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. 2016 Sep 24;76(9):517. doi: 10.1140/epjc/s10052-016-4344-x

Search for supersymmetry in a final state containing two photons and missing transverse momentum in s = 13 TeV pp collisions at the LHC using the ATLAS detector

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Cerutti 18, M Cerv 45, A Cervelli 20, S A Cetin 24, A Chafaq 176, D Chakraborty 138, S K Chan 81, Y L Chan 86, P Chang 217, J D Chapman 43, D G Charlton 21, A Chatterjee 72, C C Chau 207, C A Chavez Barajas 198, S Che 141, S Cheatham 213,215, A Chegwidden 119, S Chekanov 8, S V Chekulaev 208, G A Chelkov 93, M A Chelstowska 118, C Chen 92, H Chen 36, K Chen 197, S Chen 51, S Chen 204, X Chen 54, Y Chen 95, H C Cheng 118, H J Cheng 49, Y Cheng 46, A Cheplakov 93, E Cheremushkina 168, R Cherkaoui El Moursli 180, V Chernyatin 1,36, E Cheu 9, L Chevalier 181, V Chiarella 70, G Chiarelli 155,156, G Chiodini 101, A S Chisholm 45, A Chitan 38, M V Chizhov 93, K Choi 89, A R Chomont 55, S Chouridou 11, B K B Chow 129, V Christodoulou 107, D Chromek-Burckhart 45, J Chudoba 165, A J Chuinard 116, J J Chwastowski 62, L Chytka 145, G Ciapetti 170,171, A K Ciftci 4, D Cinca 66, V Cindro 104, I A Cioara 29, C Ciocca 27,28, A Ciocio 18, F Cirotto 133,134, Z H Citron 223, M Citterio 120, M Ciubancan 38, A Clark 72, B L Clark 81, M R Clark 56, P J Clark 69, R N Clarke 18, C Clement 194,195, Y Coadou 114, M Cobal 213,215, A Coccaro 72, J Cochran 92, L Colasurdo 136, B Cole 56, A P Colijn 137, J Collot 80, T Colombo 212, G Compostella 130, P Conde Muiño 158,159, E Coniavitis 71, S H Connell 192, I A Connelly 106, V Consorti 71, S Constantinescu 38, G Conti 45, F Conventi 133, M Cooke 18, B D Cooper 107, A M Cooper-Sarkar 150, K J R Cormier 207, T Cornelissen 226, M Corradi 170,171, F Corriveau 116, A Corso-Radu 212, A Cortes-Gonzalez 45, G Cortiana 130, G Costa 120, M J Costa 218, D Costanzo 184, G Cottin 43, G Cowan 106, B E Cox 113, K Cranmer 140, S J Crawley 78, G Cree 44, S Crépé-Renaudin 80, F Crescioli 109, W A Cribbs 194,195, M Crispin Ortuzar 150, M Cristinziani 29, V Croft 136, G Crosetti 58,59, A Cueto 111, T Cuhadar Donszelmann 184, J Cummings 227, M Curatolo 70, J Cúth 112, H Czirr 186, P Czodrowski 3, G D’amen 27,28, S D’Auria 78, M D’Onofrio 103, M J Da Cunha Sargedas De Sousa 158,159, C Da Via 113, W Dabrowski 60, T Dado 189, T Dai 118, O Dale 17, F Dallaire 124, C Dallapiccola 115, M Dam 57, J R Dandoy 46, N P Dang 71, A C Daniells 21, N S Dann 113, M Danninger 219, M Dano Hoffmann 181, V Dao 71, G Darbo 73, S Darmora 10, J Dassoulas 3, A Dattagupta 146, W Davey 29, C David 220, T Davidek 167, M Davies 202, P Davison 107, E Dawe 117, I Dawson 184, K De 10, R de Asmundis 133, A De Benedetti 143, S De Castro 27,28, S De Cecco 109, N De Groot 136, P de Jong 137, H De la Torre 119, F De Lorenzi 92, A De Maria 79, D De Pedis 170, A De Salvo 170, U De Sanctis 198, A De Santo 198, J B De Vivie De Regie 147, W J Dearnaley 100, R Debbe 36, C Debenedetti 182, D V Dedovich 93, N Dehghanian 3, I Deigaard 137, M Del Gaudio 58,59, J Del Peso 111, T Del Prete 155,156, D Delgove 147, F Deliot 181, C M Delitzsch 72, A Dell’Acqua 45, L Dell’Asta 30, M Dell’Orso 155,156, M Della Pietra 133, D della Volpe 72, M Delmastro 7, P A Delsart 80, D A DeMarco 207, S Demers 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Duffield 18, L Duflot 147, M Dührssen 45, M Dumancic 223, M Dunford 82, H Duran Yildiz 4, M Düren 77, A Durglishvili 76, D Duschinger 67, B Dutta 65, M Dyndal 65, C Eckardt 65, K M Ecker 130, R C Edgar 118, N C Edwards 69, T Eifert 45, G Eigen 17, K Einsweiler 18, T Ekelof 216, M El Kacimi 178, V Ellajosyula 114, M Ellert 216, S Elles 7, F Ellinghaus 226, A A Elliot 220, N Ellis 45, J Elmsheuser 36, M Elsing 45, D Emeliyanov 169, Y Enari 204, O C Endner 112, J S Ennis 221, J Erdmann 66, A Ereditato 20, G Ernis 226, J Ernst 2, M Ernst 36, S Errede 217, E Ertel 112, M Escalier 147, H Esch 66, C Escobar 157, B Esposito 70, A I Etienvre 181, E Etzion 202, H Evans 89, A Ezhilov 154, M Ezzi 180, F Fabbri 27,28, L Fabbri 27,28, G Facini 46, R M Fakhrutdinov 168, S Falciano 170, R J Falla 107, J Faltova 45, Y Fang 49, M Fanti 120,121, A Farbin 10, A Farilla 174, C Farina 157, E M Farina 151,152, T Farooque 15, S Farrell 18, S M Farrington 221, P Farthouat 45, F Fassi 180, P Fassnacht 45, D 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Freeborn 107, S M Fressard-Batraneanu 45, F Friedrich 67, D Froidevaux 45, J A Frost 150, C Fukunaga 205, E Fullana Torregrosa 112, T Fusayasu 131, J Fuster 218, C Gabaldon 80, O Gabizon 226, A Gabrielli 27,28, A Gabrielli 18, G P Gach 60, S Gadatsch 45, S Gadomski 106, G Gagliardi 73,74, L G Gagnon 124, P Gagnon 89, C Galea 136, B Galhardo 158,160, E J Gallas 150, B J Gallop 169, P Gallus 166, G Galster 57, K K Gan 141, J Gao 50, Y Gao 69, Y S Gao 188, F M Garay Walls 69, C García 218, J E García Navarro 218, M Garcia-Sciveres 18, R W Gardner 46, N Garelli 188, V Garonne 149, A Gascon Bravo 65, K Gasnikova 65, C Gatti 70, A Gaudiello 73,74, G Gaudio 151, L Gauthier 124, I L Gavrilenko 125, C Gay 219, G Gaycken 29, E N Gazis 12, Z Gecse 219, C N P Gee 169, Ch Geich-Gimbel 29, M Geisen 112, M P Geisler 82, K Gellerstedt 194,195, C Gemme 73, M H Genest 80, C Geng 50, S Gentile 170,171, C Gentsos 203, S George 106, D Gerbaudo 15, A Gershon 202, S Ghasemi 186, M Ghneimat 29, B Giacobbe 27, S Giagu 170,171, P Giannetti 155,156, B Gibbard 36, S M Gibson 106, M Gignac 219, M Gilchriese 18, T P S Gillam 43, D Gillberg 44, G Gilles 226, D M Gingrich 3, N Giokaris 11, M P Giordani 213,215, F M Giorgi 27, F M Giorgi 19, P F Giraud 181, P Giromini 81, D Giugni 120, F Giuli 150, C Giuliani 130, M Giulini 83, B K Gjelsten 149, S Gkaitatzis 203, I Gkialas 203, E L Gkougkousis 147, L K Gladilin 128, C Glasman 111, J Glatzer 71, P C F Glaysher 69, A Glazov 65, M Goblirsch-Kolb 31, J Godlewski 62, S Goldfarb 117, T Golling 72, D Golubkov 168, A Gomes 158,159,161, R Gonçalo 158, J Goncalves Pinto Firmino Da Costa 181, G Gonella 71, L Gonella 21, A Gongadze 93, S González de la Hoz 218, G Gonzalez Parra 15, S Gonzalez-Sevilla 72, L Goossens 45, P A Gorbounov 126, H A Gordon 36, I Gorelov 135, B Gorini 45, E Gorini 101,102, A Gorišek 104, E Gornicki 62, A T Goshaw 68, C Gössling 66, M I Gostkin 93, C R Goudet 147, D Goujdami 178, A G Goussiou 183, N Govender 192, E Gozani 201, L Graber 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Kim 210, Y K Kim 46, N Kimura 203, O M Kind 19, B T King 103, M King 218, J Kirk 169, A E Kiryunin 130, T Kishimoto 204, D Kisielewska 60, F Kiss 71, K Kiuchi 210, O Kivernyk 181, E Kladiva 190, M H Klein 56, M Klein 103, U Klein 103, K Kleinknecht 112, P Klimek 138, A Klimentov 36, R Klingenberg 66, J A Klinger 184, T Klioutchnikova 45, E -E Kluge 82, P Kluit 137, S Kluth 130, J Knapik 62, E Kneringer 90, E B F G Knoops 114, A Knue 78, A Kobayashi 204, D Kobayashi 206, T Kobayashi 204, M Kobel 67, M Kocian 188, P Kodys 167, N M Koehler 130, T Koffas 44, E Koffeman 137, T Koi 188, H Kolanoski 19, M Kolb 83, I Koletsou 7, A A Komar 1,125, Y Komori 204, T Kondo 94, N Kondrashova 65, K Köneke 71, A C König 136, T Kono 94, R Konoplich 140, N Konstantinidis 107, R Kopeliansky 89, S Koperny 60, L Köpke 112, A K Kopp 71, K Korcyl 62, K Kordas 203, A Korn 107, A A Korol 139, I Korolkov 15, E V Korolkova 184, O Kortner 130, S Kortner 130, T Kosek 167, V V Kostyukhin 29, A Kotwal 68, A 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218, E Ladygin 93, R Lafaye 7, B Laforge 109, T Lagouri 227, S Lai 79, S Lammers 89, W Lampl 9, E Lançon 181, U Landgraf 71, M P J Landon 105, M C Lanfermann 72, V S Lang 82, J C Lange 15, A J Lankford 212, F Lanni 36, K Lantzsch 29, A Lanza 151, S Laplace 109, C Lapoire 45, J F Laporte 181, T Lari 120, F Lasagni Manghi 27,28, M Lassnig 45, P Laurelli 70, W Lavrijsen 18, A T Law 182, P Laycock 103, T Lazovich 81, M Lazzaroni 120,121, B Le 117, O Le Dortz 109, E Le Guirriec 114, E P Le Quilleuc 181, M LeBlanc 220, T LeCompte 8, F Ledroit-Guillon 80, C A Lee 36, S C Lee 200, L Lee 1, B Lefebvre 116, G Lefebvre 109, M Lefebvre 220, F Legger 129, C Leggett 18, A Lehan 103, G Lehmann Miotto 45, X Lei 9, W A Leight 44, A Leisos 203, A G Leister 227, M A L Leite 35, R Leitner 167, D Lellouch 223, B Lemmer 79, K J C Leney 107, T Lenz 29, B Lenzi 45, R Leone 9, S Leone 155,156, C Leonidopoulos 69, S Leontsinis 12, G Lerner 198, C Leroy 124, A A J Lesage 181, C G Lester 43, M Levchenko 154, J 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124, M J Shochet 46, S Shojaii 120,121, D R Shope 143, S Shrestha 141, E Shulga 127, M A Shupe 9, P Sicho 165, A M Sickles 217, P E Sidebo 196, O Sidiropoulou 225, D Sidorov 144, A Sidoti 27,28, F Siegert 67, Dj Sijacki 16, J Silva 158,161, S B Silverstein 194, V Simak 166, Lj Simic 16, S Simion 147, E Simioni 112, B Simmons 107, D Simon 55, M Simon 112, P Sinervo 207, N B Sinev 146, M Sioli 27,28, G Siragusa 225, S Yu Sivoklokov 128, J Sjölin 194,195, M B Skinner 100, H P Skottowe 81, P Skubic 143, M Slater 21, T Slavicek 166, M Slawinska 137, K Sliwa 211, R Slovak 167, V Smakhtin 223, B H Smart 7, L Smestad 17, J Smiesko 189, S Yu Smirnov 127, Y Smirnov 127, L N Smirnova 128, O Smirnova 110, M N K Smith 56, R W Smith 56, M Smizanska 100, K Smolek 166, A A Snesarev 125, I M Snyder 146, S Snyder 36, R Sobie 220, F Socher 67, A Soffer 202, D A Soh 200, G Sokhrannyi 104, C A Solans Sanchez 45, M Solar 166, E Yu Soldatov 127, U Soldevila 218, A A Solodkov 168, A Soloshenko 93, O V 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Strom 146, R Stroynowski 63, A Strubig 136, S A Stucci 36, B Stugu 17, N A Styles 65, D Su 188, J Su 157, S Suchek 82, Y Sugaya 148, M Suk 166, V V Sulin 125, S Sultansoy 6, T Sumida 96, S Sun 81, X Sun 49, J E Sundermann 71, K Suruliz 198, G Susinno 58,59, M R Sutton 198, S Suzuki 94, M Svatos 165, M Swiatlowski 46, I Sykora 189, T Sykora 167, D Ta 71, C Taccini 174,175, K Tackmann 65, J Taenzer 207, A Taffard 212, R Tafirout 208, N Taiblum 202, H Takai 36, R Takashima 97, T Takeshita 185, Y Takubo 94, M Talby 114, A A Talyshev 139, K G Tan 117, J Tanaka 204, M Tanaka 206, R Tanaka 147, S Tanaka 94, R Tanioka 95, B B Tannenwald 141, S Tapia Araya 48, S Tapprogge 112, S Tarem 201, G F Tartarelli 120, P Tas 167, M Tasevsky 165, T Tashiro 96, E Tassi 58,59, A Tavares Delgado 158,159, Y Tayalati 180, A C Taylor 135, G N Taylor 117, P T E Taylor 117, W Taylor 209, F A Teischinger 45, P Teixeira-Dias 106, K K Temming 71, D Temple 187, H Ten Kate 45, P K Teng 200, J J Teoh 148, F Tepel 226, S Terada 94, K Terashi 204, J Terron 111, S Terzo 15, M Testa 70, R J Teuscher 207, T Theveneaux-Pelzer 114, J P Thomas 21, J Thomas-Wilsker 106, E N Thompson 56, P D Thompson 21, A S Thompson 78, L A Thomsen 227, E Thomson 153, M Thomson 43, M J Tibbetts 18, R E Ticse Torres 114, V O Tikhomirov 125, Yu A Tikhonov 139, S Timoshenko 127, P Tipton 227, S Tisserant 114, K Todome 206, T Todorov 1,7, S Todorova-Nova 167, J Tojo 98, S Tokár 189, K Tokushuku 94, E Tolley 81, L Tomlinson 113, M Tomoto 132, L Tompkins 188, K Toms 135, B Tong 81, P Tornambe 71, E Torrence 146, H Torres 187, E Torró Pastor 183, J Toth 114, F Touchard 114, D R Tovey 184, T Trefzger 225, A Tricoli 36, I M Trigger 208, S Trincaz-Duvoid 109, M F Tripiana 15, W Trischuk 207, B Trocmé 80, A Trofymov 65, C Troncon 120, M Trottier-McDonald 18, M Trovatelli 220, L Truong 213,215, M Trzebinski 62, A Trzupek 62, J C-L Tseng 150, P V Tsiareshka 122, G Tsipolitis 12, N Tsirintanis 11, S Tsiskaridze 15, V Tsiskaridze 71, E G Tskhadadze 75, K M Tsui 86, I I Tsukerman 126, V Tsulaia 18, S Tsuno 94, D Tsybychev 197, Y Tu 87, A Tudorache 38, V Tudorache 38, A N Tuna 81, S A Tupputi 27,28, S Turchikhin 93, D Turecek 166, D Turgeman 223, R Turra 120,121, P M Tuts 56, M Tyndel 169, G Ucchielli 27,28, I Ueda 204, M Ughetto 194,195, F Ukegawa 210, G Unal 45, A Undrus 36, G Unel 212, F C Ungaro 117, Y Unno 94, C Unverdorben 129, J Urban 190, P Urquijo 117, P Urrejola 112, G Usai 10, L Vacavant 114, V Vacek 166, B Vachon 116, C Valderanis 129, E Valdes Santurio 194,195, N Valencic 137, S Valentinetti 27,28, A Valero 218, L Valery 15, S Valkar 167, J A Valls Ferrer 218, W Van Den Wollenberg 137, P C Van Der Deijl 137, H van der Graaf 137, N van Eldik 201, P van Gemmeren 8, J Van Nieuwkoop 187, I van Vulpen 137, M C van Woerden 45, M Vanadia 170,171, W Vandelli 45, R Vanguri 153, A Vaniachine 168, P Vankov 137, G Vardanyan 228, R Vari 170, E W Varnes 9, T Varol 63, D Varouchas 109, A Vartapetian 10, K E Varvell 199, J 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PMCID: PMC5332019  PMID: 28303085

Abstract

A search has been made for supersymmetry in a final state containing two photons and missing transverse momentum using the ATLAS detector at the Large Hadron Collider. The search makes use of 3.2fb-1 of proton-proton collision data collected at a centre-of-mass energy of 13 TeV in 2015. Using a combination of data-driven and Monte-Carlo-based approaches, the Standard Model background is estimated to be 0.27-0.10+0.22 events. No events are observed in the signal region; considering the expected background and its uncertainty, this observation implies a model-independent 95 % CL upper limit of 0.93 fb (3.0 events) on the visible cross section due to physics beyond the Standard Model. In the context of a generalized model of gauge-mediated supersymmetry breaking with a bino-like next-to-lightest supersymmetric particle, this leads to a lower limit of 1650 GeV on the mass of a degenerate octet of gluino states, independent of the mass of the lighter bino-like neutralino.

Introduction

This paper presents a search for signatures of supersymmetry in events containing two energetic isolated photons and large missing transverse momentum (with magnitude denoted ETmiss) in 3.2fb-1 of proton–proton (pp) collision data at s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider (LHC) in 2015. The results are interpreted in the context of general gauge mediation (GGM) [1, 2] models that include the production of supersymmetric partners of Standard Model (SM) particles that possess color charge. In all models of GGM, the lightest supersymmetric particle (LSP) is the gravitino G~ (the partner of the hypothetical quantum of the gravitational field), with a mass significantly less than 1 GeV. In the GGM model considered here, the decay of the supersymmetric states produced in pp collisions would proceed through the next-to-lightest supersymmetric particle (NLSP), which would then decay to the G~ LSP and one or more SM particles, with a high probability of decay into γ + G~. All accessible supersymmetric states with the exception of the G~ are assumed to be short-lived, leading to prompt production of SM particles that would be observed in the ATLAS detector. These results extend those of prior studies with 8 TeV collision data from Run 1 by the ATLAS [3] and CMS [4] experiments.

Supersymmetry (SUSY) [510] introduces a symmetry between fermions and bosons, resulting in a SUSY particle (sparticle) with identical quantum numbers, with the exception of a difference of half a unit of spin relative to its corresponding SM partner. If SUSY were an exact symmetry of nature, each sparticle would have a mass equal to that of its SM partner. Since no sparticles have yet been observed, SUSY would have to be a broken symmetry. Assuming R-parity conservation [11], sparticles are produced in pairs. These would then decay through cascades involving other sparticles until the stable, undetectable LSP is produced, leading to a final state with significant ETmiss.

Experimental signatures of gauge-mediated supersymmetry-breaking models [1214] are largely determined by the nature of the NLSP. For GGM, the NLSP is often formed from an admixture of any of the SUSY partners of the electroweak gauge and Higgs boson states. In this study the NLSP, assumed to be electrically neutral and purely bino-like (the SUSY partner of the SM U(1) gauge boson), is the lightest gaugino state χ~10. In this case, the final decay in each of the two cascades in a GGM event would be predominantly χ~10γ+G~, leading to final states with γγ+ETmiss.

In addition to the bino-like χ~10 NLSP, a degenerate octet of gluinos (the SUSY partner of the SM gluon) is taken to be potentially accessible with 13 TeV pp collisions. Both the gluino and χ~10 masses are considered to be free parameters, with the χ~10 mass constrained to be less than that of the gluino. All other SUSY masses are set to values that preclude their production in 13 TeV pp collisions. This results in a SUSY production process that proceeds through the creation of pairs of gluino states, each of which subsequently decays via a virtual squark (the 12 squark flavour/chirality eigenstates are taken to be fully degenerate) to a quark–antiquark pair plus the NLSP neutralino. Additional SM objects (jets, leptons, photons) may be produced in these cascades. The χ~10 branching fraction to γ + G~ is 100 % for mχ~100 and approaches cos2θW for mχ~10mZ, with the remainder of the χ~10 sample decaying to Z + G~. For all χ~10 masses, then, the branching fraction is dominated by the photonic decay, leading to the diphoton-plus-ETmisssignature. For this model with a bino-like NLSP, a typical production and decay channel for strong (gluino) production is exhibited in Fig. 1. Finally, it should be noted that the phenomenology relevant to this search has a negligible dependence on the ratio tanβ of the two SUSY Higgs-doublet vacuum expectation values; for this analysis tanβ is set to 1.5.

Fig. 1.

Fig. 1

Typical production and decay-chain processes for the gluino-pair production GGM model for which the NLSP is a bino-like neutralino

Samples of simulated processes

For the GGM models under study, the SUSY mass spectra and branching fractions are calculated using SUSPECT 2.41 [15] and SDECAY 1.3b [16], respectively, inside the package SUSY-HIT 1.3 [17]. The Monte Carlo (MC) SUSY signal samples are produced using Herwig++ 2.7.1 [18] with CTEQ6L1 parton distribution functions (PDFs) [19]. Signal cross sections are calculated to next-to-leading order (NLO) in the strong coupling constant, including, for the case of strong production, the resummation of soft gluon emission at next-to-leading-logarithmic accuracy (NLO+NLL) [2024]. The nominal cross section and its uncertainty are taken from an envelope of cross-section predictions using different PDF sets and factorization and renormalization scales [25]. At fixed centre-of-mass energy, SUSY production cross sections decrease rapidly with increasing SUSY particle mass. At s=13 TeV, the gluino-pair production cross section is approximately 25 fb for a gluino mass of 1.4 TeV and falls to below 1 fb for a gluino mass of 2.0 TeV.

While most of the backgrounds to the GGM models under examination are estimated through the use of control samples selected from data, as described below, the extrapolation from control regions (CRs) to the signal region (SR) depends on simulated samples, as do the optimization studies. Diphoton, photon+jet, Wγ, Zγ, Wγγ and Zγγ SM processes are generated using the SHERPA 2.1.1 simulation package [26], making use of the CT10 PDFs [27]. The matrix elements are calculated with up to three parton emissions at leading order (four in the case of photon+jet samples) and merged with the SHERPA parton shower [28] using the ME+PS@LO prescription [29]. The tt¯γ process is generated using MadGraph5_aMC@NLO [30] with the CTEQ6L1 PDFs [19], in conjunction with PYTHIA 8.186 [31] with the NNPDF2.3LO PDF set [32, 33] and the A14 set [34] of tuned parameters.

All simulated samples are processed with a full ATLAS detector simulation [35] based on GEANT4 [36]. The effect of additional pp interactions per bunch crossing (“pile-up”) as a function of the instantaneous luminosity is taken into account by overlaying simulated minimum-bias events according to the observed distribution of the number of pile-up interactions in data, with an average of 13 interactions per event.

ATLAS detector

The ATLAS experiment records pp collision data with a multipurpose detector [37] that has a forward-backward symmetric cylindrical geometry and nearly 4π solid angle coverage. Closest to the beam line are solid-state tracking devices comprising layers of silicon-based pixel and strip detectors covering η<2.5 and straw-tube detectors covering η<2.0, located inside a thin superconducting solenoid that provides a 2T magnetic field. Outside of this “inner detector”, fine-grained lead/liquid-argon electromagnetic (EM) calorimeters provide coverage over η<3.2 for the measurement of the energy and direction of electrons and photons. A presampler, covering η<1.8, is used to correct for energy lost upstream of the EM calorimeter. A steel/scintillator-tile hadronic calorimeter covers the region |η|<1.7, while a copper/liquid-argon medium is used for hadronic calorimeters in the end cap region 1.5<|η|<3.2. In the forward region 3.2<|η|<4.9 liquid-argon calorimeters with copper and tungsten absorbers measure the electromagnetic and hadronic energy. A muon spectrometer consisting of three superconducting toroidal magnet systems, each comprising eight toroidal coils, tracking chambers, and detectors for triggering, surrounds the calorimeter system. The muon system reconstructs penetrating tracks over a range |η|<2.7 and provides input to the trigger system over a range |η|<2.4. A two-level trigger system [38] is used to select events. The first-level trigger is implemented in hardware and uses a subset of the detector information to reduce the accepted rate to less than 100 kHz. This is followed by a software-based ’high-level’ trigger (HLT) that reduces the recorded event rate to approximately 1 kHz.

Event reconstruction

Primary vertices are formed from sets of two or more tracks, each with transverse momentum pTtrack> 400 MeV, that are mutually consistent with having originated at the same three-dimensional point within the luminous region of the colliding proton beams. When more than one such primary vertex is found, the vertex with the largest sum of the squared transverse momenta of the associated tracks is chosen.

Electron candidates are reconstructed from EM calorimeter energy clusters consistent in transverse shape and longitudinal development with having arisen from the impact of an electromagnetic particle (electron or photon) upon the face of the calorimeter. For the object to be considered an electron, it is required to match a track identified by a reconstruction algorithm optimized for recognizing charged particles with a high probability of bremsstrahlung [39]. The energy of the electron candidate is determined from the EM cluster, while its direction is determined from the associated reconstructed track. Electron candidates are required to have pT>25GeV and |η|<2.37, and to be outside the transition region 1.37<η<1.52 between the central and forward portions of the EM calorimeter. Finally, the electron track is required to be consistent with originating from the primary vertex in both the r-z and r-ϕ planes. Further details of the reconstruction of electrons can be found in Refs. [40] and [41].

Electromagnetic clusters are classified as photon candidates provided that they either have no matched track or have one or more matched tracks consistent with having arisen from a photon conversion. Based on the characteristics of the longitudinal and transverse shower development in the EM calorimeter, photons are classified as “loose” or “tight”, with the tight requirements leading to a more pure but less efficienct selection of photons relative to that of the loose requirements [42]. Photon candidates are required to have pT>25GeV, to be within η<2.37, and to be outside the transition region 1.37<η<1.52. Additionally, an isolation requirement is imposed: after correcting for contributions from pile-up and the deposition ascribed to the photon itself, the energy within a cone of ΔR=0.4 around the cluster barycentre is required to be less than 2.45GeV+0.022×pTγ, where pTγ is the transverse momentum of the cluster. In the case that an EM calorimeter deposition identified as a photon overlaps the cluster of an identified electron within a cone of ΔR=0.4, the photon candidate is discarded and the electron candidate is retained. Further details of the reconstruction of photons can be found in Ref. [42].

Muon candidates make use of reconstructed tracks from the inner detector as well as information from the muon system [43]. Muons are required to be either “combined”, for which the muon is reconstructed independently in both the muon spectrometer and the inner detector and then combined, or “segment-tagged”, for which the muon spectrometer is used to tag tracks as muons, without requiring a fully reconstructed candidate in the muon spectrometer. Muons are required to have pT>25GeV and |η|<2.7, with the muon track required to be consistent with originating from the primary vertex in both the r-z and r-ϕ planes.

Jets are reconstructed from three-dimensional energy clusters [44] in the electromagnetic and hadronic calorimeters using the anti-kt algorithm [45] with a radius parameter R = 0.4. Each cluster is calibrated to the electromagnetic scale prior to jet reconstruction. The reconstructed jets are then calibrated to particle level by the application of a jet energy scale derived from simulation and in situ corrections based on 8 TeV data [46, 47]. In addition, the expected average energy contribution from pile-up clusters is subtracted using a factor dependent on the jet area [46]. Track-based selection requirements are applied to reject jets with pT<60 GeV and |η|<2.4 that originate from pile-up interactions [48]. Once calibrated, jets are required to have pT> 40 GeV and |η|<2.8.

To resolve the ambiguity that arises when a photon is also reconstructed as a jet, if a jet and a photon are reconstructed within an angular distance ΔR=0.4 of one another, the photon is retained and the jet is discarded. If a jet and an electron are reconstructed within an angular distance ΔR=0.2 of one another, the electron is retained and the jet is discarded; if 0.2<ΔR<0.4 then the jet is retained and the electron is discarded. Finally, in order to suppress the reconstruction of muons arising from showers induced by jets, if a jet and a muon are found with ΔR<0.4 the jet is retained and the muon is discarded.

The missing transverse momentum pTmiss is defined as the negative vector sum of the pT of all reconstructed physics objects in the event, with an extra term added to account for soft energy in the event that is not associated with any of the objects. This “ETmiss soft term” is calculated from inner-detector tracks with pTabove 400 MeV matched to the primary vertex to make it less dependent upon pile-up contamination [49, 50]. The scalar observable ETmiss is defined to be the magnitude of the resulting pTmiss vector.

Several additional observables are defined to help in the discrimination of SM backgrounds from potential GGM signals. The total visible transverse energy, HT, is calculated as the scalar sum of the transverse momenta of the reconstructed photons and any additional leptons and jets in the event. The “effective mass”, meff, is defined as the scalar sum of HT and ETmiss. The minimum jet–pTmiss separation, Δϕmin(jet,pTmiss), is defined as the minimum azimuthal angle between the missing transverse momentum vector and the two leading (highest-pT) jets with pT>75 GeV in the event, if they are present. If no such jets exist, no requirement is placed on this observable.

Event selection

The data sample is selected by a HLT trigger requiring the presence of two loose photons, each with pT greater than 50 GeV. Offline, two tight photons with pT>75GeV are required. In order to ensure that ETmiss is measured well, events are removed from the data sample if they contain jets likely to be produced by beam backgrounds, cosmic rays or detector noise [51].

To exploit the significant undetectable transverse momentum carried away by the gravitinos, a requirement on ETmiss is imposed on the diphoton event sample. To take advantage of the high production energy scale associated with signal events near the expected reach of the analysis, an additional requirement on meff is applied. To further ensure the accurate reconstruction of ETmiss and to suppress backgrounds associated with the mismeasurement of hadronic jets, a requirement of Δϕmin(jet,pTmiss)>0.5 is imposed. Figure 2 shows the ETmiss and meff distributions of the diphoton sample after the application of requirements of pTγ>75 GeV on each selected photon and of Δϕmin(jet,pTmiss)>0.5, but with no requirements yet imposed on ETmiss and meff. Also shown are the expected contributions from SM processes, estimated using the combination of Monte Carlo and data-driven estimates discussed in Sect. 6.

Fig. 2.

Fig. 2

Distributions of ETmiss(left) and meff(right) for the diphoton sample after the application of requirements of pTγ>75 GeV on each selected photon and of Δϕmin(jet,pTmiss)>0.5, but with no requirements imposed on ETmiss and meff. The expected contributions from SM processes are estimated using the combination of Monte Carlo and data-driven estimates discussed in Sect. 6. Uncertainties (shaded bands for MC simulation, error bars for data) are statistical only. The yellow band represents the uncertainty in the data/SM ratio that arises from the statisical limitations of the estimates of the various expected sources of SM background. Also shown are the expected contributions from the GGM signal for the two benchmark points, (mg~,mχ~10)=(1500,1300) GeV and (mg~,mχ~10)=(1500,100) GeV. The final bin of each plot includes the ‘overflow’ contribution that lies above the nominal upper range of the plot

As discussed in Sect. 1, the GGM signal space is parameterized by the masses of the gluino (mg~) and bino-like NLSP (mχ~10). The sensitivity of this analysis was optimized for two signal scenarios near the expected reach in mg~: high and low neutralino-mass benchmark points were chosen with (mg~,mχ~10)=(1500,1300) GeV and (mg~,mχ~10)=(1500,100) GeV, respectively.

Based on background estimates derived from the MC samples described in Sect. 2, the selection requirements were optimized as a function of ETmiss, meff and pTγ by maximizing the expected discovery sensitivity of the analysis, for each of the two signal benchmark points. The selected values of the minimum requirements on all three optimization parameters were found to be very similar for the low and high neutralino-mass benchmark points, leading to the definition of a single signal region (SR). The selection requirements for this SR are shown in Table 1.

Table 1.

Requirements defining the signal region (SR) and the Wγγ CR referred to in Sect. 6

SR Wγγ CR
2 Tight photons with pT>75 GeV 2 Tight photons with pT>50 GeV
1 e or μ with pT>25 GeV
Δϕmin(jet,pTmiss)>0.5 Δϕmin(jet,pTmiss)>0.5
ETmiss>175 GeV 50<ETmiss<175 GeV
meff>1500 GeV N(jets)<3
meγ 83–97 GeV

Background estimation

Processes that contribute to the Standard Model background of diphoton final states can be divided into three primary components. The largest contribution to the inclusive diphoton spectrum is the “QCD background”, which can be further divided into a contribution from two real photons produced in association with jets, and a “jet-faking-photon” contribution arising from γ+jet and multijet events for which one or both reconstructed photons are faked by a jet, typically by producing a π0γγ decay that is misidentified as a prompt photon. An “electron-faking-photon background” arises predominantly from W, Z, and tt¯ events, possibly accompanied by additional jets and/or photons, for which an electron is misidentified as a photon. Electron-to-photon misidentification is due primarily to instances for which an electron radiates a high-momentum photon as it traverses the material of the ATLAS inner detector. Last, an “irreducible background” arises from Wγγ and Zγγ events. These backgrounds are estimated with a combination of data-driven and simulation-based methods described as follows.

The component of the QCD background arising from real diphoton events (γγ) is estimated directly from diphoton MC events, rescaled as function of ETmissand the number of selected jets to match the respective distributions for the inclusive diphoton sample in the range ETmiss< 100 GeV. While this background dominates the inclusive diphoton sample, it is very steeply falling in ETmiss, making it small relative to backgrounds with real ETmiss for ETmiss 100 GeV, independent of the reweighting.

The component of the QCD background arising from jets faking photons and the background arising from electrons faking photons are both estimated with a data-driven “fake-factor” method, for which events in data samples enriched in the background of interest are weighted by factors parameterizing the misidentification rate.

To estimate the jet-faking-photon fake-factor, the jet-faking-photon background is enriched by using an inverted isolation requirement, selecting events only if they contain one or more non-isolated photons. The relative probability of an energy cluster being reconstructed as an isolated, rather than non-isolated, photon is known as the photon-isolation fake factor, and is measured in an orthogonal “non-tight” sample of photons. The selection of this sample requires that all the tight photon identification requirements be satisfied, with the exception that at least one of the requirements on the calorimeter variables defined only with the first (strip) layer of the electromagnetic calorimeter fails. This leads to a sample enriched in identified (non-tight) photons that are actually π0s within jets. The correlation between the isolation variable and the photon identification requirements was found to be small and to have no significant impact on the estimation of the jet-faking-photon fake-factor. The fake factors depend upon pT and η, and vary between 10 and 30 %. The jet-faking photon background is then estimated by weighting events with non-isolated photons by the applicable photon-isolation fake factor.

The electron-faking-photon background is estimated with a similar fake-factor method. For this case, the electron-faking-photon background is enriched by selecting events with a reconstructed electron instead of a second photon. Fake factors for electrons being misidentified as photons are then measured by comparing the ratio of reconstructed eγ to ee events arising from Z bosons decaying to electron–positron pairs, selected within the mass range of 75–105 GeV. The electron-faking-photon background is then estimated by weighting selected eγ events by their corresponding fake factors, which are typically a few percent.

The irreducible background from Wγγ events is estimated with MC simulation; however, because it is a potentially dominant background contribution, the overall normalization is derived in a γγ control region (Wγγ CR) as follows. Events in the Wγγ CR are required to have two tight, isolated photons with pT>50 GeV, and exactly one selected lepton (electron or muon) with pT>25 GeV. As with the SR, events are required to have Δϕmin(jet,pTmiss)>0.5, so that the direction of the missing transverse momentum vector is not aligned with that of any high-pT jet. To ensure that the control sample has no overlap with the signal region, events are discarded if ETmiss>175 GeV. While these requirements target Wγγ production, they also are expected to select appreciable backgrounds from tt¯γ, Zγ and Zγγ events, and thus additional requirements are applied. To suppress tt¯γ contributions to the Wγγ CR, events are discarded if they contain more than two selected jets. To suppress Zγ contributions, events are discarded if there is an eγ pair in the events with 83<meγ<97 GeV. Finally, to suppress Zγγ contributions, events with ETmiss<50 GeV are discarded. The event selection requirements for the Wγγ CR are summarized in Table 1. A total of seven events are observed in this Wγγ control region, of which 1.6 are expected to arise from sources other than Wγγ production. The MC expectation for the Wγγ process is 1.9 events, leading to a Wγγ scale factor of 2.9±1.4, assuming that no GGM signal events contaminate the Wγγ CR. This scale factor is consistent with that of the corresponding s= 8 TeV analysis [3], and is reconciled by a large and uncertain NLO correction to the Wγγ production cross section that depends strongly upon the momentum of the Wγγ system [52]. When setting limits on specific signal models, a simultaneous fit to the control region and the signal region is performed, allowing both the signal and Wγγ contributions to float to their best-fit values.

Last, the irreducible background from Z(νν)γγ events, the only background without a data-derived normalization, is estimated with simulation and found to be 0.02 events. A ±100% uncertainty is conservatively applied to account for modelling uncertainties [53].

A summary of the background contributions to the signal region is presented in Table 2. The QCD background can be traced to a few hundredths of an event at high ETmissand high meff, but no events are observed for either the diphoton Monte Carlo or the jet-faking-photon control sample when the full signal region requirements are applied. Relaxing the meff requirement, and using a conservative extrapolation of the expected QCD background as a function of meff, the combined QCD background is estimated to be 0.05-0.05+0.20 events. The estimate of the electron-faking-photon background is established by the presence of two eγ events in the background model passing the SR requirements, yielding a background estimate of 0.03±0.02 events after application of the fake-factor weights. Summing all background contributions, a total of 0.27-0.10+0.22 SM events are expected in the SR, with the largest contribution, 0.17±0.08 events, expected to arise from Wγγ production. The background modelling was found to agree well in several validation regions, including the inclusive high-pT diphoton sample, as well as event selections with relaxed meff and ETmiss requirements relative to those of the SR.

Table 2.

Summary of background estimates by source, and total combined background, in the signal region. The uncertainties shown include the total statistical and systematic uncertainty. Also shown is the expected number of signal events for the benchmark points (mg~,mχ~10)=(1500,100) and (mg~,mχ~10)=(1500,1300), where all masses are in GeV

Source Number of events
QCD (γγ, γj, jj) 0.05-0.05+0.20
eγ fakes 0.03±0.02
Wγγ 0.17±0.08
Zγγ 0.02±0.02
Sum 0.27-0.10+0.22
(mg~,mχ~10)=(1500,100) 7.0
(mg~,mχ~10)=(1500,1300) 8.0

Signal efficiencies and uncertainties

GGM signal acceptances and efficiencies are estimated using MC simulation for each simulated point in the gluino–bino parameter space, and vary significantly across this space due to variations in the photon pT, ETmiss, and meff spectra. For example, for a gluino mass of 1600 GeV, the acceptance-times-efficiency product varies between 14 and 28 %, reaching a minimum as the NLSP mass approaches the Z boson mass, below which the photonic branching fraction of the NLSP rises to unity. Table 3 summarizes the contributions to the systematic uncertainty of the signal acceptance-times-efficiency, which are discussed below.

Table 3.

Summary of individual and total contributions to the systematic uncertainty of the signal acceptance-times-efficiency. Relative uncertainties are shown in percent, and as the average over the full range of the (mg~,mχ~10) grid. Because the individual contributions are averaged over the grid only for that particular source, the average total uncertainty is not exactly equal to the quadrature sum of the individual average uncertainties

Source of systematic uncertainty Value
Luminosity (%) 2.1
Photon identification (%) 3.0
Photon energy scale (%) 0.2
Photon energy resolution (%) 0.2
Jet energy scale (%) 0.4
Jet energy resolution (%) 0.3
ETmiss soft term (%) <0.1
Pile-up uncertainty (%) 1.8
MC statistics (%) 2.3
Total experimental uncert (%) 4.7

Making use of a bootstrap method [54], the efficiency of the diphoton trigger is determined to be greater than 99 %, with an uncertainty of less than 1 %. The uncertainty in the integrated luminosity is ±2.1%. It is derived, following a methodology similar to that detailed in Ref. [55], from a calibration of the luminosity scale using x–y beam-separation scans performed in August 2015.

The reconstruction and identification efficiency for tight, isolated photons is estimated with complementary data-driven methods [42]. Photons selected kinematically as originating from radiative decays of a Z boson (Z+-γ events) are used to study the photon reconstruction efficiency as a function of pT and η. Independent measurements making use of a tag-and-probe approach with Zee events, with one of the electrons used to probe the calorimeter response to electromagnetic depositions, also provide information about the photon reconstruction efficiency. For photons with pT>75 GeV, the identification efficiency varies between 93 and 99 %, depending on the values of the photon pT and |η| and whether the photon converted in the inner detector. The uncertainty also depends upon these factors, and is generally no more than a few percent.

Uncertainties in the photon and jet energy scales lead to uncertainties in the signal acceptance-times-efficiency that vary across the GGM parameter space, and contribute the dominant source of acceptance-times-efficiency uncertainty in certain regions of the parameter space. The photon energy scale is determined using samples of Zee and J/ψee events [56]. The jet-energy scale uncertainty is constrained from an assessment of the effect of uncertainties in the modelling of jet properties and by varying the response to differing jet flavour composition in MC simulations, as well as from in situ measurements with 8 TeV dijet data [46, 47].

Uncertainties in the values of whole-event observables, such as ETmiss and meff, arise from uncertainties in the energy of the underlying objects from which they are constructed. Uncertainties in the ETmiss soft term due to uncertainties in hadronic fragmentation, detector material modeling and energy scale were found to introduce an uncertainty of less than 0.1 % in the signal acceptance-times-efficiency. The uncertainty due to pile-up is estimated by varying the mean of the distribution of the number of interactions per bunch crossing overlaid in the simulation by ±11%.

Including the contribution from the statistical limitations of the MC samples used to model the GGM parameter space, the quadrature sum of the individual systematic uncertainties in the signal reconstruction efficiency is, on average, about 4 %. Adding the uncertainty in the integrated luminosity gives a total systematic uncertainty of about 5 %.

Results

An accounting of the numbers of events observed in the SR after the successive application of the selection requirements is shown in Table 4 along with the size of the expected SM background. After the full selection is applied, no events are observed in the SR, to be compared to an expectation of 0.27-0.10+0.22 SM events.

Table 4.

Numbers of events observed in the SR after the successive application of the selection requirements, as well as the size of the expected SM background

Requirement Number of events
Two photons, pTγ>75 4982
Δϕmin(jet,pTmiss)>0.5 4724
meff>1500 GeV 1
ETmiss>175 GeV 0
Expected SM background 0.27-0.10+0.22

Based on the observation of zero events in the SR and the magnitude of the estimated SM background expectation and uncertainty, an upper limit is set on the number of events from any scenario of physics beyond the SM, using the profile likelihood and CLs prescriptions [57]. The various sources of experimental uncertainty, including those in the background expectation, are treated as Gaussian-distributed nuisance parameters in the likelihood definition. Assuming that no events due to physical processes beyond those of the SM populate the γγ CR used to estimate the W(ν)+γγ background, the observed 95 % confidence-level (CL) upper limit on the number of non-SM events in the SR is found to be 3.0. Taking into account the integrated luminosity of 3.2fb-1, this number-of-event limit translates into a 95 % CL upper limit on the visible cross section for new physics, defined by the product of cross section, branching fraction, acceptance and efficiency, of 0.93 fb.

By considering, in addition, the value and uncertainty of the acceptance-times-efficiency of the selection requirements associated with the SR, as well as the NLO (+NLL) GGM cross Sect. [2024], which varies steeply with gluino mass, 95 % CL lower limits may be set on the mass of the gluino as a function of the mass of the lighter bino-like neutralino, in the context of the GGM scenario described in Sect. 1. The resulting observed limit on the gluino mass is exhibited, as a function of neutralino mass, in Fig. 3. For the purpose of establishing these model-dependent limits, the W(ν)+γγbackground estimate and the limit on the possible number of events from new physics are extracted from a simultaneous fit to the SR and W(ν)+γγcontrol region, although for a gluino mass in the range of the observed limit the signal contamination in the W(ν)+γγcontrol sample is less than 0.03 events for any value of the neutralino mass. Also shown for this figure is the expected limit, including its statistical and background uncertainty range, as well as observed limits for a SUSY model cross section ±1 standard deviation of theoretical uncertainty from its central value. Because the background expectation is close to zero and no events are observed in data, the expected and observed limits nearly overlap. The observed lower limit on the gluino mass is observed to be roughly independent of neutralino mass, reaching a minimum value of approximately 1650 GeV at a neutralino mass of 250 GeV. Within the context of this model, gluino masses as low as 400 GeV have been excluded in a prior analysis making use of 7 TeV ATLAS data [58].

Fig. 3.

Fig. 3

Exclusion limits in the neutralino–gluino mass plane at 95 % CL. The observed limits are exhibited for the nominal SUSY model cross section, as well as for a SUSY cross section increased and lowered by one standard deviation of the cross-section systematic uncertainty. Also shown is the expected limit, as well as the ±1 standard-deviation range of the expected limit, which is asymmetric because of the low count expected. Because the background expectation is close to zero and the observed number of events is zero, the expected and observed limits nearly overlap. The previous limit from ATLAS using 8 TeV data [3] is shown in grey. Within the context of this model, gluino masses as low as 400 GeV have been excluded in a prior analysis making use of 7 TeV ATLAS data [58]

Conclusion

A search has been made for a diphoton + ETmiss final state using the ATLAS detector at the Large Hadron Collider in 3.2fb-1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV in 2015. At least two photon candidates with pT>75GeV are required, as well as minimum values of 175 and 1500 GeV of the missing transverse momentum and effective mass of the event, respectively. The resulting signal region targets events with pair-produced high-mass gluinos each decaying to either a high-mass or low-mass bino-like neutralino. Using a combination of data-driven and direct Monte Carlo approaches, the SM background is estimated to be 0.27-0.10+0.22 events, with most of the expected background arising from the production of a W boson in association with two energetic photons. No events are observed in the signal region; considering the expected background and its uncertainty, this observation implies model-independent 95 % CL upper limits of 3.0 events (0.93 fb) on the number of events (visible cross section) due to physics beyond the Standard Model. In the context of a generalized model of gauge-mediated supersymmetry breaking with a bino-like NLSP, this leads to a lower limit of 1650 GeV on the mass of a degenerate octet of gluino states, independent of the mass of the lighter bino-like neutralino. This extends the corresponding limit of 1340 GeV derived from a similar analysis of 8 TeV data by the ATLAS Collaboration.

Acknowledgments

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, The Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, UK. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [59].

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