8(09), P09006 (2013). https://doi.org/10. 54. S. Kubota, M. Hishida, S. Himi, J. Suzuki, J. Ruan, Nucl. Instrum. 1088/1748-0221/8/09/p09006 Methods Phys. Res. Sect. A Accel. Spectrom. Detect. Assoc. Equip. 29. Y. Abraham, et al. Wavelength-shifting performance of polyethy- 327(1), 71 (1993) lene naphthalate films in a liquid argon environment (2021). 55. A. Neumeier, T. Dandl, T. Heindl, A. Himpsl, L. Oberauer, W. arXiv:2103.03232 Potzel, S. Roth, S. Schönert, J. Wieser, A. Ulrich, EPL (Europhysics 30. A. Bueno, J. Lozano, A.J. Melgarejo, F.J. Muñoz, J.L. Navarro, S. Letters) 109(1), 12001 (2015). https://doi.org/10.1209/0295-5075/ Navas, A.G. Ruiz, J. Instrum. 3(01), P01006 (2008). https://doi. 109/12001 org/10.1088/1748-0221/3/01/p01006 56. A. Neumeier, T. Dandl, A. Himpsl, L. Oberauer, W. Potzel, S. 31. Q. Zhao, M. Guan, P. Zhang, C. Yang, J. Li, Y. Wei, L. Wang, Y. Schönert, A. Ulrich, EPL (Europhysics Letters) 111(1), 12001 Gan, W. Xiong, J. Instrum. 16(06), T06014 (2021). https://doi.org/ (2015). https://doi.org/10.1209/0295-5075/111/12001 10.1088/1748-0221/16/06/t06014 57. R. Acciarri et al., Nuc. Phys. B Proc. Suppl. 197, 70 (2009). https:// 32. C. Benson et al., Eur. Phys. J. C 78, 329 (2018). https://doi.org/10. doi.org/10.1016/j.nuclphysbps.2009.10.037 1140/epjc/s10052-018-5807-z 33. J.R. Graybill, C.B. Shahi, M.A. Coplan, A.K. Thompson, R.E. Vest, C.W. Clark, Appl. Opt. 59(4), 1217 (2020). http://ao.osa.org/ abstract.cfm?URI=ao-59-4-1217 34. C.H. Lally, G.J. Davies, W.G. Jones, N.J.T. Smith (1995) 35. B. Aimard et al., JINST 16(03), P03007 (2021). https://doi.org/10. 1088/1748-0221/16/03/P03007 123