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. 2016 Jan 25;76(1):45. doi: 10.1140/epjc/s10052-015-3820-z

Search for an additional, heavy Higgs boson in the HZZ decay channel at s=8TeV in pp collision data with the ATLAS detector

Atlas Collaboration229, G Aad 85, B Abbott 113, J Abdallah 151, O Abdinov 11, R Aben 107, M Abolins 90, O S AbouZeid 158, H Abramowicz 153, H Abreu 152, R Abreu 116, Y Abulaiti 146, B S Acharya 164, L Adamczyk 38, D L Adams 25, J Adelman 108, S Adomeit 100, T Adye 131, A A Affolder 74, T Agatonovic-Jovin 13, J Agricola 54, J A Aguilar-Saavedra 126, S P Ahlen 22, F Ahmadov 65, G Aielli 133, H Akerstedt 146, T P A Åkesson 81, A V Akimov 96, G L Alberghi 20, J Albert 169, S Albrand 55, M J Alconada Verzini 71, M Aleksa 30, I N Aleksandrov 65, C Alexa 26, G Alexander 153, T Alexopoulos 10, M Alhroob 113, G Alimonti 91, L Alio 85, J Alison 31, S P Alkire 35, B M M Allbrooke 149, P P Allport 74, A Aloisio 104, A Alonso 36, F Alonso 71, C Alpigiani 76, A Altheimer 35, B Alvarez Gonzalez 30, D Álvarez Piqueras 167, M G Alviggi 104, B T Amadio 15, K Amako 66, Y Amaral Coutinho 24, C Amelung 23, D Amidei 89, S P Amor Dos Santos 126, A Amorim 126, S Amoroso 48, N Amram 153, G Amundsen 23, C Anastopoulos 139, L S Ancu 49, N Andari 108, T Andeen 35, C F Anders 58, G Anders 30, J K Anders 74, K J Anderson 31, A Andreazza 91, V Andrei 58, S Angelidakis 9, I Angelozzi 107, P Anger 44, A Angerami 35, F Anghinolfi 30, A V Anisenkov 109, N Anjos 12, A Annovi 124, M Antonelli 47, A Antonov 98, J Antos 144, F Anulli 132, M Aoki 66, L Aperio Bella 18, G Arabidze 90, Y Arai 66, J P Araque 126, A T H Arce 45, F A Arduh 71, J-F Arguin 95, S Argyropoulos 42, M Arik 19, A J Armbruster 30, O Arnaez 30, V Arnal 82, H Arnold 48, M Arratia 28, O Arslan 21, A Artamonov 97, G Artoni 23, S Asai 155, N Asbah 42, A Ashkenazi 153, B Åsman 146, L Asquith 149, K Assamagan 25, R Astalos 144, M Atkinson 165, N B Atlay 141, K Augsten 128, M Aurousseau 145, G Avolio 30, B Axen 15, M K Ayoub 117, G Azuelos 95, M A Baak 30, A E Baas 58, M J Baca 18, C Bacci 134, H Bachacou 136, K Bachas 154, M Backes 30, M Backhaus 30, P Bagiacchi 132, P Bagnaia 132, Y Bai 33, T Bain 35, J T Baines 131, O K Baker 176, E M Baldin 109, P Balek 129, T Balestri 148, F Balli 84, E Banas 39, Sw Banerjee 173, A A E Bannoura 175, H S Bansil 18, L Barak 30, E L Barberio 88, D Barberis 50, M Barbero 85, T Barillari 101, M Barisonzi 164, T Barklow 143, N Barlow 28, S L Barnes 84, B M Barnett 131, R M Barnett 15, Z Barnovska 5, A Baroncelli 134, G Barone 23, A J Barr 120, F Barreiro 82, J Barreiro Guimarães da Costa 57, R Bartoldus 143, A E Barton 72, P Bartos 144, A Basalaev 123, A Bassalat 117, A Basye 165, R L Bates 53, S J Batista 158, J R Batley 28, M Battaglia 137, M Bauce 132, F Bauer 136, H S Bawa 143, J B Beacham 111, M D Beattie 72, T Beau 80, P H Beauchemin 161, R Beccherle 124, P Bechtle 21, H P Beck 17, K Becker 120, M Becker 83, S Becker 100, M Beckingham 170, C Becot 117, A J Beddall 19, A Beddall 19, V A Bednyakov 65, C P Bee 148, L J Beemster 107, T A Beermann 175, M Begel 25, J K Behr 120, C Belanger-Champagne 87, W H Bell 49, G Bella 153, L Bellagamba 20, A Bellerive 29, M Bellomo 86, K Belotskiy 98, O Beltramello 30, O Benary 153, D Benchekroun 135, M Bender 100, K Bendtz 146, N Benekos 10, Y Benhammou 153, E Benhar Noccioli 49, J A Benitez Garcia 159, D P Benjamin 45, J R Bensinger 23, S Bentvelsen 107, L Beresford 120, M Beretta 47, D Berge 107, E Bergeaas Kuutmann 166, N Berger 5, F Berghaus 169, J Beringer 15, C Bernard 22, N R Bernard 86, C Bernius 110, F U Bernlochner 21, T Berry 77, P Berta 129, C Bertella 83, G Bertoli 146, F Bertolucci 124, C Bertsche 113, D Bertsche 113, M I Besana 91, G J Besjes 36, O Bessidskaia Bylund 146, M Bessner 42, N Besson 136, C Betancourt 48, S Bethke 101, A J Bevan 76, W Bhimji 15, R M Bianchi 125, L Bianchini 23, M Bianco 30, O Biebel 100, D Biedermann 16, S P Bieniek 78, M Biglietti 134, J Bilbao De Mendizabal 49, H Bilokon 47, M Bindi 54, S Binet 117, A Bingul 19, C Bini 132, S Biondi 20, C W Black 150, J E Black 143, K M Black 22, D Blackburn 138, R E Blair 6, J-B Blanchard 136, J E Blanco 77, T Blazek 144, I Bloch 42, C Blocker 23, W Blum 83, U Blumenschein 54, G J Bobbink 107, V S Bobrovnikov 109, S S Bocchetta 81, A Bocci 45, C Bock 100, M Boehler 48, J A Bogaerts 30, D Bogavac 13, A G Bogdanchikov 109, C Bohm 146, V Boisvert 77, T Bold 38, V Boldea 26, A S Boldyrev 99, M Bomben 80, M Bona 76, M Boonekamp 136, A Borisov 130, G Borissov 72, S Borroni 42, J Bortfeldt 100, V Bortolotto 60, K Bos 107, D Boscherini 20, M Bosman 12, J Boudreau 125, J Bouffard 2, E V Bouhova-Thacker 72, D Boumediene 34, C Bourdarios 117, N Bousson 114, A Boveia 30, J Boyd 30, I R Boyko 65, I Bozic 13, J Bracinik 18, A Brandt 8, G Brandt 54, O Brandt 58, U Bratzler 156, B Brau 86, J E Brau 116, H M Braun 175, S F Brazzale 164, W D Breaden Madden 53, K Brendlinger 122, A J Brennan 88, L Brenner 107, R Brenner 166, S Bressler 172, K Bristow 145, T M Bristow 46, D Britton 53, D Britzger 42, F M Brochu 28, I Brock 21, R Brock 90, J Bronner 101, G Brooijmans 35, T Brooks 77, W K Brooks 32, J Brosamer 15, E Brost 116, J Brown 55, P A Bruckman de Renstrom 39, D Bruncko 144, R Bruneliere 48, A Bruni 20, G Bruni 20, M Bruschi 20, N Bruscino 21, L Bryngemark 81, T Buanes 14, Q Buat 142, P Buchholz 141, A G Buckley 53, S I Buda 26, I A Budagov 65, F Buehrer 48, L Bugge 119, M K Bugge 119, O Bulekov 98, D Bullock 8, H Burckhart 30, S Burdin 74, C D Burgard 48, B Burghgrave 108, S Burke 131, I Burmeister 43, E Busato 34, D Büscher 48, V Büscher 83, P Bussey 53, J M Butler 22, A I Butt 3, C M Buttar 53, J M Butterworth 78, P Butti 107, W Buttinger 25, A Buzatu 53, A R Buzykaev 109, S Cabrera Urbán 167, D Caforio 128, V M Cairo 37, O Cakir 4, N Calace 49, P Calafiura 15, A Calandri 136, G Calderini 80, P Calfayan 100, L P Caloba 24, D Calvet 34, S Calvet 34, R Camacho Toro 31, S Camarda 42, P Camarri 133, D Cameron 119, R Caminal Armadans 165, S Campana 30, M Campanelli 78, A Campoverde 148, V Canale 104, A Canepa 159, M Cano Bret 33, J Cantero 82, R Cantrill 126, T Cao 40, M D M Capeans Garrido 30, I Caprini 26, M Caprini 26, M Capua 37, R Caputo 83, R Cardarelli 133, F Cardillo 48, T Carli 30, G Carlino 104, L Carminati 91, S Caron 106, E Carquin 32, G D Carrillo-Montoya 30, J R Carter 28, J Carvalho 126, D Casadei 78, M P Casado 12, M Casolino 12, E Castaneda-Miranda 145, A Castelli 107, V Castillo Gimenez 167, N F Castro 126, P Catastini 57, A Catinaccio 30, J R Catmore 119, A Cattai 30, J Caudron 83, V Cavaliere 165, D Cavalli 91, M Cavalli-Sforza 12, V Cavasinni 124, F Ceradini 134, B C Cerio 45, K Cerny 129, A S Cerqueira 24, A Cerri 149, L Cerrito 76, F Cerutti 15, M Cerv 30, A Cervelli 17, S A Cetin 19, A Chafaq 135, D Chakraborty 108, I Chalupkova 129, P Chang 165, J D Chapman 28, D G Charlton 18, C C Chau 158, C A Chavez Barajas 149, S Cheatham 152, A Chegwidden 90, S Chekanov 6, S V Chekulaev 159, G A Chelkov 65, M A Chelstowska 89, C Chen 64, H Chen 25, K Chen 148, L Chen 33, S Chen 33, X Chen 33, Y Chen 67, H C Cheng 89, Y Cheng 31, A Cheplakov 65, E Cheremushkina 130, R Cherkaoui El Moursli 135, V Chernyatin 25, E Cheu 7, L Chevalier 136, V Chiarella 47, G Chiarelli 124, G Chiodini 73, A S Chisholm 18, R T Chislett 78, A Chitan 26, M V Chizhov 65, K Choi 61, S Chouridou 9, B K B Chow 100, V Christodoulou 78, D Chromek-Burckhart 30, J Chudoba 127, A J Chuinard 87, J J Chwastowski 39, L Chytka 115, G Ciapetti 132, A K Ciftci 4, D Cinca 53, V Cindro 75, I A Cioara 21, A Ciocio 15, F Cirotto 104, Z H Citron 172, M Ciubancan 26, A Clark 49, B L Clark 57, P J Clark 46, R N Clarke 15, W Cleland 125, C Clement 146, Y Coadou 85, M Cobal 164, A Coccaro 138, J Cochran 64, L Coffey 23, J G Cogan 143, L Colasurdo 106, B Cole 35, S Cole 108, A P Colijn 107, J Collot 55, T Colombo 58, G Compostella 101, P Conde Muiño 126, E Coniavitis 48, S H Connell 145, I A Connelly 77, V Consorti 48, S Constantinescu 26, C Conta 121, G Conti 30, F Conventi 104, M Cooke 15, B D Cooper 78, A M Cooper-Sarkar 120, T Cornelissen 175, M Corradi 20, F Corriveau 87, A Corso-Radu 163, A Cortes-Gonzalez 12, G Cortiana 101, G Costa 91, M J Costa 167, D Costanzo 139, D Côté 8, G Cottin 28, G Cowan 77, B E Cox 84, K Cranmer 110, G Cree 29, S Crépé-Renaudin 55, F Crescioli 80, W A Cribbs 146, M Crispin Ortuzar 120, M Cristinziani 21, V Croft 106, G Crosetti 37, T Cuhadar Donszelmann 139, J Cummings 176, M Curatolo 47, C Cuthbert 150, H Czirr 141, P Czodrowski 3, S D’Auria 53, M D’Onofrio 74, M J Da Cunha Sargedas De Sousa 126, C Da Via 84, W Dabrowski 38, A Dafinca 120, T Dai 89, O Dale 14, F Dallaire 95, C Dallapiccola 86, M Dam 36, J R Dandoy 31, N P Dang 48, A C Daniells 18, M Danninger 168, M Dano Hoffmann 136, V Dao 48, G Darbo 50, S Darmora 8, J Dassoulas 3, A Dattagupta 61, W Davey 21, C David 169, T Davidek 129, E Davies 120, M Davies 153, P Davison 78, Y Davygora 58, E Dawe 88, I Dawson 139, R K Daya-Ishmukhametova 86, K De 8, R de Asmundis 104, A De Benedetti 113, S De Castro 20, S De Cecco 80, N De Groot 106, P de Jong 107, H De la Torre 82, F De Lorenzi 64, D De Pedis 132, A De Salvo 132, U De Sanctis 149, A De Santo 149, J B De Vivie De Regie 117, W J Dearnaley 72, R Debbe 25, C Debenedetti 137, D V Dedovich 65, I Deigaard 107, J Del Peso 82, T Del Prete 124, D Delgove 117, F Deliot 136, C M Delitzsch 49, M Deliyergiyev 75, A Dell’Acqua 30, L Dell’Asta 22, M Dell’Orso 124, M Della Pietra 104, D della Volpe 49, M Delmastro 5, P A Delsart 55, C Deluca 107, D A DeMarco 158, S Demers 176, M Demichev 65, A Demilly 80, S P Denisov 130, D Derendarz 39, J E Derkaoui 135, F Derue 80, P Dervan 74, K Desch 21, C Deterre 42, P O Deviveiros 30, A Dewhurst 131, S Dhaliwal 23, A Di Ciaccio 133, L Di Ciaccio 5, A Di Domenico 132, C Di Donato 104, A Di Girolamo 30, B Di Girolamo 30, A Di Mattia 152, B Di Micco 134, R Di Nardo 47, A Di Simone 48, R Di Sipio 158, D Di Valentino 29, C Diaconu 85, M Diamond 158, F A Dias 46, M A Diaz 32, E B Diehl 89, J Dietrich 16, S Diglio 85, A Dimitrievska 13, J Dingfelder 21, P Dita 26, S Dita 26, F Dittus 30, F Djama 85, T Djobava 51, J I Djuvsland 58, M A B do Vale 24, D Dobos 30, M Dobre 26, C Doglioni 81, T Dohmae 155, J Dolejsi 129, Z Dolezal 129, B A Dolgoshein 98, M Donadelli 24, S Donati 124, P Dondero 121, J Donini 34, J Dopke 131, A Doria 104, M T Dova 71, A T Doyle 53, E Drechsler 54, M Dris 10, E Dubreuil 34, E Duchovni 172, G Duckeck 100, O A Ducu 26,85, D Duda 107, A Dudarev 30, L Duflot 117, L Duguid 77, M Dührssen 30, M Dunford 58, H Duran Yildiz 4, M Düren 52, A Durglishvili 51, D Duschinger 44, M Dyndal 38, C Eckardt 42, K M Ecker 101, R C Edgar 89, W Edson 2, N C Edwards 46, W Ehrenfeld 21, T Eifert 30, G Eigen 14, K Einsweiler 15, T Ekelof 166, M El Kacimi 135, M Ellert 166, S Elles 5, F Ellinghaus 175, A A Elliot 169, N Ellis 30, J Elmsheuser 100, M Elsing 30, D Emeliyanov 131, Y Enari 155, O C Endner 83, M Endo 118, J Erdmann 43, A Ereditato 17, G Ernis 175, J Ernst 2, M Ernst 25, S Errede 165, E Ertel 83, M Escalier 117, H Esch 43, C Escobar 125, B Esposito 47, A I Etienvre 136, E Etzion 153, H Evans 61, A Ezhilov 123, L Fabbri 20, G Facini 31, R M Fakhrutdinov 130, S Falciano 132, R J Falla 78, J Faltova 129, Y Fang 33, M Fanti 91, A Farbin 8, A Farilla 134, T Farooque 12, S Farrell 15, S M Farrington 170, P Farthouat 30, F Fassi 135, P Fassnacht 30, D Fassouliotis 9, M Faucci Giannelli 77, A Favareto 50, L Fayard 117, P Federic 144, O L Fedin 123, W Fedorko 168, S Feigl 30, L Feligioni 85, C Feng 33, E J Feng 6, H Feng 89, A B Fenyuk 130, L Feremenga 8, P Fernandez Martinez 167, S Fernandez Perez 30, J Ferrando 53, A Ferrari 166, P Ferrari 107, R Ferrari 121, D E Ferreira de Lima 53, A Ferrer 167, D Ferrere 49, C Ferretti 89, A Ferretto Parodi 50, M Fiascaris 31, F Fiedler 83, A Filipčič 75, M Filipuzzi 42, F Filthaut 106, M Fincke-Keeler 169, K D Finelli 150, M C N Fiolhais 126, L Fiorini 167, A Firan 40, A Fischer 2, C Fischer 12, J Fischer 175, W C Fisher 90, E A Fitzgerald 23, N Flaschel 42, I Fleck 141, P Fleischmann 89, S Fleischmann 175, G T Fletcher 139, G Fletcher 76, R R M Fletcher 122, T Flick 175, A Floderus 81, L R Flores Castillo 60, M J Flowerdew 101, A Formica 136, A Forti 84, D Fournier 117, H Fox 72, S Fracchia 12, P Francavilla 80, M Franchini 20, D Francis 30, L Franconi 119, M Franklin 57, M Frate 163, M Fraternali 121, D Freeborn 78, S T French 28, F Friedrich 44, D Froidevaux 30, J A Frost 120, C Fukunaga 156, E Fullana Torregrosa 83, B G Fulsom 143, T Fusayasu 102, J Fuster 167, C Gabaldon 55, O Gabizon 175, A Gabrielli 20, A Gabrielli 132, G P Gach 38, S Gadatsch 30, S Gadomski 49, G Gagliardi 50, P Gagnon 61, C Galea 106, B Galhardo 126, E J Gallas 120, B J Gallop 131, P Gallus 128, G Galster 36, K K Gan 111, J Gao 33,85, Y Gao 46, Y S Gao 143, F M Garay Walls 46, F Garberson 176, C García 167, J E García Navarro 167, M Garcia-Sciveres 15, R W Gardner 31, N Garelli 143, V Garonne 119, C Gatti 47, A Gaudiello 50, G Gaudio 121, B Gaur 141, L Gauthier 95, P Gauzzi 132, I L Gavrilenko 96, C Gay 168, G Gaycken 21, E N Gazis 10, P Ge 33, Z Gecse 168, C N P Gee 131, Ch Geich-Gimbel 21, M P Geisler 58, C Gemme 50, M H Genest 55, S Gentile 132, M George 54, S George 77, D Gerbaudo 163, A Gershon 153, S Ghasemi 141, H Ghazlane 135, B Giacobbe 20, S Giagu 132, V Giangiobbe 12, P Giannetti 124, B Gibbard 25, S M Gibson 77, M Gilchriese 15, T P S Gillam 28, D Gillberg 30, G Gilles 34, D M Gingrich 3, N Giokaris 9, M P Giordani 164, F M Giorgi 20, F M Giorgi 16, P F Giraud 136, P Giromini 47, D Giugni 91, C Giuliani 48, M Giulini 58, B K Gjelsten 119, S Gkaitatzis 154, I Gkialas 154, E L Gkougkousis 117, L K Gladilin 99, C Glasman 82, J Glatzer 30, P C F Glaysher 46, A Glazov 42, M Goblirsch-Kolb 101, J R Goddard 76, J Godlewski 39, S Goldfarb 89, T Golling 49, D Golubkov 130, A Gomes 126, R Gonçalo 126, J Goncalves Pinto Firmino Da Costa 136, L Gonella 21, S González de la Hoz 167, G Gonzalez Parra 12, S Gonzalez-Sevilla 49, L Goossens 30, P A Gorbounov 97, H A Gordon 25, I Gorelov 105, B Gorini 30, E Gorini 73, A Gorišek 75, E Gornicki 39, A T Goshaw 45, C Gössling 43, M I Gostkin 65, D Goujdami 135, A G Goussiou 138, N Govender 145, E Gozani 152, H M X Grabas 137, L Graber 54, I Grabowska-Bold 38, P O J Gradin 166, P Grafström 20, K-J Grahn 42, J Gramling 49, E Gramstad 119, S Grancagnolo 16, V Gratchev 123, H M Gray 30, E Graziani 134, Z D Greenwood 79, K Gregersen 78, I M Gregor 42, P Grenier 143, J Griffiths 8, A A Grillo 137, K Grimm 72, S Grinstein 12, Ph Gris 34, J-F Grivaz 117, J P Grohs 44, A Grohsjean 42, E Gross 172, J Grosse-Knetter 54, G C Grossi 79, Z J Grout 149, L Guan 89, J Guenther 128, F Guescini 49, D Guest 176, O Gueta 153, E Guido 50, T Guillemin 117, S Guindon 2, U Gul 53, C Gumpert 44, J Guo 33, Y Guo 33, S Gupta 120, G Gustavino 132, P Gutierrez 113, N G Gutierrez Ortiz 78, C Gutschow 44, C Guyot 136, C Gwenlan 120, C B Gwilliam 74, A Haas 110, C Haber 15, H K Hadavand 8, N Haddad 135, P Haefner 21, S Hageböck 21, Z Hajduk 39, H Hakobyan 177, M Haleem 42, J Haley 114, D Hall 120, G Halladjian 90, G D Hallewell 85, K Hamacher 175, P Hamal 115, K Hamano 169, A Hamilton 145, G N Hamity 139, P G Hamnett 42, L Han 33, K Hanagaki 66, K Hanawa 155, M Hance 15, P Hanke 58, R Hanna 136, J B Hansen 36, J D Hansen 36, M C Hansen 21, P H Hansen 36, K Hara 160, A S Hard 173, T Harenberg 175, F Hariri 117, S Harkusha 92, R D Harrington 46, P F Harrison 170, F Hartjes 107, M Hasegawa 67, Y Hasegawa 140, A Hasib 113, S Hassani 136, S Haug 17, R Hauser 90, L Hauswald 44, M Havranek 127, C M Hawkes 18, R J Hawkings 30, A D Hawkins 81, T Hayashi 160, D Hayden 90, C P Hays 120, J M Hays 76, H S Hayward 74, S J Haywood 131, S J Head 18, T Heck 83, V Hedberg 81, L Heelan 8, S Heim 122, T Heim 175, B Heinemann 15, L Heinrich 110, J Hejbal 127, L Helary 22, S Hellman 146, D Hellmich 21, C Helsens 12, J Henderson 120, R C W Henderson 72, Y Heng 173, C Hengler 42, A Henrichs 176, A M Henriques Correia 30, S Henrot-Versille 117, G H Herbert 16, Y Hernández Jiménez 167, R Herrberg-Schubert 16, G Herten 48, R Hertenberger 100, L Hervas 30, G G Hesketh 78, N P Hessey 107, J W Hetherly 40, R Hickling 76, E Higón-Rodriguez 167, E Hill 169, J C Hill 28, K H Hiller 42, S J Hillier 18, I Hinchliffe 15, E Hines 122, R R Hinman 15, M Hirose 157, D Hirschbuehl 175, J Hobbs 148, N Hod 107, M C Hodgkinson 139, P Hodgson 139, A Hoecker 30, M R Hoeferkamp 105, F Hoenig 100, M Hohlfeld 83, D Hohn 21, T R Holmes 15, M Homann 43, T M Hong 125, L Hooft van Huysduynen 110, W H Hopkins 116, Y Horii 103, A J Horton 142, J-Y Hostachy 55, S Hou 151, A Hoummada 135, J Howard 120, J Howarth 42, M Hrabovsky 115, I Hristova 16, J Hrivnac 117, T Hryn’ova 5, A Hrynevich 93, C Hsu 145, P J Hsu 151, S-C Hsu 138, D Hu 35, Q Hu 33, X Hu 89, Y Huang 42, Z Hubacek 128, F Hubaut 85, F Huegging 21, T B Huffman 120, E W Hughes 35, G Hughes 72, M Huhtinen 30, T A Hülsing 83, N Huseynov 65, J Huston 90, J Huth 57, G Iacobucci 49, G Iakovidis 25, I Ibragimov 141, L Iconomidou-Fayard 117, E Ideal 176, Z Idrissi 135, P Iengo 30, O Igonkina 107, T Iizawa 171, Y Ikegami 66, K Ikematsu 141, M Ikeno 66, Y Ilchenko 31, D Iliadis 154, N Ilic 143, T Ince 101, G Introzzi 121, P Ioannou 9, M Iodice 134, K Iordanidou 35, V Ippolito 57, A Irles Quiles 167, C Isaksson 166, M Ishino 68, M Ishitsuka 157, R Ishmukhametov 111, C Issever 120, S Istin 19, J M Iturbe Ponce 84, R Iuppa 133, J Ivarsson 81, W Iwanski 39, H Iwasaki 66, J M Izen 41, V Izzo 104, S Jabbar 3, B Jackson 122, M Jackson 74, P Jackson 1, M R Jaekel 30, V Jain 2, K Jakobs 48, S Jakobsen 30, T Jakoubek 127, J Jakubek 128, D O Jamin 114, D K Jana 79, E Jansen 78, R Jansky 62, J Janssen 21, M Janus 54, G Jarlskog 81, N Javadov 65, T Javůrek 48, L Jeanty 15, J Jejelava 51, G-Y Jeng 150, D Jennens 88, P Jenni 48, J Jentzsch 43, C Jeske 170, S Jézéquel 5, H Ji 173, J Jia 148, Y Jiang 33, S Jiggins 78, J Jimenez Pena 167, S Jin 33, A Jinaru 26, O Jinnouchi 157, M D Joergensen 36, P Johansson 139, K A Johns 7, K Jon-And 146, G 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Thompson 53, L A Thomsen 176, E Thomson 122, M Thomson 28, R P Thun 89, M J Tibbetts 15, R E Ticse Torres 85, V O Tikhomirov 96, Yu A Tikhonov 109, S Timoshenko 98, E Tiouchichine 85, P Tipton 176, S Tisserant 85, K Todome 157, T Todorov 5, S Todorova-Nova 129, J Tojo 70, S Tokár 144, K Tokushuku 66, K Tollefson 90, E Tolley 57, L Tomlinson 84, M Tomoto 103, L Tompkins 143, K Toms 105, E Torrence 116, H Torres 142, E Torró Pastor 138, J Toth 85, F Touchard 85, D R Tovey 139, T Trefzger 174, L Tremblet 30, A Tricoli 30, I M Trigger 159, S Trincaz-Duvoid 80, M F Tripiana 12, W Trischuk 158, B Trocmé 55, C Troncon 91, M Trottier-McDonald 15, M Trovatelli 169, P True 90, L Truong 164, M Trzebinski 39, A Trzupek 39, C Tsarouchas 30, J C-L Tseng 120, P V Tsiareshka 92, D Tsionou 154, G Tsipolitis 10, N Tsirintanis 9, S Tsiskaridze 12, V Tsiskaridze 48, E G Tskhadadze 51, I I Tsukerman 97, V Tsulaia 15, S Tsuno 66, D Tsybychev 148, A Tudorache 26, V Tudorache 26, A N Tuna 122, S A Tupputi 20, S Turchikhin 99, D Turecek 128, R Turra 91, A J Turvey 40, P M Tuts 35, A Tykhonov 49, M Tylmad 146, M Tyndel 131, I Ueda 155, R Ueno 29, M Ughetto 146, M Ugland 14, F Ukegawa 160, G Unal 30, A Undrus 25, G Unel 163, F C Ungaro 48, Y Unno 66, C Unverdorben 100, J Urban 144, P Urquijo 88, P Urrejola 83, G Usai 8, A Usanova 62, L Vacavant 85, V Vacek 128, B Vachon 87, C Valderanis 83, N Valencic 107, S Valentinetti 20, A Valero 167, L Valery 12, S Valkar 129, E Valladolid Gallego 167, S Vallecorsa 49, J A Valls Ferrer 167, W Van Den Wollenberg 107, P C Van Der Deijl 107, R van der Geer 107, H van der Graaf 107, N van Eldik 152, P van Gemmeren 6, J Van Nieuwkoop 142, I van Vulpen 107, M C van Woerden 30, M Vanadia 132, W Vandelli 30, R Vanguri 122, A Vaniachine 6, F Vannucci 80, G Vardanyan 177, R Vari 132, E W Varnes 7, T Varol 40, D Varouchas 80, A Vartapetian 8, K E Varvell 150, F Vazeille 34, T Vazquez Schroeder 87, J Veatch 7, L M Veloce 158, F Veloso 126, T Velz 21, S Veneziano 132, A Ventura 73, D Ventura 86, M Venturi 169, N Venturi 158, A Venturini 23, V Vercesi 121, M Verducci 132, W Verkerke 107, J C Vermeulen 107, A Vest 44, M C Vetterli 142, O Viazlo 81, I Vichou 165, T Vickey 139, O E Vickey Boeriu 139, G H A Viehhauser 120, S Viel 15, R Vigne 62, M Villa 20, M Villaplana Perez 91, E Vilucchi 47, M G Vincter 29, V B Vinogradov 65, I Vivarelli 149, F Vives Vaque 3, S Vlachos 10, D Vladoiu 100, M Vlasak 128, M Vogel 32, P Vokac 128, G Volpi 124, M Volpi 88, H von der Schmitt 101, H von Radziewski 48, E von Toerne 21, V Vorobel 129, K Vorobev 98, M Vos 167, R Voss 30, J H Vossebeld 74, N Vranjes 13, M Vranjes Milosavljevic 13, V Vrba 127, M Vreeswijk 107, R Vuillermet 30, I Vukotic 31, Z Vykydal 128, P Wagner 21, W Wagner 175, H Wahlberg 71, S Wahrmund 44, J Wakabayashi 103, J Walder 72, R Walker 100, W Walkowiak 141, C Wang 151, F Wang 173, H Wang 15, H Wang 40, J Wang 42, J Wang 33, K Wang 87, R Wang 6, S M Wang 151, T Wang 21, T Wang 35, X Wang 176, C Wanotayaroj 116, A Warburton 87, C P Ward 28, D R Wardrope 78, A Washbrook 46, C Wasicki 42, P M Watkins 18, A T Watson 18, I J Watson 150, M F Watson 18, G Watts 138, S Watts 84, B M Waugh 78, S Webb 84, M S Weber 17, S W Weber 174, J S Webster 31, A R Weidberg 120, B Weinert 61, J Weingarten 54, C Weiser 48, H Weits 107, P S Wells 30, T Wenaus 25, T Wengler 30, S Wenig 30, N Wermes 21, M Werner 48, P Werner 30, M Wessels 58, J Wetter 161, K Whalen 116, A M Wharton 72, A White 8, M J White 1, R White 32, S White 124, D Whiteson 163, F J Wickens 131, W Wiedenmann 173, M Wielers 131, P Wienemann 21, C Wiglesworth 36, L A M Wiik-Fuchs 21, A Wildauer 101, H G Wilkens 30, H H Williams 122, S Williams 107, C Willis 90, S Willocq 86, A Wilson 89, J A Wilson 18, I Wingerter-Seez 5, F Winklmeier 116, B T Winter 21, M Wittgen 143, J Wittkowski 100, S J Wollstadt 83, M W Wolter 39, H Wolters 126, B K Wosiek 39, J Wotschack 30, M J Woudstra 84, K W Wozniak 39, M Wu 55, M Wu 31, S L Wu 173, X Wu 49, Y Wu 89, T R Wyatt 84, B M Wynne 46, S Xella 36, D Xu 33, L Xu 25, B Yabsley 150, S Yacoob 145, R Yakabe 67, M Yamada 66, D Yamaguchi 157, Y Yamaguchi 118, A Yamamoto 66, S Yamamoto 155, T Yamanaka 155, K Yamauchi 103, Y Yamazaki 67, Z Yan 22, H Yang 33, H Yang 173, Y Yang 151, W-M Yao 15, Y Yasu 66, E Yatsenko 5, K H Yau Wong 21, J Ye 40, S Ye 25, I Yeletskikh 65, A L Yen 57, E Yildirim 42, K Yorita 171, R Yoshida 6, K Yoshihara 122, C Young 143, C J S Young 30, S Youssef 22, D R Yu 15, J Yu 8, J M Yu 89, J Yu 114, L Yuan 67, S P Y Yuen 21, A Yurkewicz 108, I Yusuff 28, B Zabinski 39, R Zaidan 63, A M Zaitsev 130, J Zalieckas 14, A Zaman 148, S Zambito 57, L Zanello 132, D Zanzi 88, C Zeitnitz 175, M Zeman 128, A Zemla 38, Q Zeng 143, K Zengel 23, O Zenin 130, T Ženiš 144, D Zerwas 117, D Zhang 89, F Zhang 173, H Zhang 33, J Zhang 6, L Zhang 48, R Zhang 33, X Zhang 33, Z Zhang 117, X Zhao 40, Y Zhao 33,117, Z Zhao 33, A Zhemchugov 65, J Zhong 120, B Zhou 89, C Zhou 45, L Zhou 35, L Zhou 40, N Zhou 33, C G Zhu 33, H Zhu 33, J Zhu 89, Y Zhu 33, X Zhuang 33, K Zhukov 96, A Zibell 174, D Zieminska 61, N I Zimine 65, C Zimmermann 83, S Zimmermann 48, Z Zinonos 54, M Zinser 83, M Ziolkowski 141, L Živković 13, G Zobernig 173, A Zoccoli 20, M zur Nedden 16, G Zurzolo 104, L Zwalinski 30
PMCID: PMC4764141  PMID: 26949371

Abstract

A search is presented for a high-mass Higgs boson in the HZZ+-+-, HZZ+-νν¯, HZZ+-qq¯, and HZZνν¯qq¯ decay modes using the ATLAS detector at the CERN Large Hadron Collider. The search uses proton–proton collision data at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 20.3 fb-1. The results of the search are interpreted in the scenario of a heavy Higgs boson with a width that is small compared with the experimental mass resolution. The Higgs boson mass range considered extends up to 1TeV for all four decay modes and down to as low as 140 GeV, depending on the decay mode. No significant excess of events over the Standard Model prediction is found. A simultaneous fit to the four decay modes yields upper limits on the production cross-section of a heavy Higgs boson times the branching ratio to Z boson pairs. 95 % confidence level upper limits range from 0.53 pb at mH=195 GeV to 0.008 pb at mH=950 GeV for the gluon-fusion production mode and from 0.31 pb at mH=195 GeV to 0.009 pb at mH=950 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.

Introduction

In 2012, a Higgs boson h with a mass of 125 GeV was discovered by the ATLAS and CMS collaborations at the LHC [1, 2]. One of the most important remaining questions is whether the newly discovered particle is part of an extended scalar sector as postulated by various extensions to the Standard Model (SM) such as the two-Higgs-doublet model (2HDM) [3] and the electroweak-singlet (EWS) model [4]. These predict additional Higgs bosons, motivating searches at masses other than 125 GeV.

This paper reports four separate searches with the ATLAS detector for a heavy neutral scalar H decaying into two SM Z bosons, encompassing the decay modes ZZ+-+-, ZZ+-νν¯, ZZ+-qq¯, and ZZνν¯qq¯, where stands for either an electron or a muon. These modes are referred to, respectively, as , νν, qq, and ννqq.

It is assumed that additional Higgs bosons would be produced predominantly via the 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, results are interpreted separately for ggF and VBF production modes. For Higgs boson masses below 200 GeV, associated production (VH, where V stands for either a W or a Z boson) is important as well. In this mass range, only the decay mode is considered. Due to its excellent mass resolution and high signal-to-background ratio, the decay mode is well-suited for a search for a narrow resonance in the range 140<mH<500 GeV; thus, this search covers the mH range down to 140GeV. The search includes channels sensitive to VH production as well as to the VBF and ggF production modes. The qq and νν searches, covering mH ranges down to 200 and 240 GeV respectively, consider ggF and VBF channels only. The ννqq search covers the mH range down to 400 GeV and does not distinguish between ggF and VBF production. Due to their higher branching ratios, the qq, νν, and ννqq decay modes dominate at higher masses, and contribute to the overall sensitivity of the combined result. The mH range for all four searches extends up to 1000 GeV.

The ggF production mode for the search is further divided into four channels based on lepton flavour, while the νν search includes four channels, corresponding to two lepton flavours for each of the ggF and VBF production modes. For the qq and ννqq searches, the ggF production modes are divided into two subchannels each based on the number of b-tagged jets in the event. For Higgs boson masses above 700 GeV, jets from Z boson decay are boosted and tend to be reconstructed as a single jet; the ggF qq search includes an additional channel sensitive to such final states.

For each channel, a discriminating variable sensitive to mH is identified and used in a likelihood fit. The and qq searches use the invariant mass of the four-fermion system as the final discriminant, while the νν and ννqq searches use a transverse mass distribution. Distributions of these discriminants for each channel are combined in a simultaneous likelihood fit which estimates the rate of heavy Higgs boson production and simultaneously the nuisance parameters corresponding to systematic uncertainties. Additional distributions from background-dominated control regions also enter the fit in order to constrain nuisance parameters. Unless otherwise stated, all figures show shapes and normalizations determined from this fit. All results are interpreted in the scenario of a new Higgs boson with a narrow width, as well as in Type-I and Type-II 2HDMs.

The ATLAS collaboration has published results of searches for a Standard Model Higgs boson decaying in the , qq, and νν modes with 4.7–4.8fb-1 of data collected at s=7TeV [57]. A heavy Higgs boson with the width and branching fractions predicted by the SM was excluded at the 95 % confidence level in the ranges 182<mH<233GeV, 256<mH<265GeV, and 268<mH<415GeV by the mode; in the ranges 300<mH<322GeV and 353<mH<410GeV by the qq mode; and in the range 319<mH<558GeV by the νν mode. The searches in this paper use a data set of 20.3fb-1 of pp collision data collected at a centre-of-mass energy of s=8TeV. Besides using a larger data set at a higher centre-of-mass energy, these searches improve on the earlier results by adding selections sensitive to VBF production for the , qq, and νν decay modes and by further optimizing the event selection and other aspects of the analysis. In addition, the ννqq decay mode has been added; finally, results of searches in all four decay modes are used in a combined search. The CMS Collaboration has also recently published a search for a heavy Higgs boson with SM width in HZZ decays [8]. Since the searches reported here use a narrow width for each Higgs boson mass hypothesis instead of the larger width corresponding to a SM Higgs boson, a direct comparison against earlier ATLAS results and the latest CMS results is not possible.

This paper is organized as follows. After a brief description of the ATLAS detector in Sect. 2, the simulation of the background and signal processes used in this analysis is outlined in Sect. 3. Section 4 summarizes the reconstruction of the final-state objects used by these searches. The event selection and background estimation for the four searches are presented in Sects. 5 to 8, and Sect. 9 discusses the systematic uncertainties common to all searches. Section 10 details the statistical combination of all the searches into a single limit, which is given in Sect. 11. Finally, Sect. 12 gives the conclusions.

ATLAS detector

ATLAS is a multi-purpose detector [9] which provides nearly full solid-angle coverage around the interaction point.1 It consists of a tracking system (inner detector or ID) surrounded by a thin superconducting solenoid providing a 2 T magnetic field, electromagnetic and hadronic calorimeters, and a muon spectrometer (MS). The ID consists of pixel and silicon microstrip detectors covering the pseudorapidity region |η|<2.5, surrounded by a transition radiation tracker (TRT), which improves electron identification in the region |η|<2.0. The sampling calorimeters cover the region |η|<4.9. The forward region (3.2<|η|<4.9) is instrumented with a liquid-argon (LAr) calorimeter for electromagnetic and hadronic measurements. In the central region, a high-granularity lead/LAr electromagnetic calorimeter covers |η|<3.2. Hadron calorimetry is based on either steel absorbers with scintillator tiles (|η|<1.7) or copper absorbers in LAr (1.5<|η|<3.2). The MS consists of three large superconducting toroids arranged with an eight-fold azimuthal coil symmetry around the calorimeters, and a system of three layers of precision gas chambers providing tracking coverage in the range |η|<2.7, while dedicated chambers allow triggering on muons in the region |η|<2.4. The ATLAS trigger system [10] consists of three levels; the first (L1) is a hardware-based system, while the second and third levels are software-based systems.

Data and Monte Carlo samples

Data sample

The data used in these searches were collected by ATLAS at a centre-of-mass energy of 8 TeV during 2012 and correspond to an integrated luminosity of 20.3fb-1.

Collision events are recorded only if they are selected by the online trigger system. For the ννqq search this selection requires that the magnitude ETmiss of the missing transverse momentum vector (see Sect. 4) is above 80GeV. Searches with leptonic final states use a combination of single-lepton and dilepton triggers in order to maximize acceptance. The main single-lepton triggers have a minimum pT (muons) or ET (electrons) threshold of 24GeV and require that the leptons are isolated. They are complemented with triggers with higher thresholds (60GeV for electrons and 36GeV for muons) and no isolation requirement in order to increase acceptance at high pT and ET. The dilepton triggers require two same-flavour leptons with a threshold of 12GeV for electrons and 13GeV for muons. The acceptance in the search is increased further with an additional asymmetric dimuon trigger selecting one muon with pT>18GeV and another one with pT>8GeV and an electron–muon trigger with thresholds of ETe>12GeV and pTμ>8GeV.

Signal samples and modelling

The acceptance and resolution for the signal of a narrow-width heavy Higgs boson decaying to a Z boson pair are modelled using Monte Carlo (MC) simulation. Signal samples are generated using Powheg r1508 [11, 12], which calculates separately the gluon and vector-boson-fusion Higgs boson production processes up to next-to-leading order (NLO) in αS. The generated signal events are hadronized with Pythia  8.165 using the AU2 set of tunable parameters for the underlying event [13, 14]; Pythia also decays the Z bosons into all modes considered in this search. The contribution from Z boson decay to τ leptons is also included. The NLO CT10 [15] parton distribution function (PDF) is used. The associated production of Higgs bosons with a W or Z boson (WH and ZH) is significant for mH<200GeV. It is therefore included as a signal process for the search for mH<400GeV and simulated using Pythia  8 with the LO CTEQ6L1 PDF set [16] and the AU2 parameter set. These samples are summarized in Table 1.

Table 1.

Details of the generation of simulated signal and background event samples. For each physics process, the table gives the final states generated, the HZZ final states(s) for which they are used, the generator, the PDF set, and the underlying-event tune. For the background samples, the order in αS used to normalize the event yield is also given; for the signal, the normalization is the parameter of interest in the fit. More details can be found in the text

Physics process HZZ search final state Generator Cross-section normalization PDF set Tune
W/Z boson + jets
Z/γ+-/νν¯ /νν Alpgen 2.14 [25] NNLO [47] CTEQ6L1 [16] AUET2 [14, 48]
qqa/ννqq Sherpa 1.4.1 [24] NNLO [49, 50] NLO CT10 Sherpa default
Wν νν Alpgen 2.14 NNLO [47] CTEQ6L1 AUET2
ννqq Sherpa 1.4.1 NNLO [49, 50] NLO CT10 Sherpa default
Top quark
tt¯ /qq/ννqq Powheg-Box r2129 [5153] NNLO+NNLL NLO CT10 Perugia2011C [54]
νν MC@NLO 4.03 [39]    [55, 56] AUET2
s-channel and Wt /qq/ννqq Powheg-Box r1556 NNLO+NNLL NLO CT10 Perugia2011C
νν MC@NLO 4.03    [57, 58] AUET2
t-channel All AcerMC 3.8 [44] NNLO+NNLL [59] CTEQ6L1 AUET2
Dibosons
qq¯ZZ() qq/ννqq Powheg-Box r1508 [60] NLO [35, 61] NLO CT10 AUET2
/νν Powheg-Box r1508 [60] NNLO QCD [31] NLO CT10 AUET2
NLO EW [32, 33]
EW qq¯(h) ZZ()+2j MadGraph 5 1.3.28 [43] CTEQ6L1 AUET2
gg(h)ZZ MCFM 6.1 [46] NNLO [38] NLO CT10 AU2
νν GG2VV 3.1.3 [36, 37]    (for hZZ) NLO CT10 AU2
qq¯WZ νν/qq/ννqq Powheg-Box r1508 NLO [35, 61] NLO CT10 AUET2
Sherpa 1.4.1 Sherpa default
qq¯WW All Powheg-Box r1508 NLO [35, 61] NLO CT10 AUET2
mh=125GeV SM Higgs boson (background)b
qq¯Zh +-bb¯/νν¯bb¯ qq/ννqq Pythia 8.165 NNLO [6264] CTEQ6L AU2
ggZh +-bb¯/νν¯bb¯ qq/ννqq Powheg-Box r1508 NLO [65] CT10 AU2
Signal
ggHZZ() All Powheg-Box r1508 NLO CT10 AU2
qq¯H+2j; HZZ() all Powheg-Box r1508 NLO CT10 AU2
qq¯(W/Z)H; HZZ() Pythia 8.163 CTEQ6L1 AU2

a The HZZ+-qq¯ VBF search uses Alpgen instead

b For the HZZ+-+- and HZZ+-νν¯ searches, the SM hZZ boson contribution, along with its interference with the continuum ZZ background, is included in the diboson samples

Besides model-independent results, a search in the context of a CP-conserving 2HDM [3] is also presented. This model has five physical Higgs bosons after electroweak symmetry breaking: two CP-even, h and H; one CP-odd, A; and two charged, H±. The model considered here has seven free parameters: the Higgs boson masses (mh, mH, mA, mH±), 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 H boson to vector bosons is proportional to cos(β-α). In the limit cos(β-α)0 the light CP-even Higgs boson, h, 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.

The production cross-sections for both the ggF and VBF processes are calculated using SusHi 1.3.0 [1722], while the branching ratios are calculated with 2HDMC 1.6.4 [23]. For the branching ratio calculations it is assumed that mA=mH=mH±, mh=125GeV, and m122=mA2tanβ/(1+tanβ2). In the 2HDM parameter space considered in this analysis, the cross-section times branching ratio for HZZ with mH=200GeV varies from 2.4 fb to 10 pb for Type-I and from 0.5 fb to 9.4 pb for Type-II.

The width of the heavy Higgs boson varies over the parameter space of the 2HDM model, and may be significant compared with the experimental resolution. Since this analysis assumes a narrow-width signal, the 2HDM interpretation is limited to regions of parameter space where the width is less than 0.5 % of mH (significantly smaller than the detector resolution). In addition, the off-shell contribution from the light Higgs boson and its interference with the non-resonant ZZ background vary over the 2HDM parameter space as the light Higgs boson couplings are modified from their SM values. Therefore the interpretation is further limited to regions of the parameter space where the light Higgs boson couplings are enhanced by less than a factor of three from their SM values; in these regions the variation is found to have a negligible effect.

Background samples

Monte Carlo simulations are also used to model the shapes of distributions from many of the sources of SM background to these searches. Table 1 summarizes the simulated event samples along with the PDF sets and underlying-event tunes used. Additional samples are also used to compute systematic uncertainties as detailed in Sect. 9.

Sherpa  1.4.1 [24] includes the effects of heavy-quark masses in its modelling of the production of W and Z bosons along with additional jets (V+jets). For this reason it is used to model these backgrounds in the hadronic qq and ννqq searches, which are subdivided based on whether the Z boson decays into b-quarks or light-flavour quarks. The Alpgen 2.14 W+jets and Z/γ+jets samples are generated with up to five hard partons and with the partons matched to final-state particle jets [25, 26]. They are used to describe these backgrounds in the other decay modes and also in the VBF channel of the qq search2 since the additional partons in the matrix element give a better description of the VBF topology. The Sherpa (Alpgen) Z/γ+jets samples have a dilepton invariant mass requirement of m>40GeV (60GeV) at the generator level.

The background from the associated production of the 125GeV h boson along with a Z boson is non-negligible in the qq and ννqq searches and is taken into account. Contributions to Zh from both qq¯ annihilation and gluon fusion are included. The qq¯Zh samples take into account NLO electroweak corrections, including differential corrections as a function of Z boson pT [27, 28]. The Higgs boson branching ratio is calculated using hdecay [29]. Further details can be found in Ref. [30].

Continuum ZZ() events form the dominant background for the and νν decay modes; this is modelled with a dedicated qq¯ZZ() sample. This sample is corrected to match the calculation described in Ref. [31], which is next-to-next-to-leading order (NNLO) in αS, with a K-factor that is differential in mZZ. Higher-order electroweak effects are included following the calculation reported in Refs. [32, 33] by applying a K-factor based on the kinematics of the diboson system and the initial-state quarks, using a procedure similar to that described in Ref. [34]. The off-shell SM ggF Higgs boson process, the ggZZ continuum, and their interference are considered as backgrounds. These samples are generated at leading order (LO) in αS using MCFM 6.1 [35] () or gg2vv 3.1.3 [36, 37] (νν) but corrected to NNLO as a function of mZZ [38] using the same procedure as described in Ref. [6]. For the qq and ννqq searches, the continuum ZZ() background is smaller so the qq¯ZZ() sample is used alone. It is scaled to include the contribution from ggZZ() using the ggZZ() cross-section calculated by MCFM 6.1 [35].

For samples in which the hard process is generated with Alpgen or MC@NLO 4.03 [39], Herwig 6.520 [40] is used to simulate parton showering and fragmentation, with Jimmy  [41] used for the underlying-event simulation. Pythia 6.426 [42] is used for samples generated with MadGraph [43] and AcerMC  [44], while Pythia 8.165 [45] is used for the gg2vv 3.1.3 [36, 37], MCFM 6.1 [46], and Powheg samples. Sherpa implements its own parton showering and fragmentation model.

In the qq and ννqq searches, which have jets in the final state, the principal background is V+jets, where V stands for either a W or a Z boson. In simulations of these backgrounds, jets are labelled according to which generated hadrons with pT>5GeV are found within a cone of size ΔR=0.4 around the reconstructed jet axis. If a b-hadron is found, the jet is labelled as a b-jet; if not and a charmed hadron is found, the jet is labelled as a c-jet; if neither is found, the jet is labelled as a light (i.e., u-, d-, or s-quark, or gluon) jet, denoted by ‘j’. For V+jets events that pass the selections for these searches, two of the additional jets are reconstructed as the hadronically-decaying Z boson candidate. Simulated V+jets events are then categorized based on the labels of these jets. If one jet is labelled as a b-jet, the event belongs to the V+b category; if not, and one of the jets is labelled as a c-jet, the event belongs to the V+c category; otherwise, the event belongs to the V+j category. Further subdivisions are defined according to the flavour of the other jet from the pair, using the same precedence order: V+bb, V+bc, V+bj, V+cc, V+cj, and V+jj; the combination of V+bb, V+bc, and V+cc is denoted by V + hf.

Detector simulation

The simulation of the detector is performed with either a full ATLAS detector simulation [66] based on Geant  4 9.6 [67] or a fast simulation3 based on a parameterization of the performance of the ATLAS electromagnetic and hadronic calorimeters [68] and on Geant  4 elsewhere. All simulated samples are generated with a variable number of minimum-bias interactions (simulated using Pythia  8 with the MSTW2008LO PDF [69] and the A2 tune [48]), overlaid on the hard-scattering event to account for additional pp interactions in either the same or a neighbouring bunch crossing (pile-up).

Corrections are applied to the simulated samples to account for differences between data and simulation for the lepton trigger and reconstruction efficiencies, and for the efficiency and misidentification rate of the algorithm used to identify jets containing b-hadrons (b-tagging).

Object reconstruction and common event selection

The exact requirements used to identify physics objects vary between the different searches. This section outlines features that are common to all of the searches; search-specific requirements are given in the sections below.

Event vertices are formed from tracks with pT>400MeV. Each event must have an identified primary vertex, which is chosen from among the vertices with at least three tracks as the one with the largest pT2 of associated tracks.

Muon candidates (‘muons’) [70] generally consist of a track in the ID matched with one in the MS. However, in the forward region (2.5<|η|<2.7), MS tracks may be used with no matching ID tracks; further, around |η|=0, where there is a gap in MS coverage, ID tracks with no matching MS track may be used if they match an energy deposit in the calorimeter consistent with a muon. In addition to quality requirements, muon tracks are required to pass close to the reconstructed primary event vertex. The longitudinal impact parameter, z0, is required to be less than 10mm, while the transverse impact parameter, d0, is required to be less than 1mm to reject non-collision backgrounds. This requirement is not applied in the case of muons with no ID track.

Electron candidates (‘electrons’) [7173] consist of an energy cluster in the EM calorimeter with |η|<2.47 matched to a track reconstructed in the inner detector. The energy of the electron is measured from the energy of the calorimeter cluster, while the direction is taken from the matching track. Electron candidates are selected using variables sensitive to the shape of the EM cluster, the quality of the track, and the goodness of the match between the cluster and the track. Depending on the search, either a selection is made on each variable sequentially or all the variables are combined into a likelihood discriminant.

Electron and muon energies are calibrated from measurements of Zee/μμ decays [70, 72]. Electrons and muons must be isolated from other tracks, using pT,isol/pT<0.1, where pT,isol is the scalar sum of the transverse momenta of tracks within a ΔR=0.2 cone around the electron or muon (excluding the electron or muon track itself), and pT is the transverse momentum of the electron or muon candidate. The isolation requirement is not applied in the case of muons with no ID track. For searches with electrons or muons in the final state, the reconstructed lepton candidates must match the trigger lepton candidates that resulted in the events being recorded by the online selection.

Jets are reconstructed [74] using the anti-kt algorithm [75] with a radius parameter R=0.4 operating on massless calorimeter energy clusters constructed using a nearest-neighbour algorithm. Jet energies and directions are calibrated using energy- and η-dependent correction factors derived using MC simulations, with an additional calibration applied to data samples derived from in situ measurements [76]. A correction is also made for effects of energy from pile-up. For jets with pT<50GeV within the acceptance of the ID (|η|<2.4), the fraction of the summed scalar pT of the tracks associated with the jet (within a ΔR=0.4 cone around the jet axis) contributed by those tracks originating from the primary vertex must be at least 50 %. This ratio is called the jet vertex fraction (JVF), and this requirement reduces the number of jet candidates originating from pile-up vertices [77, 78].

In the qq search at large Higgs boson masses, the decay products of the boosted Z boson may be reconstructed as a single anti-kt jet with a radius of R=0.4. Such configurations are identified using the jet invariant mass, obtained by summing the momenta of the jet constituents. After the energy calibration, the jet masses are calibrated, based on Monte Carlo simulations, as a function of jet pT, η, and mass.

The missing transverse momentum, with magnitude ETmiss, is the negative vectorial sum of the transverse momenta from calibrated objects, such as identified electrons, muons, photons, hadronic decays of tau leptons, and jets [79]. Clusters of calorimeter cells not matched to any object are also included.

Jets containing b-hadrons (b-jets) can be discriminated from other jets (‘tagged’) based on the relatively long lifetime of b-hadrons. Several methods are used to tag jets originating from the fragmentation of a b-quark, including looking for tracks with a large impact parameter with respect to the primary event vertex, looking for a secondary decay vertex, and reconstructing a b-hadron c hadron decay chain. For the qq and ννqq searches, this information is combined into a single neural-network discriminant (‘MV1c’). This is a continuous variable that is larger for jets that are more like b-jets. A selection is then applied that gives an efficiency of about 70 %, on average, for identifying true b-jets, while the efficiencies for accepting c-jets or light-quark jets are 1/5 and 1/140 respectively [30, 8083]. The νν search uses an alternative version of this discriminant, ‘MV1’ [80], to reject background due to top-quark production; compared with MV1c it has a smaller c-jet rejection. Tag efficiencies and mistag rates are calibrated using data. For the purpose of forming the invariant mass of the b-jets, mbb, the energies of b-tagged jets are corrected to account for muons within the jets and an additional pT-dependent correction is applied to account for biases in the response due to resolution effects.

In channels which require two b-tagged jets in the final state, the efficiency for simulated events of the dominant Z+jets background to pass the b-tagging selection is low. To effectively increase the sizes of simulated samples, jets are ‘truth tagged’: each event is weighted by the flavour-dependent probability of the jets to actually pass the b-tagging selection.

HZZ+-+- event selection and background estimation

Event selection

The event selection and background estimation for the HZZ+-+- () search is very similar to the analysis described in Ref. [84]. More details may be found there; a summary is given here.

Higgs boson candidates in the search must have two same-flavour, opposite-charge lepton pairs. Muons must satisfy pT>6GeV and |η|<2.7, while electrons are identified using the likelihood discriminant corresponding to the ‘loose LH’ selection from Ref. [73] and must satisfy pT>7GeV. The impact parameter requirements that are made for muons are also applied to electrons, and electrons (muons) must also satisfy a requirement on the transverse impact parameter significance, |d0|/σd0<6.5 (3.5). For this search, the track-based isolation requirement is relaxed to pT,isol/pT<0.15 for both the electrons and muons. In addition, lepton candidates must also be isolated in ET,isol, the sum of the transverse energies in calorimeter cells within a ΔR=0.2 cone around the candidate (excluding the deposit from the candidate itself). The requirement is ET,isol/pT<0.2 for electrons, <0.3 for muons with a matching ID track, and <0.15 for other muons. The three highest-pT leptons in the event must satisfy, in order, pT>20, 15, and 10GeV. To ensure well-measured leptons, and reduce backgrounds containing electrons from bremsstrahlung, same-flavour leptons must be separated from each other by ΔR>0.1, and different-flavour leptons by ΔR>0.2. Jets that are ΔR<0.2 from electrons are removed. Final states in this search are classified depending on the flavours of the leptons present: 4μ, 2e2μ, 2μ2e, and 4e. The selection of lepton pairs is made separately for each of these flavour combinations; the pair with invariant mass closest to the Z boson mass is called the leading pair and its invariant mass, m12, must be in the range 50106GeV. For the 2e2μ channel, the electrons form the leading pair, while for the 2μ2e channel the muons are leading. The second, subleading, pair of each combination is the pair from the remaining leptons with invariant mass m34 closest to that of the Z boson in the range mmin<m34<115GeV. Here mmin is 12GeV for m<140GeV, rises linearly to 50GeV at m=190GeV, and remains at 50GeV for m>190GeV. Finally, if more than one flavour combination passes the selection, which could happen for events with more than four leptons, the flavour combination with the highest expected signal acceptance is kept; i.e., in the order: 4μ, 2e2μ, 2μ2e, and 4e. For 4μ and 4e events, if an opposite-charge same-flavour dilepton pair is found with m below 5GeV, the event is vetoed in order to reject backgrounds from J/ψ decays.

To improve the mass resolution, the four-momentum of any reconstructed photon consistent with having been radiated from one of the leptons in the leading pair is added to the final state. Also, the four-momenta of the leptons in the leading pair are adjusted by means of a kinematic fit assuming a Z decay; this improves the m resolution by up to 15 %, depending on mH. This is not applied to the subleading pair in order to retain sensitivity at lower mH where one of the Z boson decays may be off-shell. For 4μ events, the resulting mass resolution varies from 1.5 % at mH=200GeV to 3.5 % at mH=1TeV, while for 4e events it ranges from 2 % at mH=200GeV to below 1 % at 1TeV.

Signal events can be produced via ggF or VBF, or associated production (VH, where V stands for either a W or a Z boson). In order to measure the rates for these processes separately, events passing the event selection described above are classified into channels, either ggF, VBF, or VH. Events containing at least two jets with pT>25GeV and |η|<2.5 or pT>30GeV and 2.5<|η|<4.5 and with the leading two such jets having mjj>130GeV are classified as VBF events. Otherwise, if a jet pair satisfying the same pT and η requirements is present but with 40<mjj<130GeV, the event is classified as VH, providing it also passes a selection on a multivariate discriminant used to separate the VH and ggF signal. The multivariate discriminant makes use of mjj, Δηjj, the pT of the two jets, and the η of the leading jet. In order to account for leptonic decays of the V (W or Z) boson, events failing this selection may still be classified as VH if an additional lepton with pT>8GeV is present. All remaining events are classified as ggF. Due to the differing background compositions and signal resolutions, events in the ggF channel are further classified into subchannels according to their final state: 4e, 2e2μ, 2μ2e, or 4μ. The selection for VBF is looser than that used in the other searches; however, the effect on the final results is small. The m distributions for the three channels are shown in Fig. 1.

Fig. 1.

Fig. 1

The distributions used in the likelihood fit of the four-lepton invariant mass m for the HZZ+-+- search in the a ggF, b VBF, and c VH channels. The ‘Z+jets, tt¯’ entry includes all backgrounds other than ZZ, as measured from data. No events are observed beyond the upper limit of the plots. The simulated mH=200GeV signal is normalized to a cross-section corresponding to five times the observed limit given in Sect. 11. Both the VBF and VH signal modes are shown in b as there is significant contamination of VH events in the VBF category

Background estimation

The dominant background in this channel is continuum ZZ() production. Its contribution to the yield is determined from simulation using the samples described in Sect. 3.3. Other background components are small and consist mainly of tt¯ and Z+jets events. These are difficult to estimate from MC simulations due to the small rate at which such events pass the event selection, and also because they depend on details of jet fragmentation, which are difficult to model reliably in simulations. Therefore, both the rate and composition of these backgrounds are estimated from data. Since the composition of these backgrounds depends on the flavour of the subleading dilepton pair, different approaches are taken for the μμ and the ee final states.

The μμ non-ZZ background comprises mostly tt¯ and Z+bb¯ events, where in the latter 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 normalization of each component is estimated by a simultaneous fit to the m12 distribution in four control regions, defined by inverting the impact parameter significance or isolation requirements on the subleading muon, or by selecting a subleading eμ or same-charge pair. A small contribution from WZ decays is estimated using simulation. The electron background contributing to the ee final states comes mainly from jets misidentified as electrons, arising in three ways: light-flavour hadrons misidentified as electrons, photon conversions reconstructed as electrons, and non-isolated electrons from heavy-flavour hadronic decays. This background is estimated in a control region in which the three highest-pT leptons must satisfy the full selection, with the third lepton being an electron. For the lowest-pT lepton, which must also be an electron, the impact parameter and isolation requirements are removed and the likelihood requirement is relaxed. In addition, it must have the same charge as the other subleading electron in order to minimize the contribution from the ZZ() background. The yields of the background components of the lowest-pT lepton are extracted with a fit to the number of hits in the innermost pixel layer and the ratio of the number of high-threshold to low-threshold TRT hits (which provides discrimination between electrons and pions). For both backgrounds, the fitted yields in the control regions are extrapolated to the signal region using efficiencies obtained from simulation.

For the non-ZZ components of the background, the m shape is evaluated for the μμ final states using simulated events, and from data for the ee final states by extrapolating the shape from the ee control region described above. The fraction of this background in each channel (ggF, VBF, VH) is evaluated using simulation. The non-ZZ background contribution for m>140GeV is found to be approximately 4 % of the total background.

Major sources of uncertainty in the estimate of the non-ZZ backgrounds include differences in the results when alternative methods are used to estimate the background [84], uncertainties in the transfer factors used to extrapolate from the control region to the signal region, and the limited statistical precision in the control regions. For the μμ (ee) background, the uncertainty is 21 % (27 %) in the ggF channel, 100 % (117 %) in the VBF channel, and 62 % (79 %) in the VH channel. The larger uncertainty in the VBF channel arises due to large statistical uncertainties on the fraction of Z+jets events falling in this channel. Uncertainties in the expected m shape are estimated from differences in the shapes obtained using different methods for estimating the background.

HZZ+-νν¯ event selection and background estimation

Event selection

The event selection for the HZZ+-νν¯ (νν) search starts with the reconstruction of either a Ze+e- or Zμ+μ- lepton pair; the leptons must be of opposite charge and must have invariant mass 76<m<106GeV. The charged lepton selection is tighter than that described in Sect. 4. Muons must have matching tracks in the ID and MS and lie in the region |η|<2.5. Electrons are identified using a series of sequential requirements on the discriminating variables, corresponding to the ‘medium’ selection from Ref. [73]. Candidate leptons for the Z+- decay must have pT>20GeV, and leptons within a cone of ΔR=0.4 around jets are removed. Jets that lie ΔR<0.2 of electrons are also removed. Events containing a third lepton or muon with pT>7GeV are rejected; for the purpose of this requirement, the ‘loose’ electron selection from Ref. [73] is used. To select events with neutrinos in the final state, the magnitude of the missing transverse momentum must satisfy ETmiss>70GeV.

As in the search, samples enriched in either ggF or VBF production are selected. An event is classified as VBF if it has at least two jets with pT>30GeV and |η|<4.5 with mjj>550GeV and Δηjj>4.4. Events failing to satisfy the VBF criteria and having no more than one jet with pT>30GeV and |η|<2.5 are classified as ggF. Events not satisfying either set of criteria are rejected.

To suppress the Drell–Yan background, the azimuthal angle between the combined dilepton system and the missing transverse momentum vector Δϕ(pT,ETmiss) must be greater than 2.8 (2.7) for the ggF (VBF) channel (optimized for signal significance in each channel), and the fractional pT difference, defined as |pTmiss,jet-pT|/pT, must be less than 20 %, where pTmiss,jet=|ETmiss+jetpTjet|. Z bosons originating from the decay of a high-mass state are boosted; thus, the azimuthal angle between the two leptons Δϕ must be less than 1.4. Events containing a b-tagged jet with pT>20GeV and |η|<2.5 are rejected in order to reduce the background from top-quark production. All jets in the event must have an azimuthal angle greater than 0.3 relative to the missing transverse momentum.

The discriminating variable used is the transverse mass mTZZ reconstructed from the momentum of the dilepton system and the missing transverse momentum, defined by:

(mTZZ)2mZ2+pT2+mZ2+ETmiss22-pT+ETmiss2. 1

The resulting resolution in mTZZ ranges from 7 % at mH=240GeV to 15 % at mH=1TeV.

Figure 2 shows the mTZZ distribution in the ggF channel. The event yields in the VBF channel are very small (see Table 2).

Fig. 2.

Fig. 2

The distribution used in the likelihood fit of the transverse mass mTZZ reconstructed from the momentum of the dilepton system and the missing transverse momentum for the HZZ+-νν¯ search in the ggF channel. The simulated signal is normalized to a cross-section corresponding to five times the observed limit given in Sect. 11. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom pane shows the ratio of the observed data to the predicted background

Table 2.

Expected background yields and observed counts of data events after all selections for the ggF and VBF channels of the HZZ+-νν¯ search. The first and second uncertainties correspond to the statistical and systematic uncertainties, respectively

Process ggF channel VBF channel
qq¯ZZ 110±1±10 0.13±0.04±0.02
ggZZ 11±0.1±5 0.12±0.01±0.05
WZ 47±1±5 0.10±0.05±0.1
WW/tt¯/Wt/Zτ+τ- 58±6±5 0.41±0.01±0.08
Z(e+e-,μ+μ-)+jets 74±7±20 0.8±0.3±0.3
Other backgrounds 4.5±0.7±0.5
Total background 310±9±40 1.6±0.3±0.5
Observed 309 4
ggF signal (mH=400GeV) 45±1±3
VBF signal (mH=400GeV) 1±<0.1±2 10±0.5±1

Background estimation

The dominant background is ZZ production, followed by WZ production. Other important backgrounds to this search include the WW, tt¯, Wt, and Zτ+τ- processes, and also the Z+jets process with poorly reconstructed ETmiss, but these processes tend to yield final states with low mT. Backgrounds from W+jets, tt¯, single top quark (s- and t-channel), and multijet processes with at least one jet misidentified as an electron or muon are very small.

The Powheg simulation is used to estimate the ZZ background in the same way as for the search. The WZ background is also estimated with Powheg and validated with data using a sample of events that pass the signal selection and that contain an extra electron or muon in addition to the Z+- candidate.

The WW, tt¯, Wt, and Zτ+τ- processes give rise to both same-flavour as well as different-flavour lepton final states. The total background from these processes in the same-flavour final state can be estimated from control samples that contain an electron–muon pair rather than a same-flavour lepton pair by

Neebkg=12×Neμdata,sub×f,Nμμbkg=12×Neμdata,sub×1f, 2

where Neebkg and Nμμbkg are the number of electron and muon pair events in the signal region and Neμdata,sub is the number of events in the eμ control sample with WZ, ZZ, and other small backgrounds (W+jets, tt¯W/Z, and triboson) subtracted using simulation. The factor of two arises because the branching ratio to final states containing electrons and muons is twice that of either ee or μμ. The factor f takes into account the different efficiencies for electrons and muons and is measured from data as f2=Needata/Nμμdata, the ratio of the number of electron pair to muon pair events in the data after the Z boson mass requirement (76<m<106GeV). The measured value of f is 0.94 with a systematic uncertainty of 0.04 and a negligible statistical uncertainty. There is also a systematic uncertainty from the background subtraction in the control sample; this is less than 1 %. For the VBF channel, no events remain in the eμ control sample after applying the full selection. In this case, the background estimate is calculated after only the requirements on ETmiss and the number of jets; the efficiencies of the remaining selections for this background are estimated using simulation.

The Z+jets background is estimated from data by comparing the signal region (A) with regions in which one (B, C) or both (D) of the Δϕ and Δϕ(pT,ETmiss) requirements are reversed. An estimate of the number of background events in the signal region is then NAest=NCobs×(NBobs/NDobs), where NXobs is the number of events observed in region X after subtracting non-Z boson backgrounds. The shape is estimated by taking NCobs (the region with the Δϕ requirement reversed) bin-by-bin and applying a correction derived from MC simulations to account for shape differences between regions A and C. Systematic uncertainties arise from differences in the shape of the ETmiss and mTZZ distributions among the four regions, the small correlation between the two variables, and the subtraction of non-Z boson backgrounds.

The W+jets and multijet backgrounds are estimated from data using the fake-factor method [85]. This uses a control sample derived from data using a loosened requirement on ETmiss and several kinematic selections. The background in the signal region is then derived using an efficiency factor from simulation to correct for the acceptance. Both of these backgrounds are found to be negligible.

Table 2 shows the expected yields of the backgrounds and signal, and observed counts of data events. The expected yields of the backgrounds in the table are after applying the combined likelihood fit to the data, as explained in Sect. 10.

HZZ+-qq¯ event selection and background estimation

Event selection

As in the previous search, the event selection starts with the reconstruction of a Z decay. For the purpose of this search, leptons are classified as either ‘loose’, with pT>7GeV, or ‘tight’, with pT>25GeV. Loose muons extend to |η|<2.7, while tight muons are restricted to |η|<2.5 and must have tracks in both the ID and the MS. The transverse impact parameter requirement for muons is tightened for this search to |d0|<0.1mm. Electrons are identified using a likelihood discriminant very similar to that used for the search, except that it was tuned for a higher signal efficiency. This selection is denoted ‘very loose LH’ [73]. To avoid double counting, the following procedure is applied to loose leptons and jets. First, any jets that lie ΔR<0.4 of an electron are removed. Next, if a jet is within a cone of ΔR=0.4 of a muon, the jet is discarded if it has less than two matched tracks or if the JVF recalculated without muons (see Sect. 4) is less than 0.5, since in this case it is likely to originate from a muon having showered in the calorimeter; otherwise the muon is discarded. (Such muons are nevertheless included in the computation of the ETmiss and in the jet energy corrections described in Sect. 4.) Finally, if an electron is within a cone of ΔR=0.2 of a muon, the muon is kept unless it has no track in the MS, in which case the electron is kept.

Events must contain a same-flavour lepton pair with invariant mass satisfying 83< m <99GeV. At least one of the leptons must be tight, while the other may be either tight or loose. Events containing any additional loose leptons are rejected. The two muons in a pair are required to have opposite charge, but this requirement is not imposed for electrons because larger energy losses from showering in material in the inner tracking detector lead to higher charge misidentification probabilities.

Jets used in this search to reconstruct the Zqq¯ decay, referred to as ‘signal’ jets, must have |η|<2.5 and pT>20GeV; the leading signal jet must also have pT>45GeV. The search for forward jets in the VBF production mode uses an alternative, ‘loose’, jet definition, which includes both signal jets and any additional jets satisfying 2.5<|η|<4.5 and pT>30GeV. Since no high-pT neutrinos are expected in this search, the significance of the missing transverse momentum, ETmiss/HT (all quantities in GeV), where HT is the scalar sum of the transverse momenta of the leptons and loose jets, must be less than 3.5. This requirement is loosened to 6.0 for the case of the resolved channel (see Sect. 7.1.1) with two b-tagged jets due to the presence of neutrinos from heavy-flavour decay. The ETmiss significance requirement rejects mainly top-quark background.

Following the selection of the Z decay, the search is divided into several channels: resolved ggF, merged-jet ggF, and VBF, as discussed below.

Resolved ggF channel

Over most of the mass range considered in this search (mH700GeV), the Zqq¯ decay results in two well-separated jets that can be individually resolved. Events in this channel should thus contain at least two signal jets. Since b-jets occur much more often in the signal (21% of the time) than in the dominant Z+jets background (2% of the time), the sensitivity of this search is optimized by dividing it into ‘tagged’ and ‘untagged’ subchannels, containing events with exactly two and fewer than two b-tagged jets, respectively. Events with more than two b-tagged jets are rejected.

In the tagged subchannel, the two b-tagged jets form the candidate Zqq¯ decay. In the untagged subchannel, if there are no b-tagged jets, the two jets with largest transverse momenta are used. Otherwise, the b-tagged jet is paired with the non-b-tagged jet with the largest transverse momentum. The invariant mass of the chosen jet pair mjj must be in the range 70105GeV in order to be consistent with Zqq¯ decay. To maintain orthogonality, any events containing a VBF-jet pair as defined by the VBF channel (see Sect. 7.1.3) are excluded from the resolved selection.

The discriminating variable in this search is the invariant mass of the jj system, mjj; a signal should appear as a peak in this distribution. To improve the mass resolution, the energies of the jets forming the dijet pair are scaled event-by-event by a single multiplicative factor to set the dijet invariant mass mjj to the mass of the Z boson (mZ). This improves the resolution by a factor of 2.4 at mH=200GeV. The resulting mjj resolution is 2–3 %, approximately independent of mH, for both the untagged and tagged channels.

Following the selection of the candidate qq decay, further requirements are applied in order to optimize the sensitivity of the search. For the untagged subchannel, the first requirement is on the transverse momentum of the leading jet, pTj, which tends to be higher for the signal than for the background. The optimal value for this requirement increases with increasing mH. In order to avoid having distinct selections for different mH regions, pTj is normalized by the reconstructed final-state mass mjj; the actual selection is pTj>0.1×mjj. Studies have shown that the optimal requirement on pTj/mjj is nearly independent of the assumed value of mH. Second, the total transverse momentum of the dilepton pair also increases with increasing mH. Following a similar strategy, the selection is pT>min[-54GeV+0.46×mjj,275GeV]. Finally, the azimuthal angle between the two leptons decreases with increasing mH; it must satisfy Δϕ<(270GeV/mjj)3.5+1. For the tagged channel, only one additional requirement is applied: pT>min[-79GeV+0.44×mjj,275GeV]; the different selection for pT increases the sensitivity of the tagged channel at low mH. Figure 3a and b show the mjj distributions of the two subchannels after the final selection.

Fig. 3.

Fig. 3

The distributions used in the likelihood fit of the invariant mass of dilepton + dijet system mjj for the HZZ+-qq¯ search in the a untagged and b tagged resolved ggF subchannels. The dashed line shows the total background used as input to the fit. The simulated signal is normalized to a cross-section corresponding to 30 times the observed limit given in Sect. 11. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Merged-jet ggF channel

For very large Higgs boson masses, mH700GeV, the Z bosons become highly boosted and the jets from Zqq¯ decay start to overlap, causing the resolved channel to lose efficiency. The merged-jet channel recovers some of this loss by looking for a Zqq¯ decay that is reconstructed as a single jet.

Events are considered for the merged-jet channel if they have exactly one signal jet, or if the selected jet pair has an invariant mass outside the range 50150GeV (encompassing both the signal region and the control regions used for studying the background). Thus, the merged-jet channel is explicitly orthogonal to the resolved channel.

To be considered for the merged-jet channel, the dilepton pair must have pT>280GeV. The leading jet must also satisfy pT>200GeV and m/pT>0.05, where m is the jet mass, in order to restrict the jet to the kinematic range in which the mass calibration has been studied. Finally, the invariant mass of the leading jet must be within the range 70105GeV. The merged-jet channel is not split into subchannels based on the number of b-tagged jets; as the sample size is small, this would not improve the expected significance.

Including this channel increases the overall efficiency for the qq signal at mH=900GeV by about a factor of two. Figure 4a shows the distribution of the invariant mass of the leading jet after all selections except for that on the jet invariant mass; it can be seen that the simulated signal has a peak at the mass of the Z boson, with a tail at lower masses due to events where the decay products of the Z boson are not fully contained in the jet cone. The discriminating variable for this channel is the invariant mass of the two leptons plus the leading jet, mj, which has a resolution of 2.5 % for a signal with mH=900GeV and is shown in Fig. 4b.

Fig. 4.

Fig. 4

Distributions for the merged-jet channel of the HZZ+-qq¯ search after the mass calibration. a The invariant mass of the leading jet, mj, after the kinematic selection for the qq merged-jet channel. b The distribution used in the likelihood fit of the invariant mass of the two leptons and the leading jet mj in the signal region. It is obtained requiring 70<mj<105GeV. The dashed line shows the total background used as input to the fit. The simulated signal is normalized to a cross-section corresponding to five times the observed limit given in Sect. 11. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background. The signal contribution is shown added on top of the background in b but not in a

VBF channel

Events produced via the VBF process contain two forward jets in addition to the reconstructed leptons and signal jets from ZZ+-qq¯ decay. These forward jets are called ‘VBF jets’. The search in the VBF channel starts by identifying a candidate VBF-jet pair. Events must have at least four loose jets, two of them being non-b-tagged and pointing in opposite directions in z (that is, η1·η2<0). If more than one such pair is found, the one with the largest invariant mass, mjj,VBF, is selected. The pair must further satisfy mjj,VBF>500GeV and have a pseudorapidity gap of |Δηjj,VBF|>4. The distributions of these two variables are shown in Fig. 5.

Fig. 5.

Fig. 5

Distribution of a invariant mass and b pseudorapidity gap for the VBF-jet pair in the VBF channel of the HZZ+-qq¯ search before applying the requirements on these variables (and prior to the combined fit described in Sect. 10). The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Once a VBF-jet pair has been identified, the ZZ+-qq¯ decay is reconstructed in exactly the same way as in the resolved channel, except that the jets used for the VBF-jet pair are excluded and no b-tagging categories are created due to the small sample size. The final mjj discriminant is shown in Fig. 6. Again, the resolution is improved by constraining the dijet mass to mZ as described in Sect. 7.1.1, resulting in a similar overall resolution of 2–3 %.

Fig. 6.

Fig. 6

The distribution of mjj used in the likelihood fit for the HZZ+-qq¯ search in the VBF channel. The dashed line shows the total background used as input to the fit. The simulated signal is normalized to a cross-section corresponding to 30 times the observed limit given in Sect. 11. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom pane shows the ratio of the observed data to the predicted background

Background estimation

The main background in the qq search is Z+jets production, with significant contributions from both top-quark and diboson production in the resolved ggF channel, as well as a small contribution from multijet production in all channels. For the multijet background, the shape and normalization is taken purely from data, as described below. For the other background processes, the input is taken from simulation, with data-driven corrections for Z+jets and tt¯ production. The normalizations of the Z+jets and top-quark backgrounds are left free to float and are determined in the final likelihood fit as described below and in Sect. 10.

The Z+jets MC sample is constrained using control regions that have the same selection as the signal regions except that mjj (mj in the case of the merged-jet channel) lies in a region just outside of that selected by the signal Z boson requirement. For the resolved channels, the requirement for the control region is 50<mjj<70GeV or 105<mjj<150GeV; for the merged-jet channel, it is 30<mj<70GeV. In the resolved ggF channel, which is split into untagged and tagged subchannels as described in Sect. 7.1.1, the Z+jets control region is further subdivided into 0-tag, 1-tag, and 2-tag subchannels based on the number of b-tagged jets. The sum of the 0-tag and 1-tag subchannels is referred to as the untagged control region, while the 2-tag subchannel is referred to as the tagged control region.

The normalization of the Z+jets background is determined by the final profile-likelihood fit as described in Sect. 10. In the resolved ggF channel, the simulated Z+jets sample is split into several different components according to the true flavour of the jets as described in Sect. 3.3: Z+jj, Z+cj, Z+bj, and Z+hf. The individual normalizations for each of these four components are free to float in the fit and are constrained by providing as input to the fit the distribution of the “b-tagging category” in the untagged and tagged Z+jets control regions. The b-tagging category is defined by the combination of the MV1c b-tagging discriminants of the two signal jets as described in Appendix A. In the VBF and merged-jet ggF channels, which are not divided into b-tag subchannels, the background is dominated by Z+light-jets. Thus, only the inclusive Z+jets normalization is varied in the fit for these channels. Since these two channels probe very different regions of phase space, each has a separate normalization factor in the fit; these are constrained by providing to the fit the distributions of mjj or mj for the corresponding Z+jets control regions.

Differences are observed between data and MC simulation for the distributions of the azimuthal angle between the two signal jets, Δϕjj, and the transverse momentum of the leptonically-decaying Z boson, pT, for the resolved region, and for the mjj distribution in the VBF channel. To correct for these differences, corrections are applied to the Sherpa Z+jets simulation (prior to the likelihood fit) as described in Appendix B. The distributions of mjj or mj in the various Z+jets control regions are shown in Fig. 7; it can be seen that after the corrections (and after normalizing to the results of the likelihood fit), the simulation provides a good description of the data.

Fig. 7.

Fig. 7

The distributions of mjj or mj in the Z+jets control region of the HZZ+-qq¯ search in the a untagged ggF, b tagged ggF, c merged-jet ggF, and d VBF channels. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

The simulation models the mjj distribution well in the resolved ggF and VBF channels. An uncertainty is assigned by weighting each event of the Z+jets MC simulation by a linear function of mjj in order to cover the residual difference between data and MC events in the control regions.

Top-quark production is a significant background in the tagged subchannel of the resolved ggF channel. This background is predominantly (>97%) tt¯ production with only a small contribution from single-top processes, mainly Wt production. Corrections to the simulation to account for discrepancies in the pTtt¯ distributions are described in Appendix B. The description of the top-quark background is cross-checked and normalized using a control region with a selection identical to that of the tagged ggF channel except that instead of two same-flavour leptons, events must contain an electron and a muon with opposite charge. The mjj distribution in this control region is used as an input to the final profile-likelihood fit, in which the normalization of the top-quark background is left free to float (see Sect. 10). There are few events in the control region for the VBF and merged-jet ggF channels, so the normalization is assumed to be the same across all channels, in which the top-quark contribution to the background is very small. Figure 8 shows that the data in the control region are well-described by the simulation after the normalization.

Fig. 8.

Fig. 8

The distribution of mjj in the eμ top-quark control region of the HZZ+-qq¯ search in the tagged ggF channel. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom pane shows the ratio of the observed data to the predicted background

Further uncertainties in the top-quark background arising from the parton showering and hadronization models are estimated by varying the amount of parton showering in AcerMC and also by comparing with Powheg+Herwig. Uncertainties in the tt¯ production matrix element are estimated by comparing the leading-order MC generator Alpgen with the NLO generator aMC@NLO. Comparisons are also made with alternate PDF sets. A similar procedure is used for single-top production. In addition, for the dominant Wt single-top channel, uncertainties in the shapes of the mjj and leading-jet pT distributions are evaluated by comparing results from Herwig to those from AcerMC.

The small multijet background in the HZZeeqq decay mode is estimated from data by selecting a sample of events with the electron isolation requirement inverted, which is then normalized by fitting the mee distribution in each channel. In the HZZμμqq decay mode, the multijet background is found to be negligible. The residual multijet background in the top-quark control region is taken from the opposite-charge eμ data events, which also accounts for the small W+jets background in that region. An uncertainty of 50 % is assigned to these two normalizations, which are taken to be uncorrelated.

The diboson background, composed mainly of ZZ and WZjj production, and the SM Zhbb background are taken directly from Monte Carlo simulation, as described in Sect. 3.3. The uncertainty in the diboson background is estimated by varying the factorization and renormalization scales in an MCFM calculation [35]. The method described in Refs. [86, 87] is used to avoid underestimating the uncertainty due to cancellations. Differences due to the choice of alternate PDF sets and variations in the value of αS are included in the normalization uncertainty. Additional shape uncertainties in the mjj distribution are obtained by comparing results from Herwig, an LO simulation, with those from Powheg+Pythia, an NLO simulation.

The rate of the SM Vh(V=W/Z,hbb) process, relative to the SM expectation, has been measured by ATLAS as μ=σ/σSM=0.52±0.32(stat.)±0.24(syst.) [30]. Since this is compatible with the SM expectation, the small Zh(hbb) background in this channel is normalized to the SM cross-section and a 50 % uncertainty is assigned to cover the difference between the prediction and the measured mean value.

HZZνν¯qq¯ event selection and background estimation

Event selection

Events selected for this search must contain no electrons or muons as defined by the ‘loose’ lepton selection of the qq search. To select events with neutrinos in the final state, the magnitude of the missing transverse momentum vector must satisfy ETmiss>160GeV; the trigger is 100 % efficient in this range. Events must have at least two jets with pT>20GeV and |η|<2.5; the leading jet must further satisfy pT>45GeV. To select a candidate Zqq¯ decay, the invariant mass of the leading two jets must satisfy 70<mjj<105GeV.

The multijet background, due mainly to the mismeasurement of jet energies, is suppressed using a track-based missing transverse momentum, pTmiss, defined as the negative vectorial sum of the transverse momenta of all good-quality inner detector tracks. The requirements are pTmiss >30GeV, the azimuthal angle between the directions of ETmiss and pTmiss satisfy ΔϕETmiss,pTmiss)<π/2, and the azimuthal angle between the directions of ETmiss and the nearest jet satisfy Δϕ(ETmiss,j)>0.6.

As in the resolved ggF channel of the qq search, this search is divided into ‘tagged’ (exactly two b-tagged jets) and ‘untagged’ (fewer than two b-tagged jets) subchannels. Events with more than two b-tags are rejected.

The sensitivity of this search is improved by adding a requirement on the jet transverse momenta. As in the qq search, the optimal threshold depends on mH. However, due to the neutrinos in the final state, this decay mode does not provide a good event-by-event measurement of the mass of the diboson system, mZZ. So, rather than having a single requirement on the jet transverse energy which is a function of the measured mZZ, instead there is a set of requirements, based on the generated mH, with the background estimated separately for each of these separate jet requirements. The specific requirement is found by rounding the generated mH to the nearest 100GeV; this is called mHbin. Then the subleading jet must satisfy pTj2>0.1×mHbin in events with no b-tagged jets, and pTj2>0.1×mHbin-10GeV in events with at least one b-tagged jet.

The discriminating variable for this search is the transverse mass of the ννqq system, shown in Fig. 9, defined as in Eq. (1) with pTjj replacing pT. To improve the transverse mass resolution, the energies of the leading two jets are scaled event-by-event by a multiplicative factor to set the dijet invariant mass mjj to the Z boson mass, in the same manner as in the qq search. This improves the transverse mass resolution by approximately 20 % at mH=400 GeV and by approximately 10 % at mH=1 TeV. The resulting resolution in mT ranges from about 9 % at mH=400GeV to 14 % at mH=1TeV.

Fig. 9.

Fig. 9

The distributions of mT, the transverse mass of the Z(νν)Z(jj) system, used in the likelihood fit for the HZZνν¯qq¯ search in the a, c untagged and b, d tagged channels, for Higgs boson mass hypotheses of a, b mH=400GeV and c, d mH=900GeV. The dashed line shows the total background used as input to the fit. For the mH=400GeV hypothesis (a, b) the simulated signal is normalized to a cross-section corresponding to 20 times the observed limit given in Sect. 11, while for the mH=900GeV hypothesis (c, d) it is normalized to 30 times the observed limit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Background estimation

The dominant backgrounds for this search are Z+jets, W+jets, and tt¯ production. The normalization of the Z+jets background is determined using the Z+jets control region from the qq channel in the final profile-likelihood fit as described in Sect. 10. To check how well this background is modelled after the ννqq selection, an alternative Z+jets control region is defined in the same way as the signal sample for mHbin=400 GeV except that events must contain exactly two loose muons. The ETmiss is calculated without including the muons and must satisfy the same requirement as for the signal: ETmissnoμ>160GeV. The Z+jets MC simulation is corrected as a function of Δϕjj and pT in the same manner as in the resolved ggF channel of the qq search, as described in Sect. 7.2 and Appendix B.

The W+jets background estimate similarly uses a control sample with the same selection as the signal sample for mHbin=400 GeV except that there must be exactly one loose muon and the ETmiss requirement is again on ETmissnoμ. The simulated W+jets sample is also split into several different flavour components, as in the case of Z+jets. The normalization of the W+jj and W+cj components are free to float in the final profile-likelihood fit, and are constrained by providing as input to the fit the distribution of the MV1c b-tagging category, described in Appendix A, in the 0-b-tag and 1-b-tag control regions. Unlike the Z+jets case, the 2-b-tag control region is not used in the final profile-likelihood fit to constrain the W+bj and W+hf background components since it is highly dominated by tt¯ production. Their normalizations are instead taken from the NNLO cross section predictions with an uncertainty of 50 %. The uncertainty is determined by comparing the nominal fit value from the profile-likelihood fit with the value when including the 2-b-tag control region, where W+bj and W+hf are free to float; this uncertainty also covers the normalization determined in Ref. [30]. Following Ref. [30], the agreement between simulation and data for this background is improved by applying a correction to Δϕjj for W+jj and W+cj, with half the correction assigned as a systematic uncertainty; in the case of W+bj and W+hf, no correction is applied, but a dedicated systematic uncertainty is assigned.

Even after these corrections, the simulation does not accurately describe the data in the Z+jets and W+jets control sample with no b-tagged jets (which is dominated by Z/W+jj) for important kinematic distributions such as ETmiss and jet transverse momenta. Moreover, because the resolution of the transverse mass of the ZZνν¯qq¯ system is worse than that of mjj, the ννqq search is more sensitive to ETmiss (i.e. Z/W boson pT) than the qq search. Therefore, a further correction is applied, as a linear function of ETmiss, derived from measuring the ratio of the ETmiss distributions from simulation and data in the control sample with no b-tagged jets after non-Z/W+jj backgrounds have been subtracted. An uncertainty of 50 % is assigned to this correction. Following this correction, there is good agreement between simulation and data, as shown in Figs. 10 and 11. For higher mHbin signal samples, which have tighter selections on kinematic variables than the control sample, the ETmiss correction is somewhat underestimated, leading to some remaining difference between data and pre-fit simulation at high mT, as can be seen in Fig. 9c. However, the profile-likelihood-ratio fit (Sect. 10) is able to correct this residual mismodelling, leading to reasonable agreement between the data and simulation.

Fig. 10.

Fig. 10

The distributions of a missing transverse momentum ETmiss and b leading-jet pT from the untagged (Zμμ)+jets control sample of the HZZνν¯qq¯ search. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Fig. 11.

Fig. 11

The distributions of a ETmiss and b leading-jet pT from the untagged (Wμν)+jets control sample of the HZZνν¯qq¯ search. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

The tt¯ background is treated in the same manner as in the qq search; in particular, pTtt¯ is corrected in the same way and the normalization is determined by tt¯ control region from qq channel in the final profile-likelihood fit.

Backgrounds from diboson and single-top production are estimated directly from MC simulations, both for shapes and normalization. The multijet background is estimated using a method similar to that used for the Z+jets background in the νν search (Sect. 6.2), except that the variables used are Δϕ(ETmiss,pTmiss) and Δϕ(ETmiss,j) [30]. It is found to be negligible.

Systematic uncertainties

The systematic uncertainties can be divided into three categories: experimental uncertainties, related to the detector or to the reconstruction algorithms, uncertainties in the modelling of the signal, and uncertainties in the estimation of the backgrounds. The first two are largely common to all the searches and are treated as fully correlated. The uncertainties in the estimates of most backgrounds vary from search to search, and are summarized in the background estimation sections above. The estimation of the uncertainty of the ZZ() background is outlined in Sect. 9.3.

Experimental uncertainties

The following detector-related systematic uncertainties are common to all the searches unless otherwise stated.

The uncertainty in the integrated luminosity is determined to be 2.8 % in a calibration following the methodology detailed in Ref. [88] using beam-separation scans performed in November 2012. This uncertainty is applied to the normalization of the signal and also to backgrounds for which the normalization is derived from MC calculations, and is correlated between all of the searches. There is also an uncertainty of 4 % in the average number of interactions per bunch crossing, which leads to an uncertainty on distributions sensitive to pile-up.

There are small systematic uncertainties of O(1%) in the reconstruction and identification efficiencies for electrons and muons [7073]. For the ννqq search, the uncertainty is instead in the efficiency of the lepton veto, and is also O(1%). Uncertainties in the lepton energy scale and resolution are also taken into account. These uncertainties are treated as uncorrelated between all of the searches due to differences in lepton selections optimized for each search.

The uncertainty in the jet energy scale has several sources, including uncertainties in the in situ calibration analysis, corrections for pile-up, and the flavour composition of the sample [76, 89]. These uncertainties are decomposed into independent components. For central jets, the total relative uncertainty on the jet energy scale ranges from about 3 % for jets with a pT of 20GeV to about 1 % for a pT of 1TeV. The calibration of the b-jet transverse energy has an additional uncertainty of 1–2 %. There is also an uncertainty in the jet energy resolution [90], which ranges from 10–20 % for jets with a pT of 20GeV to less than 5 % for jets with pT>200GeV. The uncertainty associated with the pile-up rejection requirement (Sect. 4) is evaluated by varying the nominal value of 50 % between 47 and 53 % [78]. The jet energy scale uncertainties are correlated between the qq and ννqq searches, and separately between the and νν searches. They are not correlated between the two pairs of searches because although the qq and ννqq control regions have the power to constrain the jet energy scale uncertainties, these constraints do not necessarily apply to the and νν searches due to differences in the jet kinematics and composition.

Uncertainties on the lepton and jet energy scales are propagated into the uncertainty on ETmiss. A contribution to ETmiss also comes from energy deposits that are not associated with any identified physics object; uncertainties on the energy calibration (8 %) and resolution (3 %) of the sum of these deposits are also propagated to the uncertainty on ETmiss [91].

Uncertainties in the efficiency for tagging b-jets and in the rejection factor for light jets are determined from tt¯ and dijet control samples  [8183]. Additional uncertainties account for differences in b-tagging efficiency between simulated samples generated with sherpa and pythia and for differences observed between standard b-tagging and truth tagging (defined at the end of Sect. 4) for close-by jets [30].

The efficiencies for the lepton triggers in events with reconstructed leptons are nearly 100 %, and hence the related uncertainties are negligible. For the selection used in the ννqq search, the efficiency for the ETmiss trigger is also close to 100 % with negligible associated uncertainties.

The merged-jet channel of the qq search relies on measuring single-jet masses. To estimate the uncertainty in this measurement, jets reconstructed as described in Sect. 4 are compared with jets constructed using the same clustering algorithm but using as input charged-particle tracks rather than calorimeter energy deposits. The uncertainty is found using a procedure similar to that described in Ref. [92] by studying the double ratio of masses of jets found by both the calorimeter- and track-based algorithms: Rtrackcalom=rtrackcalom,data/rtrackcalom,MC, where rtrackcalom,X=mcaloX/mtrackX, X= data or MC simulation, and m is the jet mass. The uncertainty is taken as the deviation of this quantity from unity. Studies performed on dijet samples yield a constant value of 10% for this uncertainty. Applying the jet mass calibration derived from single jets in generic multijet samples to merged jets originating from boosted Z bosons results in a residual topology-dependent miscalibration. This effect can be bounded by an additional uncertainty of 10%. Adding these two effects in quadrature gives a total uncertainty on the jet mass scale of 14%. The uncertainty on the jet mass resolution has a negligible effect on the final result.

Signal acceptance uncertainty

The uncertainty in the experimental acceptance for the Higgs boson signal due to the modelling of Higgs boson production is estimated by varying parameters in the generator and re-applying the signal selection at generator level. The renormalization and factorization scales are varied up and down both independently and coherently by a factor of two; the amounts of initial- and final-state radiation (ISR/FSR) are increased and decreased separately; and the PDF set used is changed from the nominal CT10 to either MSTW2008 or NNPDF23.

ZZ() background uncertainties

Uncertainties on the ZZ() background are treated as correlated between the and νν searches.

Uncertainties in the PDF and in αS are taken from Ref. [93] and are derived separately for the qq¯ZZ() and ggZZ() backgrounds, using the envelope of the CT10, MSTW, and NNPDF error sets following the PDF4LHC prescription given in Refs. [94, 95], giving an uncertainty parameterized in mZZ. These uncertainties amount to 3 % for the qq¯ZZ() process and 8 % for the ggZZ() process and are found to be anti-correlated between the two processes; this is taken into account in the fit. The QCD scale uncertainty for the qq¯ZZ() process is also taken from Ref. [93] and is based on varying the factorization and renormalization scales up and down by a factor of two, giving an uncertainty parameterized in mZZ amounting to 4 % on average.

The deviation of the NLO electroweak K-factor from unity is varied up and down by 100 % in events with high QCD activity or with an off-shell Z boson, as described in Ref. [96]; this leads to an additional overall uncertainty of 1–3 % for the qq¯ZZ() process.

Full NLO and NNLO QCD calculations exist for the gghZZ() process, but not for the ggZZ() continuum process. However, Ref. [97] showed that higher-order corrections affect ggWW and gghWW similarly, within a 30 % uncertainty on the interference term. This yields about a 60 % uncertainty on the ggWW process. Furthermore, Ref. [97] states that this conclusion also applies to the ZZ() final state, so the gg-induced part of the off-shell light Higgs boson K-factor from Ref. [38] is applied to the ggZZ() background. The uncertainty on this K-factor depends on mZZ and is about 30 %. An additional uncertainty of 100 % is assigned to this procedure; this covers the 60 % mentioned above. This uncertainty corresponds to the range considered for the ggZZ() background K-factor in the ATLAS off-shell Higgs boson signal-strength measurement described in Ref. [96].

Acceptance uncertainties for the ggF and VBF (and VH for ) channels due to the uncertainty on the 1-jet and 2-jet cross-sections are estimated for the qq¯ZZ() background by comparing the acceptance upon varying the factorization and renormalization scales and changing the PDF set. For this leads to uncertainties of 4, 8, and 3 % on the ggF, VBF, and VH channels, respectively, where the uncertainty is fully anti-correlated between the ggF channel and the VBF and VH channels. For the ggZZ() process where only LO generators are available, the VBF jets are simulated only in the parton shower, and so the acceptance uncertainty is estimated by taking the difference between the acceptances predicted by MCFM+Pythia8 and Sherpa, which have different parton shower simulations; this amounts to 90 % for the VH channel.

Combination and statistical interpretation

The statistical treatment of the data is similar to that described in Refs. [98102], and uses a simultaneous profile-likelihood-ratio fit to the data from all of the searches. The parameter of interest is the cross-section times branching ratio for heavy Higgs boson production, assumed to be correlated between all of the searches. It is assumed that an additional Higgs boson 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. The VH production mechanism is included in the fit for the search and is assumed to scale with the VBF signal since both the VH and VBF production mechanisms depend on the coupling of the Higgs boson to vector bosons.

The simultaneous fit proceeds as follows. For each channel of each search, there is a distribution of the data with respect to some discriminating variable; these distributions are fitted to a sum of signal and backgrounds. The particular variables used are summarized in Table 3. The distributions for the search are unbinned, since the resolution of m is very good, while other searches have binned distributions. For the VBF channels of the νν search, only the overall event counts are used, rather than distributions, as the sample sizes are very small. The qq and ννqq searches include additional distributions in control regions in order to constrain the background, using either distributions of the mass variable or of the MV1c b-tagging category. The details of the specific variables used and the definitions of the signal and control regions are discussed in Sects. 5 to 8.

Table 3.

Summary of the distributions entering the likelihood fit for each channel of each search, both in the signal region (SR) and the various control regions (CR) used to constrain the background. Each entry represents one distribution; some channels have several distributions for different lepton flavours. MV1c cat. refers to the MV1c b-tagging event category. The distributions are unbinned for the search and binned elsewhere. The VBF channels of the νν search use only the overall event counts. See the text for the definitions of the specific variables used as well as for the definitions of the signal and control regions

Search Channel SR Z CR W CR Top CR
ggF meeee, mμμμμ, meeμμ, mμμee
VBF m
VH m
νν ggF mTee, mTμμ
VBF Nevtee, Nevtμμ
qq ggF Untagged mjj MV1c cat.
Tagged mjj MV1c cat. mjj
Merged-jet mj mj
VBF mjj mjj
ννqq ggF Untagged mT MV1c cat. (0 b-tags)
Tagged mT MV1c cat. (1 b-tag)

As discussed in Sect. 9, 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 mass hypothesis for the heavy Higgs boson strongly affects which sources of systematic uncertainty have the greatest effect on the result. At lower masses, the ZZ() background theory uncertainties, the Z+jets modelling uncertainties, and the uncertainties on the jet energy scale dominate. At higher masses, uncertainties in the νν non-ZZ background, the jet mass scale, and the Z+jets background in the merged-jet regime dominate. The contribution to the uncertainty on the best-fit signal cross-section from the dominant systematic uncertainties is shown in Table 4.

Table 4.

The effect of the leading systematic uncertainties on the best-fit signal cross-section uncertainty, expressed as a percentage of the total (systematic and statistical) uncertainty, for the ggF (left) and VBF (right) modes at mH=200, 400, and 900GeV. The uncertainties are listed in decreasing order of their effect on the total uncertainty; additional uncertainties with smaller effects are not shown

ggF mode VBF mode
Systematic source Effect [%] Systematic source Effect [%]
mH=200GeV
ggZZ K-factor uncertainty 26.5 ggZZ acceptance 13.4
Z+ hf Δϕ reweighting 5.3 Jet vertex fraction (qq/ννqq) 13.4
Luminosity 5.2 ggZZ K-factor uncertainty 12.9
Jet energy resolution (qq/ννqq) 3.9 Z+jets Δϕ reweighting 7.9
QCD scale ggZZ 3.7 Jet energy scale η modelling (qq/ννqq) 5.3
mH=400GeV
qqZZ PDF 20.8 Z+jets estimate (νν) 33.8
QCD scale qqZZ 13.2 Jet energy resolution (/νν) 6.5
Z+jets estimate (νν) 12.6 VBF Z+jets mjj 5.5
Signal acceptance ISR/FSR (/νν) 7.8 Jet flavour composition (/νν) 5.3
Z+bb¯, Z+cc¯, pT 5.6 Jet vertex fraction (qq/ννqq) 4.8
mH=900GeV
Jet mass scale (qq) 7 Z+jets estimate (νν) 19.2
Z+jj pTZ shape (ννqq) 5.6 Jet mass scale (qq) 8.7
qqZZ PDF 4.3 Z+jj pT shape 7.3
QCD scale qqZZ 3.5 Jet energy resolution (/νν) 4.4
Luminosity 2.6 Jet flavour composition (VV/Signal) 2.6

As no significant excess is observed, exclusion limits are calculated with a modified frequentist method [103], also known as CLs, using the q~μ test statistic in the asymptotic approximation [104, 105]. The observed limits can be compared with expectations by generating ‘Asimov’ data sets, which are representative event samples that provide both the median expectation for an experimental result and its expected statistical variation in the asymptotic approximation, as described in Refs. [104, 105]. When producing the Asimov data set for the expected limits, the background-only hypothesis is assumed and the cross-sections for both ggF and VBF production of the heavy Higgs boson are set to zero. The remaining nuisance parameters are set to the value that maximizes the likelihood function for the observed data (profiled). When using the asymptotic procedure to calculate limits it is necessary to generate an Asimov data set both for the background-only hypothesis and for the signal hypothesis. When setting the observed limits, the cross-section for the other production mode not under consideration is profiled to data before generating the background-only Asimov data set.

Results

Limits on the cross-section times branching ratio from the combination of all of the searches are shown in Fig. 12. Also shown are expected limits from the , νν and the combined qq +ννqq searches (the latter two searches are only shown in combination as they share control regions). At low mass the search has the best sensitivity while at high mass the sensitivity of the combined qq +ννqq search is greatest, with the sensitivity of the νν channel only slightly inferior. In the mass range considered for this search the 95 % confidence level (CL) upper limits on the cross-section times branching ratio for heavy Higgs boson production vary between 0.53 pb at mH=195 GeV and 0.008 pb at mH=950 GeV in the ggF channel and between 0.31 pb at mH=195 GeV and 0.009 pb at mH=950 GeV in the VBF channel. The excursions into the 2σ band around the expected limit originate from local deviations in the input distributions. For example, the excess occurring around 200GeV and the deficit occurring around 300GeV arise from the (see Fig. 1) search. Deficits at higher mass are driven by fluctuations in the qq search (see Figs. 3 and 6).

Fig. 12.

Fig. 12

95 % CL upper limits on σ×BR(HZZ) as a function of mH, resulting from the combination of all of the searches in the a ggF and b VBF channels. The solid black line and points indicate the observed limit. The dashed black line indicates the expected limit and the bands the 1-σ and 2-σ uncertainty ranges about the expected limit. The dashed coloured lines indicate the expected limits obtained from the individual searches; for the qq and ννqq searches, only the combination of the two is shown as they share control regions

Figure 13 shows exclusion limits in the cos(β-α) versus tanβ plane for Type-I and Type-II 2HDMs, for a heavy Higgs boson with mass mH=200 GeV. This mH value is chosen so the assumption of a narrow-width Higgs boson is valid over most of the parameter space, and the experimental sensitivity is at a maximum. As explained in Sect. 3.2, the range of cos(β-α) and tanβ explored is limited to the region where the assumption of a heavy narrow-width Higgs boson with negligible interference is valid. When calculating the limits at a given choice of cos(β-α) and tanβ, the relative rate of ggF and VBF production in the fit is set according to the prediction of the 2HDM for that parameter choice. Figure 14 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 not excluded by the present analysis; in these regions the cross-section predicted by the 2HDM is below the experimental sensitivity. Compared with recent studies of indirect limits [106], the exclusion presented here is considerably more stringent for Type-I with cos(β-α)<0 and 1<tanβ<2, and for Type-II with 0.5<tanβ<2.

Fig. 13.

Fig. 13

95 % CL exclusion contours in the 2HDM a Type-I and b Type-II models for mH=200GeV, shown as a function of the parameters cos(β-α) and tanβ. The red hashed area shows the observed exclusion, with the solid red line denoting the edge of the excluded region. The dashed blue line represents the expected exclusion contour and the shaded bands the 1-σ and 2-σ uncertainties on the expectation. The vertical axis range is set such that regions where the light Higgs couplings are enhanced by more than a factor of three from their SM values are avoided

Fig. 14.

Fig. 14

95 % CL exclusion contours in the 2HDM a Type-I and b Type-II models for cos(β-α)=-0.1, shown as a function of the heavy Higgs boson mass mH and the parameter tanβ. The shaded area shows the observed exclusion, with the black line denoting the edge of the excluded region. The blue line represents the expected exclusion contour and the shaded bands the 1-σ and 2-σ uncertainties on the expectation. The grey area masks regions where the width of the boson is greater than 0.5% of mH. For the choice of cos(β-α)=-0.1 the light Higgs couplings are not altered from their SM values by more than a factor of two

The previously published ATLAS results using data collected at s=7TeV [57] assumed a SM Higgs boson with the relative rate of ggF and VBF production fixed to the SM prediction. Thus, they are not directly comparable with the current results, which assume that the heavy Higgs boson has a narrow width but also allow the rates of ggF and VBF production to vary independently. These results are also not directly comparable with the recent results published by the CMS Collaboration [8] for similar reasons.

Summary

A search is presented for a high-mass Higgs boson in the HZZ+-+-, HZZ+-νν¯, HZZ+-qq¯, and HZZνν¯qq¯ decay modes using the ATLAS detector at the CERN Large Hadron Collider. The search uses proton–proton collision data at a centre-of-mass energy of 8TeV corresponding to an integrated luminosity of 20.3 fb-1. The results of the search are interpreted in the scenario of a heavy Higgs boson with a width that is small compared with the experimental mass resolution. The Higgs boson mass range considered extends up to 1TeV for all four decay modes and down to as low as 140GeV, depending on the decay mode. No significant excess of events over the Standard Model prediction is found. Limits on production and decay of a heavy Higgs boson to two Z bosons are set separately for gluon-fusion and vector-boson-fusion production modes. For the combination of all decay modes, 95 % CL upper limits range from 0.53 pb at mH=195 GeV to 0.008 pb at mH=950 GeV for the gluon-fusion production mode and from 0.31 pb at mH=195 GeV to 0.009 pb at mH=950 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 cos(β-α) versus  tanβ and mH versus  tanβ planes for mH=200GeV. This mH value is chosen so that the assumption of a narrow-width Higgs boson is valid over most of the parameter space, and so that the experimental sensitivity is at a maximum. Compared with recent studies of indirect limits, the two-Higgs-doublet model exclusion presented here is considerably more stringent for Type-I with cos(β-α)<0 and 1<tanβ<2, and for Type-II with 0.5<tanβ<2.

Acknowledgments

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET, ERC and NSRF, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT and NSRF, Greece; RGC, Hong Kong SAR, China; ISF, MINERVA, GIF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; BRF and RCN, Norway; MNiSW and NCN, Poland; GRICES and FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, UK; DOE and NSF, USA. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN and 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) and in the Tier-2 facilities worldwide.

Appendix A: Flavour tagging in the qq and ννqq searches

In order to constrain the normalizations of the various flavour components of the Z+jets (Z+jj, Z+cj, Z+bj, and Z+hf) and W+jets (W+jj and W+cj) backgrounds in the qq and ννqq searches, it is necessary to distinguish the different combinations of jet flavour. This is achieved by combining the information from the MV1c b-tagging discriminant of the two signal jets in order to disentangle the different light- and heavy-flavour components.

Besides the MV1c selection criterion described in Sect. 4, which had an average efficiency of 70 % for jets with pT>20GeV containing b-hadrons (b-jets), additional criteria, or operating points, are defined with average efficiencies of 80, 60, and 50 %. The efficiencies for accepting c-jets or light-quark jets for the 50 % (80 %) operating point are 1/29 (1/3) and 1/1400 (1/30), respectively. Based on these operating points, five bins in MV1c are defined:

Bin b-Tagging efficiency (%)
Very loose (VL) >80
Loose (L) 80-70
Medium (M) 70-60
Tight (T) 60-50
Very tight (VT) <50

In this analysis, jets selected by the M, T, or VT operating points (i.e. >70% efficiency for b-jets) are considered as b-tagged. Events are then categorized based on the combination of the binned MV1c operating points for the two signal jets, as shown in Fig. 15, in order to obtain optimal separation of the flavour components.

Fig. 15.

Fig. 15

Event categorization as a function of the output of the MV1c b-tagging algorithm for the two signal jets. The bin boundaries correspond to the operating points (MV1c(jet) OP) giving b-tagging efficiencies of 100, 80, 70, and 50 %; i.e., the b-jet purity increases from left (bottom) to right (top). The event categories are labelled VL, L, M, T, and VT according to the definitions in the text, and the different colours correspond to events with 0, 1, and 2 identified b-jets

Distributions of the resulting MV1c event categories are shown in Figs. 16 and 17 for the qq Z+jets and ννqq W+jets control regions, respectively. These distributions are provided as input to the simultaneous profile-likelihood-ratio fit described in Sect. 10 in order to determine the normalization of the background flavour components defined above. Following the fit, the data are well-described by the MC simulation.

Fig. 16.

Fig. 16

The distribution of the MV1c b-tagging event categories, based on the two signal jets, in the Z+jets control region in the a untagged ggF and b tagged ggF channels of the HZZ+-qq¯ search. The b-jet purity generally increases from left to right. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Fig. 17.

Fig. 17

The distribution of the MV1c b-tagging event categories, based on the two signal jets, in the W+jets a 0-b-tag and b 1-b-tag control regions of the HZZνν¯qq¯ search. The b-jet purity generally increases from left to right. The dashed line shows the total background used as input to the fit. The contribution labelled as ‘Top’ includes both the tt¯ and single-top processes. The bottom panes show the ratio of the observed data to the predicted background

Appendix B: Corrections to MC simulation for the qq search

In order to improve the description of the data in the resolved ggF channel, corrections are applied to the Sherpa Z+jets simulation (prior to the likelihood fit) as a function of the azimuthal angle between the two signal jets, Δϕjj, and the transverse momentum of the leptonic Z boson, pT, following Ref. [30]. The simulation does not model well the observed Δϕjj distribution in the untagged control regions for pT<120GeV; this is not seen at higher pT or in the tagged control region. In order to improve the modelling, the Z+jj component of the background with pT<120GeV is scaled by a linear function derived from the control region with no b-tagged jets at low pT with non-Z boson backgrounds subtracted. Half the value of the correction is taken as a systematic uncertainty where it is applied. In the Z+hf sample with pT<120GeV, the full value of the correction is taken as an uncertainty. For pT>120GeV, no correction is applied for any sample. In this region, a linear fit is performed to the data/MC ratio of Δϕjj in the untagged subchannel after subtracting the small non-Z background, and the uncertainty on the fitted slope taken as an uncertainty for all Z+jets samples. Following this correction, the description of the pT distribution in the control region with no b-tagged jets also improves, but there is still some residual discrepancy seen in the control regions that have b-tagged jets. Thus, the Z+hf background component is scaled by a function logarithmic in pT, determined from the combination of the control regions with one or more b-tagged jets (after subtracting the Z+jj and non-Z+jets background components). An uncertainty of half this correction is applied for all Z+jets channels. (All these uncertainties are taken to be uncorrelated between the Z+light-jet and Z+hf samples.) Following these corrections, the simulation models both the Δϕjj and pT distributions well in all Z+jets control regions.

For the VBF channel, no significant differences are seen in the Δϕjj and pT distributions, but there is a small difference in the mjj distribution in the control region. The simulated Z+jets background is corrected for this bin-by-bin and the full value of this correction is taken as an uncertainty, again uncorrelated between light- and heavy-flavour samples. No corrections are needed for the merged-jet ggF channel given the small sample size available.

It has been observed in an unfolded measurement of the pT distribution of tt¯ quark pairs that the simulation does not accurately describe the pTtt¯ distribution [107]. To correct for this, tt¯ MC events are weighed by a function of pTtt¯ taken from 7TeV data from Ref. [107] in order to make the simulation match the data. The correction is validated for 8TeV data using the eμ top-quark control region, and the uncertainty in this correction is estimated by varying it from 50 to 150 % of its nominal value.

Footnotes

1

ATLAS 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 coinciding with the axis of the beam pipe. The x-axis points from the IP towards 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). The distance in (η,ϕ) coordinates, ΔR=(Δϕ)2+(Δη)2, is also used to define cone sizes. Transverse momentum and energy are defined as pT=psinθ and ET=Esinθ, respectively.

2

The VBF channel is inclusive in quark flavour and hence dominated by the Z + light-quark jet background.

3

The background samples that use the parameterized fast simulation are: Sherpa W/Z+jets production with pTW/Z<280GeV (for higher pTW/Z the full simulation is used since it improves the description of the jet mass in the merged qq search described in Sect. 7.1.2); Powheg-Box tt¯, single top, and diboson production; and SM Pythia qq¯Zh and Powheg-Box ggZh production with hbb. The remaining background samples and the signal samples, with the exception of those used for the ννqq search, use the full Geant  4 simulation.

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