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. 2017 Dec 22;77(12):898. doi: 10.1140/epjc/s10052-017-5445-x

Search for direct top squark pair production in final states with two leptons in s=13 TeV pp collisions with the ATLAS detector

M Aaboud 180, G Aad 115, B Abbott 144, O Abdinov 14, B Abeloos 148, S H Abidi 209, O S AbouZeid 183, N L Abraham 199, H Abramowicz 203, H Abreu 202, R Abreu 147, Y Abulaiti 195,196, B S Acharya 217,218, S Adachi 205, L Adamczyk 61, J Adelman 139, M Adersberger 130, T Adye 170, A A Affolder 183, Y Afik 202, T Agatonovic-Jovin 16, C Agheorghiesei 39, J A Aguilar-Saavedra 159,164, S P Ahlen 30, F Ahmadov 94, G Aielli 173,174, S Akatsuka 97, H Akerstedt 195,196, T P A Åkesson 111, E Akilli 73, A V Akimov 126, G L Alberghi 27,28, J Albert 224, P Albicocco 71, M J AlconadaVerzini 100, S C Alderweireldt 137, M Aleksa 46, I N Aleksandrov 94, C Alexa 38, G Alexander 203, T Alexopoulos 12, M Alhroob 144, B Ali 167, M Aliev 102,103, G Alimonti 121, J Alison 47, S P Alkire 57, B M M Allbrooke 199, B W Allen 147, P P Allport 21, A Aloisio 134,135, A Alonso 58, F Alonso 100, C Alpigiani 184, A A Alshehri 79, M I Alstaty 115, B AlvarezGonzalez 46, D ÁlvarezPiqueras 222, M G Alviggi 134,135, B T Amadio 18, Y AmaralCoutinho 32, C Amelung 31, D Amidei 119, S P AmorDosSantos 159,161, S Amoroso 46, G Amundsen 31, C Anastopoulos 185, L S Ancu 73, N Andari 21, T Andeen 13, C F Anders 84, J K Anders 104, K J Anderson 47, A Andreazza 121,122, V Andrei 83, S Angelidakis 56, I Angelozzi 138, A Angerami 57, A V Anisenkov 140, N Anjos 15, A Annovi 156,157, C Antel 83, M Antonelli 71, A Antonov 128, D J Antrim 216, F Anulli 171, M Aoki 95, L AperioBella 46, G Arabidze 120, Y Arai 95, J P Araque 159, V AraujoFerraz 32, A T H Arce 69, R E Ardell 107, F A Arduh 100, J-F Arguin 125, S Argyropoulos 92, M Arik 22, A J Armbruster 46, L J Armitage 106, O Arnaez 209, H Arnold 72, M Arratia 44, O Arslan 29, A Artamonov 127, G Artoni 151, S Artz 113, S Asai 205, N Asbah 66, A Ashkenazi 203, L Asquith 199, K Assamagan 36, R Astalos 190, M Atkinson 221, N B Atlay 187, K Augsten 167, G Avolio 46, B Axen 18, M K Ayoub 148, G Azuelos 125, A E Baas 83, M J Baca 21, H Bachacou 182, K Bachas 102,103, M Backes 151, P Bagnaia 171,172, M Bahmani 63, H Bahrasemani 188, J T Baines 170, M Bajic 58, O K Baker 231, E M Baldin 140, P Balek 227, F Balli 182, W K Balunas 154, E Banas 63, A Bandyopadhyay 29, Sw Banerjee 228, A A E Bannoura 230, L Barak 203, E L Barberio 118, D Barberis 74,75, M Barbero 115, T Barillari 131, M-S Barisits 46, J T Barkeloo 147, T Barklow 189, N Barlow 44, S L Barnes 55, B M Barnett 170, R M Barnett 18, Z Barnovska-Blenessy 53, A Baroncelli 175, G Barone 31, A J Barr 151, L Barranco Navarro 222, F Barreiro 112, J Barreiro Guimarães da Costa 50, R Bartoldus 189, A E Barton 101, P Bartos 190, A Basalaev 155, A Bassalat 148, R L Bates 79, S J Batista 209, J R Batley 44, M Battaglia 183, M Bauce 171,172, F Bauer 182, H S Bawa 189, J B Beacham 142, M D Beattie 101, T Beau 110, P H Beauchemin 215, P Bechtle 29, H P Beck 20, H C Beck 80, K Becker 151, M Becker 113, C Becot 141, A J Beddall 20, A Beddall 23, V A Bednyakov 94, M Bedognetti 138, C P Bee 198, T A Beermann 46, M Begalli 32, M Begel 36, J K Behr 66, A S Bell 108, G Bella 203, L Bellagamba 27, A Bellerive 45, M Bellomo 202, K Belotskiy 128, O Beltramello 46, N L Belyaev 128, O Benary 203, D Benchekroun 177, M Bender 130, K Bendtz 195,196, N Benekos 12, Y Benhammou 203, E Benhar Noccioli 231, J Benitez 92, D P Benjamin 69, M Benoit 73, J R Bensinger 31, S Bentvelsen 138, L Beresford 151, M Beretta 71, D Berge 138, E Bergeaas Kuutmann 220, N Berger 7, J Beringer 18, S Berlendis 81, N R Bernard 116, G Bernardi 110, C Bernius 189, F U Bernlochner 29, T Berry 107, P Berta 113, C Bertella 50, G Bertoli 195,196, F Bertolucci 156,157, I A Bertram 101, C Bertsche 66, D Bertsche 144, G J Besjes 58, O Bessidskaia Bylund 195,196, M Bessner 66, N Besson 182, A Bethani 114, S Bethke 131, A J Bevan 106, J Beyer 131, R M Bianchi 158, O Biebel 130, D Biedermann 19, R Bielski 114, K Bierwagen 113, N V Biesuz 156,157, M Biglietti 175, T R V Billoud 125, H Bilokon 71, M Bindi 80, A Bingul 23, C Bini 171,172, S Biondi 27,28, T Bisanz 80, C Bittrich 68, D M Bjergaard 69, J E Black 189, K M Black 30, R E Blair 8, T Blazek 190, I Bloch 66, C Blocker 31, A Blue 79, W Blum 113, U Blumenschein 106, S Blunier 48, G J Bobbink 138, V S Bobrovnikov 140, S S Bocchetta 111, A Bocci 69, C Bock 130, M Boehler 72, D Boerner 230, D Bogavac 130, A G Bogdanchikov 140, C Bohm 195, V Boisvert 107, P Bokan 220, T Bold 61, A S Boldyrev 129, A E Bolz 84, M Bomben 110, M Bona 106, M Boonekamp 182, A Borisov 169, G Borissov 101, J Bortfeldt 46, D Bortoletto 151, V Bortolotto 86,87,88, D Boscherini 27, M Bosman 15, J D Bossio Sola 43, J Boudreau 158, J Bouffard 2, E V Bouhova-Thacker 101, D Boumediene 56, C Bourdarios 148, S K Boutle 79, A Boveia 142, J Boyd 46, I R Boyko 94, J Bracinik 21, A Brandt 10, G Brandt 80, O Brandt 83, U Bratzler 206, B Brau 116, J E Brau 147, W D Breaden Madden 79, K Brendlinger 66, A J Brennan 118, L Brenner 138, R Brenner 220, S Bressler 227, D L Briglin 21, T M Bristow 70, D Britton 79, D Britzger 66, F M Brochu 44, I Brock 29, R Brock 120, G Brooijmans 57, T Brooks 107, W K Brooks 49, J Brosamer 18, E Brost 139, J H Broughton 21, P A Bruckman de Renstrom 63, D Bruncko 191, A Bruni 27, G Bruni 27, L S Bruni 138, S Bruno 173,174, BH Brunt 44, M Bruschi 27, N Bruscino 29, P Bryant 47, L Bryngemark 66, T Buanes 17, Q Buat 188, P Buchholz 187, A G Buckley 79, I A Budagov 94, F Buehrer 72, M K Bugge 150, O Bulekov 128, D Bullock 10, T J Burch 139, S Burdin 104, C D Burgard 72, A M Burger 7, B Burghgrave 139, K Burka 63, S Burke 170, I Burmeister 67, J T P Burr 151, E Busato 56, D Büscher 72, V Büscher 113, P Bussey 79, J M Butler 30, C M Buttar 79, J M Butterworth 108, P Butti 46, W Buttinger 36, A Buzatu 201, A R Buzykaev 140, S Cabrera Urbán 222, D Caforio 167, V M Cairo 59,60, O Cakir 4, N Calace 73, P Calafiura 18, A Calandri 115, G Calderini 110, P Calfayan 90, G Callea 59,60, L P Caloba 32, S Calvente Lopez 112, D Calvet 56, S Calvet 56, T P Calvet 115, R Camacho Toro 47, S Camarda 46, P Camarri 173,174, D Cameron 150, R Caminal Armadans 221, C Camincher 81, S Campana 46, M Campanelli 108, A Camplani 121,122, A Campoverde 187, V Canale 134,135, M Cano Bret 55, J Cantero 145, T Cao 203, M D M Capeans Garrido 46, I Caprini 38, M Caprini 38, M Capua 59,60, R M Carbone 57, R Cardarelli 173, F Cardillo 72, I Carli 168, T Carli 46, G Carlino 134, B T Carlson 158, L Carminati 121,122, R M D Carney 195,196, S Caron 137, E Carquin 49, S Carrá 121,122, G D Carrillo-Montoya 46, D Casadei 21, M P Casado 15, M Casolino 15, D W Casper 216, R Castelijn 138, V Castillo Gimenez 222, N F Castro 159, A Catinaccio 46, J R Catmore 150, A Cattai 46, J Caudron 29, V Cavaliere 221, E Cavallaro 15, D Cavalli 121, M Cavalli-Sforza 15, V Cavasinni 156,157, E Celebi 25, F Ceradini 175,176, L Cerda Alberich 222, A S Cerqueira 33, A Cerri 199, L Cerrito 173,174, F Cerutti 18, A Cervelli 20, S A Cetin 25, A Chafaq 177, D Chakraborty 139, S K Chan 82, W S Chan 138, Y L Chan 86, P Chang 221, J D Chapman 44, D G Charlton 21, C C Chau 45, C A Chavez Barajas 199, S Che 142, S Cheatham 217,219, A Chegwidden 120, S Chekanov 8, S V Chekulaev 212, G A Chelkov 94, M A Chelstowska 46, C Chen 93, H Chen 36, J Chen 53, S Chen 51, S Chen 205, X Chen 52, Y Chen 96, H C Cheng 119, H J Cheng 50, A Cheplakov 94, E Cheremushkina 169, R Cherkaoui El Moursli 181, E Cheu 9, K Cheung 89, L Chevalier 182, V Chiarella 71, G Chiarelli 156,157, G Chiodini 102, A S Chisholm 46, A Chitan 38, Y H Chiu 224, M V Chizhov 94, K Choi 90, A R Chomont 56, S Chouridou 204, Y S Chow 86, V Christodoulou 108, M C Chu 86, J Chudoba 166, A J Chuinard 117, J J Chwastowski 63, L Chytka 146, A K Ciftci 4, D Cinca 67, V Cindro 105, I A Cioara 29, C Ciocca 27,28, A Ciocio 18, F Cirotto 134,135, Z H Citron 227, M Citterio 121, M Ciubancan 38, A Clark 73, B L Clark 82, M R Clark 57, P J Clark 70, R N Clarke 18, C Clement 195,196, Y Coadou 115, M Cobal 217,219, A Coccaro 73, J Cochran 93, L Colasurdo 137, B Cole 57, A P Colijn 138, J Collot 81, T Colombo 216, P Conde Muiño 159,160, E Coniavitis 72, S H Connell 193, I A Connelly 114, S Constantinescu 38, G Conti 46, F Conventi 134, M Cooke 18, A M Cooper-Sarkar 151, F Cormier 223, K J R Cormier 209, M Corradi 171,172, F Corriveau 117, A Cortes-Gonzalez 46, G Cortiana 131, G Costa 121, M J Costa 222, D Costanzo 185, G Cottin 44, G Cowan 107, B E Cox 114, K Cranmer 141, S J Crawley 79, R A Creager 154, G Cree 45, S Crépé-Renaudin 81, F Crescioli 110, W A Cribbs 195,196, M Cristinziani 29, V Croft 141, G Crosetti 59,60, A Cueto 112, T Cuhadar Donszelmann 185, A R Cukierman 189, J Cummings 231, M Curatolo 71, J Cúth 113, S Czekierda 63, P Czodrowski 46, G D’amen 27,28, S D’Auria 79, L D’eramo 110, M D’Onofrio 104, M J Da Cunha Sargedas De Sousa 159,160, C Da Via 114, W Dabrowski 61, T Dado 190, T Dai 119, O Dale 17, F Dallaire 125, C Dallapiccola 116, M Dam 58, J R Dandoy 154, M F Daneri 43, N P Dang 228, A C Daniells 21, N S Dann 114, M Danninger 223, M Dano Hoffmann 182, V Dao 198, G Darbo 74, S Darmora 10, J Dassoulas 3, A Dattagupta 147, T Daubney 66, W Davey 29, C David 66, T Davidek 168, D R Davis 69, P Davison 108, E Dawe 118, I Dawson 185, K De 10, R de Asmundis 134, A De Benedetti 144, S De Castro 27,28, S De Cecco 110, N De Groot 137, P de Jong 138, H De la Torre 120, F De Lorenzi 93, A De Maria 80, D De Pedis 171, A De Salvo 171, U De Sanctis 173,174, A De Santo 199, K De Vasconcelos Corga 115, J B De Vivie De Regie 148, R Debbe 36, C Debenedetti 183, D V Dedovich 94, N Dehghanian 3, I Deigaard 138, M Del Gaudio 59,60, J Del Peso 112, D Delgove 148, F Deliot 182, C M Delitzsch 9, A Dell’Acqua 46, L Dell’Asta 30, M Dell’Orso 156,157, M Della Pietra 134,135, D della Volpe 73, M Delmastro 7, C Delporte 148, P A Delsart 81, D A DeMarco 209, S Demers 231, M Demichev 94, A Demilly 110, S P Denisov 169, D Denysiuk 182, D Derendarz 63, J E Derkaoui 180, F Derue 110, P Dervan 104, K Desch 29, C Deterre 66, K Dette 209, M R Devesa 43, P O Deviveiros 46, A Dewhurst 170, S Dhaliwal 31, F A Di Bello 73, A Di Ciaccio 173,174, L Di Ciaccio 7, W K Di Clemente 154, C Di Donato 134,135, A Di Girolamo 46, B Di Girolamo 46, B Di Micco 175,176, R Di Nardo 46, K F Di Petrillo 82, A Di Simone 72, R Di Sipio 209, D Di Valentino 45, C Diaconu 115, M Diamond 209, F A Dias 58, M A Diaz 48, E B Diehl 119, J Dietrich 19, S Díez Cornell 66, A Dimitrievska 16, J Dingfelder 29, P Dita 38, S Dita 38, F Dittus 46, F Djama 115, T Djobava 77, J I Djuvsland 83, M A B do Vale 34, D Dobos 46, M Dobre 38, C Doglioni 111, J Dolejsi 168, Z Dolezal 168, M Donadelli 35, S Donati 156,157, P Dondero 152,153, J Donini 56, J Dopke 170, A Doria 134, M T Dova 100, A T Doyle 79, E Drechsler 80, M Dris 12, Y Du 54, J Duarte-Campderros 203, A Dubreuil 73, E Duchovni 227, G Duckeck 130, A Ducourthial 110, O A Ducu 125, D Duda 138, A Dudarev 46, A Chr Dudder 113, E M Duffield 18, L Duflot 148, M Dührssen 46, C Dulsen 230, M Dumancic 227, A E Dumitriu 38, A K Duncan 79, M Dunford 83, H Duran Yildiz 4, M Düren 78, A Durglishvili 77, D Duschinger 68, B Dutta 66, D Duvnjak 1, M Dyndal 66, B S Dziedzic 63, C Eckardt 66, K M Ecker 131, R C Edgar 119, T Eifert 46, G Eigen 17, K Einsweiler 18, T Ekelof 220, M El Kacimi 179, R El Kosseifi 115, V Ellajosyula 115, M Ellert 220, S Elles 7, F Ellinghaus 230, A A Elliot 224, N Ellis 46, J Elmsheuser 36, M Elsing 46, D Emeliyanov 170, Y Enari 205, O C Endner 113, J S Ennis 225, J Erdmann 67, A Ereditato 20, M Ernst 36, S Errede 221, M Escalier 148, C Escobar 222, B Esposito 71, O Estrada Pastor 222, A I Etienvre 182, E Etzion 203, H Evans 90, A Ezhilov 155, M Ezzi 181, F Fabbri 27,28, L Fabbri 27,28, G Facini 108, R M Fakhrutdinov 169, S Falciano 171, R J Falla 108, J Faltova 46, Y Fang 50, M Fanti 121,122, A Farbin 10, A Farilla 175, C Farina 158, E M Farina 152,153, T Farooque 120, S Farrell 18, S M Farrington 225, P Farthouat 46, F Fassi 181, P Fassnacht 46, D Fassouliotis 11, M Faucci Giannelli 70, A Favareto 74,75, W J Fawcett 151, L Fayard 148, O L Fedin 155, W Fedorko 223, S Feigl 150, L Feligioni 115, C Feng 54, E J Feng 46, H Feng 119, M J Fenton 79, A B Fenyuk 169, L Feremenga 10, P Fernandez Martinez 222, S Fernandez Perez 15, J Ferrando 66, A Ferrari 220, P Ferrari 138, R Ferrari 152, D E Ferreirade Lima 84, A Ferrer 222, D Ferrere 73, C Ferretti 119, F Fiedler 113, A Filipčič 105, M Filipuzzi 66, F Filthaut 137, M Fincke-Keeler 224, K D Finelli 200, M C N Fiolhais 159,161, L Fiorini 222, A Fischer 2, C Fischer 15, J Fischer 230, W C Fisher 120, N Flaschel 66, I Fleck 187, P Fleischmann 119, R R M Fletcher 154, T Flick 230, B M Flierl 130, L R Flores Castillo 86, M J Flowerdew 131, G T Forcolin 114, A Formica 182, F A Förster 15, A Forti 114, A G Foster 21, D Fournier 148, H Fox 101, S Fracchia 185, P Francavilla 110, M Franchini 27,28, S Franchino 83, D Francis 46, L Franconi 150, M Franklin 82, M Frate 216, M Fraternali 152,153, D Freeborn 108, S M Fressard-Batraneanu 46, B Freund 125, D Froidevaux 46, J A Frost 151, C Fukunaga 206, T Fusayasu 132, J Fuster 222, C Gabaldon 81, O Gabizon 202, A Gabrielli 27,28, A Gabrielli 18, G P Gach 61, S Gadatsch 46, S Gadomski 107, G Gagliardi 74,75, L G Gagnon 125, C Galea 137, B Galhardo 159,161, E J Gallas 151, B J Gallop 170, P Gallus 167, G Galster 58, K K Gan 142, S Ganguly 56, Y Gao 104, Y S Gao 189, F M Garay Walls 48, C García 222, J E García Navarro 222, J A García Pascual 50, M Garcia-Sciveres 18, R W Gardner 47, N Garelli 189, V Garonne 150, A Gascon Bravo 66, K Gasnikova 66, C Gatti 71, A Gaudiello 74,75, G Gaudio 152, I L Gavrilenko 126, C Gay 223, G Gaycken 29, E N Gazis 12, C N P Gee 170, J Geisen 80, M Geisen 113, M P Geisler 83, K Gellerstedt 195,196, C Gemme 74, M H Genest 81, C Geng 119, S Gentile 171,172, C Gentsos 204, S George 107, D Gerbaudo 15, A Gershon 203, G Geßner 67, S Ghasemi 187, M Ghneimat 29, B Giacobbe 27, S Giagu 171,172, N Giangiacomi 27,28, P Giannetti 156,157, S M Gibson 107, M Gignac 223, M Gilchriese 18, D Gillberg 45, G Gilles 230, D M Gingrich 3, M P Giordani 217,219, F M Giorgi 27, P F Giraud 182, P Giromini 82, G Giugliarelli 217,219, D Giugni 121, F Giuli 151, C Giuliani 131, M Giulini 84, B K Gjelsten 150, S Gkaitatzis 204, I Gkialas 11, E L Gkougkousis 15, P Gkountoumis 12, L K Gladilin 129, C Glasman 112, J Glatzer 15, P C F Glaysher 66, A Glazov 66, M Goblirsch-Kolb 31, J Godlewski 63, S Goldfarb 118, T Golling 73, D Golubkov 169, A Gomes 159,160,162, R Gonçalo 159, R GoncalvesGama 32, J Goncalves Pinto Firmino Da Costa 182, G Gonella 72, L Gonella 21, A Gongadze 94, S González de la Hoz 222, S Gonzalez-Sevilla 73, L Goossens 46, P A Gorbounov 127, H A Gordon 36, I Gorelov 136, B Gorini 46, E Gorini 102,103, A Gorišek 105, A T Goshaw 69, C Gössling 67, M I Gostkin 94, C A Gottardo 29, C R Goudet 148, D Goujdami 179, A G Goussiou 184, N Govender 193, E Gozani 202, L Graber 80, I Grabowska-Bold 61, P O J Gradin 220, J Gramling 216, E Gramstad 150, S Grancagnolo 19, V Gratchev 155, P M Gravila 42, C Gray 79, H M Gray 18, Z D Greenwood 109, C Grefe 29, K Gregersen 108, I M Gregor 66, P Grenier 189, K Grevtsov 7, J Griffiths 10, A A Grillo 183, K Grimm 101, S Grinstein 15, Ph Gris 56, J-F Grivaz 148, S Groh 113, E Gross 227, J Grosse-Knetter 80, G C Grossi 109, Z J Grout 108, A Grummer 136, L Guan 119, W Guan 228, J Guenther 91, F Guescini 212, D Guest 216, O Gueta 203, B Gui 142, E Guido 74,75, T Guillemin 7, S Guindon 46, U Gul 79, C Gumpert 46, J Guo 55, W Guo 119, Y Guo 53, R Gupta 64, S Gupta 151, G Gustavino 144, B J Gutelman 202, P Gutierrez 144, N G Gutierrez Ortiz 108, C Gutschow 108, C Guyot 182, M P Guzik 61, C Gwenlan 151, C B Gwilliam 104, A Haas 141, C Haber 18, H K Hadavand 10, N Haddad 181, A Hadef 115, S Hageböck 29, M Hagihara 214, H Hakobyan 232, M Haleem 66, J Haley 145, G Halladjian 120, G D Hallewell 115, K Hamacher 230, P Hamal 146, K Hamano 224, A Hamilton 192, G N Hamity 185, P G Hamnett 66, L Han 53, S Han 50, K Hanagaki 95, K Hanawa 205, M Hance 183, B Haney 154, P Hanke 83, J B Hansen 58, J D Hansen 58, M C Hansen 29, P H Hansen 58, K Hara 214, A S Hard 228, T Harenberg 230, F Hariri 148, S Harkusha 123, P F Harrison 225, N M Hartmann 130, Y Hasegawa 186, A Hasib 70, S Hassani 182, S Haug 20, R Hauser 120, L Hauswald 68, L B Havener 57, M Havranek 167, C M Hawkes 21, R J Hawkings 46, D Hayakawa 207, D Hayden 120, C P Hays 151, J M Hays 106, H S Hayward 104, S J Haywood 170, S J Head 21, T Heck 113, V Hedberg 111, L Heelan 10, S Heer 29, K K Heidegger 72, S Heim 66, T Heim 18, B Heinemann 66, J J Heinrich 130, L Heinrich 141, C Heinz 78, J Hejbal 166, L Helary 46, A Held 223, S Hellman 195,196, C Helsens 46, R C W Henderson 101, Y Heng 228, S Henkelmann 223, A M Henriques Correia 46, S Henrot-Versille 148, G H Herbert 19, H Herde 31, V Herget 229, Y Hernández Jiménez 194, H Herr 113, G Herten 72, R Hertenberger 130, L Hervas 46, T C Herwig 154, G G Hesketh 108, N P Hessey 212, J W Hetherly 64, S Higashino 95, E Higón-Rodriguez 222, K Hildebrand 47, E Hill 224, J C Hill 44, K H Hiller 66, S J Hillier 21, M Hils 68, I Hinchliffe 18, M Hirose 72, D Hirschbuehl 230, B Hiti 105, O Hladik 166, X Hoad 70, J Hobbs 198, N Hod 212, M C Hodgkinson 185, P Hodgson 185, A Hoecker 46, M R Hoeferkamp 136, F Hoenig 130, D Hohn 29, T R Holmes 47, M Homann 67, S Honda 214, T Honda 95, T M Hong 158, B H Hooberman 221, W H Hopkins 147, Y Horii 133, A J Horton 188, J-Y Hostachy 81, A Hostiuc 184, S Hou 201, A Hoummada 177, J Howarth 114, J Hoya 100, M Hrabovsky 146, J Hrdinka 46, I Hristova 19, J Hrivnac 148, T Hryn’ova 7, A Hrynevich 124, P J Hsu 89, S-C Hsu 184, Q Hu 53, S Hu 55, Y Huang 50, Z Hubacek 167, F Hubaut 115, F Huegging 29, T B Huffman 151, E W Hughes 57, G Hughes 101, M Huhtinen 46, P Huo 198, N Huseynov 94, J Huston 120, J Huth 82, G Iacobucci 73, G Iakovidis 36, I Ibragimov 187, L Iconomidou-Fayard 148, Z Idrissi 181, P Iengo 46, O Igonkina 138, T Iizawa 226, Y Ikegami 95, M Ikeno 95, Y Ilchenko 13, D Iliadis 204, N Ilic 189, G Introzzi 152,153, P Ioannou 11, M Iodice 175, K Iordanidou 57, V Ippolito 82, M F Isacson 220, N Ishijima 149, M Ishino 205, M Ishitsuka 207, C Issever 151, S Istin 22, F Ito 214, J M Iturbe Ponce 86, R Iuppa 210,211, H Iwasaki 95, J M Izen 65, V Izzo 134, S Jabbar 3, P Jackson 1, R M Jacobs 29, V Jain 2, K B Jakobi 113, K Jakobs 72, S Jakobsen 91, T Jakoubek 166, D O Jamin 145, D K Jana 109, R Jansky 73, J Janssen 29, M Janus 80, P A Janus 61, G Jarlskog 111, N Javadov 94, T Javůrek 72, M Javurkova 72, F Jeanneau 182, L Jeanty 18, J Jejelava 76, A Jelinskas 225, P Jenni 72, C Jeske 225, S Jézéquel 7, H Ji 228, J Jia 198, H Jiang 93, Y Jiang 53, Z Jiang 189, S Jiggins 108, J Jimenez Pena 222, S Jin 50, A Jinaru 38, O Jinnouchi 207, H Jivan 194, P Johansson 185, K A Johns 9, C A Johnson 90, W J Johnson 184, K Jon-And 195,196, R W L Jones 101, S D Jones 199, S Jones 9, T J Jones 104, J Jongmanns 83, 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PMCID: PMC6954046  PMID: 31985737

Abstract

The results of a search for direct pair production of top squarks in events with two opposite-charge leptons (electrons or muons) are reported, using 36.1fb-1 of integrated luminosity from proton–proton collisions at s=13 TeV collected by the ATLAS detector at the Large Hadron Collider. To cover a range of mass differences between the top squark t~ and lighter supersymmetric particles, four possible decay modes of the top squark are targeted with dedicated selections: the decay t~bχ~1± into a b-quark and the lightest chargino with χ~1±Wχ~10, the decay t~tχ~10 into an on-shell top quark and the lightest neutralino, the three-body decay t~bWχ~10 and the four-body decay t~bνχ~10. No significant excess of events is observed above the Standard Model background for any selection, and limits on top squarks are set as a function of the t~ and χ~10 masses. The results exclude at 95% confidence level t~ masses up to about 720 GeV, extending the exclusion region of supersymmetric parameter space covered by previous searches.

Introduction

The standard model (SM) of particle physics is extremely successful in describing the phenomena of elementary particles and their interactions. Nevertheless, it is believed to be only a low-energy realisation of a more general theory. In its current form, it fails to explain several observations, such as the nature of dark matter, the baryon asymmetry of the universe and the stabilisation of the Higgs boson mass against radiative corrections from the Planck scale. These shortcomings could be remedied by the existence of new particles at the TeV scale, which motivates extensive searches at the Large Hadron Collider (LHC).

One of the most compelling theories beyond the SM is Supersymmetry (SUSY) [16]. SUSY is a space-time symmetry that for each SM particle postulates the existence of a partner particle whose spin (S) differs by one-half unit. The introduction of gauge-invariant and renormalisable interactions into SUSY models can violate the conservation of baryon number (B) and lepton number (L), resulting in a proton lifetime shorter than current experimental limits [7]. This is usually solved by assuming that the multiplicative quantum number R-parity [8], defined as R=(-1)3(B-L)+2S, is conserved.

In the framework of a generic R-parity-conserving model, SUSY particles are produced in pairs, and the lightest supersymmetric particle (LSP) is stable and a candidate for dark matter [9, 10]. The scalar partners of right-handed and left-handed quarks (squarks), q~R and q~L, can mix to form two mass eigenstates, q~1 and q~2, with q~1 defined to be the lighter one. In the case of the supersymmetric partner of the top quark, t~, large mixing effects can lead to one top squark mass eigenstate, t~1, that is significantly lighter than the other squarks. The charginos and neutralinos are mixtures of the bino, winos and Higgsinos that are superpartners of the U(1) and SU(2) gauge bosons and the Higgs bosons, respectively. Their mass eigenstates are referred to as χ~i± (i=1,2) and χ~j0 (j=1,2,3,4) in order of increasing masses. In a large variety of models, the LSP is the lightest neutralino χ~10.

In this paper a search for direct pair production of the top squark is reported, in final states with two isolated leptons (electrons or muons) and missing transverse momentum. The search utilises 36.1fb-1 of proton–proton collision data collected by the ATLAS experiment in 2015 and 2016 at a centre-of-mass energy s=13 TeV.

The top squark is assumed to decay into either the lightest chargino or the lightest neutralino. Depending on the mass difference between the top squark and the lighter SUSY particles, different decay modes are relevant. The decays t~tχ~10 and t~bχ~1± (where t and b represent either the quark or the anti-quark, depending on the charge conjugation) with χ~1±Wχ~10 dominate when they are kinematically accessible. For intermediate mass differences, mχ~10+mW+mb<mt~<mχ~10+mt, the three-body decay t~bWχ~10 is considered. For smaller mass differences, the four-body decay channel t~bffχ~10, where f and f are two fermions from the W decay, is assumed to occur. In this search, f and f are a lepton and its associated neutrino. For each of these decay modes, shown by the diagrams in Fig. 1, a dedicated event selection is performed to optimise the search significance, as detailed in Table 1.

Fig. 1.

Fig. 1

Diagrams representing the four main signals targeted by the analyses: a the decay of the top squark via the lightest chargino (t~bχ~1±), b the two-body decay into an on-shell top quark and the lightest neutralino (t~tχ~10), c the three-body decay mode into an on-shell W boson, a b-quark and the lightest neutralino (t~bWχ~10) and d the four-body decay mode (t~bffχ~10) where the two fermions f and f are a lepton with its neutrino in this article

Table 1.

Summary of the sections dedicated to the two-body, three-body and four-body selections and signal types targeted by each selection

Two-body Three-body Four-body
Variables Section 4.1
Event selection Section 4.2 Section 4.3 Section 4.4
Background determination Section 6.1 Section 6.2 Section 6.3
Results Section 8.1 Section 8.2 Section 8.3
Interpretation Section 8.4
Targeted decay modes bχ~1± and tχ~10 bWχ~10 bνχ~10
Signal diagram Figure 1a, b Figure 1c Figure 1d
Targeted mt~ range >mb+mχ~1± mb+mW+mχ~10 <mb+mW+mχ~10
or >mt+mχ~10 and <mt+mχ~10

The results of the searches are interpreted in simplified models [1113] as a function of the top squark and lightest neutralino masses. Additionally, results are also interpreted in one phenomenological minimal supersymmetric standard model (pMSSM) [1417] model including the following decay modes: t~tχ~10, t~bχ~1± with χ~1±Wχ~10 and t~tχ~20, with χ~20h/Zχ~10. Previous ATLAS [18, 19] and CMS [202632] analyses have set exclusion limits at 95% confidence level (CL) on the signal scenarios considered here. When considering simplified models including the t~tχ~10 decay, top squark masses up to about 700 GeV have been excluded for a nearly massless lightest neutralino. For the same assumptions about the lightest neutralino mass, if the t~bχ~1± decay is dominant, top squark masses up to about 500 GeV have been excluded.

ATLAS detector

The ATLAS detector [33] at the LHC is a multi-purpose particle detector with a cylindrical forward–backward symmetric geometry1 and an approximate 4π coverage in solid angle. It consists of an inner tracking detector (ID) surrounded by a thin superconducting solenoid providing a 2 T axial magnetic field, electromagnetic and hadron calorimeters, and a muon spectrometer. The inner tracking detector covers the pseudorapidity range |η|<2.5. It consists of silicon pixel, silicon microstrip, and transition radiation tracking detectors. The newly installed innermost layer of pixel sensors [34] was operational for the first time during the 2015 data-taking. Lead/liquid-argon (LAr) sampling calorimeters provide electromagnetic (EM) energy measurements with high granularity. A hadron (steel/scintillator-tile) calorimeter covers the central pseudorapidity range (|η|<1.7). The end-cap and forward regions are instrumented with LAr calorimeters for both the EM and hadronic energy measurements up to |η|=4.9. The muon spectrometer surrounds the calorimeters and features three large air-core toroid superconducting magnets with eight coils each. It includes a system of precision tracking chambers and fast detectors for triggering. The field integral of the toroids ranges between 2.0 and 6.0 Tm across most of the detector.

Data samples and event reconstruction

The data were collected by the ATLAS detector in 2015 and 2016 during pp collisions at a centre-of-mass energy of s=13 TeV, with a peak instantaneous luminosity of L=1.4×1034cm-2s-1, a bunch spacing of 25 ns, and an average number of pp interactions per bunch crossing (pile-up) of μ=14 in 2015 and μ=24 in 2016. Only events taken in stable beam conditions, and for which all relevant detector systems were operational, are considered in this analysis. The integrated luminosity of the resulting data set is 36.1fb-1, with an uncertainty of ±3.2%. This uncertainty is derived, following a methodology similar to that detailed in Ref. [35], from a preliminary calibration of the luminosity scale using xy beam-separation scans performed in August 2015 and May 2016.

Candidate events are required to have a reconstructed vertex with at least two associated tracks with transverse momentum pT>400MeV. The vertex with the highest scalar sum of the squared transverse momenta of the associated tracks is considered the primary vertex of the event.

Electron (baseline) candidates are reconstructed from three-dimensional electromagnetic calorimeter energy depositions matched to ID tracks, and are required to have pseudorapidity |η|<2.47, pT>7GeV, and to pass a loose likelihood-based identification requirement [36]. The likelihood input variables include measurements of calorimeter shower shapes and of track properties from the ID.

Muon (baseline) candidates are reconstructed in the pseudorapidity region |η|<2.4 from muon spectrometer tracks matching ID tracks. They must have pT>7GeV and must pass the medium identification requirements defined in Ref. [37], which are based on requirements on the number of hits in the different ID and muon spectrometer subsystems, and on the significance of the charge-to-momentum ratio (q / p) measurement  [37].

Jets are reconstructed from three-dimensional energy clusters in the calorimeter [38] with the anti-kt jet clustering algorithm [39, 40] with a radius parameter R=0.4. Only jet candidates with pT>20GeV and |η|<2.8 are considered. Jets are calibrated as described in Refs. [41, 42], and the expected average energy contribution from pile-up clusters is subtracted according to the jet area [43]. Additional selections are applied to jets with pT<60GeV and |η|<2.4 in order to reject jets produced in pile-up collisions [44]. The “medium” working point is used for the pile-up rejection, which has an efficiency of about 92% for jets produced by the hard scatter. Jets resulting from the hadronisation of b-quarks are identified using a multivariate b-tagging algorithm (MV2c10), which is based on quantities such as impact parameters of associated tracks and reconstructed secondary vertices [45, 46]. This algorithm is used at a working point that provides 77% b-tagging efficiency in simulated tt¯ events, and a rejection factor of 134 for light-quark flavours and gluons and 6 for charm jets. The jets satisfying the b-tagging requirements are referred to as b-jets.

Events are discarded if they contain any jet with pT>20GeV failing to satisfy basic quality selection criteria that reject detector noise and non-collision backgrounds [47].

To resolve reconstruction ambiguities, an overlap removal algorithm is applied to candidate leptons and jets. Non-b-tagged jets which lie within ΔR=(Δy)2+(Δϕ)2<0.2 (here y stands for the rapidity) from an electron candidate are removed, and the same is done for jets which lie close to a muon candidate and are consistent with the characteristics of jets produced by muon bremsstrahlung. Finally, any lepton candidate which lies within ΔR<0.4 from the direction of a surviving jet candidate is removed, in order to reject leptons from the decay of a b- or c-hadron. Electrons which share an ID track with a muon candidate are also removed.

Additional selections are then applied to the remaining lepton and jet candidates. Tighter requirements on the lepton candidates are imposed, which are then referred to as “signal” electrons or muons. Signal electrons must satisfy the medium likelihood-based identification requirement as defined in Ref. [36]. Signal electrons must have a transverse impact parameter with respect to the reconstructed primary vertex, d0, with a significance of |d0|/σ(d0)<5. For signal muons, the corresponding requirement is |d0|/σ(d0)<3. The tracks associated with the signal leptons must have a longitudinal impact parameter with respect to the reconstructed primary vertex, z0, satisfying |z0sinθ|<0.5 mm. Isolation criteria are applied to both electrons and muons by placing an upper limit on the sum of the transverse energy of the calorimeter energy clusters in a cone of ΔRη=(Δη)2+(Δϕ)2=0.2 around the electron (excluding the deposit from the electron itself), and the scalar sum of the pT of tracks within a variable-size cone around the lepton (excluding its own track). The track isolation cone radius for electrons (muons) is given by the smaller of ΔR=10GeV/pT and ΔRη=0.2(0.3). The isolation criteria are optimised such that the isolation selection efficiency is uniform across η, and it increases from 95% for pT=25GeV to 99% for pT=60GeV in Z events.

Jets are required to have |η|<2.5.

The missing transverse momentum (pTmiss), whose magnitude is denoted by ETmiss, is defined as the negative vector sum of the transverse momenta of all identified baseline objects (electrons, muons, jets) and an additional soft term. The soft term is constructed from all tracks that are not associated with any reconstructed electron, muon or jet, but which are associated with the primary vertex. In this way, the ETmiss value is adjusted for the best calibration of the jets and the other identified objects above, while maintaining pile-up independence in the soft term [48, 49].

Event selection

For the two-body and three-body selections, events are accepted if they pass an online selection (trigger) requiring a minimum of two electrons, two muons or an electron and a muon matched to the trigger objects. The offline selection requires that the leading lepton has a pT larger than 25 GeV and the subleading lepton a pT larger than 20 GeV, ensuring that trigger efficiencies are constant in the relevant phase space. The four-body selection accepts events passing an ETmiss-based trigger and having offline ETmiss > 200 GeV. This ensures that the trigger efficiency is constant in the relevant phase space. Using this trigger permits the use of a reduced lepton pT threshold of 7 GeV, increasing acceptance for the low lepton pT produced in the four-body t~bνχ~10 decay.

Events are required to have exactly two signal leptons which must be of opposite charge (electrons, muons, or one of each) with an invariant mass (regardless of the flavour of the leptons in the pair) m greater than 20GeV (10GeV for the four-body selection) in order to remove leptons from low-mass resonances. Except for the four-body selection, events with same-flavour (SF) lepton pairs with m between 71.2 and 111.2 GeV are rejected, in order to reduce the backgrounds with leptons produced by Z bosons. No additional selection is applied to the m value of different-flavour (DF) lepton pairs. In the following, the requirements described in the preceding part of this section are referred to as “common selection”.

Discriminators and kinematic variables

For the different decay modes considered, dedicated sets of discriminating variables are used to separate the signal from the SM backgrounds.

The missing transverse momentum and the pT of the leading leptons and jets are used to define three useful ratio variables :

R22j=ETmiss/(ETmiss+pT(1)+pT(2)+pT(j1)+pT(j2)),R2=ETmiss/(pT(1)+pT(2)),

and

R24j=ETmiss/(ETmiss+pT(1)+pT(2)+i=1,,N4pT(ji)),

where pT(1) and pT(2) are the leading and subleading lepton transverse momenta and pT(ji=1,,N4) are the transverse momenta in decreasing order of up to the four leading jets. The variables R22j and R2 are used to reject backgrounds, e.g. Z/γ+jets, which peak at lower values than the signal. Similarly, R24j is a powerful discriminant against multi-jet events.

Other variables employed are :

  • pT,boost: defined as the vector
    pT,boost=pTmiss+pT(1)+pT(2).
    The pT,boost variable, with magnitude pT,boost, can be interpreted as the opposite of the vector sum of all the transverse hadronic activity in the event.
  • Δϕboost: the azimuthal angle between the pTmiss vector and the pT,boost vector.

  • Δx: defined as
    Δx=2·pz(1)+pz(2)ECM
    where ECM=13 TeV is used and pz(1),pz(2) are respectively the leading and subleading lepton longitudinal momenta. This variable helps to discriminate between gluon- and quark-initiated processes. The former tend to peak towards zero, while the latter tend to peak at higher values.
  • cosθb: the cosine of the angle between the direction of motion of either of the two leptons and the beam axis in the centre-of-mass frame of the two leptons [50]. This variable is sensitive to the spin of the pair-produced particle, providing additional rejection against diboson backgrounds.

  • mT2: lepton-based “stransverse” mass. The stransverse mass defined in Refs. [51, 52] is a kinematic variable used to bound the masses of a pair of identical particles which have each decayed into a visible and an invisible particle. This quantity is defined as
    mT2(pT,1,pT,2,qT)=minqT,1+qT,2=qTmax[mT(pT,1,qT,1),mT(pT,2,qT,2)],
    where mT indicates the transverse mass,2 pT,1 and pT,2 are the transverse momentum vectors of two particles, and qT,1 and qT,2 are transverse momentum vectors with qT=qT,1+qT,2. The minimisation is performed over all the possible decompositions of qT. For tt¯ or WW decays with tbν and Wν, when the transverse momenta of the two leptons in each event are taken as pT,1 and pT,2, and pTmiss as qT, mT2(pT(1),pT(2),pTmiss) is bounded sharply from above by the mass of the W boson [53, 54]. In the t~bχ~1± decay mode the upper bound is strongly correlated with the mass difference between the chargino and the lightest neutralino. In this paper, mT2(pT(1),pT(2),pTmiss) is referred to simply as mT2.

The three-body selection uses a number of “super-razor” variables that are defined in Ref. [55]. They are designed to identify events with two massive parent particles (i.e. top squarks) each decaying into a set of visible (only leptons are considered in this case, all other particles including jets are ignored) and invisible particles (i.e. neutrinos and neutralinos). These variables are:

  • RpT: defined as
    RpT=|JT||JT|+s^R/4,
    where JT is the vector sum of the transverse momenta of the visible particles and the missing transverse momentum, and s^R is a measure of the system’s energy in the razor frame R as defined in Ref. [55] as the frame in which the two visible leptons have equal and opposite pz. In the case where all possible visible particles are considered, the razor frame R becomes an approximation of the pair production centre-of-mass frame with the centre-of-mass energy s^R. In this analysis, only leptons are considered in the visible system. Therefore, RpT tends towards zero in events that do not contain additional activity (i.e. dibosons) due to vanishing |JT|, whereas in events that contain additional activity (i.e. tt¯) this variable tends towards unity, thus providing separation power between the two cases.
  • γR+1: The Lorentz factor associated with the boosts from the razor frame R to the approximations of the two decay frames of the parent particles. It is a measure of how the two visible systems are distributed, tending towards unity when the visible particles are back-to-back or have different momenta, while preferring lower values when they are equal in momenta and collinear.

  • MΔR: defined as
    MΔR=s^RγR+1.
    This variable has a kinematic end-point that is proportional to the mass-splitting between the parent particle and the invisible particle. Therefore, it provides rejection against both the top quark and diboson production processes when it is required to be greater than the mass of the W boson, and in this case it also helps to reject the residual Z/γ+jets background.
  • ΔϕβR: The quantity ΔϕβR is the azimuthal angle between the razor boost from the laboratory to the R frame and the sum of the visible momenta as evaluated in the R frame. For systems where the invisible particle has a mass that is comparable to the pair-produced massive particle, this variable has a pronounced peak near π, making it, in general, a good discriminator in searches for models with small mass differences.

Two-body event selection

This selection targets the top squark two-body decays (Fig. 1a, b) into either a bottom quark and a chargino, with the chargino decaying into the lightest neutralino and a W boson, or a near-mass-shell top quark and a neutralino.

In these decays, the kinematic properties of signal events are similar to those of tt¯ events. In particular, when the top squarks are produced at rest the momenta carried by the neutralinos in the final state are small and the discrimination difficult. Better separation between signal events and the tt¯ background can be obtained for top squark pairs which recoil from initial-state radiation (ISR).

Three signal regions (SRs), summarised in Table 2 and denoted by SR(A,B,C)x2-body, where x stands for the lower bound of the mT2 interval, were optimised to target different scenarios:

  • SRA1802-body targets the decays into bχ~1± in scenarios where mt~1-mχ~1± is below 10 GeV and the b-jets from the decay of the t~1 are too low in energy to be reconstructed. For this reason, b-jets with pT>25 GeV are vetoed to reduce the contamination from SM processes including top quarks. No further requirement is imposed on the hadronic activity of the event. Events with SF leptons are required to have m>111.2 GeV and R22j>0.3 to reduce the contamination from Z/γ+jets events. The contribution from diboson production is expected to be the dominant background in the SR and it is reduced by requiring the events to have Δx<0.07. Furthermore, events are required to have mT2>180 GeV.

  • SRB1402-body targets the decays into bχ~1± in scenarios with a mass-splitting between the top squark and the chargino larger than 10 GeV, such that the jets from the hadronisation of b-quarks are expected to be detectable. At least two jets with pT>25 GeV are required, with at least one of them being identified as a b-jet. Events from tt¯ and Z/γ+jets production are suppressed by requiring Δϕboost<1.5. The main expected SM processes satisfying this selection are tt¯ and tt¯+Z with the Z boson decaying into neutrinos. A final selection of mT2>140 GeV is applied. Because of the similar final state, this selection is the most sensitive to signal scenarios in which the t~1 decays into t+χ~10, with large mt~1-mχ~10.

  • SRC1102-body targets the decays into t+χ~10, in scenarios where mt~1mχ~10+mt. Candidate events are required to have ETmiss>200 GeV and at least three jets with pT>25 GeV, where one of the jets is interpreted as ISR. The other two jets are expected to arise from the decay of the top quarks in the final state. One of the jets in the event is required to be b-tagged, effectively separating the signal events from SM diboson production. The Z/γ+jets background is suppressed by requiring R2 to be larger than 1.2. Events are finally required to have mT2>110 GeV.

For the model-dependent exclusion limits, a shape fit of the mT2 distribution is performed for the SRA1802-body and SRB1402-body selections: the distribution is divided into bins of width 20 GeV, starting from mT2=120 GeV; the last bin’s low boundary corresponds to the requirement on the same variable in the definitions of SRA1802-body and SRB1402-body; each bin is referred to as SR(A,B)x,y2-body, where x and y denote the low and high edges of the bin.

Table 2.

Two-body selection signal region definitions

SRA1802-body SRB1402-body SRC1102-body
Lepton flavour SF DF SF DF SF DF
pT(1),pT(2) [GeV] >25, >20 >25, >20 >25, >20
[20, 71.2] [20, 71.2]
m [GeV] >111.2 >20 or >20 or >20
>111.2 >111.2
R22j >0.3 - - -
R2 - - >1.2
Δx <0.07 - -
Δϕboost - <1.5 -
njets - 2 3
nb-jets =0 1 1
ETmiss [GeV] - - >200
mT2 [GeV] >180 >140 >110

Three-body event selection

This selection targets the top squark three-body decay mode (Fig. 1c), which is expected to be the dominant decay mode when the two-body decay mode into the lightest chargino or neutralino is kinematically forbidden, i.e. for mχ~10+mW+mb<mt~1<mχ~10+mt and mt~1<mχ~1±+mb.

Two orthogonal signal regions, SRW3-body and SRt3-body, are summarised in Table 3. The SRW3-body targets the region where Δm(t~,χ~10)mW in which the produced b-jets have low transverse momentum, and hence are often not reconstructed. The second signal region SRt3-body targets the region in which Δm(t~,χ~10)mt.

Table 3.

Three-body selection signal region definitions

SRW3-body SRt3-body
Lepton flavour SF DF SF DF
pT(1),pT(2) [GeV] >25, >20 >25, >20
[20, 71.2] [20, 71.2]
m [GeV] or >20 or >20
>111.2 >111.2
nb-jets =0 1
MΔR [GeV] >95 >110
RpT >0.7 >0.7
1/γR+1 >0.7 >0.7
ΔϕβR >0.9|cosθb|+1.6 >0.9|cosθb|+1.6

The two regions make use of a common set of requirements on RpT, γR+1, and in the two-dimensional (cosθb, ΔϕβR) plane. In addition, SRW3-body requires that no b-jet is identified in the event and that MΔR  >95 GeV. The large MΔR requirement suppresses the top quark and diboson backgrounds. In the case of SRt3-body, the requirements are: at least one b-jet and MΔR >110 GeV. The b-jet requirement makes the selection orthogonal to SRW3-body, so that the two SRs can be statistically combined. Furthermore, a slightly tighter MΔR requirement is necessary to eliminate the background that originates from top quark production processes.

Four-body event selection

The selection described here targets the four-body decay mode of the top squark (Fig. 1d) for scenarios where mt~1<mχ~10+mb+mW and mt~1<mχ~1±+mb. In this region the top squark decay into cχ~10 might be dominant, depending on various SUSY model parameters. The branching ratio into this final state is here assumed to be negligible. For these small mass splittings, the leptons in the final state, originating from the virtual W boson decays, are expected to have low pT.

Signal events can be distinguished from SM processes if a high-pT jet from ISR leads to a large transverse boost of the sparticle pair system and enhances the ETmiss value. At least two jets with pT>25GeV are required in the event. The leading jet is considered to be the ISR jet and required to have pT>150 GeV. Since the jets resulting from t~ decays tend to have low pT in this scenario, at most one more energetic jet with pT>25GeV is permitted in the event and the transverse momentum of the third jet (if present) must satisfy pT(j3)/ETmiss<0.14.

In order to remove events originating from low-mass resonances, the invariant mass of the two leptons, m, is required to be greater than 10 GeV. Furthermore, upper limits on pT(1) and pT(2), respectively of 80 GeV and 35 GeV, are applied.

The signal region SR4-body is defined as summarised in Table 4. The two variables R24j and R2 must be larger than 0.35 and 12 to reject multi-jet and tt¯ backgrounds, respectively. Finally, the two most energetic jets in the event must not be tagged as b-jets.

Table 4.

Four-body selection signal region definition

SR4-body
Lepton flavour SF and DF
ETmiss [GeV] >200
pT(1) [GeV] [7, 80]
pT(2) [GeV] [7, 35]
m [GeV] >10
njets 2
pT(j1) [GeV] >150
pT(j2) [GeV] >25
pT(j3)/ETmiss <0.14
R24j >0.35
R2 >12
nb-jets veto on j1 and j2

Samples of simulated events

Monte Carlo (MC) simulated event samples are used to aid in the estimation of the background from SM processes and to model the SUSY signal. The event generator, parton shower and hadronisation generator, cross-section normalisation, parton distribution function (PDF) set and underlying-event parameter set (tune) of these samples are given in Table 5, and more details of the event generator configurations can be found in Refs. [5659]. Cross-sections calculated at next-to-next-to-leading order (NNLO) in QCD including resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms were used for top quark production processes. For production of top quark pairs in association with vector or Higgs bosons, cross-sections calculated at next-to-leading order (NLO) were used, and the event generator cross-sections calculated by Sherpa (at NLO for most of the processes) are used when normalising the multi-boson backgrounds. In all MC samples, except those produced by Sherpa, the EvtGen v1.2.0 program [60] was used to model the properties of the bottom and charm hadron decays. Additional MC samples are used when estimating systematic uncertainties, as detailed in Sect. 7.

Table 5.

Simulated signal and background event samples: the corresponding event generator, parton shower generator, cross-section normalisation, PDF set and underlying-event tune are shown

Physics process Event generator Parton shower generator Cross-section normalisation PDF set Tune
SUSY Signals MadGraph5_aMC@NLO 2.2.3 [61] Pythia 8.186 [62] NLO + NLL [6368] NNPDF23LO [69] A14 [70]
Z/γ+jets Sherpa 2.2.1 [71] Sherpa 2.2.1 NNLO [72] NLO CT10 [69] Sherpa default
tt¯ powheg-box v2 [73] Pythia 6.428 [74] NNLO + NNLL [7580] NLO CT10 Perugia2012 [81]
Wt powheg-box v2 Pythia 6.428 NNLO + NNLL [82] NLO CT10 Perugia2012
tt¯W/Z/γ MadGraph5_aMC@NLO 2.2.2 Pythia 8.186 NLO [61] NNPDF23LO A14
Diboson Sherpa 2.2.1 Sherpa 2.2.1 Generator NLO NLO CT10 Sherpa default
tt¯h MadGraph5_aMC@NLO 2.2.2 Herwig 2.7.1 [83] NLO [84] CTEQ6L1 [85] A14
Wh, Zh MadGraph5_aMC@NLO 2.2.2 Pythia 8.186 NLO [84] NNPDF23LO A14
tt¯WW, tt¯tt¯ MadGraph5_aMC@NLO 2.2.2 Pythia 8.186 NLO [61] NNPDF23LO A14
tZ, tWZ, tt¯t MadGraph5_aMC@NLO 2.2.2 Pythia 8.186 LO NNPDF23LO A14
Triboson Sherpa 2.2.1 Sherpa 2.2.1 Generator LO, NLO CT10 Sherpa default

SUSY signal samples were generated from leading-order (LO) matrix elements with up to two extra partons, using the MadGraph5_aMC@NLO  [61] event generator. The two-body signals used Pythia 8.186 [62] for the modelling of the SUSY decay chain, parton showering, hadronisation and the description of the underlying event. The three-body and four-body signals were decayed with Pythia8 + MadSpin [86] instead. Parton luminosities were provided by the NNPDF23LO PDF set. Jet–parton matching was realised following the CKKW-L prescription [87], with a matching scale set to one quarter of the pair-produced superpartner mass. In all cases, the mass of the top quark was fixed at 172.5 GeV. Signal cross-sections were calculated to next-to-leading order in the strong coupling constant, adding the resummation of soft gluon emission at next-to-leading-logarithmic accuracy (NLO + NLL) [67, 88, 89]. The nominal cross-sections and their uncertainties were taken from an envelope of cross-section predictions using different PDF sets and factorisation and renormalisation scales, as described in Ref. [68]. All two-, three- and four-body samples were generated assuming a 100% branching ratio into the respective final states.

For the pMSSM inspired models, the mass spectrum of sparticles was calculated using Softsusy 3.7.3 [90] and cross-checked with SPheno 3.3.8 [91, 92] and Suspect 2.5 [93]. Hdecay and Sdecay, included in Susy-Hit [94] were used to generate decay tables of the SUSY particles.

To simulate the effects of additional pp collisions in the same and nearby bunch crossings, additional interactions were generated using the soft QCD processes of Pythia 8.186 with the A2 tune [95] and the MSTW2008LO PDF set [96], and they were overlaid onto each simulated hard-scatter event. The MC samples were reweighted to the pile-up distribution observed in the data. The MC samples were processed through an ATLAS detector simulation [97] based on Geant4 [98] or, in the case of tt¯t and the SUSY signal samples, a fast simulation using a parameterisation of the calorimeter response and Geant4 for the other parts of the detector [99]. All MC samples are reconstructed in the same manner as the data. Corrections derived from data control samples are applied to simulated events to account for differences between data and simulation in reconstruction efficiencies, momentum scale and resolution of leptons and in the efficiency and false positive rate for identifying jets resulting from the hadronisation of b-quarks.

Background estimation

The dominant SM background processes satisfying the SR requirements are estimated by simulation, which is normalised to data and verified in separate regions of the phase space. Dedicated control regions (CRs), described in Sects. 6.16.3, enhanced in a particular background component are used for the normalisation. Subdominant background yields are taken directly from MC simulation or from additional independent studies in data. For each signal region, a simultaneous “background fit” is performed to the number of events found in the CRs, using a statistical minimisation based on a likelihood implemented in the HistFitter package [100]. In each fit, the normalisations of the background contributions having dedicated CRs are allowed to float, while the MC simulation is used to describe the shape of distributions of kinematical variables. The level of agreement between the background prediction and data is compared in dedicated validation regions (VRs), which are not used to constrain the background normalisation or nuisance parameters in the fit.

In order to keep the background control region kinematically as close as possible to the SR, the two-body, three-body and four-body selections use different sets of CRs. The definitions of the regions used in each analysis and the results of the fits are described in the following subsections.

The background due to jets misidentified as leptons (hereafter referred to as “fake” leptons) and non-prompt leptons is collectively referred to as “FNP”: it consists of semileptonic tt¯, s-channel and t-channel single-top-quark, W + jets and light- and heavy-flavour multi-jet events. It is estimated from data with a method similar to that described in Refs. [101, 102]. Two types of lepton identification criteria are defined for this evaluation: “tight” and “loose”, corresponding to signal and baseline leptons described in Sect. 3. The method makes use of the number of observed events containing loose–loose, loose–tight, tight–loose and tight–tight lepton pairs in a given SR. The probability for prompt leptons satisfying the loose selection criteria to also pass the tight selection is measured using a Z (=e,μ) sample. The equivalent probability for fake or non-prompt leptons is measured in data from multi-jet- and tt¯-enriched control samples. The number of events containing a contribution from one or two fake or non-prompt leptons is calculated from these probabilities.

Systematic uncertainties in the samples of simulated events affect the expected yields in the different regions and are taken into account to determine the uncertainties in the background predictions. The systematic uncertainties are described by nuisance parameters, which are not constrained by the fit, since the number of floating background normalisation parameters is equal to the number of CRs. Each uncertainty source is described by a single nuisance parameter, and all correlations between background processes and selections are taken into account. A list of systematic uncertainties considered in the fits is provided in Sect. 7.

Two-body selection background determination

The main background sources for the two-body selection are respectively diboson production in SRA1802-bodyand tt¯ and tt¯ + Z in SRB1402-body and SRC1102-body. These processes are normalised to data in dedicated CRs, summarised in Table 6 together with the corresponding VRs: CRtt¯2-body (included in the background fits of SRA1802-body and SRB1402-body), CRtt¯,3j2-body (included in the background fit of SRC1102-body), CRVV-SF2-body (included in the background fits of SRA1802-body and SRB1402-body), CRtt¯Z2-body (included in the background fits of SRA1802-body, SRB1402-body and SRC1102-body) and CRVZ2-body (included in the background fits of SRA1802-body and SRB1402-body). The control and validation regions are labelled using the targeted background process as subscript, which can also include additional selection details, and the associated selection as superscript. For example, the “3j” subscript of CRtt¯,3j2-bodyrefers to the minimum jet multiplicity which is required in this control region. In CRtt¯Z2-body and CRVZ2-body, events with three charged leptons including one same-flavour opposite-charge pair with |m-mZ|<20 GeV are selected. In order to mimic the kinematics of the tt¯ + Z events with invisible Z decays, a corrected ETmiss variable, ET,corrmiss, is defined by vectorially adding the momentum of the same-flavour opposite-charge lepton pair to the pTmiss vector.

Table 6.

Two-body selection control and validation regions definition. The common selection defined in Sect. 4 also applies to all regions except CRtt¯Z2-body and CRVZ2-body, which require three leptons including one same-flavour opposite-charge pair with |m-mZ|<20 GeV

CRtt¯2-body CRtt¯,3j2-body CRVV-SF2-body CRtt¯Z2-body CRVZ2-body VRtt¯2-body VRtt¯,3j2-body VRVV-DF2-body
Leptons 2, DF 2 2, SF 3 3 2, DF 2 2, DF
mT2 [GeV] [100, 120] [60, 100] [100, 120] - - >120 >100 [100, 120]
nb-jetsnjets 1- 13 0- 23 or =14 0- 12 13 0-
pT,boost [GeV] - - <25 - - - - <25
Δϕboost - - - - - >1.5 - -
R22j - - >0.3 - - - - -
ET,corrmiss [GeV] - - - >120 >120 - - -
ETmiss [GeV] >200 - - - - >200 -
R2 - <1.2 - - - - <1.2 -

In order to test the reliability of the background prediction, the results of the simultaneous fit are cross-checked in VRs which are disjoint from both the corresponding control and signal regions. Overlapping regions, e.g. CRtt¯2-body and CRtt¯,3j2-body, are only included in independent background fits, so that no correlation is introduced. The expected signal contamination in the CRs is generally below 5%. The highest signal contamination in the VRs, of about 18%, is expected in VRtt¯,3j2-body for a top squark mass of 400 GeV and a lightest neutralino mass of 175 GeV.

Figure 2 shows the distributions of some of the kinematic variables used to define the four control regions after the SRA1802-body background fit, so that the plots illustrate the modelling of the shape of each variable. In general, good agreement is found between the data and the background model within uncertainties. The other selection variables are equally well described by the background prediction.

Fig. 2.

Fig. 2

Two-body selection distributions of a nb-jets in CRtt¯2-body, b R22j in CRVV-SF2-body and c, d ET,corrmiss in CRtt¯Z2-body and CRVZ2-body after the SRA1802-body background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events

The results of the background fits, as well as the MC expected background composition before the fit, are reported in Table 7 for the CRs used in the SRA1802-body and SRB1402-body background fits, and in Table 8 for the CRs used in the SRC1102-body background fit. The normalisations for fitted backgrounds are found to be consistent with the theoretical predictions, when uncertainties are considered. By construction, in the CRs the yields observed and predicted by the fits are the same. Good agreement, within one standard deviation from the SM background prediction, is observed in the VRs and summarised in Fig. 5.

Table 7.

Two-body selection background fit results for the CRs of the SRA1802-body and SRB1402-body background fits. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV-SF, tt¯Z and VZ) that are normalised to data in dedicated CRs. The “Others” category contains the contributions from tt¯W, tt¯h, tt¯WW, tt¯t, tt¯tt¯, Wh, ggh and Zh production. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution

CRtt¯2-body CRVV-SF2-body CRtt¯Z2-body CRVZ2-body
Observed events 587 213 91 836
Estimated SM events 587±24 213±15 91±10 836±29
tt¯ 532±25 14±4 - -
Wt 44±6 4.0±1.5 - -
Z/γ+jets 0.02-0.02+0.05 19±10 - -
VV-SF - 135±18 - -
VV-DF 2.2±0.8 - - -
VZ 0.18±0.12 38±7 17.5±2.5 730±50
tt¯+Z 2.2±0.8 0.07±0.07 47±12 8.9±2.5
Others 3.8±0.4 0.41±0.18 14.5±1.4 10.3±0.9
Fake and non-prompt 1.6±0.9 0-0+5 12±7 86±34
Nominal MC, tt¯ 504 14 - -
Nominal MC, VV-SF - 122 - -
Nominal MC, VZ 0.18 39 18 735
Nominal MC, tt¯+Z 3.57 0.08 56 11

Table 8.

Two-body selection background fit results for the CRs of the SRC1102-body background fit. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯ and tt¯Z) that are normalised to data in dedicated CRs. The “Others” category contains the contributions from tt¯W, tt¯h, tt¯WW, tt¯t, tt¯tt¯, Wh, ggh and Zh production. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution

CRtt¯,3j2-body CRtt¯Z2-body
Observed events 212 91
Estimated SM events 212±15 91±10
tt¯ 184±16 -
tt¯ + Z 1.03±0.32 47±12
Wt 23±7 -
VV 1.69±0.30 17.7±2.2
Z/γ+jets 0.05±0.02 -
Others 1.91±0.12 14.6±1.0
Fake and non-prompt - 12±7
Nominal MC, tt¯ 201 -
Nominal MC, tt¯+Z 1.23 55.7

Fig. 5.

Fig. 5

Comparison of the observed data (nobs) with the predicted SM background (nexp) in the SRs and associated VRs. The background predictions are obtained using the background-only fit configuration, and the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The bottom panel shows the difference between data and the predicted SM background divided by the total uncertainty (σtot)

Three-body selection background determination

In the three-body signal regions defined in Sect. 4.3, the SM background is dominated by diboson and tt¯ production. A single control region is used for tt¯ production, while two CRs are defined to target diboson events with either same-flavour or different-flavour lepton pairs. The background predictions are tested in VRs that are defined to be kinematically adjacent to, yet disjoint from, the signal regions. The definitions of the control and validation regions are shown in Table 9. The overlap between VRtt¯3-body and VRVV-DF3-body does not affect the final results as these regions are not used to constrain the background normalisations. The signal contamination in the CRs and VRs is generally small, with the maximum found to be about 12% in VRVV-DF3-body for a top squark mass of 220 GeV and a lightest neutralino mass of 110 GeV.

Table 9.

Three-body selection control and validation regions definitions. The common selection defined in Sect. 4 also applies to all regions

CRtt¯3-body CRVV-DF3-body CRVV-SF3-body VRtt¯3-body VRVV-DF3-body VRVV-SF3-body
Lepton flavour DF DF SF DF DF SF
|m-mZ| [GeV] - - >20 - - >20
nb-jets >0 =0 =0 =0 =0 =0
MΔR [GeV] >80 >50 >70 >80 [50, 95] [60, 95]
RpT >0.7 <0.5 <0.5 <0.7 <0.7 <0.4
1/γR+1 - >0.7 >0.7 - >0.7 >0.7
(cosθb, ΔϕβR) ΔϕβR<(0.9×|cosθb|+1.6) ΔϕβR>(0.9×|cosθb|+1.6)

Table 10 shows the expected and observed numbers of events in each of the control regions after the background fit. The total number of fitted background events in the validation regions is in agreement with the observed number of data events. Figure 3 shows three distributions in the control regions after the background fit, so that the plots illustrate the MC modelling of the shape of each variable. In general, good agreement between the data and the background model is found within uncertainties. The other selection variables are equally well described by the background prediction. Good agreement, within one standard deviation from the SM background prediction, is observed in the VRs and summarised in Fig. 5.

Table 10.

Three-body selection background fit results for the CRs of the SRW3-body and SRt3-body background fit. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV-DF and VV-SF) that are normalised to data in dedicated CRs. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution

CRtt¯3-body CRVV-DF3-body CRVV-SF3-body
Observed events 951 2046 1275
Estimated SM events 951±31 2046±50 1275±40
tt¯ 833±33 620±110 330±60
VV-DF 11.5±2.4 1090±130 -
VV-SF - - 380±90
Wt 101±10 186±28 103±17
tt¯ + V 4.3±0.4 0.39±0.06 0.36±0.07
Z/γ + jets 0.70±0.22 1.8-1.8+2.5 430±50
Higgs bosons 0.31±0.08 79±9 6.2±0.8
Fake and non-prompt 0.00-0.00+0.30 65.4±2.2 24.0±1.3
Nominal MC, tt¯ 787 590 320
Nominal MC, VV-DF 11.3 1069 -
Nominal MC, VV-SF - - 370

Fig. 3.

Fig. 3

Three-body selection distributions of a RpT in CRtt¯3-body, b cosθb in CRVV-DF3-body, and c MΔR in CRVV-SF3-body after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events

Four-body selection background determination

In the four-body SR, the largest SM background contributions stem from tt¯ and diboson production, as well as Z/γ+jets production with the Z boson decaying into ττ with both τ leptons decaying leptonically. Three dedicated control regions are defined: CRtt¯4-body, CRVV4-body and CRZττ4-body. The background predictions are tested in three validation regions that are defined to be kinematically similar to, but disjoint from, both the control and signal regions. The definitions of the control and validation regions are shown in Table 11. In the tt¯ control region the signal contamination is less than 6%, while in CRVV4-body and CRZττ4-body the highest signal contamination, for a top squark mass of 260 GeV and a lightest neutralino mass of 180 GeV, is respectively 30% and 9%.

Table 11.

Four-body selection control and validation regions definition. The common selection reported in Table 4 also applies to all regions

CRtt¯4-body CRVV4-body CRZττ4-body VRtt¯4-body VRVV4-body VRZττ4-body
Leading lepton pT [GeV] [7, 80] [7, 80] >20 [7, 80] [7, 80] >50
Subleading lepton pT [GeV] [7, 35] [7, 35] >20 [7, 35] [7, 35] [7, 20]
njets 2 =1 =1 2 =1 =1
Leading jet pT [GeV] [100, 150] >150 >150 >150 >150 >150
m [GeV] >10 >45 [10, 45] >10 >45 [10, 45]
R24j <0.35
R2 <5 <12 >5
nb-jets =0 =0 =0 =0

Table 12 shows the expected and observed numbers of events in each of the control regions after the background fit. Good agreement between data and the SM predictions is observed in the validation regions and shown in Fig. 5. Figure 4 shows three distributions in the control regions for this analysis after applying the normalisation factors provided by the background fit. Good agreement between data and the SM predictions is observed. The other selection variables are equally well described by the background prediction. The largest observed deviation (1.4σ) from the SM background prediction is found in VRZττ4-body. The yields in the other VRs are found to be compatible with the SM predictions within one standard deviation.

Table 12.

Four-body selection background fit results for the CRs of the SR4-body background fit. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV and Zττ) that are normalised to data in dedicated CRs. Combined statistical and systematic uncertainties are given

CRtt¯4-body CRVV4-body CRZττ4-body
Observed events 1251 110 106
Estimated SM events 1251±35 110±10 106±10
tt¯ 960±50 47±20 10±6
VV 37±22 40±22 18±11
Zττ 22±8 0.00-0.00+0.17 54±16
tt¯ + Z 5.6±0.8 0.08±0.01 0.05±0.02
Wt 62±19 9.0±2.7 2.7±2.4
Zee, Zμμ 0.7±0.5 0.2-0.2+0.4 1.6±0.6
Others 11.2±1.6 0.51±0.12 3.2±0.6
Fake and non-prompt 154±14 13.1±2.0 16±7
Nominal MC,tt¯ 931 46 10
Nominal MC,VV 47 51 23
Nominal MC,Zττ 20 0 51

Fig. 4.

Fig. 4

Four-body selection distributions of the a pT(j1) in CRtt¯4-body, b R2 in CRVV4-body and c ETmiss in CRZττ4-bodyafter the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events

Systematic uncertainties

The primary sources of systematic uncertainty are related to: the jet energy scale (JES), jet energy resolution (JER), and the theoretical and MC modelling uncertainties in the backgrounds. The statistical uncertainties of the simulated event samples are also taken into account. The effect of the systematic uncertainties is evaluated for all signal samples and background processes. Since the normalisation of the dominant background processes is extracted in dedicated control regions, the systematic uncertainties only affect the extrapolation to the signal regions in these cases. Statistical uncertainties due to the limited number of data events in the CRs are also included in the fit for each region.

The JES and JER uncertainties are derived as a function of the pT and η of the jet, as well as of the pile-up conditions and the jet flavour composition of the selected jet sample [43]. Uncertainties associated to the modelling of the b-tagging efficiencies for b-jets, c-jets and light-flavour jets [103, 104] are also considered.

The systematic uncertainties related to the modelling of ETmiss in the simulation are estimated by propagating the uncertainties in the energy and momentum scale of electrons, muons and jets, as well as the uncertainties in the resolution and scale of the soft term [49].

Other detector-related systematic uncertainties, such as those in lepton reconstruction efficiency, energy scale, energy resolution and in the modelling of the trigger efficiency [36, 37], are found to have a small impact on the results and are generally negligible compared to the other detector-related uncertainties.

The uncertainties in the modelling of the tt¯ and single-top backgrounds in simulation are estimated by varying the renormalisation and factorisation scales by a factor of two, as well as the amount of initial- and final-state radiation used to generate the samples [56]. Uncertainties in the parton shower modelling are assessed as the difference between the predictions from Powheg showered with Pythia and Herwig, and those due to the event generator choice by comparing Powheg and MadGraph5_aMC@NLO  [56]. An uncertainty in the acceptance due to the interference between tt¯ and single top quark Wt production is assigned by comparing the predictions of dedicated LO MadGraph  2.5 samples. These samples are used to compare the predictions for tt¯ and Wtb with the inclusive WWbb process, where the same production diagrams are included, but top quarks are not required to be on-shell.

The diboson background MC modelling uncertainties are estimated by varying up and down by a factor of two the renormalisation, factorisation and resummation scales used to generate the sample [58]. For tt¯Z production, the predictions from the MadGraph5_aMC@NLO and Sherpa event generators are compared and the full difference between the respective predictions is assigned as an uncertainty. Uncertainties related to the choice of renormalisation and factorisation scales are assessed by varying the corresponding event generator parameters up and down by a factor of two around their nominal values [105].

The uncertainties related to the choice of QCD renormalisation and factorisation scales in Z/γ+jets events are assessed by varying the corresponding event generator parameters up and down by a factor of two around their nominal values. Uncertainties due to our choice of the resummation scale and the matching scale between the matrix element and the parton shower are estimated by varying up and down by a factor of two the corresponding parameters in Sherpa.

The cross-sections used to normalise the MC samples are varied according to the uncertainty in the cross-section calculation, i.e., 5.3% uncertainty for single top quark Wt-channel [106], 6% for diboson, 13% for tt¯W and 12% for tt¯Z production [61]. For tt¯WW, tZ, tWZ, tt¯h, tt¯t, tt¯tt¯, and triboson production processes, which constitute a small background, a 50% uncertainty in the event yields is assumed.

Systematic uncertainties are assigned to the FNP background estimate to account for potentially different compositions (heavy flavour, light flavour or photon conversions) between the signal and control regions, as well for the contamination from prompt leptons in the regions used to measure the probabilities for loose fake or non-prompt leptons to satisfy the tight signal criteria. Parameterisations of these probabilities are independently derived from tt¯- and multi-jet-enriched same-charge dilepton samples. The tt¯-enriched sample is used to derive the parameterisation from which the central prediction for the FNP background is obtained. The full difference between the predictions derived from the tt¯ and the multi-jet parameterisation is assigned as the systematic uncertainty in the central FNP prediction and symmetrised.

A 3.2% uncertainty in the luminosity measurement is also taken into consideration for all signal and background estimates that are directly derived from MC simulations.

Table 13 summarises the contributions of the different sources of systematic uncertainty in the total SM background predictions in the signal regions. The total systematic uncertainty ranges between 15% and 46%, with the dominant sources being the size of the MC event samples, the JES and ETmiss modelling, the numbers of events in the CRs and the tt¯ theoretical uncertainties.

Table 13.

Sources of systematic uncertainty in the SM background estimates, estimated after the background fits. The values are given as relative uncertainties in the total expected background event yields in the SRs. Entries marked “–” indicate either a negligible contribution or an uncertainty that does not apply (for example the normalisation uncertainty for a background whose normalisation is not fitted for that specific signal region). MC statistics refer to the statistical uncertainty from the simulated event samples. The individual components can be correlated and therefore do not necessarily add up in quadrature to the total systematic uncertainty

Signal region SRA1802-body SF SRA1802-body DF SRB1402-body SF SRB1402-body DF SRC1102-body SF SRC1102-body DF SRW3-body SF SRW3-body DF SRt3-body SF SRt3-body DF SR4-body
Total SM background uncertainty 21% 32% 15% 21% 35% 38% 36% 39% 46% 42% 20%
Diboson theoretical uncertainties 4.0% 5.9% - - - - 9.1% 10% 1.3% - 2.7%
tt¯ theoretical uncertainties - - 4.2% 6.6% 12% 13% 13% 18% 25% 24% 8.1%
Wt theoretical uncertainties - - - 1.9% - 5.4% - - - - -
tt¯-Wt interference - - 1.8% 7.9% - - - - - - -
MC statistical uncertainties 13% 28% 12% 13% 15% 15% 16% 14% 20% 22% 10%
VV normalisation 14% - - - - - 12% 4.3% 1.3% - 9.2%
tt¯ normalisation - - - - 16% 15% 1.8% 2.5% 3.5% 3.5% 8.6%
tt¯+Z normalisation - - 7.6% 9.9% 8.5% 10% - - - - -
Zττ normalisation - - - - - - - - - - 1.5%
Jet energy scale 6.9% 3.1% 4.1% 6.4% 13% 22% 19% 18% 27% 11% 4.4%
Jet energy resolution - - - - 12% 16% 7.2% 18% 2.9% 22% 1.0%
ETmiss modelling 5.0% 13% 2.2% 3.2% 26% 23% 18% 11% 14% 6.5% 1.3%
b-tagging - - 3.0% 1.5% - - 2.7% 3.0% 1.0% 3.0% 2.2%
Pile-up reweighting 2.0% 3.2% 1.1% 4.3% 2.9% 4.6% 2.9% 5.0% 5.1% 4.9% 1.4%
Lepton modelling 1.3% 2.1% - 1.1% - - 1.1% 3.1% 4.6% 3.0% 2.5%
Fake and non-prompt leptons - - 7.4% - 4.0% - 2.8% - - - 14%

Theory uncertainties in the signal acceptance are taken into account. These are computed by varying the strong coupling constant αs, the renormalization and factorization scales, the CKKW scale used to match the parton shower and matrix element descriptions and the parton shower tunes. These uncertainties are mostly relevant for the four-body selection and range between 10% and 30% depending on the mass difference mt~1-mχ~10.

Results

The data are compared to background predictions in the signal regions of the different selections. The number of observed events and the predicted number of SM background events from the background-only fits in all SRs and VRs are shown in Fig. 5. In all SRs, good agreement is observed between data and the SM background predictions. A detailed discussion of the results is given in the following sections.

Two-body results

Figure 6 shows the mT2 distribution in each of the two-body signal regions, split between the same- and different-flavour lepton channels, omitting the selection on mT2 itself. The estimated SM yields in SRA1802-body and SRB1402-body are determined with a background fit simultaneously determining the normalisations of the background contributions from tt¯, diboson with a SF lepton pair, tt¯+Z and diboson with more than two charged leptons by including CRtt¯2-body, CRVV-SF2-body, CRtt¯Z2-body and CRVZ2-body in the likelihood minimisation. The estimated SM yields in SRC1102-body are determined with a background fit simultaneously determining the normalisations of the background contributions from tt¯ and tt¯+Z by including CRtt¯,3j2-body and CRtt¯Z2-body in the likelihood minimisation. No significant excess over the SM prediction is observed, as can be seen from the background-only fit results which are shown in Table 14 for SRA1802-body and SRB1402-body, and Table 15 for the SRC1102-body. Table 16 reports the observed and expected yields for the SRs used for the computation of the exclusion limits.

Fig. 6.

Fig. 6

Two-body selection distributions of mT2 for events satisfying the selection criteria of the six SRs, except for the one on mT2, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria

Table 14.

Two-body selection background fit results for SRA1802-body and SRB1402-body. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV-SF, tt¯Z and VZ) that are normalised to data in dedicated CRs. The “Others” category contains the contributions from tt¯W, tt¯h, tt¯WW, tt¯t, tt¯tt¯, Wh, ggh and Zh production. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution. The “Others” contribution to SRB1402-body is dominated by tt¯W

SRA1802-body SF SRA1802-body DF SRB1402-body SF SRB1402-body DF
Observed events 16 8 9 7
Estimated SM events 12.3±2.6 5.4±1.7 7.4±1.1 4.8±1.0
tt¯ - - 0.8±0.4 0.8±0.5
Wt events - - 0.38±0.29 0.7±0.5
Z/γ+jets 0.35±0.21 - 1.24±0.32 0.03±0.01
Fake and non-prompt 0.00-0.00+0.30 0.00-0.00+0.30 0.8±0.5 0.00-0.00+0.30
VV-DF - 4.5±1.5 - 0.23±0.06
VV-SF 9.8±2.5 - 0.39±0.11 -
VZ 1.91±0.31 0.52±0.17 0.53±0.14 0.04±0.01
tt¯ + Z 0.08±0.03 0.15±0.06 2.3±0.6 1.8±0.5
Others 0.18±0.02 0.24±0.07 1.10±0.16 1.11±0.16
Nominal MC, tt¯ - - 0.78 0.8
Nominal MC, VV-SF 8.8 - 0.35 -
Nominal MC, VZ 1.9 0.52 0.54 0.04
Nominal MC, tt¯+Z 0.09 0.17 2.6 2.2

Table 15.

Two-body selection background fit results for SRC1102-body. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯ and tt¯Z) that are normalised to data in dedicated CRs. The “Others” category contains the contributions from tt¯W, tt¯h, tt¯WW, tt¯t, tt¯tt¯, Wh, ggh and Zh production. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution

SRC1102-body SF SRC1102-body DF
Observed events 11 7
Estimated SM events 5.3±1.8 3.8±1.5
tt¯ 2.1±1.3 1.4±1.2
tt¯ + Z 1.6±0.5 1.4±0.5
Wt 0.05-0.05+0.09 0.00-0.00+0.23
VV + VZ 0.33±0.06 0.12±0.04
Z/γ+jets 0.3-0.3+0.5 -
Others 0.67±0.13 0.81±0.15
Fake and non-prompt 0.18-0.18+0.41 0.00-0.00+0.02
Nominal MC, tt¯ 2.3 1.6
Nominal MC, tt¯+Z 1.9 1.70

Table 16.

Two-body selection background fit results for SR(A,B)x,y2-body regions, where x and y denote the low and high edges of the bin. Combined statistical and systematic uncertainties are given. Uncertainties in the predicted background event yields are quoted as being symmetric

Lepton flavour SRA120,1402-body SRB120,1402-body SRA140,1602-body SRA160,1802-body
Observed events SF 22 17 6 10
Estimated SM events 20.0±4.6 16.3±6.2 11.0±2.5 5.6±1.8
Observed events DF 27 13 6 7
Estimated SM events 23.8±4.2 16.1±5.3 10.8±2.1 6.4±1.3

Three-body results

Figure 7 shows the distributions of RpT and MΔR in each of the signal regions, split between the same- and different-flavour channels, omitting the requirement on RpT and on MΔR. The estimated SM yields in SRW3-body and SRt3-body are determined with a background fit simultaneously determining the normalisations of tt¯, SF diboson production and DF diboson production by including CRtt¯3-body, CRVV-SF3-body and CRVV-DF3-body in the likelihood minimisation. No excess over the SM prediction is observed. Table 17 shows the background fit results.

Fig. 7.

Fig. 7

Three-body selection distributions of RpT in a same-flavour and b different-flavour events that satisfy all the SRW3-body selection criteria except for the one on RpT, and of MΔR in the c same-flavour and d different-flavour events that satisfy all the SRt3-body selection criteria except for the one on MΔR after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria

Table 17.

Three-body selection background fit results for SRW3-body and SRt3-body. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV-DF and VV-SF) that are normalised to data in dedicated CRs. Combined statistical and systematic uncertainties are given. Entries marked “–” indicate a negligible background contribution

SRW3-body SF SRW3-body DF SRt3-body SF SRt3-body DF
Observed events 4 6 6 6
Estimated SM events 9.8±3.4 7.8±3.0 3.1±1.4 4.4±1.8
tt¯ 4.2±1.6 4.6±2.1 2.5±1.3 3.6±1.8
VV-DF - 2.9±1.4 - 0.04±0.03
VV-SF 3.4±2.1 - 0.16±0.08 -
Wt 0.31±0.22 0.23±0.12 0.12±0.05 0.14±0.08
tt¯+V 0.03±0.01 0.06±0.02 0.18±0.04 0.24±0.07
Z/γ + jets 1.5±0.7 0.05±0.01 0.1±0.03 0.0±0.0
Fake and non-prompt 0.42±0.28 0.06±0.06 0.00-0.00+0.30 0.41±0.09
Nominal MC, tt¯ 4.0 4.3 2.4 3.4
Nominal MC, VV-DF - 2.8 - 0.04
Nominal MC, VV-SF 3.4 - 0.16 -

Four-body results

Figure 8 shows the distributions of R24j and R2 for events satisfying all the SR4-body selections. No significant excess over the SM prediction is visible. The estimated SM yields in SR4-body are determined with a background fit simultaneously determining the normalisations of tt¯, diboson production, and Z/γ+jets where Zττ, by including CRtt¯4-body, CRVV4-body and CRZττ4-body in the likelihood minimisation. The background fit results are shown in Table 18. The observed yield is less than one standard deviation from the background prediction in the SR.

Fig. 8.

Fig. 8

Four-body selection distributions of a R24j and b R2 for events satisfying all the SR4-body selections except for the one on the variable shown in the figure, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total uncertainty in the background predictions after the fit to the data has been performed. The counting uncertainty on data is also shown by the black error bars. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria

Table 18.

Four-body selection background fit results for SR4-body. The nominal predictions from MC simulation, are given for comparison for those backgrounds (tt¯, VV and Zττ) that are normalised to data in dedicated CRs. The “Others” category contains the contributions from tt¯W, tt¯h, tt¯WW, tt¯t, tt¯tt¯, Wh, ggh and Zh production. Combined statistical and systematic uncertainties are given

SR4-body
Observed events 30
Estimated SM events 28±6
tt¯ 7.9±2.0
VV 4.5±2.3
Zττ 1.2±0.6
tt¯+Z 0.03±0.01
Wt 1.08±0.27
Zee, Zμμ 0.21±0.09
Others 0.80±0.30
Fake and non-prompt 12.8±4.3
Nominal MC, tt¯ 7.7
Nominal MC, VV 5.7
Nominal MC, Zττ 1.1

Interpretation

Two different sets of exclusion limits are derived for models of new physics beyond the SM. A model-independent upper limit on the visible cross-section σvis of new physics, defined as the ratio between the upper limit at 95% CL on the number of signal events S95 and the integrated luminosity, is derived in each SR by performing a fit which includes the observed yield in the SR as a constraint, and a free signal yield in the SR as an additional process. The CLs method [107] is used to derive all the exclusion confidence levels. These limits assume negligible signal contamination in the CRs. This assumption leads to conservative results when comparing with model-dependent limits for models that predict a sizeable contamination in the CRs. Model-independent upper limits are presented in Table 19.

Table 19.

Model-independent 95% CL upper limits on the visible cross-section (σvis) of new physics, the visible number of signal events (Sobs95), the visible number of signal events (Sexp95) given the expected number of background events (and ±1σ excursions of the expected number), and the discovery p-value (p(s=0)), all calculated with pseudo-experiments, are shown for each SR

Signal region σvis [fb] Sobs95 Sexp95 p(s=0)
Two-body SRA1802-body SF 0.37 13.2 10-3+4 0.20
SRA1802-body DF 0.26 9.5 7.0-1.8+3.0 0.19
SRB1402-body SF 0.24 8.6 7.2-1.8+2.7 0.28
SRB1402-body DF 0.23 8.4 6.0-1.3+2.7 0.19
SRC1102-body SF 0.36 13.0 7.4-2.0+3.1 0.05
SRC1102-body DF 0.26 9.5 6.3-1.6+2.5 0.12
Three-body SRW3-body-SF 0.17 6.1 9-2+4 0.72
SRW3-body-DF 0.21 7.5 8.5-2.0+3.5 0.85
SRt3-body-SF 0.24 8.8 6.0-1.4+2.4 0.12
SRt3-body-DF 0.23 8.2 6.6-1.6+2.8 0.28
Four-body SR4-body 0.48 17.4 16-5+7 0.37

Model-dependent limits are computed for various t~1 pair production scenarios. Profile likelihood fits are performed including the expected signal yield and its associated uncertainties in the CRs and SRs. All limits are quoted at 95% CL. When setting limits, the regions included in the mT2 shape fits (SRAx,y2-body and SRBx,y2-body) are statistically combined. Similarly, the SRW3-body and SRt3-body signal regions are statistically combined as well. For each signal model, the SR with the best expected limit is used for setting the final limit.

Limits for simplified models in which pair-produced t~1 decay with 100% branching ratio into a top quark and χ~10 are shown in the t~1χ~10 mass plane in Fig. 9. The various SRs cover the different t~1 mass ranges, as described in Table 1. Top squark masses up to 720 GeV are excluded for a massless lightest neutralino. Neutralino masses up to 300 GeV are excluded for mt~1=645 GeV. In the three-body decay hypothesis, top squark masses are excluded up to 430 GeV for mt~1-mχ~10 close to the W boson mass. In the four-body decay hypothesis, top squark masses are excluded up to 400 GeV for mt~1-mχ~10=40 GeV.

Fig. 9.

Fig. 9

Exclusion contour for a simplified model assuming t~1 pair production, decaying via t~1t()χ~10 with 100% branching ratio. The dashed grey line and the shaded yellow band are the expected limit and its ±1σ uncertainty. The thick solid red line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by ±1σ of the theoretical uncertainty. The shaded blue areas show the observed exclusion from the ATLAS s=8 TeV analyses [18]

Limits are shown for a class of simplified models in which only pair-produced t~1 decaying with 100% branching ratio into the lightest chargino and a b-quark are considered. Figure 10 shows the interpretation in the t~1χ~10 mass plane assuming that mt~1-mχ~1±=10 GeV. Top squark masses up to 700 GeV are excluded for an LSP mass up to 200 GeV.

Fig. 10.

Fig. 10

Exclusion contour for a simplified model assuming t~1 pair production, decaying via t~1bχ~1± with 100% branching ratio. The lightest chargino mass is assumed to be close to the stop mass, mχ~1±=mt~1-10 GeV. The dashed grey line and the shaded yellow band are the expected limit and its ±1σ uncertainty. The thick solid red line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by ±1σ of the theoretical uncertainty. The shaded blue area shows the observed exclusion from the ATLAS s=8 TeV analysis [18]

Finally, limits are set on a pMSSM model where the wino and bino mass parameters, M1 and M2, are set to M2=2M1 and mt~1>mχ~1±. The remaining pMSSM parameters [16, 17] have the following values: M3=2.2 TeV (gluino mass parameter), MS=mt~1mt~2=1.2 TeV (product of top squark masses), Xt/MS=6 (mixing parameter between the left- and right-handed states), and tanβ=20 (ratio of vacuum expectation values of the two Higgs doublets). The values of M3 and MS have been chosen in order to avoid the current gluino and top squark mass limits, while the value of Xt/MS is assumed to obtain a low-mass lightest top squark while maintaining the models consistent with the observed Higgs boson mass of 125 GeV. Limits are set for both the positive and negative values of μ (the Higgs mass parameter) as a function of mt~1 and mχ~10, and are shown in Fig. 11. Top squark masses up to about 700 GeV are excluded for a lightest neutralino of about 280 GeV. The sensitivity for low values of mχ~10 is limited by the mT2 selection acceptance, since mχ~1±-mχ~10 is reduced by assuming M2=2M1.

Fig. 11.

Fig. 11

Exclusion contour as a function of mt~1 and mχ~10 in the pMSSM model described in the text. Pair production of t~1 and b~1 are considered. Limits are set for both the positive (red in the figure) and negative (blue in the figure) values of μ. The dashed and dotted grey lines indicate constant values of the b~1 mass. The signal models included within the shown contours are excluded at 95% CL. The dashed lines and the shaded band are the expected limit and its ±1σ uncertainty. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section

Conclusion

This article reports a search for direct top squark pair production in final states containing two opposite-charge leptons and large missing transverse momentum, based on a 36.1fb-1 dataset of s=13 TeV proton–proton collisions recorded by the ATLAS experiment at the LHC in 2015 and 2016. Good agreement was found between the observed events in the data and the expected Standard Model yields.

Model-independent 95% CL upper limits on the visible cross-section for new phenomena were computed. The results are also interpreted in terms of simplified models assuming a range of top squark and lightest neutralino masses, with the former decaying into the latter via either a direct two-, three- or four-body decay or via an intermediate chargino state. In the case of top squark decays into t()χ~10, top squark masses below 720 GeV are excluded for a massless lightest neutralino. In the three-body decay hypothesis, top squark masses are excluded up to 430 GeV for mt~1-mχ~10 close to the W boson mass. In the four-body decay hypothesis, top squark masses are excluded up to 400 GeV for mt~1-mχ~10=40 GeV. Both these results extend the coverage of previous searches by about 100 GeV. The chargino decay mode, t~1bχ~1±, is excluded for top squark masses up to 700 GeV, assuming that mt~1-mχ~1±=10 GeV, extending the previous results by almost 200 GeV. When considering a pMSSM-inspired model including multiple decay chains, top squark masses up to about 700 GeV are excluded for a lightest neutralino of about 280 GeV. These results extend the region of supersymmetric parameter space excluded by previous LHC searches.

Acknowledgements

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.

We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; SRNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, The Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, UK.

The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (The Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [108].

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 along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. 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). Rapidity is defined as y=0.5lnE+pz/E-pz where E denotes the energy and pz is the component of the momentum along the beam direction.

2

The transverse mass is defined by the equation mT(pT,qT)=2|pT||qT|(1-cos(Δϕ)), where Δϕ is the angle between the particles of negligible mass with transverse momenta pT and qT.

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