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. 2018 Apr 11;78(4):293. doi: 10.1140/epjc/s10052-018-5686-3

Search for heavy ZZ resonances in the +-+- and +-νν¯ final states using proton–proton collisions at s=13 TeV with the ATLAS detector

M Aaboud 181, G Aad 116, B Abbott 145, O Abdinov 14, B Abeloos 149, S H Abidi 210, O S AbouZeid 184, N L Abraham 200, H Abramowicz 204, H Abreu 203, R Abreu 148, Y Abulaiti 196,197, B S Acharya 218,219, S Adachi 206, L Adamczyk 62, J Adelman 140, M Adersberger 131, T Adye 171, A A Affolder 184, Y Afik 203, T Agatonovic-Jovin 16, C Agheorghiesei 39, J A Aguilar-Saavedra 160,165, S P Ahlen 30, F Ahmadov 95, G Aielli 174,175, S Akatsuka 98, H Akerstedt 196,197, T P A Åkesson 112, E Akilli 74, A V Akimov 127, G L Alberghi 27,28, J Albert 225, P Albicocco 72, M J Alconada Verzini 101, S C Alderweireldt 138, M Aleksa 46, I N Aleksandrov 95, C Alexa 38, G Alexander 204, T Alexopoulos 12, M Alhroob 145, B Ali 168, M Aliev 103,104, G Alimonti 122, J Alison 47, S P Alkire 58, B M M Allbrooke 200, B W Allen 148, P P Allport 21, A Aloisio 135,136, A Alonso 59, F Alonso 101, C Alpigiani 185, A A Alshehri 80, M I Alstaty 116, B Alvarez Gonzalez 46, D Álvarez Piqueras 223, M G Alviggi 135,136, B T Amadio 18, Y Amaral Coutinho 32, C Amelung 31, D Amidei 120, S P Amor Dos Santos 160,162, S Amoroso 46, C Anastopoulos 186, L S Ancu 74, N Andari 21, T Andeen 13, C F Anders 85, J K Anders 105, K J Anderson 47, A Andreazza 122,123, V Andrei 84, S Angelidakis 57, I Angelozzi 139, A Angerami 58, A V Anisenkov 141, N Anjos 15, A Annovi 157, C Antel 84, M Antonelli 72, A Antonov 129, D J Antrim 217, F Anulli 172, M Aoki 96, L Aperio Bella 46, G Arabidze 121, Y Arai 96, J P Araque 160, V Araujo Ferraz 32, A T H Arce 70, R E Ardell 108, F A Arduh 101, J-F Arguin 126, S Argyropoulos 93, M Arik 22, A J Armbruster 46, L J Armitage 107, O Arnaez 210, H Arnold 73, M Arratia 44, O Arslan 29, A Artamonov 128, G Artoni 152, S Artz 114, S Asai 206, N Asbah 67, A Ashkenazi 204, L Asquith 200, K Assamagan 36, R Astalos 191, M Atkinson 222, N B Atlay 188, K Augsten 168, G Avolio 46, B Axen 18, M K Ayoub 50, G Azuelos 126, A E Baas 84, M J Baca 21, H Bachacou 183, K Bachas 103,104, M Backes 152, P Bagnaia 172,173, M Bahmani 64, H Bahrasemani 189, J T Baines 171, M Bajic 59, O K Baker 232, P J Bakker 139, E M Baldin 141, P Balek 228, F Balli 183, W K Balunas 155, E Banas 64, A Bandyopadhyay 29, Sw Banerjee 229, A A E Bannoura 231, L Barak 204, E L Barberio 119, D Barberis 75,76, M Barbero 116, T Barillari 132, M-S Barisits 46, J T Barkeloo 148, T Barklow 190, N Barlow 44, S L Barnes 56, B M Barnett 171, R M Barnett 18, Z Barnovska-Blenessy 54, A Baroncelli 176, G Barone 31, A J Barr 152, L Barranco Navarro 223, F Barreiro 113, J Barreiro Guimarães da Costa 50, R Bartoldus 190, A E Barton 102, P Bartos 191, A Basalaev 156, A Bassalat 149, R L Bates 80, S J Batista 210, J R Batley 44, M Battaglia 184, M Bauce 172,173, F Bauer 183, H S Bawa 190, J B Beacham 143, M D Beattie 102, T Beau 111, P H Beauchemin 216, P Bechtle 29, H P Beck 20, H C Beck 81, K Becker 152, M Becker 114, C Becot 142, A J Beddall 25, A Beddall 23, V A Bednyakov 95, M Bedognetti 139, C P Bee 199, T A Beermann 46, M Begalli 32, M Begel 36, J K Behr 67, A S Bell 109, G Bella 204, L Bellagamba 27, A Bellerive 45, M Bellomo 203, K Belotskiy 129, O Beltramello 46, N L Belyaev 129, O Benary 204, D Benchekroun 178, M Bender 131, N Benekos 12, Y Benhammou 204, E Benhar Noccioli 232, J Benitez 93, D P Benjamin 70, M Benoit 74, J R Bensinger 31, S Bentvelsen 139, L Beresford 152, M Beretta 72, D Berge 139, E Bergeaas Kuutmann 221, N Berger 7, L J Bergsten 31, J Beringer 18, S Berlendis 82, N R Bernard 117, G Bernardi 111, C Bernius 190, F U Bernlochner 29, T Berry 108, P Berta 114, C Bertella 50, G Bertoli 196,197, I A Bertram 102, C Bertsche 67, G J Besjes 59, O Bessidskaia Bylund 196,197, M Bessner 67, N Besson 183, A Bethani 115, S Bethke 132, A Betti 29, A J Bevan 107, J Beyer 132, R M Bianchi 159, O Biebel 131, D Biedermann 19, R Bielski 115, K Bierwagen 114, N V Biesuz 157,158, M Biglietti 176, T R V Billoud 126, H Bilokon 72, M Bindi 81, A Bingul 23, C Bini 172,173, S Biondi 27,28, T Bisanz 81, C Bittrich 69, D M Bjergaard 70, J E Black 190, K M Black 30, R E Blair 8, T Blazek 191, I Bloch 67, C Blocker 31, A Blue 80, U Blumenschein 107, Dr Blunier 48, G J Bobbink 139, V S Bobrovnikov 141, S S Bocchetta 112, A Bocci 70, C Bock 131, M Boehler 73, D Boerner 231, D Bogavac 131, A G Bogdanchikov 141, C Bohm 196, V Boisvert 108, P Bokan 221, T Bold 62, A S Boldyrev 130, A E Bolz 85, M Bomben 111, M Bona 107, M Boonekamp 183, A Borisov 170, G Borissov 102, J Bortfeldt 46, D Bortoletto 152, V Bortolotto 87, D Boscherini 27, M Bosman 15, J D Bossio Sola 43, J Boudreau 159, E V Bouhova-Thacker 102, D Boumediene 57, C Bourdarios 149, S K Boutle 80, A Boveia 143, J Boyd 46, I R Boyko 95, A J Bozson 108, J Bracinik 21, A Brandt 10, G Brandt 81, O Brandt 84, F Braren 67, U Bratzler 207, B Brau 117, J E Brau 148, W D Breaden Madden 80, K Brendlinger 67, A J Brennan 119, L Brenner 139, R Brenner 221, S Bressler 228, D L Briglin 21, T M Bristow 71, D Britton 80, D Britzger 67, F M Brochu 44, I Brock 29, R Brock 121, G Brooijmans 58, T Brooks 108, W K Brooks 49, J Brosamer 18, E Brost 140, J H Broughton 21, P A Bruckman de Renstrom 64, D Bruncko 192, A Bruni 27, G Bruni 27, L S Bruni 139, S Bruno 174,175, BH Brunt 44, M Bruschi 27, N Bruscino 159, P Bryant 47, L Bryngemark 67, T Buanes 17, Q Buat 189, P Buchholz 188, A G Buckley 80, I A Budagov 95, F Buehrer 73, M K Bugge 151, O Bulekov 129, D Bullock 10, T J Burch 140, S Burdin 105, C D Burgard 139, A M Burger 7, B Burghgrave 140, K Burka 64, S Burke 171, I Burmeister 68, J T P Burr 152, D Büscher 73, V Büscher 114, P Bussey 80, J M Butler 30, C M Buttar 80, J M Butterworth 109, P Butti 46, W Buttinger 36, A Buzatu 202, A R Buzykaev 141, C-Q Li 54, S Cabrera Urbán 223, D Caforio 168, H Cai 222, V M Cairo 60,61, O Cakir 4, N Calace 74, P Calafiura 18, A Calandri 116, G Calderini 111, P Calfayan 91, G Callea 60,61, L P Caloba 32, S CalventeLopez 113, D Calvet 57, S Calvet 57, T P Calvet 116, R Camacho Toro 47, S Camarda 46, P Camarri 174,175, D Cameron 151, R Caminal Armadans 222, C Camincher 82, S Campana 46, M Campanelli 109, A Camplani 122,123, A Campoverde 188, V Canale 135,136, M Cano Bret 56, J Cantero 146, T Cao 204, M D M Capeans Garrido 46, I Caprini 38, M Caprini 38, M Capua 60,61, R M Carbone 58, R Cardarelli 174, F Cardillo 73, I Carli 169, T Carli 46, G Carlino 135, B T Carlson 159, L Carminati 122,123, R M D Carney 196,197, S Caron 138, E Carquin 49, S Carrá 122,123, G D Carrillo-Montoya 46, D Casadei 21, M P Casado 15, A F Casha 210, M Casolino 15, D W Casper 217, R Castelijn 139, V Castillo Gimenez 223, N F Castro 160, A Catinaccio 46, J R Catmore 151, A Cattai 46, J Caudron 29, V Cavaliere 222, E Cavallaro 15, D Cavalli 122, M Cavalli-Sforza 15, V Cavasinni 157,158, E Celebi 25, F Ceradini 176,177, L Cerda Alberich 223, A S Cerqueira 33, A Cerri 200, L Cerrito 174,175, F Cerutti 18, A Cervelli 27,28, S A Cetin 25, A Chafaq 178, D Chakraborty 140, S K Chan 83, W S Chan 139, Y L Chan 87, P Chang 222, J D Chapman 44, D G Charlton 21, C C Chau 45, C A Chavez Barajas 200, S Che 143, S Cheatham 218,220, A Chegwidden 121, S Chekanov 8, S V Chekulaev 213, G A Chelkov 95, M A Chelstowska 46, C Chen 54, C Chen 94, H Chen 36, J Chen 54, S Chen 51, S Chen 206, X Chen 52, Y Chen 97, H C Cheng 120, H J Cheng 50,53, A Cheplakov 95, E Cheremushkina 170, R Cherkaoui El Moursli 182, E Cheu 9, K Cheung 90, L Chevalier 183, V Chiarella 72, G Chiarelli 157, G Chiodini 103, A S Chisholm 46, A Chitan 38, Y H Chiu 225, M V Chizhov 95, K Choi 91, A R Chomont 57, S Chouridou 205, Y S Chow 87, V Christodoulou 109, M C Chu 87, J Chudoba 167, A J Chuinard 118, J J Chwastowski 64, L Chytka 147, A K Ciftci 4, D Cinca 68, V Cindro 106, I A Cioara 29, A Ciocio 18, F Cirotto 135,136, Z H Citron 228, M Citterio 122, M Ciubancan 38, A Clark 74, B L Clark 83, M R Clark 58, P J Clark 71, R N Clarke 18, C Clement 196,197, Y Coadou 116, M Cobal 218,220, A Coccaro 74, J Cochran 94, L Colasurdo 138, B Cole 58, A P Colijn 139, J Collot 82, T Colombo 217, P Conde Muiño 160,161, E Coniavitis 73, S H Connell 194, I A Connelly 115, S Constantinescu 38, G Conti 46, F Conventi 135, M Cooke 18, A M Cooper-Sarkar 152, F Cormier 224, K J R Cormier 210, M Corradi 172,173, F Corriveau 118, A Cortes-Gonzalez 46, G Costa 122, M J Costa 223, D Costanzo 186, G Cottin 44, G Cowan 108, B E Cox 115, K Cranmer 142, S J Crawley 80, R A Creager 155, G Cree 45, S Crépé-Renaudin 82, F Crescioli 111, W A Cribbs 196,197, M Cristinziani 29, V Croft 142, G Crosetti 60,61, A Cueto 113, T Cuhadar Donszelmann 186, A R Cukierman 190, J Cummings 232, M Curatolo 72, J Cúth 114, S Czekierda 64, P Czodrowski 46, G D’amen 27,28, S D’Auria 80, L D’eramo 111, M D’Onofrio 105, M J Da Cunha Sargedas De Sousa 160,161, C DaVia 115, W Dabrowski 62, T Dado 191, T Dai 120, O Dale 17, F Dallaire 126, C Dallapiccola 117, M Dam 59, J R Dandoy 155, M F Daneri 43, N P Dang 229, A C Daniells 21, N S Dann 115, M Danninger 224, M Dano Hoffmann 183, V Dao 199, G Darbo 75, S Darmora 10, J Dassoulas 3, A Dattagupta 148, T Daubney 67, W Davey 29, C David 67, T Davidek 169, D R Davis 70, P Davison 109, E Dawe 119, I Dawson 186, K De 10, R de Asmundis 135, A De Benedetti 145, S De Castro 27,28, S De Cecco 111, N De Groot 138, P de Jong 139, H De la Torre 121, F De Lorenzi 94, A De Maria 81, D De Pedis 172, A De Salvo 172, U De Sanctis 174,175, A De Santo 200, K De Vasconcelos Corga 116, J B De Vivie De Regie 149, R Debbe 36, C Debenedetti 184, D V Dedovich 95, N Dehghanian 3, I Deigaard 139, M Del Gaudio 60,61, J Del Peso 113, D Delgove 149, F Deliot 183, C M Delitzsch 9, A Dell’Acqua 46, L Dell’Asta 30, M Dell’Orso 157,158, M Della Pietra 135,136, D della Volpe 74, M Delmastro 7, C Delporte 149, P A Delsart 82, D A DeMarco 210, S Demers 232, M Demichev 95, A Demilly 111, S P Denisov 170, D Denysiuk 183, D Derendarz 64, J E Derkaoui 181, F Derue 111, P Dervan 105, K Desch 29, C Deterre 67, K Dette 210, M R Devesa 43, P O Deviveiros 46, A Dewhurst 171, S Dhaliwal 31, F A DiBello 74, A DiCiaccio 174,175, L DiCiaccio 7, W K DiClemente 155, C DiDonato 135,136, A DiGirolamo 46, B DiGirolamo 46, B DiMicco 176,177, R DiNardo 46, K F DiPetrillo 83, A Di Simone 73, R Di Sipio 210, D DiValentino 45, C Diaconu 116, M Diamond 210, F A Dias 59, M A Diaz 48, J Dickinson 18, E B Diehl 120, J Dietrich 19, S Díez Cornell 67, A Dimitrievska 16, J Dingfelder 29, P Dita 38, S Dita 38, F Dittus 46, F Djama 116, T Djobava 78, J I Djuvsland 84, M A B doVale 34, D Dobos 46, M Dobre 38, D Dodsworth 31, C Doglioni 112, J Dolejsi 169, Z Dolezal 169, M Donadelli 35, S Donati 157,158, P Dondero 153,154, J Donini 57, J Dopke 171, A Doria 135, M T Dova 101, A T Doyle 80, E Drechsler 81, M Dris 12, Y Du 55, J Duarte-Campderros 204, F Dubinin 127, A Dubreuil 74, E Duchovni 228, G Duckeck 131, A Ducourthial 111, O A Ducu 126, D Duda 139, A Dudarev 46, A Chr Dudder 114, E M Duffield 18, L Duflot 149, M Dührssen 46, C Dulsen 231, M Dumancic 228, A E Dumitriu 38, A K Duncan 80, M Dunford 84, A Duperrin 116, H Duran Yildiz 4, M Düren 79, A Durglishvili 78, D Duschinger 69, B Dutta 67, D Duvnjak 1, M Dyndal 67, B S Dziedzic 64, C Eckardt 67, K M Ecker 132, R C Edgar 120, T Eifert 46, G Eigen 17, K Einsweiler 18, T Ekelof 221, M El Kacimi 180, R El Kosseifi 116, V Ellajosyula 116, M Ellert 221, S Elles 7, F Ellinghaus 231, A A Elliot 225, N Ellis 46, J Elmsheuser 36, M Elsing 46, D Emeliyanov 171, Y Enari 206, J S Ennis 226, M B Epland 70, J Erdmann 68, A Ereditato 20, M Ernst 36, S Errede 222, M Escalier 149, C Escobar 223, B Esposito 72, O EstradaPastor 223, A I Etienvre 183, E Etzion 204, H Evans 91, A Ezhilov 156, M Ezzi 182, F Fabbri 27,28, L Fabbri 27,28, V Fabiani 138, G Facini 109, R M Fakhrutdinov 170, S Falciano 172, R J Falla 109, J Faltova 46, Y Fang 50, M Fanti 122,123, A Farbin 10, A Farilla 176, C Farina 159, E M Farina 153,154, T Farooque 121, S Farrell 18, S M Farrington 226, P Farthouat 46, F Fassi 182, P Fassnacht 46, D Fassouliotis 11, M Faucci Giannelli 71, A Favareto 75,76, W J Fawcett 152, L Fayard 149, O L Fedin 156, W Fedorko 224, S Feigl 151, L Feligioni 116, C Feng 55, E J Feng 46, M J Fenton 80, A B Fenyuk 170, L Feremenga 10, P Fernandez Martinez 223, J Ferrando 67, A Ferrari 221, P Ferrari 139, R Ferrari 153, D E Ferreira de Lima 85, A Ferrer 223, D Ferrere 74, C Ferretti 120, F Fiedler 114, A Filipčič 106, M Filipuzzi 67, F Filthaut 138, M Fincke-Keeler 225, K D Finelli 30, M C N Fiolhais 160,162, L Fiorini 223, A Fischer 2, C Fischer 15, J Fischer 231, W C Fisher 121, N Flaschel 67, I Fleck 188, P Fleischmann 120, R R M Fletcher 155, T Flick 231, B M Flierl 131, L R FloresCastillo 87, M J Flowerdew 132, G T Forcolin 115, A Formica 183, F A Förster 15, A Forti 115, A G Foster 21, D Fournier 149, H Fox 102, S Fracchia 186, P Francavilla 157,158, M Franchini 27,28, S Franchino 84, D Francis 46, L Franconi 151, M Franklin 83, M Frate 217, M Fraternali 153,154, D Freeborn 109, S M Fressard-Batraneanu 46, B Freund 126, D Froidevaux 46, J A Frost 152, C Fukunaga 207, T Fusayasu 133, J Fuster 223, O Gabizon 203, A Gabrielli 27,28, A Gabrielli 18, G P Gach 62, S Gadatsch 46, S Gadomski 108, G Gagliardi 75,76, L G Gagnon 126, C Galea 138, B Galhardo 160,162, E J Gallas 152, B J Gallop 171, P Gallus 168, G Galster 59, K K Gan 143, S Ganguly 57, Y Gao 105, Y S Gao 190, F M Garay Walls 48, C García 223, J E García Navarro 223, J A García Pascual 50, M Garcia-Sciveres 18, R W Gardner 47, N Garelli 190, V Garonne 151, A GasconBravo 67, K Gasnikova 67, C Gatti 72, A Gaudiello 75,76, G Gaudio 153, I L Gavrilenko 127, C Gay 224, G Gaycken 29, E N Gazis 12, C N P Gee 171, J Geisen 81, M Geisen 114, M P Geisler 84, K Gellerstedt 196,197, C Gemme 75, M H Genest 82, C Geng 120, S Gentile 172,173, C Gentsos 205, S George 108, D Gerbaudo 15, G Geßner 68, S Ghasemi 188, M Ghneimat 29, B Giacobbe 27, S Giagu 172,173, N Giangiacomi 27,28, P Giannetti 157, S M Gibson 108, M Gignac 224, M Gilchriese 18, D Gillberg 45, G Gilles 231, D M Gingrich 3, M P Giordani 218,220, F M Giorgi 27, P F Giraud 183, P Giromini 83, G Giugliarelli 218,220, D Giugni 122, F Giuli 152, C Giuliani 132, M Giulini 85, B K Gjelsten 151, S Gkaitatzis 205, I Gkialas 11, E L Gkougkousis 15, P Gkountoumis 12, L K Gladilin 130, C Glasman 113, J Glatzer 15, P C F Glaysher 67, A Glazov 67, M Goblirsch-Kolb 31, J Godlewski 64, S Goldfarb 119, T Golling 74, D Golubkov 170, A Gomes 160,161,163, R Gonçalo 160, R Goncalves Gama 32, J Goncalves Pinto Firmino Da Costa 183, G Gonella 73, L Gonella 21, A Gongadze 95, J L Gonski 83, S González de laHoz 223, S Gonzalez-Sevilla 74, L Goossens 46, P A Gorbounov 128, H A Gordon 36, I Gorelov 137, B Gorini 46, E Gorini 103,104, A Gorišek 106, A T Goshaw 70, C Gössling 68, M I Gostkin 95, C A Gottardo 29, C R Goudet 149, D Goujdami 180, A G Goussiou 185, N Govender 194, E Gozani 203, I Grabowska-Bold 62, P O J Gradin 221, J Gramling 217, E Gramstad 151, S Grancagnolo 19, V Gratchev 156, P M Gravila 42, C Gray 80, H M Gray 18, Z D Greenwood 110, C Grefe 29, K Gregersen 109, I M Gregor 67, P Grenier 190, K Grevtsov 7, J Griffiths 10, A A Grillo 184, K Grimm 102, S Grinstein 15, Ph Gris 57, J-F Grivaz 149, S Groh 114, E Gross 228, J Grosse-Knetter 81, G C Grossi 110, Z J Grout 109, A Grummer 137, L Guan 120, W Guan 229, J Guenther 46, F Guescini 213, D Guest 217, O Gueta 204, B Gui 143, E Guido 75,76, T Guillemin 7, S Guindon 46, U Gul 80, C Gumpert 46, J Guo 56, W Guo 120, Y Guo 54, R Gupta 65, S Gurbuz 22, G Gustavino 145, B J Gutelman 203, P Gutierrez 145, N G Gutierrez Ortiz 109, C Gutschow 109, C Guyot 183, M P Guzik 62, C Gwenlan 152, C B Gwilliam 105, A Haas 142, C Haber 18, H K Hadavand 10, N Haddad 182, A Hadef 116, S Hageböck 29, M Hagihara 215, H Hakobyan 233, M Haleem 67, J Haley 146, G Halladjian 121, G D Hallewell 116, K Hamacher 231, P Hamal 147, K Hamano 225, A Hamilton 193, G N Hamity 186, P G Hamnett 67, L Han 54, S Han 50,53, K Hanagaki 96, K Hanawa 206, M Hance 184, D M Handl 131, B Haney 155, P Hanke 84, J B Hansen 59, J D Hansen 59, M C Hansen 29, P H Hansen 59, K Hara 215, A S Hard 229, T Harenberg 231, F Hariri 149, S Harkusha 124, P F Harrison 226, N M Hartmann 131, Y Hasegawa 187, A Hasib 71, S Hassani 183, S Haug 20, R Hauser 121, L Hauswald 69, L B Havener 58, M Havranek 168, C M Hawkes 21, R J Hawkings 46, D Hayakawa 208, D Hayden 121, C P Hays 152, J M Hays 107, H S Hayward 105, S J Haywood 171, S J Head 21, T Heck 114, V Hedberg 112, L Heelan 10, S Heer 29, K K Heidegger 73, S Heim 67, T Heim 18, B Heinemann 67, J J Heinrich 131, L Heinrich 142, C Heinz 79, J Hejbal 167, L Helary 46, A Held 224, S Hellman 196,197, C Helsens 46, R C W Henderson 102, Y Heng 229, S Henkelmann 224, A M Henriques Correia 46, S Henrot-Versille 149, G H Herbert 19, H Herde 31, V Herget 230, Y Hernández Jiménez 195, H Herr 114, G Herten 73, R Hertenberger 131, L Hervas 46, T C Herwig 155, G G Hesketh 109, N P Hessey 213, J W Hetherly 65, S Higashino 96, E Higón-Rodriguez 223, K Hildebrand 47, E Hill 225, J C Hill 44, K H Hiller 67, S J Hillier 21, M Hils 69, I Hinchliffe 18, M Hirose 73, D Hirschbuehl 231, B Hiti 106, O Hladik 167, D R Hlaluku 195, X Hoad 71, J Hobbs 199, N Hod 213, M C Hodgkinson 186, P Hodgson 186, A Hoecker 46, M R Hoeferkamp 137, F Hoenig 131, D Hohn 29, T R Holmes 47, M Holzbock 131, M Homann 68, S Honda 215, T Honda 96, T M Hong 159, B H Hooberman 222, W H Hopkins 148, Y Horii 134, A J Horton 189, J-Y Hostachy 82, A Hostiuc 185, S Hou 202, A Hoummada 178, J Howarth 115, J Hoya 101, M Hrabovsky 147, J Hrdinka 46, I Hristova 19, J Hrivnac 149, T Hryn’ova 7, A Hrynevich 125, P J Hsu 90, S-C Hsu 185, Q Hu 36, S Hu 56, Y Huang 50, Z Hubacek 168, F Hubaut 116, F Huegging 29, T B Huffman 152, E W Hughes 58, M Huhtinen 46, R F H Hunter 45, P Huo 199, N Huseynov 95, J Huston 121, J Huth 83, R Hyneman 120, G Iacobucci 74, G Iakovidis 36, I Ibragimov 188, L 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Stelzer-Chilton 213, H Stenzel 79, T J Stevenson 107, G A Stewart 80, M C Stockton 148, M Stoebe 118, G Stoicea 38, P Stolte 81, S Stonjek 132, A R Stradling 10, A Straessner 69, M E Stramaglia 20, J Strandberg 198, S Strandberg 196,197, M Strauss 145, P Strizenec 192, R Ströhmer 230, D M Strom 148, R Stroynowski 65, A Strubig 71, S A Stucci 36, B Stugu 17, N A Styles 67, D Su 190, J Su 159, S Suchek 84, Y Sugaya 150, M Suk 168, V V Sulin 127, DMS Sultan 211,212, S Sultansoy 6, T Sumida 98, S Sun 83, X Sun 3, K Suruliz 200, C J E Suster 201, M R Sutton 200, S Suzuki 96, M Svatos 167, M Swiatlowski 47, S P Swift 2, I Sykora 191, T Sykora 169, D Ta 73, K Tackmann 67, J Taenzer 204, A Taffard 217, R Tafirout 213, E Tahirovic 107, N Taiblum 204, H Takai 36, R Takashima 99, E H Takasugi 132, K Takeda 97, T Takeshita 187, Y Takubo 96, M Talby 116, A A Talyshev 141, J Tanaka 206, M Tanaka 208, R Tanaka 149, S Tanaka 96, R Tanioka 97, B B Tannenwald 143, S Tapia Araya 49, S Tapprogge 114, S Tarem 203, G F Tartarelli 122, P Tas 169, M Tasevsky 167, T Tashiro 98, E Tassi 60,61, A Tavares Delgado 160,161, Y Tayalati 182, A C Taylor 137, A J Taylor 71, G N Taylor 119, P T E Taylor 119, W Taylor 214, P Teixeira-Dias 108, D Temple 189, H TenKate 46, P K Teng 202, J J Teoh 150, F Tepel 231, S Terada 96, K Terashi 206, J Terron 113, S Terzo 15, M Testa 72, R J Teuscher 210, S J Thais 232, T Theveneaux-Pelzer 116, F Thiele 59, J P Thomas 21, J Thomas-Wilsker 108, P D Thompson 21, A S Thompson 80, L A Thomsen 232, E Thomson 155, Y Tian 58, M J Tibbetts 18, R E TicseTorres 81, V O Tikhomirov 127, Yu A Tikhonov 141, S Timoshenko 129, P Tipton 232, S Tisserant 116, K Todome 208, S Todorova-Nova 7, S Todt 69, J Tojo 100, S Tokár 191, K Tokushuku 96, E Tolley 143, L Tomlinson 115, M Tomoto 134, L Tompkins 190, K Toms 137, B Tong 83, P Tornambe 73, E Torrence 148, H Torres 69, E TorróPastor 185, J Toth 116, F Touchard 116, D R Tovey 186, C J Treado 142, T Trefzger 230, F Tresoldi 200, A Tricoli 36, I M Trigger 213, S Trincaz-Duvoid 111, M F Tripiana 15, W Trischuk 210, B Trocmé 82, A Trofymov 67, C Troncon 122, M Trottier-McDonald 18, M Trovatelli 225, L Truong 194, M Trzebinski 64, A Trzupek 64, K W Tsang 87, JC-L Tseng 152, P V Tsiareshka 124, N Tsirintanis 11, S Tsiskaridze 15, V Tsiskaridze 73, E G Tskhadadze 77, I I Tsukerman 128, V Tsulaia 18, S Tsuno 96, D Tsybychev 199, Y Tu 88, A Tudorache 38, V Tudorache 38, T T Tulbure 37, A N Tuna 83, S Turchikhin 95, D Turgeman 228, I TurkCakir 5, R Turra 122, P M Tuts 58, G Ucchielli 27,28, I Ueda 96, M Ughetto 196,197, F Ukegawa 215, G Unal 46, A Undrus 36, G Unel 217, F C Ungaro 119, Y Unno 96, K Uno 206, C Unverdorben 131, J Urban 192, P Urquijo 119, P Urrejola 114, G Usai 10, J Usui 96, L Vacavant 116, V Vacek 168, B Vachon 118, K O H Vadla 151, A Vaidya 109, C Valderanis 131, E Valdes Santurio 196,197, M Valente 74, S Valentinetti 27,28, A Valero 223, L Valéry 15, S Valkar 169, A Vallier 7, J A Valls Ferrer 223, W Van Den Wollenberg 139, H van der Graaf 139, P van Gemmeren 8, J Van Nieuwkoop 189, I van Vulpen 139, M C van Woerden 139, M Vanadia 174,175, W Vandelli 46, A Vaniachine 209, P Vankov 139, G Vardanyan 233, R Vari 172, E W Varnes 9, C Varni 75,76, T Varol 65, D Varouchas 149, A Vartapetian 10, K E Varvell 201, J G Vasquez 232, G A Vasquez 49, F Vazeille 57, D Vazquez Furelos 15, T Vazquez Schroeder 118, J Veatch 81, V Veeraraghavan 9, L M Veloce 210, F Veloso 160,162, S Veneziano 172, A Ventura 103,104, M Venturi 225, N Venturi 46, A Venturini 31, V Vercesi 153, M Verducci 176,177, W Verkerke 139, A T Vermeulen 139, J C Vermeulen 139, M C Vetterli 189, N Viaux Maira 49, O Viazlo 112, I Vichou 222, T Vickey 186, O E Vickey Boeriu 186, G H A Viehhauser 152, S Viel 18, L Vigani 152, M Villa 27,28, M VillaplanaPerez 122,123, E Vilucchi 72, M G Vincter 45, V B Vinogradov 95, A Vishwakarma 67, C Vittori 27,28, I Vivarelli 200, S Vlachos 12, M Vogel 231, P Vokac 168, G Volpi 15, H von der Schmitt 132, E von Toerne 29, V Vorobel 169, K Vorobev 129, M Vos 223, R Voss 46, J H Vossebeld 105, N Vranjes 16, M Vranjes Milosavljevic 16, V Vrba 168, M Vreeswijk 139, R Vuillermet 46, I Vukotic 47, P Wagner 29, W Wagner 231, J Wagner-Kuhr 131, H Wahlberg 101, S Wahrmund 69, K Wakamiya 97, J Walder 102, R Walker 131, W Walkowiak 188, V Wallangen 196,197, C Wang 51, C Wang 55, F Wang 229, H Wang 18, H Wang 3, J Wang 67, J Wang 201, Q Wang 145, R-J Wang 111, R Wang 8, S M Wang 202, T Wang 58, W Wang 202, W Wang 54, Z Wang 56, C Wanotayaroj 67, A Warburton 118, C P Ward 44, D R Wardrope 109, A Washbrook 71, P M Watkins 21, A T Watson 21, M F Watson 21, G Watts 185, S Watts 115, B M Waugh 109, A F Webb 13, S Webb 114, M S Weber 20, S M Weber 84, S W Weber 230, S A Weber 45, J S Webster 8, A R Weidberg 152, B Weinert 91, J Weingarten 81, M Weirich 114, C Weiser 73, H Weits 139, P S Wells 46, T Wenaus 36, T Wengler 46, S Wenig 46, N Wermes 29, M D Werner 94, P Werner 46, M Wessels 84, T D Weston 20, K Whalen 148, N L Whallon 185, A M Wharton 102, A S White 120, A White 10, M J White 1, R White 49, D Whiteson 217, B W Whitmore 102, F J Wickens 171, W Wiedenmann 229, M Wielers 171, C Wiglesworth 59, L A M Wiik-Fuchs 73, A Wildauer 132, F Wilk 115, H G Wilkens 46, H H Williams 155, S Williams 139, C Willis 121, S Willocq 117, J A Wilson 21, I Wingerter-Seez 7, E Winkels 200, F Winklmeier 148, O J Winston 200, B T Winter 29, M Wittgen 190, M Wobisch 110, A Wolf 114, T M H Wolf 139, R Wolff 116, M W Wolter 64, H Wolters 160,162, V W S Wong 224, N L Woods 184, S D Worm 21, B K Wosiek 64, J Wotschack 46, K W Wozniak 64, M Wu 47, S L Wu 229, X Wu 74, Y Wu 120, T R Wyatt 115, B M Wynne 71, S Xella 59, Z Xi 120, L Xia 52, D Xu 50, L Xu 36, T Xu 183, W Xu 120, B Yabsley 201, S Yacoob 193, D Yamaguchi 208, Y Yamaguchi 208, A Yamamoto 96, S Yamamoto 206, T Yamanaka 206, F Yamane 97, M Yamatani 206, T Yamazaki 206, Y Yamazaki 97, Z Yan 30, H Yang 56, H Yang 18, Y Yang 202, Z Yang 17, W-M Yao 18, Y C Yap 67, Y Yasu 96, E Yatsenko 7, K H YauWong 29, J Ye 65, S Ye 36, I Yeletskikh 95, E Yigitbasi 30, E Yildirim 114, K Yorita 227, K Yoshihara 155, C Young 190, C J S Young 46, J Yu 10, J Yu 94, S P Y Yuen 29, I Yusuff 44, B Zabinski 64, G Zacharis 12, R Zaidan 15, A M Zaitsev 170, N Zakharchuk 67, J Zalieckas 17, A Zaman 199, S Zambito 83, D Zanzi 119, C Zeitnitz 231, G Zemaityte 152, A Zemla 62, J C Zeng 222, Q Zeng 190, O Zenin 170, T Ženiš 191, D Zerwas 149, D Zhang 55, D Zhang 120, F Zhang 229, G Zhang 54, H Zhang 149, J Zhang 8, L Zhang 73, L Zhang 54, M Zhang 222, P Zhang 51, R Zhang 29, R Zhang 54, X Zhang 55, Y Zhang 50,53, Z Zhang 149, X Zhao 65, Y Zhao 55, Z Zhao 54, A Zhemchugov 95, B Zhou 120, C Zhou 229, L Zhou 65, M Zhou 50,53, M Zhou 199, N Zhou 56, Y Zhou 9, C G Zhu 55, H Zhu 50, J Zhu 120, Y Zhu 54, X Zhuang 50, K Zhukov 127, A Zibell 230, D Zieminska 91, N I Zimine 95, C Zimmermann 114, S Zimmermann 73, Z Zinonos 132, M Zinser 114, M Ziolkowski 188, L Živković 16, G Zobernig 229, A Zoccoli 27,28, R Zou 47, M zur Nedden 19, L Zwalinski 46; ATLAS Collaboration24,41,166,179,236
PMCID: PMC6445556  PMID: 31009022

Abstract

A search for heavy resonances decaying into a pair of Z bosons leading to +-+- and +-νν¯ final states, where stands for either an electron or a muon, is presented. The search uses proton–proton collision data at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 36.1 fb-1 collected with the ATLAS detector during 2015 and 2016 at the Large Hadron Collider. Different mass ranges for the hypothetical resonances are considered, depending on the final state and model. The different ranges span between 200 and 2000 GeV. The results are interpreted as upper limits on the production cross section of a spin-0 or spin-2 resonance. The upper limits for the spin-0 resonance are translated to exclusion contours in the context of Type-I and Type-II two-Higgs-doublet models, while those for the spin-2 resonance are used to constrain the Randall–Sundrum model with an extra dimension giving rise to spin-2 graviton excitations.

Introduction

In 2012, the ATLAS and CMS Collaborations at the LHC discovered a new particle [1, 2], an important milestone in the understanding of the mechanism of electroweak (EW) symmetry breaking [35]. Both experiments have confirmed that the spin, parity and couplings of the new particle are consistent with those predicted for the Standard Model (SM) Higgs boson [68] (denoted by h throughout this paper). They measured its mass to be mh=125.09±0.21(stat)±0.11(syst) GeV[9] and reported recently on a combination of measurements of its couplings to other SM particles [10].

One important question is whether the newly discovered particle is part of an extended scalar sector as postulated by various extensions to the Standard Model such as the two-Higgs-doublet model (2HDM) [11]. These extensions predict additional Higgs bosons, motivating searches in an extended range of mass.

This paper reports on two searches for a heavy resonance decaying into two SM Z bosons, encompassing the final states ZZ+-+- and ZZ+-νν¯ where stands for either an electron or a muon and ν stands for all three neutrino flavours. These final states are referred to as +-+- and +-νν¯ respectively.

It is assumed that an additional Higgs boson (denoted as H throughout this paper) would be produced predominantly via gluon–gluon fusion (ggF) and vector-boson fusion (VBF) processes, but that the ratio of the two production mechanisms is unknown in the absence of a specific model. For this reason, the results are interpreted separately for the ggF and VBF production modes, with events being classified into ggF- and VBF-enriched categories in both final states, as discussed in Sects. 5 and 6. With good mass resolution and a high signal-to-background ratio, the +-+- final state is well suited to a search for a narrow resonance with mass mH between 200GeV and 1200GeV. The +-νν¯ search covers the 300GeV<mH<1400GeV range and dominates at high masses due to its larger branching ratio.

These searches look for an excess in distributions of the four-lepton invariant mass, m4, for the +-+- final state, and the transverse invariant mass, mT, for the +-νν¯ final state, as the escaping neutrinos do not allow the full reconstruction of the final state. The transverse invariant mass is defined as:

mTmZ2+pT2+mZ2+ETmiss22-pT+ETmiss2,

where mZ is the mass of the Z boson, pT is the transverse momentum of the lepton pair and ETmiss is the missing transverse momentum, with magnitude ETmiss. In the absence of such an excess, limits on the production rate of different signal hypotheses are obtained from a simultaneous likelihood fit to the two mass distributions. The first hypothesis is the ggF and VBF production of a heavy Higgs boson (spin-0 resonance) under the narrow-width approximation (NWA). The upper limits on the production rate of a heavy Higgs boson are then translated into exclusion contours in the context of the two-Higgs-doublet model. As several theoretical models favour non-negligible natural widths, large-width assumption (LWA) models, assuming widths of 1%, 5% and 10% of the resonance mass, are also studied. The interference between the heavy scalar and the SM Higgs boson as well as between the heavy scalar and the ggZZ continuum background are taken into account in this study. Limits are also set on the Randall–Sundrum (RS) model [12, 13] with a warped extra dimension giving rise to a spin-2 Kaluza–Klein (KK) excitation of the graviton GKK.

Other searches for diboson resonances decaying into WW or ZZ or WZ have been performed by ATLAS [1416] and CMS [1719].

With a significant increase in integrated luminosity and an improved discovery potential from the higher parton luminosities [20] at a centre-of-mass energy of s = 13 TeV as compared to s = 8 TeV, the results of this paper improve upon previous results published by the ATLAS Collaboration from a search for an additional heavy Higgs boson [21]. Results of a similar search from the data collected at the LHC with s = 8 TeV have also been reported by the CMS Collaboration [22].

ATLAS detector

The ATLAS experiment is described in detail in Ref. [23]. ATLAS is a multi-purpose detector with a forward–backward symmetric cylindrical geometry and a solid-angle1 coverage of nearly 4π. The inner tracking detector (ID), covering the region |η|< 2.5, consists of a silicon pixel detector, a silicon microstrip detector and a transition-radiation tracker. The innermost layer of the pixel detector, the insertable B-layer (IBL) [24], was installed between Run 1 and Run 2 of the LHC. The inner detector is surrounded by a thin superconducting solenoid providing a 2T magnetic field, and by a finely segmented lead/liquid-argon (LAr) electromagnetic calorimeter covering the region |η|< 3.2. A steel/scintillator-tile hadronic calorimeter provides coverage in the central region |η|< 1.7. The end-cap and forward regions, covering the pseudorapidity range 1.5 <|η|< 4.9, are instrumented with electromagnetic and hadronic LAr calorimeters, with steel, copper or tungsten as the absorber material. A muon spectrometer (MS) system incorporating large superconducting toroidal air-core magnets surrounds the calorimeters. Three layers of precision wire chambers provide muon tracking in the range |η|< 2.7, while dedicated fast chambers are used for triggering in the region |η|< 2.4. The trigger system, composed of two stages, was upgraded [25] before Run 2. The first stage, implemented with custom hardware, uses information from calorimeters and muon chambers to reduce the event rate from about 40 MHz to a maximum of 100 kHz. The second stage, called the high-level trigger (HLT), reduces the data acquisition rate to about 1 kHz on average. The HLT is software-based and runs reconstruction algorithms similar to those used in the offline reconstruction.

Data and Monte Carlo samples

The proton–proton (pp) collision data used in these searches were collected by the ATLAS detector at a centre-of-mass energy of 13 TeV with a 25 ns bunch-spacing configuration during 2015 and 2016. The data are subjected to quality requirements: if any relevant detector component is not operating correctly during a period in which an event is recorded, the event is rejected. After these quality requirements, the total accumulated data sample corresponds to an integrated luminosity of 36.1 fb-1.

Simulated events are used to determine the signal acceptance and some of the background contributions to these searches. The particle-level events produced by each Monte Carlo (MC) event generator were processed through the ATLAS detector simulation [26] within the GEANT4 framework [27]. Additional inelastic pp interactions (pile-up) were overlaid on the simulated signal and background events. The MC event generator used for this is Pythia 8.186 [28] with the A2 set of tuned parameters [29] and the MSTW2008LO [30] parton distribution functions (PDF) set. The simulated events are weighted to reproduce the observed distribution of the mean number of interactions per bunch crossing in data (pile-up reweighting). The properties of the bottom and charm hadron decays were simulated by the EvtGen v1.2.0 program [31].

Heavy spin-0 resonance production was simulated using the Powheg-Box v2 [32] MC event generator. Gluon–gluon fusion and vector-boson fusion production modes were calculated separately with matrix elements up to next-to-leading order (NLO) in QCD. Powheg-Box was interfaced to Pythia 8.212 [33] for parton showering and hadronisation, and for decaying the Higgs boson into the HZZ+-+- or HZZ+-νν¯ final states. The CT10 PDF set [34] was used for the hard process. Events from ggF and VBF production were generated in the 300GeV<mH<1600 GeV mass range under the NWA, using a step of 100 (200) GeV up to (above) 1000 GeV in mass. For the +-+- final state, due to the sensitivity of the analysis at lower masses, events were also generated for mH=200 GeV.

In addition, events from ggF production with a boson width of 5, 10 and 15% of the scalar mass mH were generated with MadGraph5_aMC@NLO v2.3.2 [35] interfaced to Pythia 8.210 for parton showering and hadronisation for both final states. For the +-+- final state, the m4 distribution is parameterised analytically as described in Sect. 5.3, and the samples with a width of 15% of mH are used to validate the parameterisation. For the +-νν¯ final state, a reweighting procedure as described in Sect. 6.3 is used on fully simulated events to obtain the reconstructed mT distribution at any value of mass and width tested. To have a better description of the jet multiplicity, MadGraph5_aMC@NLO was also used to generate events for the process ppH + 2 jets at NLO QCD accuracy with the FxFx merging scheme [36].

The fraction of the ggF events that enter into the VBF-enriched category is estimated from the MadGraph5_aMC@NLO simulation.

Spin-2 Kaluza–Klein gravitons from the Bulk Randall–Sundrum model [37] were generated with MadGraph5_aMC@NLO at leading order (LO) in QCD. The dimensionless coupling k/M¯Pl, where M¯Pl=MPl/8π is the reduced Planck scale and k is the curvature scale of the extra dimension, is set to 1. In this configuration, the width of the resonance is expected to be 6% of its mass.

Mass points between 600 GeV and 2 TeV with 200 GeV spacing were generated for the +-νν¯ final state. These samples were processed through a fast detector simulation [26] that uses a parameterisation of the response of electromagnetic and hadronic calorimeters [38], while the response of the ID and MS detectors is fully simulated.

The qq¯ZZ background for the +-νν¯ final state was simulated by the Powheg-Box v2 event generator [32] and interfaced to Pythia 8.186 [28] for parton showering and hadronisation. The CT10nlo PDF set [34] was used for hard-scattering processes. Next-to-next-to-leading-order (NNLO) QCD and NLO EW corrections are included [3941] as a function of the invariant mass mZZ of the ZZ system. For the +-+- final state, this background was simulated with the Sherpa v2.2.1 [4244] event generator, with the NNPDF3.0 NNLO PDF set [45] for the hard-scattering process. NLO accuracy is achieved in the matrix-element calculation for 0- and 1-jet final states and LO accuracy for 2- and 3-jet final states. The merging with the Sherpa parton shower [46] was performed using the MePs@NLO prescription [47].

NLO EW corrections were applied as a function of mZZ [41, 48]. In addition, Sherpa v2.2.1 was used for the +-νν¯ final state to scale the fraction of events in the VBF-enriched category obtained from Powheg-Box simulation, because the Sherpa event generator calculates matrix elements up to one parton at NLO and up to three partons at LO. The EW production of a ZZ pair and two additional jets via vector-boson scattering up to O(αEW6) was generated using Sherpa, where the process ZZZ4qq is also taken into account.

The ggZZ production was modelled by Sherpa v2.1.1 at LO in QCD for the +-+- final state and by gg2VV [49] for the +-νν¯ final state, both including the off-shell h boson contribution and the interference between the h and ZZ backgrounds. The K-factor accounting for higher-order QCD effects for the ggZZ continuum production was calculated for massless quark loops [5052] in the heavy-top-quark approximation [53], including the ggHZZ process [54]. Based on these studies, a constant K-factor of 1.7 is used, and a relative uncertainty of 60% is assigned to the normalisation in both searches.

The WW and WZ diboson events were simulated by Powheg-Box, using the CT10nlo PDF set and Pythia 8.186 for parton showering and hadronisation. The production cross section of these samples is predicted at NLO in QCD.

Events containing a single Z boson with associated jets were simulated using the Sherpa v2.2.1 event generator. Matrix elements were calculated for up to two partons at NLO and four partons at LO using the Comix [43] and OpenLoops [44] matrix-element generators and merged with the Sherpa parton shower [46] using the ME+PS@NLO prescription [47]. The NNPDF3.0 NNLO PDF set was used in conjunction with dedicated parton-shower tuning developed by the Sherpa authors. The Z + jets events are normalised using the NNLO cross sections [55].

The triboson backgrounds ZZZ, WZZ, and WWZ with fully leptonic decays and at least four prompt charged leptons were modelled using Sherpa v2.1.1. For the fully leptonic tt¯+Z background, with four prompt leptons originating from the decays of the top quarks and Z boson, MadGraph5_aMC@NLO was used. The tt¯ background, as well as the single-top and Wt production, were modelled using Powheg-Box v2 interfaced to Pythia 6.428 [56] with the Perugia 2012 [57] set of tuned parameters for parton showering and hadronisation, to PHOTOS [58] for QED radiative corrections and to Tauola [59, 60] for the simulation of τ-lepton decays.

In order to study the interference treatment for the LWA case, samples containing the ggZZ continuum background (B) as well as its interference (I) with a hypothetical heavy scalar (S) were used and are referred to as SBI samples hereafter. In the +-+- final state the MCFM NLO event generator [61], interfaced to Pythia 8.212, was used to produce SBI samples where the width of the heavy scalar is set to 15% of its mass, for masses of 200, 300, 400, 500, 600, 800, 1000, 1200 and 1400 GeV. Background-only samples were also generated with the MCFM event generator, and are used to extract the signal-plus-interference term (SI) by subtracting them from the aforementioned SBI samples. For the +-νν¯ final state, the SBI samples were generated with the gg2VV event generator. The samples include signal events with a scalar mass of 400, 700, 900, 1200 and 1500 GeV.

Event reconstruction

Electrons are reconstructed using information from the ID and the electromagnetic calorimeter [62]. Electron candidates are clusters of energy deposits associated with ID tracks, where the final track–cluster matching is performed after the tracks have been fitted with a Gaussian-sum filter (GSF) to account for bremsstrahlung energy losses. Background rejection relies on the longitudinal and transverse shapes of the electromagnetic showers in the calorimeters, track–cluster matching and properties of tracks in the ID. All of this information, except for that related to track hits, is combined into a likelihood discriminant.

The selection used combines the likelihood with the number of track hits and defines two working points (WP) which are used in the analyses presented here. The +-+- analysis uses a “loose” WP, with an efficiency ranging from 90% for transverse momentum pT=20GeV to 96% for pT>60GeV. A “medium” WP was chosen for the +-νν¯ analysis with an efficiency increasing from 82% at pT=20GeV to 93% for pT>60GeV. The electron’s transverse momentum is computed from the cluster energy and the track direction at the interaction point.

Muons are formed from tracks reconstructed in the ID and MS, and their identification is primarily based on the presence of the track or track segment in the MS [63]. If a complete track is present in both the ID and the MS, a combined muon track is formed by a global fit using the hit information from both the ID and MS detectors (combined muon), otherwise the momentum is measured using the ID, and the MS track segment serves as identification (segment-tagged muon). The segment-tagged muon is limited to the centre of the barrel region (|η|<0.1) which has reduced MS geometrical coverage. Furthermore, in this central region an ID track with pT >15 GeV is identified as a muon if its calorimetric energy deposition is consistent with a minimum-ionising particle (calorimeter-tagged muon). In the forward region (2.5<|η|<2.7) with limited or no ID coverage, the MS track is either used alone (stand-alone muon) or combined with silicon hits, if found in the forward ID (combined muon). The ID tracks associated with the muons are required to have a minimum number of associated hits in each of the ID subdetectors to ensure good track reconstruction. The stand-alone muon candidates are required to have hits in each of the three MS stations they traverse. A “loose” muon identification WP, which uses all muon types and has an efficiency of 98.5%, is adopted by the +-+- analysis. For the +-νν¯ analysis a “medium” WP is used, which only includes combined muons and has an efficiency of 97%.

Jets are reconstructed using the anti-kt algorithm [64] with a radius parameter R = 0.4 implemented in the FastJet package [65], and positive-energy clusters of calorimeter cells as input. The algorithm suppresses noise and pile-up by keeping only cells with a significant energy deposit and their neighbouring cells. Jets are calibrated using a dedicated scheme designed to adjust, on average, the energy measured in the calorimeter to that of the true jet energy [66]. The jets used in this analysis are required to satisfy pT>20GeV and |η|<4.5. To reduce the number of jet candidates originating from pile-up vertices, an additional requirement that uses the track and vertex information inside a jet is imposed on jets with pT<60GeV and |η|<2.4 [67].

Jets containing b-hadrons, referred to as b-jets, are identified by the long lifetime, high mass and decay multiplicity of b-hadrons, as well as the hard b-quark fragmentation function. The +-νν¯ analysis identifies b-jets of pT>20GeV and |η|<2.5 using an algorithm that achieves an identification efficiency of about 85% in simulated tt¯ events, with a rejection factor for light-flavour jets of about 33 [68, 69].

Selected events are required to have at least one vertex with two associated tracks with pT > 400 MeV, and the primary vertex is chosen to be the vertex reconstructed with the largest pT2. As lepton and jet candidates can be reconstructed from the same detector information, a procedure to resolve overlap ambiguities is applied. If an electron and a muon share the same ID track, the muon is selected unless it is calorimeter-tagged and does not have a MS track, or is a segment-tagged muon, in which case the electron is selected. Reconstructed jets which overlap with electrons (muons) in a cone of size ΔR(Δη)2+(Δϕ)2= 0.2 (0.1) are removed.

The missing transverse momentum ETmiss, which accounts for the imbalance of visible momenta in the plane transverse to the beam axis, is computed as the negative vector sum of the transverse momenta of all identified electrons, muons and jets, as well as a “soft term”, accounting for unclassified soft tracks and energy clusters in the calorimeters [70]. This analysis uses a track-based soft term, which is built by combining the information provided by the ID and the calorimeter, in order to minimise the effect of pile-up which degrades the ETmiss resolution. The soft term is computed using the momenta of the tracks associated with the primary vertex, while the jet and electron momenta are computed at the calorimeter level to allow the inclusion of neutral particles. Jet–muon overlap is accounted for in the ETmiss calculation. This corrects for fake jets due to pile-up close to muons and double-counted jets from muon energy losses.

HZZ+-+- event selection and background estimation

Event selection

Four-lepton events are selected and initially classified according to the lepton flavours: 4μ, 2e2μ, 4e, called “channels” hereafter. They are selected with single-lepton, dilepton and trilepton triggers, with the dilepton and trilepton ones including electron(s)–muon(s) triggers. Single-electron triggers apply “medium” or “tight” likelihood identification, whereas multi-electron triggers apply “loose” or “medium” identification. For the bulk of the data, recorded in 2016, the lowest pT threshold for the single-electron (muon) triggers used is set to 26 (26) GeV, for the dielectron (dimuon) triggers to 15 (10) GeV and for the trielectron (trimuon) triggers to 12 (6) GeV. For the data collected in 2015, the instantaneous luminosity was lower so the trigger thresholds were lower; this increases the signal efficiency by less than 1%. Globally, the trigger efficiency for signal events passing the final selection requirements is about 98%.

In each channel, four-lepton candidates are formed by selecting a lepton-quadruplet made out of two same-flavour, opposite-sign lepton pairs, selected as described in Sect. 4. Each electron (muon) must satisfy pT>7 (5) GeV and be measured in the pseudorapidity range of η<2.47 (2.7). The highest-pT lepton in the quadruplet must satisfy pT >20 GeV, and the second (third) lepton in pT order must satisfy pT >15 GeV (10 GeV). In the case of muons, at most one calorimeter-tagged, segment-tagged or stand-alone (2.5<|η|<2.7) muon is allowed per quadruplet.

If there is ambiguity in assigning leptons to a pair, only one quadruplet per channel is selected by keeping the quadruplet with the lepton pairs closest (leading pair) and second closest (subleading pair) to the Z boson mass, with invariant masses referred to as m12 and m34 respectively. In the selected quadruplet, m12 is required to be 50GeV<m12<106GeV, while m34 is required to be less than 115 GeV and greater than a threshold that is 12 GeV for m4140GeV, rises linearly from 12 GeV to 50 GeV with m4 in the interval of [140 GeV, 190 GeV] and is fixed to 50 GeV for m4>190GeV.

Selected quadruplets are required to have their leptons separated from each other by ΔR>0.1 if they are of the same flavour and by ΔR>0.2 otherwise. For 4μ and 4e quadruplets, if an opposite-charge same-flavour lepton pair is found with m below 5 GeV, the quadruplet is removed to suppress the contamination from J/ψ mesons. If multiple quadruplets from different channels are selected at this point, only the quadruplet from the channel with the highest expected signal rate is retained, in the order: 4μ, 2e2μ, 4e.

The Z + jets and tt¯ background contributions are reduced by imposing impact-parameter requirements as well as track- and calorimeter-based isolation requirements on the leptons. The transverse impact-parameter significance, defined as the impact parameter calculated with respect to the measured beam line position in the transverse plane divided by its uncertainty, |d0|/σd0, for all muons (electrons) is required to be lower than 3 (5). The normalised track-isolation discriminant, defined as the sum of the transverse momenta of tracks, inside a cone of size ΔR=0.3(0.2) around the muon (electron) candidate, excluding the lepton track, divided by the lepton pT, is required to be smaller than 0.15. The larger muon cone size corresponds to that used by the muon trigger. Contributions from pile-up are suppressed by requiring tracks in the cone to originate from the primary vertex. To retain efficiency at higher pT, the track-isolation cone size is reduced to 10 GeV/pT for pT above 33 (50) GeV for muons (electrons).

The relative calorimetric isolation is computed as the sum of the cluster transverse energies ET, in the electromagnetic and hadronic calorimeters, with a reconstructed barycentre inside a cone of size ΔR=0.2 around the candidate lepton, divided by the lepton pT. The clusters used for the isolation are the same as those for reconstructing jets. The relative calorimetric isolation is required to be smaller than 0.3 (0.2) for muons (electrons). The measured calorimeter energy around the muon (inside a cone of size ΔR=0.1) and the cells within 0.125×0.175 in η×ϕ around the electron barycentre are excluded from the respective sums. The pile-up and underlying-event contributions to the calorimeter isolation are subtracted event by event [71]. For both the track- and calorimeter-based isolation requirements, any contribution arising from other leptons of the quadruplet is subtracted.

An additional requirement based on a vertex-reconstruction algorithm, which fits the four-lepton candidates with the constraint that they originate from a common vertex, is applied in order to further reduce the Z+jets and tt¯ background contributions. A loose cut of χ2/ndof<6 for 4μ and <9 for the other channels is applied, which retains a signal efficiency larger than 99% in all channels.

The QED process of radiative photon production in Z boson decays is well modelled by simulation. Some of the final-state-radiation (FSR) photons can be identified in the calorimeter and incorporated into the +-+- analysis. The strategy to include FSR photons into the reconstruction of Z bosons is the same as in Run 1 [21]. It consists of a search for collinear (for muons) and non-collinear FSR photons (for muons and electrons) with only one FSR photon allowed per event. After the FSR correction, the lepton four-momenta of both dilepton pairs are recomputed by means of a Z-mass-constrained kinematic fit. The fit uses a Breit–Wigner Z boson line-shape and a single Gaussian function per lepton to model the momentum response function with the Gaussian width set to the expected resolution for each lepton. The Z-mass constraint is applied to both Z candidates, and improves the m4 resolution by about 15%.

In order to be sensitive to the VBF production mode, events are classified into four categories: one for the VBF production mode and three for the ggF production mode, one for each of the three channels. If an event has two or more jets with pT greater than 30 GeV, with the two leading jets being well separated in η, |Δηjj|>3.3, and having an invariant mass mjj>400GeV, this event is classified into the VBF-enriched category; otherwise the event is classified into one of the ggF-enriched categories. Such classification is used only in the search for a heavy scalar produced with the NWA.

The signal acceptance, defined as the ratio of the number of reconstructed events passing the analysis requirements to the number of simulated events in each category, is shown in Table 1, for the ggF and VBF production modes as well as different resonance masses. The contribution from final states with τ leptons decaying into electrons or muons is found to be negligible.

Table 1.

Signal acceptance for the +-+- analysis, for both the ggF and VBF production modes and resonance masses of 300 and 600 GeV. The acceptance is defined as the ratio of the number of reconstructed events after all selection requirements to the number of simulated events for each channel/category

Mass Production mode ggF-enriched categories VBF-enriched category (%)
4μ channel (%) 2e2μ channel (%) 4e channel (%)
300 GeV ggF 56 48 40 1
VBF 36 30 24 21
600 GeV ggF 64 56 48 3
VBF 36 34 32 26

Background estimation

The main background component in the HZZ+-+- final state, accounting for 97% of the total expected background events, is non-resonant ZZ production. This arises from quark–antiquark annihilation (86%), gluon-initiated production (10%) and a small contribution from EW vector-boson scattering (1%). The last is more important in the VBF-enriched category, where it accounts for 16% of the total expected background. These backgrounds are all modelled by MC simulation as described in Sect. 3. Additional background comes from the Z + jets and tt¯ processes, which contribute at the percent level and decrease more rapidly than the non-resonant ZZ production as a function of m4. These backgrounds are estimated using data where possible, following slightly different approaches for final states with a dimuon (+μμ) or a dielectron (+ee) subleading pair [72].

The +μμ non-ZZ background comprises mostly tt¯ and Z + jets events, where in the latter case the muons arise mostly from heavy-flavour semileptonic decays and to a lesser extent from π/K in-flight decays. The contribution from single-top production is negligible. The normalisations of the Z + jets and tt¯ backgrounds are determined using fits to the invariant mass of the leading lepton pair in dedicated data control regions. The control regions are formed by relaxing the χ2 requirement on the vertex fit, and by inverting and relaxing isolation and/or impact-parameter requirements on the subleading muon pair. An additional control region (eμμμ) is used to improve the tt¯ background estimate. Transfer factors to extrapolate from the control regions to the signal region are obtained separately for tt¯ and Z + jets using simulated events. The transfer factors have a negligible impact on the m4 shape of the +μμ background.

The main background for the +ee process arises from the misidentification of light-flavour jets as electrons, photon conversions and the semileptonic decays of heavy-flavour hadrons. The +ee control-region selection requires the electrons in the subleading lepton pair to have the same charge, and relaxes the identification and isolation requirements on the electron candidate, denoted X, with the lower transverse momentum. The heavy-flavour background is completely determined from simulation, whereas the light-flavour and photon-conversion background is obtained with the sPlot [73] method, based on a fit to the number of hits in the innermost ID layer in the data control region. Transfer factors for the light-flavour jets and converted photons, obtained from simulated samples, are corrected using a Z+X control region and then used to extrapolate the extracted yields to the signal region. Both the yield extraction and the extrapolation are performed in bins of the transverse momentum of the electron candidate and the jet multiplicity.

The WZ production process is included in the data-driven estimates for the +ee final states, while it is added from simulation for the +μμ final states. The contributions from tt¯V (where V stands for either a W or a Z boson) and triboson processes are minor and taken from simulated samples.

Signal and background modelling

The parameterisation of the reconstructed four-lepton invariant mass m4 distribution for signal and background is based on the MC simulation and used to fit the data.

In the case of a narrow resonance, the width in m4 is determined by the detector resolution, which is modelled by the sum of a Crystal Ball (C) function [74, 75] and a Gaussian (G) function:

Ps(m4)=fC×C(m4;μ,σC,αC,nC)+(1-fC)×G(m4;μ,σG).

The Crystal Ball and the Gaussian functions share the same peak value of m4 (μ), but have different resolution parameters, σC and σG. The αC and nC parameters control the shape and position of the non-Gaussian tail and the parameter fC ensures the relative normalisation of the two probability density functions. To improve the stability of the parameterisation in the full mass range considered, the parameter nC is set to a fixed value. The bias in the extraction of signal yields introduced by using the analytical function is below 1.5%. The function parameters are determined separately for each final state using signal simulation, and fitted to first- and second-degree polynomials in scalar mass mH to interpolate between the generated mass points. The use of this parameterisation for the function parameters introduces an extra bias in the signal yield and mH extraction of about 1%. An example of this parameterisation is illustrated in Fig. 1, where the left plot shows the mass distribution for simulated samples at mH =300,600,900 GeV and the right plot shows the RMS of the m4 distribution in the range considered for this search.

Fig. 1.

Fig. 1

a Parameterisation of the four-lepton invariant mass (m4) spectrum for various resonance mass (mH) hypotheses in the NWA. Markers show the simulated m4 distribution for three specific values of mH (300, 600, 900 GeV), normalised to unit area, and the dashed lines show the parameterisation used in the 2e2μ channel for these mass points as well as for intervening ones. b RMS of the four-lepton invariant mass distribution as a function of mH

In the case of the LWA, the particle-level line-shape of m4 is derived from a theoretical calculation, as described in Ref. [76], and is then convolved with the detector resolution, using the same procedure as for the modelling of the narrow resonance.

The m4 distribution for the ZZ continuum background is taken from MC simulation, and parameterised by an empirical function for both the quark- and gluon-initiated processes:

fqqZZ/ggZZ(m4)=(f1(m4)+f2(m4))×H(m0-m4)×C0+f3(m4)×H(m4-m0),

where:

f1(m4)=exp(a1+a2·m4),f2(m4)=12+12erfm4-b1b2×11+expm4-b1b3,f3(m4)=exp(c1+c2·m4+c3·m42+c4·m42.7),C0=f3(m0)f1(m0)+f2(m0).

The function’s first part, f1, covers the low-mass part of the spectrum where one of the Z bosons is off-shell, while f2 models the ZZ threshold around 2·mZ and f3 describes the high-mass tail. The transition between low- and high-mass parts is performed by the Heaviside step function H(x) around m0=240 GeV. The continuity of the function around m0 is ensured by the normalisation factor C0 that is applied to the low-mass part. Finally, ai, bi and ci are shape parameters which are obtained by fitting the m4 distribution in simulation for each category. The uncertainties in the values of these parameters from the fit are found to be negligible. The MC statistical uncertainties in the high-mass tail are taken into account by assigning a 1% uncertainty to c4.

The m4 shapes are extracted from simulation for most background components (tt¯V, VVV, +μμ and heavy-flavour hadron component of +ee), except for the light-flavour jets and photon conversions in the case of +ee background, which is taken from the control region as described in Sect. 5.2.

Interference modelling

The gluon-initiated production of a heavy scalar H, the SM h and the ggZZ continuum background all share the same initial and final state, and thus lead to interference terms in the total amplitude. Theoretical calculations described in Ref. [77] have shown that the effect of interference could modify the integrated cross section by up to O(10%), and this effect is enhanced as the width of the heavy scalar increases. Therefore, a search for a heavy scalar Higgs boson in the LWA case must properly account for two interference effects: the interference between the heavy scalar and the SM Higgs boson (denoted by Hh) and between the heavy scalar and the ggZZ continuum (denoted by HB).

Assuming that H and h bosons have similar properties, as postulated by the 2HDM, they have the same production and decay amplitudes and therefore the only difference between the signal and interference terms in the production cross section comes from the propagator. Hence, the acceptance and resolution of the signal and interference terms are expected to be the same. The Hh interference is obtained by reweighting the particle-level line-shape of generated signal events using the following formula:

w(m4)=2·Re1s-sH·1(s-sh)1s-sH2,

where 1/s-sH(h) is the propagator for a scalar (H or h). The particle-level line-shape is then convolved with the detector resolution function, and the signal and interference acceptances are assumed to be the same.

In order to extract the HB interference contribution, signal-only and background-only samples are subtracted from the generated SBI samples. The extracted particle-level m4 distribution for the HB interference term is then convolved with the detector resolution.

Figure 2 shows the overlay of the signal, both interference effects and the total line-shape for different mass and width hypotheses assuming the couplings expected in the SM for a heavy Higgs boson. As can be seen, the two interference effects tend to cancel out, and the total interference yield is for the most part positive, enhancing the signal.

Fig. 2.

Fig. 2

Particle-level four-lepton mass m4 model for signal only (red), Hh interference (green), HB interference (blue) and the sum of the three processes (black). Three values of the resonance mass mH (400, 600, 800 GeV) are chosen, as well as three values of the resonance width ΓH (1, 5, 10% of mH). The signal cross section, which determines the relative contribution of the signal and interference, is taken to be the cross section of the expected limit for each combination of mH and ΓH. The full model (black) is finally normalised to unity and the other contributions are scaled accordingly

HZZ+-νν¯ event selection and background estimation

Event selection

The analysis is designed to select ZZ+-νν¯ events (with =e,μ), where the missing neutrinos are identified by a large ETmiss, and to discriminate against the large Z + jets, WZ and top-quark backgrounds.

Events are required to pass either a single-electron or a single-muon trigger, where different pT thresholds are used depending on the instantaneous luminosity of the LHC. For the 2015 data the electron and muon triggers had pT thresholds of 24 and 20 GeV respectively, while for 2016 the muon trigger threshold was increased to 24 GeV. For both triggers, the threshold is set to 26 GeV when the instantaneous luminosity exceeds the value of 1034 cm-2s-1. The trigger efficiency for signal events passing the final selection is about 99%.

Events are selected if they contain exactly two opposite-charge leptons of the same flavour and “medium” identification, with the more energetic lepton having pT>30 GeV and the other one having pT>20 GeV. The same impact-parameter significance criteria as defined in Sect. 5.1 are applied to the selected leptons. Track- and calorimeter-based isolation criteria as defined in Sect. 5.1 are also applied to the leptons, but in this analysis the isolation criteria are optimised by adjusting the isolation threshold so that their selection efficiency is 99%. If an additional lepton with pT>7 GeV and “loose” identification is found, the event is rejected to reduce the amount of WZ background. In order to select leptons originating from the decay of a Z boson, the invariant mass of the pair is required to be in the range 76 to 106 GeV. Moreover, since a Z boson originating from the decay of a high-mass particle is boosted, the two leptons are required to be produced with an angular separation of ΔR<1.8.

Events with neutrinos in the final state are selected by requiring ETmiss>120 GeV, and this requirement heavily reduces the amount of Z + jets background. In signal events with no initial- or final-state radiation the visible Z boson’s transverse momentum is expected to be opposite the missing transverse momentum, and this characteristic is used to further suppress the Z + jets background. The azimuthal angle between the dilepton system and the missing transverse momentum (Δϕ(,ETmiss)) is thus required to be greater than 2.7 and the fractional pT difference, defined as |pTmiss,jet-pT|/pT, to be less than 20%, where pTmiss,jet=|ETmiss+ΣjetpTjet|.

Additional selection criteria are applied to keep only events with ETmiss originating from neutrinos rather than detector inefficiencies, poorly reconstructed high-pT muons or mismeasurements in the hadronic calorimeter. If at least one reconstructed jet has a pT greater than 100 GeV, the azimuthal angle between the highest-pT jet and the missing transverse momentum is required to be greater than 0.4. Similarly, if ETmiss is found to be less than 40% of the scalar sum of the transverse momenta of leptons and jets in the event (HT), the event is rejected. Finally, to reduce the tt¯ background, events are rejected whenever a b-tagged jet is found.

The sensitivity of the analysis to the VBF production mode is increased by creating a dedicated category of VBF-enriched events. The selection criteria, determined by optimising the expected signal significance using signal and background MC samples, require the presence of at least two jets with pT>30 GeV  where the two highest-pT jets are widely separated in η, |Δηjj|>4.4, and have an invariant mass mjj greater than 550 GeV.

The signal acceptance, defined as the ratio of the number of reconstructed events passing the analysis requirements to the number of simulated events in each category, is shown in Table 2, for the ggF and VBF production modes as well as for different resonance masses. The acceptance increases with mass due to a kinematic threshold determined by the ETmiss selection criteria. Hence the +-νν¯ search considers only masses of 300 GeV and above, where its inclusion improves the combined sensitivity.

Table 2.

Signal acceptance for the +-νν¯ analysis, for both the ggF and VBF production modes and resonance masses of 300 and 600 GeV. The acceptance is defined as the ratio of the number of reconstructed events after all selection requirements to the number of simulated events for each channel/category

Mass Production mode ggF-enriched categories VBF-enriched category (%)
μ+μ- channel (%) e+e- channel (%)
300 GeV ggF 6 5 <0.05
VBF 2.6 2.4 0.7
600 GeV ggF 44 44 1
VBF 27 27 13

Background estimation

The dominant and irreducible background for this search is non-resonant ZZ production, which accounts for about 60% of the expected background events. The second largest background comes from WZ production ( 30%) followed by Z + jets production with poorly reconstructed ETmiss ( 6%). Other sources of background are the WW, tt¯, Wt and Zττ processes ( 3%). Finally, a small contribution comes from W + jets, tt¯, single-top-quark and multi-jet processes, with at least one jet misidentified as an electron or muon, as well as from tt¯V/VVV events. In both the ggF- and in the VBF-enriched signal regions, the ZZ background is modelled using MC simulation and normalised using SM predictions, as explained in Sect. 3. The remaining backgrounds are mostly estimated using control samples in data.

The WZ background is modelled using simulation but a correction factor for its normalisation is extracted as the ratio of data to simulated events in a dedicated control region, after subtracting from data the non-WZ background contributions. The WZ-enriched control sample, called the 3 control region, is built by selecting Z candidates with an additional electron or muon. This additional lepton is required to satisfy all selection criteria used for the other two leptons, with the only difference that its transverse momentum is required to be greater than 7 GeV. The contamination from Z + jets and tt¯ events is reduced by vetoing events with at least one b-tagged jet and by requiring the transverse mass of the W boson (mTW), built using the additional lepton and the ETmiss vector, to be greater than 60 GeV. The distribution of the missing transverse momentum for data and simulated events in the 3 control region is shown in Fig. 3a. The correction factor derived in the 3 control region is found to be 1.29±0.09, where the uncertainty includes effects from the number of events in the control region as well as from experimental systematic uncertainties. Since there are few events after applying all the VBF selection requirements to the WZ-enriched control sample, the estimation for the VBF-enriched category is performed by including in the 3 control region only the requirement of at least two jets with pT>30 GeV. Finally, a transfer factor is derived from MC simulation by calculating the probability of events satisfying all analysis selection criteria and containing two jets with pT>30 GeV to satisfy the |Δηjj|>4.4 and mjj>550 GeV requirements. An additional systematic uncertainty obtained from the comparison of the |Δηjj| distribution between Sherpa and Powheg-Box generators is included to cover potential mismodellings of the VBF selection. Such systematic uncertainty is included in all background estimations when extrapolating from a control region.

Fig. 3.

Fig. 3

Missing transverse momentum ETmiss distribution a for events in the 3 control region as defined in the text and b for e±μ lepton pairs after applying the dilepton invariant mass requirement, before applying the rest of the control region selection. The backgrounds are determined following the description in Sect. 6.2 and the last bin includes the overflow. The small excess below 120 GeV in (b) arises from Z + jets background which is here taken from simulation, and lies outside the control region. The error bars on the data points indicate the statistical uncertainty, while the systematic uncertainty in the prediction is shown by the hatched band. The lower panels show the ratio of data to prediction

The non-resonant background includes mainly WW, tt¯ and Wt processes, but also Zττ events in which the τ leptons produce light leptons and ETmiss. It is estimated by using a control sample of events with lepton pairs of different flavour (e±μ), satisfying all analysis selection criteria.

Figure 3b shows the missing-transverse-momentum distribution for e±μ events in data and simulation after applying the dilepton invariant-mass selection but before applying the other selection requirements. The non-resonant background in the e+e- and μ+μ- channels is estimated by applying a scale factor (f) to the selected events in the e±μ control region, such that:

Neebkg=12×Neμdata,sub×f,Nμμbkg=12×Neμdata,sub×1f,

where Neebkg and Nμμbkg are the numbers of electron- and muon-pair events estimated in the signal region and Neμdata,sub is the number of events in the e±μ control sample with ZZ, WZ and other small backgrounds subtracted using simulation. The factor f takes into account the different selection efficiencies of e+e- and μ+μ- pairs at the level of the Z selection, and is measured from data as f2=Needata/Nμμdata, where Needata and Nμμdata are the numbers of events passing the Z boson mass requirement (76<m<106 GeV) in the electron and muon channel respectively. As no events survive in the e±μ control region after applying the full VBF selection, the background estimation is performed by including only the requirement of at least two jets with pT>30 GeV. The efficiency of the remaining selection requirements on |Δηjj| and mjj is obtained from simulated events.

The number of Z + jets background events in the signal region is estimated from data, using a so-called ABCD method [78], since events with no genuine ETmiss in the final state are difficult to model using simulation. The method combines the selection requirements presented in Sect. 6.1 (with nb-tags representing the number of b-tagged jets in the event) into two Boolean discriminants, V1 and V2, defined as:

V1ETmiss>120GeVandETmiss/HT>0.4,V2|pTmiss,jet-pT|/pT<0.2andΔϕ(,ETmiss)>2.7andΔR<1.8andnb-tags=0,

with all events required to pass the trigger and dilepton invariant-mass selections. The signal region (A) is thus obtained by requiring both V1 and V2 to be true, control regions B and C require only one of the two Boolean discriminants to be false (V1 and V2 respectively) and finally control region D is defined by requiring both V1 and V2 to be false. With this definition, an estimate of the number of events in region A is given by NAest=NCobs×(NBobs/NDobs), where NXobs is the number of events observed in region X after subtracting non-Z-boson backgrounds. This relation holds as long as the correlation between V1 and V2 is small, and this is achieved by introducing two additional requirements on control regions B and D, namely ETmiss > 30 GeV and ETmiss/ HT > 0.1. The estimation of the Z + jets background was cross-checked with another approach in which a control region is defined by inverting the analysis selection on ETmiss/HT and then using Z + jets MC simulation to perform the extrapolation to the signal region, yielding results compatible with the ABCD method. Finally, the estimate for the VBF-enriched category is performed by extrapolating the inclusive result obtained with the ABCD method to the VBF signal region, extracting the efficiency of the two-jet, |Δηjj| and mjj selection criteria from Z + jets simulation.

The W + jets and multi-jet background contributions are estimated from data using a so-called fake-factor method [79]. A control region enriched in fake leptons or non-prompt leptons from decays of hadrons is designed by requiring one lepton to pass all analysis requirements (baseline selection) and the other one to not pass either the lepton “medium” identification or the isolation criteria (inverted selection). The background in the signal region is then derived using a transfer factor, measured in a data sample enriched in Z + jets events, as the ratio of jets passing the baseline selection to those passing the inverted selection.

Finally, the background from the tt¯V and VVV processes is estimated using MC simulation.

Signal and background modelling

The modelling of the transverse mass mT distribution for signal and background is based on templates derived from fully-simulated events and afterwards used to fit the data. In the case of a narrow resonance, simulated MC events generated for fixed mass hypotheses as described in Sect. 3 are used as the inputs in the moment-morphing technique [80] to obtain the mT distribution for any other mass hypothesis.

The extraction of the interference terms for the LWA case is performed in the same way as in the +-+- final state, as described in Sect. 5.3. In the case of the +-νν¯ final state a correction factor, extracted as a function of mZZ, is used to reweight the interference distributions obtained at particle level to account for reconstruction effects. The final expected LWA mT distribution is obtained from the combination of the interference distributions with simulated mT distributions, which are interpolated between the simulated mass points with a weighting technique using the Higgs propagator, a method similar to that used for the interference.

Systematic uncertainties

The systematic uncertainties can be classified into experimental and theoretical uncertainties. The first category relates to the reconstruction and identification of leptons and jets, their energy scale and resolution, and the integrated luminosity. Systematic uncertainties in the data-driven background estimates are also included in this category. The second category includes uncertainties in the theoretical description of the signal and background processes.

In both cases the uncertainties are implemented as additional nuisance parameters (NP) that are constrained by a Gaussian distribution in the profile likelihood ratio, as discussed in Sect. 8.1. The uncertainties affect the signal acceptance, its selection efficiency and the discriminant distributions as well as the background estimates for both final states. Each source of uncertainty is either fully correlated or anti-correlated among the different channels and categories.

Experimental uncertainties

The uncertainty in the combined 2015 and 2016 integrated luminosity is 3.2%. This is derived from a preliminary calibration of the luminosity scale using xy beam-separation scans performed in August 2015 and May 2016, following a methodology similar to that detailed in Ref. [81].

The lepton identification and reconstruction efficiency and energy/momentum scale and resolution are derived from data using large samples of J/ψ and Z decays. The uncertainties in the reconstruction performance are computed following the method described in Ref. [63] for muons and Ref. [62] for electrons. Typical uncertainties in the identification and reconstruction efficiency are in the range 0.5–3.0% for muons and 1.0%–1.7% for electrons. The uncertainties in the electron energy scale, the muon momentum scale and their resolutions are small, and are fully correlated between the two searches (+-+- and +-νν¯ final states).

The uncertainties in the jet energy scale and resolution have several sources, including uncertainties in the absolute and relative in situ calibration, the correction for pile-up, the flavour composition and response [66]. These uncertainties are separated into independent components, which are fully correlated between the two searches. They vary from 4.5% for jets with transverse momentum pT = 20 GeV, decreasing to 1% for jets with pT=100–1500 GeV and increasing again to 3% for jets with higher pT, for the average pile-up conditions of the 2015 and 2016 data-taking period.

Uncertainties in the lepton and jet energy scales are propagated to the uncertainty in the ETmiss. Additionally, the uncertainties from the momentum scale and resolution of the tracks that are not associated with any identified lepton or jet contribute 8 and 3% respectively, to the uncertainty in the ETmiss value.

The efficiency of the lepton triggers in events with reconstructed leptons is nearly 100%, and hence the related uncertainties are negligible.

Theoretical uncertainties

For simulated signal and backgrounds, theoretical modelling uncertainties associated with the PDFs, missing QCD higher-order corrections (via variations of factorisation and renormalisation scales), and parton showering are considered.

For all signal hypotheses under consideration, the largest theoretical modelling uncertainties are due to missing QCD higher-order corrections and parton showering. The missing QCD higher-order corrections for ggF production events that fall into the VBF-enriched category are accounted for by varying the scales in MadGraph5_aMC@NLO and affect the signal acceptance by 10%. Parton showering uncertainties are of order 10% and are estimated by comparing Pythia 8.212 to Herwig++ [82].

For the qq¯ZZ background, the effect of the PDF uncertainties in the full mass range varies between 2% and 5% in all categories, and that of missing QCD higher-order corrections is about 10% in the ggF-enriched categories and 30% in the VBF-enriched category. The parton-shower uncertainties result in less than 1% impact in the ggF-enriched categories and about 10% impact in the VBF-enriched category.

For the ggZZ background, as described in Sect. 3, a 60% relative uncertainty in the inclusive cross section is considered, while a 100% uncertainty is assigned in the VBF-enriched category.

Results and interpretations

Statistical procedure

The statistical treatment of the data follows the procedure for the Higgs-boson search combination [83, 84], and is implemented with RooFit [85] and RooStats [86]. The test statistic employed for hypothesis testing and limit setting is the profiled likelihood ratio Λ(α,θ), which depends on one or more parameters of interest α, and additional nuisance parameters θ. The parameter of interest is the cross section times branching ratio for heavy-resonance production, assumed to be correlated between the two searches. The nuisance parameters represent the estimates of the systematic uncertainties and are each constrained by a Gaussian distribution. For each category of each search, a likelihood fit to the kinematic distribution of a discriminating variable is used to further separate signal from background. The +-+- final state uses m4 as the discriminant in each category, while the +-νν¯ final state uses mT in each category except for the VBF-enriched one where only the overall event counts are used.

As discussed in Sect. 7, the signal acceptance uncertainties, and many of the background theoretical and experimental uncertainties, are treated as fully correlated between the searches. A given correlated uncertainty is modelled in the fit by using a nuisance parameter common to all of the searches. The impact of a systematic uncertainty on the result depends on the production mode and the mass hypothesis. For ggF production, at lower masses the luminosity uncertainty, the modelling uncertainty of the Z + jets background and the statistical uncertainty in the eμ control region of the +-νν¯ final state dominate, and at higher masses the uncertainties in the electron-isolation efficiency become important, as also seen in VBF production. For VBF production, the dominant uncertainties come from the theoretical predictions of the ZZ events in the VBF category. Additionally at lower masses, the pile-up reweighting and the jet-energy-resolution uncertainties are also important. Table 3 shows the impact of the leading systematic uncertainties on the predicted signal event yield when the cross section times branching ratio is set to the expected upper limit (shown in Fig. 6), for ggF and VBF production modes. The impact of the uncertainty in the integrated luminosity, 3.2%, enters both in the normalisation of the fitted number of signal events as well as in the background predicted by simulation. This leads to a luminosity uncertainty which varies from 4 to 7% across the mass distribution, depending on the signal-to-background ratio.

Table 3.

Impact of the leading systematic uncertainties on the predicted signal event yield which is set to the expected upper limit, expressed as a percentage of the yield for the ggF (left) and VBF (right) production modes at mH=300, 600, and 1000GeV

ggF production VBF production
Systematic source Impact [%] Systematic source Impact [%]
mH=300GeV
Luminosity 4 Parton showering 9
Z + jets modelling (+-νν¯) 3.3 Jet energy scale 4
Parton showering 3.2 Luminosity 4
eμ statistical uncertainty +-νν¯ 3.2 qq¯ZZ QCD scale (VBF-enriched category) 4
mH=600GeV
Luminosity 6 Parton showering 6
Pile-up reweighting 5 Pile-up reweighting 6
Z + jets modelling (+-νν¯) 4 Jet energy scale 6
QCD scale of qq¯ZZ 3.1 Luminosity 4
mH=1000GeV
Luminosity 4 Parton showering 6
QCD scale of ggZZ 2.3 Jet energy scale 5
Jet vertex tagger 1.9 Z + jets modelling (+-νν¯) 4
Z + jets modelling (+-νν¯) 1.8 Luminosity 4

Fig. 6.

Fig. 6

The upper limits at 95% CL on the cross section times branching ratio as a function of the heavy resonance mass mH for a the ggF production mode(σggF×B(HZZ)) and b for the VBF production mode (σVBF×B(HZZ)) in the case of the NWA. The green and yellow bands represent the ± 1σ and ± 2σ uncertainties in the expected limits. The dashed coloured lines indicate the expected limits obtained from the individual searches

General results

The numbers of observed candidate events with mass above 130 GeV together with the expected background yields are presented in Table 4 for each of the four categories of the +-+- analysis. The m4 spectrum for the ggF-enriched and VBF-enriched categories is shown in Fig. 4.

Table 4.

+-+- search: expected and observed numbers of events for m4 >130 GeV, together with their statistical and systematic uncertainties, for the ggF- and VBF-enriched categories

Process ggF-enriched categories VBF-enriched category
4μ channel 2e2μ channel 4e channel
ZZ 297±1±40 480±1±60 193±1±25 15±0.1±6.0
ZZ (EW) 1.92±0.11±0.19 3.36±0.14±0.33 1.88±0.12±0.20 3.0±0.1±2.2
Z + jets/tt¯/WZ 3.7±0.1±0.8 7.8±0.1±1.1 4.4±0.1±0.8 0.37±0.01±0.05
Other backgrounds 5.1±0.1±0.6 8.7±0.1±1.0 4.0±0.1±0.5 0.80±0.02±0.30
Total background 308±1±40 500±1±60 203±1±25 19.5±0.2±8.0
Observed 357 545 256 31

Fig. 4.

Fig. 4

Distribution of the four-lepton invariant mass m4 in the +-+- search for a the ggF-enriched category and b the VBF-enriched category. The backgrounds are determined following the description in Sect. 5.2 and the last bin includes the overflow. The simulated mH=600 GeV signal is normalized to a cross section corresponding to five times the observed limit given in Sect. 8.3.1. The error bars on the data points indicate the statistical uncertainty, while the systematic uncertainty in the prediction is shown by the hatched band. The lower panels show the ratio of data to prediction

Table 5 contains the number of observed candidate events along with the background yields for the +-νν¯ analysis, while Fig. 5 shows the mT distribution for the electron and muon channels with the ggF-enriched and VBF-enriched categories combined.

Table 5.

+-νν¯ search: expected and observed number of events together with their statistical and systematic uncertainties, for the ggF- and VBF-enriched categories

Process ggF-enriched categories VBF-enriched category
e+e- channel μ+μ- channel
ZZ 177±3±21 180±3±21 2.1±0.2±0.7
WZ 93±2±4 99.5±2.3±3.2 1.29±0.04±0.27
WW/tt¯/Wt/Zττ 9.2±2.2±1.4 10.7±2.5±0.9 0.39±0.24±0.26
Z + jets 17±1±11 19±1±17 0.8±0.1±0.5
Other backgrounds 1.12±0.04±0.08 1.03±0.04±0.08 0.03±0.01±0.01
Total background 297±4±24 311±5±27 4.6±0.4±0.9
Observed 320 352 9

Fig. 5.

Fig. 5

Transverse mass mT distribution in the +-νν¯ search for a the electron channel and b the muon channel, including events from both the ggF-enriched and the VBF-enriched categories. The backgrounds are determined following the description in Sect. 6.2 and the last bin includes the overflow. The simulated mH=600 GeV signal is normalized to a cross section corresponding to five times the observed limit given in Sect. 8.3.1. The error bars on the data points indicate the statistical uncertainty and markers are drawn at the bin centre. The systematic uncertainty in the prediction is shown by the hatched band. The lower panels show the ratio of data to prediction

In the +-+- search, two excesses are observed in the data for m4 around 240 and 700 GeV, each with a local significance of 3.6σ estimated in the asymptotic approximation, assuming the signal comes only from ggF production. The global significance is 2.2σ and is calculated, for each excess individually, using the NWA, in the range of 200 GeV< mH < 1200 GeV using pseudo-experiments.

The excess at 240 GeV is observed mostly in the 4e channel, while the one at 700 GeV is observed in all channels and categories. No significant deviation from the expected background is observed in the +-νν¯ final state. The excess observed in the +-+- search at a mass around 700 GeV is excluded at 95% confidence level (CL) by the +-νν¯ search, which is more sensitive in this mass range. The excess at 240 GeV is not covered by the +-νν¯ search, the sensitivity of which starts from 300 GeV. When combining the results from the two final states, the largest deviation with respect to the background expectation is observed around 700 GeV with a global significance of less than 1σ and a local significance of about 2σ. The combined yield of the two final states is 1870 events observed in data compared to 1643±164 (combined statistical and systematic uncertainty) for the expected background. This corresponds to a 1.3σ global excess in data. Since no significant excess is found, the results are interpreted as upper limits on the production cross section of a spin-0 or spin-2 resonance.

Spin-0 resonance interpretation

Limits from the combination of the two searches in the context of a spin-0 resonance are described below.

NWA interpretation

Upper limits on the cross section times branching ratio (σ×B(HZZ)) for a heavy resonance are obtained as a function of mH with the CLs procedure [87] in the asymptotic approximation from the combination of the two final states. It is assumed that an additional heavy scalar would be produced predominantly via the ggF and VBF processes but that the ratio of the two production mechanisms is unknown in the absence of a specific model. For this reason, fits for the ggF and VBF production processes are done separately, and in each case the other process is allowed to float in the fit as an additional nuisance parameter. Figure 6 presents the observed and expected limits at 95% CL on σ×B(HZZ) of a narrow scalar resonance for the ggF (left) and VBF (right) production modes, as well as the expected limits from the +-+- and +-νν¯ searches. This result is valid for models in which the width is less than 0.5% of mH. When combining the two final states, the 95% CL upper limits range from 0.68 pb at mH=242 GeV to 11 fb at mH=1200 GeV for the ggF production mode and from 0.41 pb at mH=236 GeV to 13 fb at mH=1200 GeV for the vector-boson fusion production mode. Compared with the results from Run 1 [21], where all four final states of ZZ decays were combined, the exclusion region presented here is significantly extended considering that the ratios of parton luminosities [88] increase by factors of about two to seven for heavy scalar masses from 200 GeV to 1200 GeV.

LWA interpretation

In the case of the LWA, limits on the cross section for the ggF production mode times branching ratio (σggF×B(HZZ)) are set for different widths of the heavy scalar. The interference between the heavy scalar and the SM Higgs boson, Hh, as well as the heavy scalar and the ggZZ continuum, HB, are modelled by either analytical functions or reweighting the signal-only events as explained in Sects. 5.3 and 6.3. Figure 7a–c show the limits for a width of 1, 5 and 10% of mH respectively. The limits are set for masses of mH higher than 400 GeV.

Fig. 7.

Fig. 7

The upper limits at 95% CL on the cross section for the ggF production mode times branching ratio (σggF×B(HZZ)) as function of mH for an additional heavy scalar assuming a width of a 1%, b 5%, and c 10% of mH. The green and yellow bands represent the ± 1σ and ± 2σ uncertainties in the expected limits. The dashed coloured lines indicate the expected limits obtained from the individual searches

2HDM interpretation

A search in the context of a CP-conserving 2HDM is also presented. This model has five physical Higgs bosons after electroweak symmetry breaking: two CP-even, one CP-odd, and two charged. The model considered here has seven free parameters: the Higgs boson masses, the ratio of the vacuum expectation values of the two doublets (tanβ), the mixing angle between the CP-even Higgs bosons (α), and the potential parameter m122 that mixes the two Higgs doublets. The two Higgs doublets Φ1 and Φ2 can couple to leptons and up- and down-type quarks in several ways. In the Type-I model, Φ2 couples to all quarks and leptons, whereas for Type-II, Φ1 couples to down-type quarks and leptons and Φ2 couples to up-type quarks. The “lepton-specific” model is similar to Type-I except for the fact that the leptons couple to Φ1, instead of Φ2; the “flipped” model is similar to Type-II except that the leptons couple to Φ2, instead of Φ1. In all these models, the coupling of the heaviest CP-even Higgs boson to vector bosons is proportional to cos(β-α). In the limit cos(β-α)0, the light CP-even Higgs boson is indistinguishable from a SM Higgs boson with the same mass. In the context of HZZ decays there is no direct coupling of the Higgs boson to leptons, and so only the Type-I and -II interpretations are presented.

Figure 8 shows exclusion limits in the tanβ versus cos(β-α) plane for Type-I and Type-II 2HDMs, for a heavy Higgs boson with mass mH = 200 GeV. This mH value is chosen so that the assumption of a narrow Higgs boson is valid over most of the parameter space, and the experimental sensitivity is maximal. At this low mass, only the +-+- final state contributes to this result. The range of cos(β-α) and tanβ explored is limited to the region where the assumption of a heavy narrow Higgs boson with negligible interference is valid. When calculating the limits at a given choice of cos(β-α) and tanβ, the relative rates of ggF and VBF production in the fit are set to the prediction of the 2HDM for that parameter choice. Figure 9 shows exclusion limits as a function of the heavy Higgs boson mass mH and the parameter tanβ for cos(β-α)=-0.1. The white regions in the exclusion plots indicate regions of parameter space which are not excluded by the present analysis. In these regions the cross section predicted by the 2HDM is below the observed cross section limit. Compared with the results from Run 1 [21], the exclusion presented here is almost twice as stringent.

Fig. 8.

Fig. 8

The exclusion contour in the 2HDM a Type-I and b Type-II models for mH=200 GeV shown as a function of the parameters cos(β-α) and tanβ. The green and yellow bands represent the ±1σ and ±2σ uncertainties in the expected limits. The hatched area shows the observed exclusion

Fig. 9.

Fig. 9

The exclusion contour in the 2HDM a Type-I and b Type-II models for cos(β-α)=-0.1, shown as a function of the heavy scalar mass mH and the parameter tanβ. The green and yellow bands represent the ±1σ and ±2σ uncertainties in the expected limits. The hatched area shows the observed exclusion

Spin-2 resonance interpretation

The results are also interpreted as a search for a Kaluza–Klein graviton excitation, GKK, in the context of the bulk RS model using the +-νν¯ final state because the +-+- final state was found to have negligible sensitivity for this type of model. The limits on σ×B(GKKZZ) at 95% CL as a function of the KK graviton mass, m(GKK), are shown in Fig. 10 together with the predicted GKK cross section. A spin-2 graviton is excluded up to a mass of 1300 GeV. These limits have been extracted using the asymptotic approximation, and they were verified to be correct within about 4% using pseudo-experiments.

Fig. 10.

Fig. 10

The upper limits at 95% CL on cross section times branching ratio σ×B(GKKZZ) for a KK graviton produced with k/M¯Pl=1. The green and yellow bands give the ± 1σ and ± 2σ uncertainties in the expected limits. The predicted production cross section times branching ratio as a function of the GKK mass m(GKK) is shown by the red solid line

Summary

A search is conducted for heavy resonances decaying into a pair of Z bosons which subsequently decay into +-+- or +-νν¯ final states. The search uses proton–proton collision data collected with the ATLAS detector during 2015 and 2016 at the Large Hadron Collider at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 36.1 fb-1. The results of the search are interpreted as upper limits on the production cross section of a spin-0 or spin-2 resonance. The mass range of the hypothetical resonances considered is between 200 and 2000 GeV depending on the final state and the model considered. The spin-0 resonance is assumed to be a heavy scalar, whose dominant production modes are gluon–gluon fusion and vector-boson fusion and it is studied in the narrow-width approximation and with the large-width assumption. In the case of the narrow-width approximation, limits on the production rate of a heavy scalar decaying into two Z bosons are set separately for ggF and VBF production modes. Combining the two final states, 95% CL upper limits range from 0.68 pb at mH=242 GeV to 11 fb at mH=1200 GeV for the gluon–gluon fusion production mode and from 0.41 pb at mH=236 GeV to 13 fb at mH=1200 GeV for the vector-boson fusion production mode. The results are also interpreted in the context of Type-I and Type-II two-Higgs-doublet models, with exclusion contours given in the tanβ versus cos(β-α) (for mH=200 GeV) and tanβ versus mH planes. This mH value is chosen so that the assumption of a narrow Higgs boson is valid over most of the parameter space and the experimental sensitivity is maximal. The limits on the production rate of a large-width scalar are obtained for widths of 1, 5 and 10% of the mass of the resonance, with the interference between the heavy scalar and the SM Higgs boson as well as the heavy scalar and the ggZZ continuum taken into account. In the framework of the Randall–Sundrum model with one warped extra dimension a graviton excitation spin-2 resonance with m(GKK)<1300GeV is excluded at 95% CL.

Acknowledgements

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-DRF/IRFU, France; SRNSFG, 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; NWO, 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, ERDF, 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; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. 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. [89].

Footnotes

1

The ATLAS experiment uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r,ϕ) are used in the transverse plane, ϕ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θ as η=-lntan(θ/2).

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