Some more stuff

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david 2019-10-26 12:22:45 +02:00
parent 330f3cbab9
commit e8c826a1a3
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@ARTICLE{TAU21_TAGGER,
@ARTICLE{TAU21,
author = {{Thaler}, Jesse and {Van Tilburg}, Ken},
title = "{Identifying boosted objects with N-subjettiness}",
journal = {Journal of High Energy Physics},
@ -780,4 +780,846 @@ archivePrefix = {arXiv},
reportNumber = "CMS-PAS-JME-18-002",
url = "https://cds.cern.ch/record/2683870",
}
@article{CMS_PLOT,
author = "Sirunyan, A.M. and Tumasyan, Armen and Adam, Wolfgang and
Asilar, Ece and Bergauer, Thomas and Brandstetter, Johannes
and Brondolin, Erica and Dragicevic, Marko and Erö, Janos
and Flechl, Martin and Friedl, Markus and Fruehwirth,
Rudolf and Ghete, Vasile Mihai and Hartl, Christian and
Krammer, Natascha and Hrubec, Josef and Jeitler, Manfred
and König, Axel and Krätschmer, Ilse and Liko, Dietrich
and Matsushita, Takashi and Mikulec, Ivan and Rabady,
Dinyar and Rad, Navid and Rahbaran, Babak and Rohringer,
Herbert and Schieck, Jochen and Strauss, Josef and
Waltenberger, Wolfgang and Wulz, Claudia-Elisabeth and
Dvornikov, Oleg and Makarenko, Vladimir and Mossolov,
Vladimir and Suarez Gonzalez, Juan and Zykunov, Vladimir
and Shumeiko, Nikolai and Alderweireldt, Sara and De Wolf,
Eddi A and Janssen, Xavier and Lauwers, Jasper and Van De
Klundert, Merijn and Van Haevermaet, Hans and Van Mechelen,
Pierre and Van Remortel, Nick and Van Spilbeeck, Alex and
Abu Zeid, Shimaa and Blekman, Freya and D'Hondt, Jorgen and
Daci, Nadir and De Bruyn, Isabelle and Deroover, Kevin and
Lowette, Steven and Moortgat, Seth and Moreels, Lieselotte
and Olbrechts, Annik and Python, Quentin and Skovpen,
Kirill and Tavernier, Stefaan and Van Doninck, Walter and
Van Mulders, Petra and Van Parijs, Isis and Brun, Hugues
and Clerbaux, Barbara and De Lentdecker, Gilles and
Delannoy, Hugo and Fasanella, Giuseppe and Favart, Laurent
and Goldouzian, Reza and Grebenyuk, Anastasia and
Karapostoli, Georgia and Lenzi, Thomas and Léonard,
Alexandre and Luetic, Jelena and Maerschalk, Thierry and
Marinov, Andrey and Randle-conde, Aidan and Seva, Tomislav
and Vander Velde, Catherine and Vanlaer, Pascal and
Vannerom, David and Yonamine, Ryo and Zenoni, Florian and
Zhang, Fengwangdong and Cornelis, Tom and Dobur, Didar and
Fagot, Alexis and Gul, Muhammad and Khvastunov, Illia and
Poyraz, Deniz and Salva Diblen, Sinem and Schöfbeck,
Robert and Tytgat, Michael and Van Driessche, Ward and
Yazgan, Efe and Zaganidis, Nicolas and Bakhshiansohi, Hamed
and Bondu, Olivier and Brochet, Sébastien and Bruno,
Giacomo and Caudron, Adrien and De Visscher, Simon and
Delaere, Christophe and Delcourt, Martin and Francois,
Brieuc and Giammanco, Andrea and Jafari, Abideh and Komm,
Matthias and Krintiras, Georgios and Lemaitre, Vincent and
Magitteri, Alessio and Mertens, Alexandre and Musich, Marco
and Piotrzkowski, Krzysztof and Quertenmont, Loic and
Selvaggi, Michele and Vidal Marono, Miguel and Wertz,
Sébastien and Beliy, Nikita and Aldá Júnior, Walter Luiz
and Alves, Fábio Lúcio and Alves, Gilvan and Brito, Lucas
and Hensel, Carsten and Moraes, Arthur and Pol, Maria Elena
and Rebello Teles, Patricia and Belchior Batista Das
Chagas, Ewerton and Carvalho, Wagner and Chinellato, Jose
and Custódio, Analu and Melo Da Costa, Eliza and Da
Silveira, Gustavo Gil and De Jesus Damiao, Dilson and De
Oliveira Martins, Carley and Fonseca De Souza, Sandro and
Huertas Guativa, Lina Milena and Malbouisson, Helena and
Matos Figueiredo, Diego and Mora Herrera, Clemencia and
Mundim, Luiz and Nogima, Helio and Prado Da Silva, Wanda
Lucia and Santoro, Alberto and Sznajder, Andre and Tonelli
Manganote, Edmilson José and Torres Da Silva De Araujo,
Felipe and Vilela Pereira, Antonio and Ahuja, Sudha and
Bernardes, Cesar Augusto and Dogra, Sunil and Tomei, Thiago
and De Moraes Gregores, Eduardo and Mercadante, Pedro G and
Moon, Chang-Seong and Novaes, Sergio F and Padula, Sandra
and Romero Abad, David and Ruiz Vargas, José Cupertino and
Aleksandrov, Aleksandar and Hadjiiska, Roumyana and
Iaydjiev, Plamen and Rodozov, Mircho and Stoykova, Stefka
and Sultanov, Georgi and Shopova, Mariana and Dimitrov,
Anton and Glushkov, Ivan and Litov, Leander and Pavlov,
Borislav and Petkov, Peicho and Fang, Wenxing and Ahmad,
Muhammad and Bian, Jian-Guo and Chen, Guo-Ming and Chen,
He-Sheng and Chen, Mingshui and Chen, Ye and Cheng,
Tongguang and Jiang, Chun-Hua and Leggat, Duncan and Liu,
Zhenan and Romeo, Francesco and Ruan, Manqi and Shaheen,
Sarmad Masood and Spiezia, Aniello and Tao, Junquan and
Wang, Chunjie and Wang, Zheng and Zhang, Huaqiao and Zhao,
Jingzhou and Ban, Yong and Chen, Geng and Li, Qiang and
Liu, Shuai and Mao, Yajun and Qian, Si-Jin and Wang, Dayong
and Xu, Zijun and Avila, Carlos and Cabrera, Andrés and
Chaparro Sierra, Luisa Fernanda and Florez, Carlos and
Gomez, Juan Pablo and González Hernández, Carlos Felipe
and Ruiz Alvarez, José David and Sanabria, Juan Carlos and
Godinovic, Nikola and Lelas, Damir and Puljak, Ivica and
Ribeiro Cipriano, Pedro M and Sculac, Toni and Antunovic,
Zeljko and Kovac, Marko and Brigljevic, Vuko and Ferencek,
Dinko and Kadija, Kreso and Mesic, Benjamin and Susa,
Tatjana and Ather, Mohsan Waseem and Attikis, Alexandros
and Mavromanolakis, Georgios and Mousa, Jehad and Nicolaou,
Charalambos and Ptochos, Fotios and Razis, Panos A and
Rykaczewski, Hans and Finger, Miroslav and Finger Jr,
Michael and Carrera Jarrin, Edgar and El-khateeb, Esraa and
Elgammal, Sherif and Mohamed, Amr and Kadastik, Mario and
Perrini, Lucia and Raidal, Martti and Tiko, Andres and
Veelken, Christian and Eerola, Paula and Pekkanen, Juska
and Voutilainen, Mikko and Härkönen, Jaakko and Jarvinen,
Terhi and Karimäki, Veikko and Kinnunen, Ritva and
Lampén, Tapio and Lassila-Perini, Kati and Lehti, Sami and
Lindén, Tomas and Luukka, Panja-Riina and Tuominiemi,
Jorma and Tuovinen, Esa and Wendland, Lauri and Talvitie,
Joonas and Tuuva, Tuure and Besancon, Marc and Couderc,
Fabrice and Dejardin, Marc and Denegri, Daniel and Fabbro,
Bernard and Faure, Jean-Louis and Favaro, Carlotta and
Ferri, Federico and Ganjour, Serguei and Ghosh, Saranya and
Givernaud, Alain and Gras, Philippe and Hamel de
Monchenault, Gautier and Jarry, Patrick and Kucher, Inna
and Locci, Elizabeth and Machet, Martina and Malcles, Julie
and Rander, John and Rosowsky, André and Titov, Maksym and
Abdulsalam, Abdulla and Antropov, Iurii and Baffioni,
Stephanie and Beaudette, Florian and Busson, Philippe and
Cadamuro, Luca and Chapon, Emilien and Charlot, Claude and
Davignon, Olivier and Granier de Cassagnac, Raphael and Jo,
Mihee and Lisniak, Stanislav and Miné, Philippe and
Nguyen, Matthew and Ochando, Christophe and Ortona, Giacomo
and Paganini, Pascal and Pigard, Philipp and Regnard, Simon
and Salerno, Roberto and Sirois, Yves and Stahl Leiton,
Andre Govinda and Strebler, Thomas and Yilmaz, Yetkin and
Zabi, Alexandre and Zghiche, Amina and Agram, Jean-Laurent
and Andrea, Jeremy and Bloch, Daniel and Brom, Jean-Marie
and Buttignol, Michael and Chabert, Eric Christian and
Chanon, Nicolas and Collard, Caroline and Conte, Eric and
Coubez, Xavier and Fontaine, Jean-Charles and Gelé, Denis
and Goerlach, Ulrich and Le Bihan, Anne-Catherine and Van
Hove, Pierre and Gadrat, Sébastien and Beauceron,
Stephanie and Bernet, Colin and Boudoul, Gaelle and
Carrillo Montoya, Camilo Andres and Chierici, Roberto and
Contardo, Didier and Courbon, Benoit and Depasse, Pierre
and El Mamouni, Houmani and Fay, Jean and Gascon, Susan and
Gouzevitch, Maxime and Grenier, Gérald and Ille, Bernard
and Lagarde, Francois and Laktineh, Imad Baptiste and
Lethuillier, Morgan and Mirabito, Laurent and Pequegnot,
Anne-Laure and Perries, Stephane and Popov, Andrey and
Sordini, Viola and Vander Donckt, Muriel and Verdier,
Patrice and Viret, Sébastien and Toriashvili, Tengizi and
Tsamalaidze, Zviad and Autermann, Christian and Beranek,
Sarah and Feld, Lutz and Kiesel, Maximilian Knut and Klein,
Katja and Lipinski, Martin and Preuten, Marius and
Schomakers, Christian and Schulz, Johannes and Verlage,
Tobias and Albert, Andreas and Brodski, Michael and
Dietz-Laursonn, Erik and Duchardt, Deborah and Endres,
Matthias and Erdmann, Martin and Erdweg, Sören and Esch,
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Matthias and Hebbeker, Thomas and Heidemann, Carsten and
Hoepfner, Kerstin and Knutzen, Simon and Merschmeyer,
Markus and Meyer, Arnd and Millet, Philipp and Mukherjee,
Swagata and Olschewski, Mark and Padeken, Klaas and Pook,
Tobias and Radziej, Markus and Reithler, Hans and Rieger,
Marcel and Scheuch, Florian and Sonnenschein, Lars and
Teyssier, Daniel and Thüer, Sebastian and Cherepanov,
Vladimir and Flügge, Günter and Kargoll, Bastian and
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Andreas and Pistone, Claudia and Pooth, Oliver and Stahl,
Achim and Aldaya Martin, Maria and Arndt, Till and
Asawatangtrakuldee, Chayanit and Beernaert, Kelly and
Behnke, Olaf and Behrens, Ulf and Bin Anuar, Afiq Aizuddin
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and Contreras-Campana, Christian and Costanza, Francesco
and Diez Pardos, Carmen and Dolinska, Ganna and Eckerlin,
Guenter and Eckstein, Doris and Eichhorn, Thomas and Eren,
Engin and Gallo, Elisabetta and Garay Garcia, Jasone and
Geiser, Achim and Gizhko, Andrii and Grados Luyando, Juan
Manuel and Grohsjean, Alexander and Gunnellini, Paolo and
Harb, Ali and Hauk, Johannes and Hempel, Maria and Jung,
Hannes and Kalogeropoulos, Alexis and Karacheban, Olena and
Kasemann, Matthias and Keaveney, James and Kleinwort, Claus
and Korol, Ievgen and Krücker, Dirk and Lange, Wolfgang
and Lelek, Aleksandra and Lenz, Teresa and Leonard, Jessica
and Lipka, Katerina and Lobanov, Artur and Lohmann,
Wolfgang and Mankel, Rainer and Melzer-Pellmann,
Isabell-Alissandra and Meyer, Andreas Bernhard and Mittag,
Gregor and Mnich, Joachim and Mussgiller, Andreas and
Pitzl, Daniel and Placakyte, Ringaile and Raspereza, Alexei
and Roland, Benoit and Sahin, Mehmet Özgür and Saxena,
Pooja and Schoerner-Sadenius, Thomas and Spannagel, Simon
and Stefaniuk, Nazar and Van Onsem, Gerrit Patrick and
Walsh, Roberval and Wissing, Christoph and Blobel, Volker
and Centis Vignali, Matteo and Draeger, Arne-Rasmus and
Dreyer, Torben and Garutti, Erika and Gonzalez, Daniel and
Haller, Johannes and Hoffmann, Malte and Junkes, Alexandra
and Klanner, Robert and Kogler, Roman and Kovalchuk,
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Marchesini, Ivan and Marconi, Daniele and Meyer, Mareike
and Niedziela, Marek and Nowatschin, Dominik and Pantaleo,
Felice and Peiffer, Thomas and Perieanu, Adrian and Scharf,
Christian and Schleper, Peter and Schmidt, Alexander and
Schumann, Svenja and Schwandt, Joern and Sonneveld, Jory
and Stadie, Hartmut and Steinbrück, Georg and Stober,
Fred-Markus Helmut and Stöver, Marc and Tholen, Heiner and
Troendle, Daniel and Usai, Emanuele and Vanelderen, Lukas
and Vanhoefer, Annika and Vormwald, Benedikt and Akbiyik,
Melike and Barth, Christian and Baur, Sebastian and Baus,
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and Chwalek, Thorsten and Colombo, Fabio and De Boer, Wim
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Kudella, Simon and Mildner, Hannes and Mozer, Matthias
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Roscher, Frank and Schröder, Matthias and Shvetsov, Ivan
and Sieber, Georg and Simonis, Hans-Jürgen and Ulrich,
Ralf and Wayand, Stefan and Weber, Marc and Weiler, Thomas
and Williamson, Shawn and Wöhrmann, Clemens and Wolf,
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Geralis, Theodoros and Giakoumopoulou, Viktoria Athina and
Kyriakis, Aristotelis and Loukas, Demetrios and
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and Manthos, Nikolaos and Papadopoulos, Ioannis and
Paradas, Evangelos and Filipovic, Nicolas and Pasztor,
Gabriella and Bencze, Gyorgy and Hajdu, Csaba and Horvath,
Dezso and Sikler, Ferenc and Veszpremi, Viktor and
Vesztergombi, Gyorgy and Zsigmond, Anna Julia and Beni,
Noemi and Czellar, Sandor and Karancsi, János and Makovec,
Alajos and Molnar, Jozsef and Szillasi, Zoltan and Bartók,
Márton and Raics, Peter and Trocsanyi, Zoltan Laszlo and
Ujvari, Balazs and Choudhury, Somnath and Komaragiri,
Jyothsna Rani and Bahinipati, Seema and Bhowmik, Sandeep
and Mal, Prolay and Mandal, Koushik and Nayak, Aruna and
Sahoo, Deepak Kumar and Sahoo, Niladribihari and Swain,
Sanjay Kumar and Bansal, Sunil and Beri, Suman Bala and
Bhatnagar, Vipin and Bhawandeep, Bhawandeep and Chawla,
Ridhi and Kalsi, Amandeep Kaur and Kaur, Anterpreet and
Kaur, Manjit and Kumar, Ramandeep and Kumari, Priyanka and
Mehta, Ankita and Mittal, Monika and Singh, Jasbir and
Walia, Genius and Kumar, Ashok and Bhardwaj, Ashutosh and
Choudhary, Brajesh C and Garg, Rocky Bala and Keshri, Sumit
and Kumar, Ajay and Malhotra, Shivali and Naimuddin, Md and
Ranjan, Kirti and Sharma, Ramkrishna and Sharma, Varun and
Bhattacharya, Rajarshi and Bhattacharya, Satyaki and
Chatterjee, Kalyanmoy and Dey, Sourav and Dutt, Suneel and
Dutta, Suchandra and Ghosh, Shamik and Majumdar, Nayana and
Modak, Atanu and Mondal, Kuntal and Mukhopadhyay, Supratik
and Nandan, Saswati and Purohit, Arnab and Roy, Ashim and
Roy, Debarati and Roy Chowdhury, Suvankar and Sarkar, Subir
and Sharan, Manoj and Thakur, Shalini and Behera, Prafulla
Kumar and Chudasama, Ruchi and Dutta, Dipanwita and Jha,
Vishwajeet and Kumar, Vineet and Mohanty, Ajit Kumar and
Netrakanti, Pawan Kumar and Pant, Lalit Mohan and Shukla,
Prashant and Topkar, Anita and Aziz, Tariq and Dugad,
Shashikant and Kole, Gouranga and Mahakud, Bibhuprasad and
Mitra, Soureek and Mohanty, Gagan Bihari and Parida,
Bibhuti and Sur, Nairit and Sutar, Bajrang and Banerjee,
Sudeshna and Dewanjee, Ram Krishna and Ganguly, Sanmay and
Guchait, Monoranjan and Jain, Sandhya and Kumar, Sanjeev
and Maity, Manas and Majumder, Gobinda and Mazumdar, Kajari
and Sarkar, Tanmay and Wickramage, Nadeesha and Chauhan,
Shubhanshu and Dube, Sourabh and Hegde, Vinay and Kapoor,
Anshul and Kothekar, Kunal and Pandey, Shubham and Rane,
Aditee and Sharma, Seema and Chenarani, Shirin and
Eskandari Tadavani, Esmaeel and Etesami, Seyed Mohsen and
Khakzad, Mohsen and Mohammadi Najafabadi, Mojtaba and
Naseri, Mohsen and Paktinat Mehdiabadi, Saeid and Rezaei
Hosseinabadi, Ferdos and Safarzadeh, Batool and Zeinali,
Maryam and Felcini, Marta and Grunewald, Martin and
Abbrescia, Marcello and Calabria, Cesare and Caputo,
Claudio and Colaleo, Anna and Creanza, Donato and
Cristella, Leonardo and De Filippis, Nicola and De Palma,
Mauro and Fiore, Luigi and Iaselli, Giuseppe and Maggi,
Giorgio and Maggi, Marcello and Miniello, Giorgia and My,
Salvatore and Nuzzo, Salvatore and Pompili, Alexis and
Pugliese, Gabriella and Radogna, Raffaella and Ranieri,
Antonio and Selvaggi, Giovanna and Sharma, Archana and
Silvestris, Lucia and Venditti, Rosamaria and Verwilligen,
Piet and Abbiendi, Giovanni and Battilana, Carlo and
Bonacorsi, Daniele and Braibant-Giacomelli, Sylvie and
Brigliadori, Luca and Campanini, Renato and Capiluppi,
Paolo and Castro, Andrea and Cavallo, Francesca Romana and
Chhibra, Simranjit Singh and Codispoti, Giuseppe and
Cuffiani, Marco and Dallavalle, Gaetano-Marco and Fabbri,
Fabrizio and Fanfani, Alessandra and Fasanella, Daniele and
Giacomelli, Paolo and Grandi, Claudio and Guiducci, Luigi
and Marcellini, Stefano and Masetti, Gianni and Montanari,
Alessandro and Navarria, Francesco and Perrotta, Andrea and
Rossi, Antonio and Rovelli, Tiziano and Siroli, Gian Piero
and Tosi, Nicolò and Albergo, Sebastiano and Costa,
Salvatore and Di Mattia, Alessandro and Giordano,
Ferdinando and Potenza, Renato and Tricomi, Alessia and
Tuve, Cristina and Barbagli, Giuseppe and Ciulli, Vitaliano
and Civinini, Carlo and D'Alessandro, Raffaello and
Focardi, Ettore and Lenzi, Piergiulio and Meschini, Marco
and Paoletti, Simone and Russo, Lorenzo and Sguazzoni,
Giacomo and Strom, Derek and Viliani, Lorenzo and Benussi,
Luigi and Bianco, Stefano and Fabbri, Franco and Piccolo,
Davide and Primavera, Federica and Calvelli, Valerio and
Ferro, Fabrizio and Monge, Maria Roberta and Robutti,
Enrico and Tosi, Silvano and Brianza, Luca and Brivio,
Francesco and Ciriolo, Vincenzo and Dinardo, Mauro Emanuele
and Fiorendi, Sara and Gennai, Simone and Ghezzi, Alessio
and Govoni, Pietro and Malberti, Martina and Malvezzi,
Sandra and Manzoni, Riccardo Andrea and Menasce, Dario and
Moroni, Luigi and Paganoni, Marco and Pedrini, Daniele and
Pigazzini, Simone and Ragazzi, Stefano and Tabarelli de
Fatis, Tommaso and Buontempo, Salvatore and Cavallo, Nicola
and De Nardo, Guglielmo and Di Guida, Salvatore and
Esposito, Marco and Fabozzi, Francesco and Fienga,
Francesco and Iorio, Alberto Orso Maria and Lanza, Giuseppe
and Lista, Luca and Meola, Sabino and Paolucci, Pierluigi
and Sciacca, Crisostomo and Thyssen, Filip and Azzi,
Patrizia and Bacchetta, Nicola and Benato, Lisa and
Bisello, Dario and Boletti, Alessio and Carlin, Roberto and
Carvalho Antunes De Oliveira, Alexandra and Checchia, Paolo
and Dall'Osso, Martino and De Castro Manzano, Pablo and
Dorigo, Tommaso and Gozzelino, Andrea and Lacaprara,
Stefano and Margoni, Martino and Meneguzzo, Anna Teresa and
Passaseo, Marina and Pazzini, Jacopo and Pozzobon, Nicola
and Ronchese, Paolo and Rossin, Roberto and Simonetto,
Franco and Torassa, Ezio and Ventura, Sandro and Zanetti,
Marco and Zotto, Pierluigi and Zumerle, Gianni and
Braghieri, Alessandro and Fallavollita, Francesco and
Magnani, Alice and Montagna, Paolo and Ratti, Sergio P and
Re, Valerio and Ressegotti, Martina and Riccardi, Cristina
and Salvini, Paola and Vai, Ilaria and Vitulo, Paolo and
Alunni Solestizi, Luisa and Bilei, Gian Mario and
Ciangottini, Diego and Fanò, Livio and Lariccia, Paolo and
Leonardi, Roberto and Mantovani, Giancarlo and Mariani,
Valentina and Menichelli, Mauro and Saha, Anirban and
Santocchia, Attilio and Androsov, Konstantin and Azzurri,
Paolo and Bagliesi, Giuseppe and Bernardini, Jacopo and
Boccali, Tommaso and Castaldi, Rino and Ciocci, Maria
Agnese and Dell'Orso, Roberto and Fedi, Giacomo and Giassi,
Alessandro and Grippo, Maria Teresa and Ligabue, Franco and
Lomtadze, Teimuraz and Martini, Luca and Messineo, Alberto
and Palla, Fabrizio and Rizzi, Andrea and Savoy-Navarro,
Aurore and Spagnolo, Paolo and Tenchini, Roberto and
Tonelli, Guido and Venturi, Andrea and Verdini, Piero
Giorgio and Barone, Luciano and Cavallari, Francesca and
Cipriani, Marco and Del Re, Daniele and Diemoz, Marcella
and Gelli, Simone and Longo, Egidio and Margaroli, Fabrizio
and Marzocchi, Badder and Meridiani, Paolo and Organtini,
Giovanni and Paramatti, Riccardo and Preiato, Federico and
Rahatlou, Shahram and Rovelli, Chiara and Santanastasio,
Francesco and Amapane, Nicola and Arcidiacono, Roberta and
Argiro, Stefano and Arneodo, Michele and Bartosik, Nazar
and Bellan, Riccardo and Biino, Cristina and Cartiglia,
Nicolo and Cenna, Francesca and Costa, Marco and Covarelli,
Roberto and Degano, Alessandro and Demaria, Natale and
Finco, Linda and Kiani, Bilal and Mariotti, Chiara and
Maselli, Silvia and Migliore, Ernesto and Monaco, Vincenzo
and Monteil, Ennio and Monteno, Marco and Obertino, Maria
Margherita and Pacher, Luca and Pastrone, Nadia and
Pelliccioni, Mario and Pinna Angioni, Gian Luca and Ravera,
Fabio and Romero, Alessandra and Ruspa, Marta and Sacchi,
Roberto and Shchelina, Ksenia and Sola, Valentina and
Solano, Ada and Staiano, Amedeo and Traczyk, Piotr and
Belforte, Stefano and Casarsa, Massimo and Cossutti, Fabio
and Della Ricca, Giuseppe and Zanetti, Anna and Kim, Dong
Hee and Kim, Gui Nyun and Kim, Min Suk and Lee, Sangeun and
Lee, Seh Wook and Oh, Young Do and Sekmen, Sezen and Son,
Dong-Chul and Yang, Yu Chul and Lee, Ari and Kim, Hyunchul
and Brochero Cifuentes, Javier Andres and Kim, Tae Jeong
and Cho, Sungwoong and Choi, Suyong and Go, Yeonju and
Gyun, Dooyeon and Ha, Seungkyu and Hong, Byung-Sik and Jo,
Youngkwon and Kim, Yongsun and Lee, Kisoo and Lee, Kyong
Sei and Lee, Songkyo and Lim, Jaehoon and Park, Sung Keun
and Roh, Youn and Almond, John and Kim, Junho and Lee,
Haneol and Oh, Sung Bin and Radburn-Smith, Benjamin Charles
and Seo, Seon-hee and Yang, Unki and Yoo, Hwi Dong and Yu,
Geum Bong and Choi, Minkyoo and Kim, Hyunyong and Kim, Ji
Hyun and Lee, Jason Sang Hun and Park, Inkyu and Ryu,
Geonmo and Ryu, Min Sang and Choi, Young-Il and Goh,
Junghwan and Hwang, Chanwook and Lee, Jongseok and Yu,
Intae and Dudenas, Vytautas and Juodagalvis, Andrius and
Vaitkus, Juozas and Ahmed, Ijaz and Ibrahim, Zainol Abidin
and Md Ali, Mohd Adli Bin and Mohamad Idris, Faridah and
Wan Abdullah, Wan Ahmad Tajuddin and Yusli, Mohd Nizam and
Zolkapli, Zukhaimira and Castilla-Valdez, Heriberto and De
La Cruz-Burelo, Eduard and Heredia-De La Cruz, Ivan and
Hernandez-Almada, Alberto and Lopez-Fernandez, Ricardo and
Magaña Villalba, Ricardo and Mejia Guisao, Jhovanny and
Sánchez Hernández, Alberto and Carrillo Moreno, Salvador
and Oropeza Barrera, Cristina and Vazquez Valencia, Fabiola
and Carpinteyro, Severiano and Pedraza, Isabel and Salazar
Ibarguen, Humberto Antonio and Uribe Estrada, Cecilia and
Morelos Pineda, Antonio and Krofcheck, David and Butler,
Philip H and Ahmad, Ashfaq and Ahmad, Muhammad and Hassan,
Qamar and Hoorani, Hafeez R and Khan, Wajid Ali and
Saddique, Asif and Shah, Mehar Ali and Shoaib, Muhammad and
Waqas, Muhammad and Bialkowska, Helena and Bluj, Michal and
Boimska, Bozena and Frueboes, Tomasz and Górski, Maciej
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Doroba, Krzysztof and Kalinowski, Artur and Konecki, Marcin
and Krolikowski, Jan and Misiura, Maciej and Olszewski,
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Joao and Toldaiev, Oleksii and Vadruccio, Daniele and
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Alexander and Malakhov, Alexander and Matveev, Viktor and
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Victor and Oreshkin, Vadim and Sulimov, Valentin and
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Yuri and Shtol, Dmitry and Azhgirey, Igor and Bayshev, Igor
and Bitioukov, Sergei and Elumakhov, Dmitry and Kachanov,
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and Fouz, Maria Cruz and Garcia-Abia, Pablo and Gonzalez
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Maurizio and Racz, Attila and Reis, Thomas and Rolandi,
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Cole, Joanne and Hobson, Peter R and Khan, Akram and
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Call, Kenneth and Dittmann, Jay and Hatakeyama, Kenichi and
Liu, Hongxuan and Pastika, Nathaniel and Bartek, Rachel and
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and Han, Jiyeon and Hindrichs, Otto and Khukhunaishvili,
Aleko and Lo, Kin Ho and Tan, Ping and Verzetti, Mauro and
Agapitos, Antonis and Chou, John Paul and Gershtein, Yuri
and Gómez Espinosa, Tirso Alejandro and Halkiadakis, Eva
and Heindl, Maximilian and Hughes, Elliot and Kaplan,
Steven and Kunnawalkam Elayavalli, Raghav and Kyriacou,
Savvas and Lath, Amitabh and Montalvo, Roy and Nash, Kevin
and Osherson, Marc and Saka, Halil and Salur, Sevil and
Schnetzer, Steve and Sheffield, David and Somalwar, Sunil
and Stone, Robert and Thomas, Scott and Thomassen, Peter
and Walker, Matthew and Delannoy, Andrés G and Foerster,
Mark and Heideman, Joseph and Riley, Grant and Rose, Keith
and Spanier, Stefan and Thapa, Krishna and Bouhali, Othmane
and Celik, Ali and Dalchenko, Mykhailo and De Mattia, Marco
and Delgado, Andrea and Dildick, Sven and Eusebi, Ricardo
and Gilmore, Jason and Huang, Tao and Juska, Evaldas and
Kamon, Teruki and Mueller, Ryan and Pakhotin, Yuriy and
Patel, Rishi and Perloff, Alexx and Perniè, Luca and
Rathjens, Denis and Safonov, Alexei and Tatarinov, Aysen
and Ulmer, Keith and Akchurin, Nural and Damgov, Jordan and
De Guio, Federico and Dragoiu, Cosmin and Dudero, Phillip
Russell and Faulkner, James and Gurpinar, Emine and Kunori,
Shuichi and Lamichhane, Kamal and Lee, Sung Won and
Libeiro, Terence and Peltola, Timo and Undleeb, Sonaina and
Volobouev, Igor and Wang, Zhixing and Greene, Senta and
Gurrola, Alfredo and Janjam, Ravi and Johns, Willard and
Maguire, Charles and Melo, Andrew and Ni, Hong and Sheldon,
Paul and Tuo, Shengquan and Velkovska, Julia and Xu, Qiao
and Arenton, Michael Wayne and Barria, Patrizia and Cox,
Bradley and Hirosky, Robert and Ledovskoy, Alexander and
Li, Hengne and Neu, Christopher and Sinthuprasith, Tutanon
and Sun, Xin and Wang, Yanchu and Wolfe, Evan and Xia, Fan
and Clarke, Christopher and Harr, Robert and Karchin, Paul
Edmund and Sturdy, Jared and Zaleski, Shawn and Belknap,
Donald and Buchanan, James and Caillol, Cécile and Dasu,
Sridhara and Dodd, Laura and Duric, Senka and Gomber,
Bhawna and Grothe, Monika and Herndon, Matthew and Hervé,
Alain and Hussain, Usama and Klabbers, Pamela and Lanaro,
Armando and Levine, Aaron and Long, Kenneth and Loveless,
Richard and Pierro, Giuseppe Antonio and Polese, Giovanni
and Ruggles, Tyler and Savin, Alexander and Smith, Nicholas
and Smith, Wesley H and Taylor, Devin and Woods, Nathaniel",
title = "{Particle-flow reconstruction and global event description
with the CMS detector. Particle-flow reconstruction and
global event description with the CMS detector}",
journal = "JINST",
collaboration = "CMS Collaboration",
number = "CMS-PRF-14-001. CMS-PRF-14-001-004. 10",
volume = "12",
pages = "P10003. 82 p",
month = "Jun",
year = "2017",
reportNumber = "CMS-PRF-14-001",
url = "https://cds.cern.ch/record/2270046",
note = "Replaced with the published version. Added the journal
reference and DOI. All the figures and tables can be found
at
http://cms-results.web.cern.ch/cms-results/public-results/publications/PRF-14-001
(CMS Public Pages)",
doi = "10.1088/1748-0221/12/10/P10003",
}

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</bcf:bibdata>
<bcf:section number="0">
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<bcf:citekey order="2">QSTAR_THEORY</bcf:citekey>
<bcf:citekey order="3">PREV_RESEARCH</bcf:citekey>
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[]\TU/TimesNewRoman(0)/m/n/12 Florian Beau-dette. The CMS Particle Flow Al
-gorithm. In: \TU/TimesNewRoman(0)/m/it/12 arXiv e-prints\TU/TimesNewRoman(0
)/m/n/12 ,
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@ -11,8 +11,16 @@ header-includes: |
\setlength{\parskip}{0.5em}
\bibliographystyle{lucas_unsrt}
abstract: |
A search for an excited quark state, called q\*, is presented using data recorded by CMS during the years 2016, 2017
and 2018. By analysing its decay channels to qW and qZ, a minimum mass of 6.1 TeV resp. 5.5 TeV is established. This
limit is about 1 TeV higher than the limits found by a previous research of data collected by CMS in 2016
[@PREV_RESEARCH], excluding the q\* particle up to a mass of 5.0 TeV resp. 4.7 TeV. Also a comparison of the new
DeepAK8 [@DEEP_BOOSTED] and the older N-subjettiness [@TAU21] tagger is conducted, showing that the newer DeepAK8
tagger is currently approximately at the same level as the N-subjettiness tagger, but has the potential to further
improve in performance.
```{=tex}
Abstract.
\end{abstract}
\begin{abstract}
Abstract 2.
@ -277,13 +285,20 @@ $L_{int} = \int L dt$.
The data used in this thesis was recorded by the Compact Muon Solenoid (CMS). It is one of the four main experiments at
the Large Hadron Collider. It can detect all elementary particles of the standard model except neutrinos. For that, it
has an onion like setup. The particles produced in a collision first go through a tracking system. They then pass an
electromegnetic as well as a hadronic calorimeter. This part is surrounded by a superconducting solenoid that generates
a magenetic field of 3.8 T. Outside of the solenoid are big muon chambers. In 2016 the CMS captured data of a integrated
luminosity of $\SI{35.92}{\per\femto\barn}$. In 2017 it collected $\SI{41.53}{\per\femto\barn}$ and in 2018
$\SI{59.74}{\per\femto\barn}$. Therefore the combined dataset of all three years has a total integrated luminosity of
has an onion like setup, as can be seen in [@fig:cms_setup]. The particles produced in a collision first go through a
tracking system. They then pass an electromegnetic as well as a hadronic calorimeter. This part is surrounded by a
superconducting solenoid that generates a magenetic field of 3.8 T. Outside of the solenoid are big muon chambers. In
2016 the CMS captured data of an integrated luminosity of $\SI{37.80}{\per\femto\barn}$. In 2017 it collected
$\SI{44.98}{\per\femto\barn}$ and in 2018 $\SI{63.67}{\per\femto\barn}$. Of that data, in 2016
$\SI{35.92}{\per\femto\barn}$, in 2017 $\SI{41.53}{\per\femto\barn}$ and in 2018 $\SI{59.74}{\per\femto\barn}$ were
usable for research. Therefore the combined integrated luminosity of data usable for research is
$\SI{137.19}{\per\femto\barn}$.
![
The setup of the Compact Muon Solenoid showing its onion like structure, the different detector parts and where
different particles are detected [@CMS_PLOT].
](./figures/cms_setup.png){#fig:cms_setup}
### Coordinate conventions
@ -330,9 +345,8 @@ and therefore makes it possible to measure momentum of charged particles by bend
### The muon system
Outside of the solenoid there is only the muon system. It consists of three types of gas detectors, the drift tubes,
cathode strip chambers and resistive plate chambers. The system is divided into a barrel part and two endcaps. Together
they cover $0 < |\eta| < 2.4$. The muons are the only detected particles, that can pass all the other systems
without a significant energy loss.
cathode strip chambers and resistive plate chambers. It covers a total of $0 < |\eta| < 2.4$. The muons are the only
detected particles, that can pass all the other systems without a significant energy loss.
### The Trigger system
@ -378,8 +392,8 @@ Comparison of the $k_t$, Cambridge/Aachen, SISCone and anti-$k_t$ algorithms clu
with many random soft "ghosts". Taken from [@ANTIKT]
](./figures/antikt-comparision.png){#fig:antiktcomparison}
[@fig:antiktcomparison] clearly shows, that the jets reconstructed using the anti-$k_t$ algorithm are closest to having
a cone like shape and are so fucking beautiful.
[@Fig:antiktcomparison] shows, that the jets reconstructed using the anti-$k_t$ algorithm have the clearest cone like
shape and is therefore chosen for this thesis.
\newpage
@ -391,16 +405,17 @@ either exclude the q\* particle to even higher masses than already done or maybe
As described in [@sec:qs], the decay of the q\* particle to a quark and a vector boson with the vector boson then
decaying hadronically will be investigated. This is the second most probable decay of the q\* particle and easier to
analyse than the dominant decay to a quark and a gluon. Therefore it is a good choice for this research.
The decay q\* $\rightarrow$ qV + q $\rightarrow q\bar{q}$ + q results in two jets, because the decay products of the
heavy vector boson are highly boosted, causing them to be very close together and therefore be reconstructed as one jet.
The dijet invariant mass of those two jets, which is identical to the mass of the q\* particle, is reconstructed. The
only background considered is the QCD background described in [@sec:qcdbg]. A selection using different kinematic
variables as well as a tagger to identify jets from the decay of a vector boson is introduced to reduce the background
and increase the sensitivity for the signal. After that, it will be looked for a peak in the dijet invariant mass
distribution at the resonance mass of the q\* particle.
The data studied was collected by the CMS experiment in the years 2016, 2017 and 2018. It is analysed with the Particle
Flow algorithm to reconstruct jets and all the other particles forming during the collision. The jets are then clustered
using the anti-$k_t$ algorithm with the distance parameter R being 0.8.
To find the signal events, described in [@sec:qs], in the data, this thesis looks at the dijet invariant mass
distribution. The only background considered is the QCD background described in [@sec:qcdbg]. A selection using
different kinematic variables as well as a tagger to identify jets from the decay of a vector boson is introduced to
reduce the background and increase the sensitivity for the signal. After that, it will be looked for a peak in the dijet
invariant mass distribution at the resonance mass of the q\* particle.
The data studied were collected by the CMS experiment in the years 2016, 2017 and 2018. They are analysed with the
Particle Flow algorithm to reconstruct jets and all the other particles forming during the collision. The jets are then
clustered using the anti-$k_t$ algorithm with the distance parameter R being 0.8.
The analysis will be conducted with two different sets of data. First, only the data collected by CMS in 2016 will be
used to compare the results to the previous analysis [@PREV_RESEARCH]. Then the combined data from 2016, 2017 and 2018
@ -641,11 +656,11 @@ QCD effects. This value will be optimized afterwards to make sure the maximum ef
## N-Subjettiness
The N-subjettiness $\tau_N$ is a jet shape parameter designed to identify boosted hadronically-decaying objects. When a
vector boson decays hadronically, it produces two quarks each causing a jet. But because of the high mass of the vector
bosons, the particles are highly boosted and appear, after applying a clustering algorithm, as just one. This algorithm
now tries to figure out, whether one jet might consist of two subjets by using the kinematics and positions of the
constituent particles of this jet.
The N-subjettiness [@TAU21] $\tau_N$ is a jet shape parameter designed to identify boosted hadronically-decaying
objects. When a vector boson decays hadronically, it produces two quarks each causing a jet. But because of the high
mass of the vector bosons, the particles are highly boosted and appear, after applying a clustering algorithm, as just
one. This algorithm now tries to figure out, whether one jet might consist of two subjets by using the kinematics and
positions of the constituent particles of this jet.
The N-subjettiness is defined as
\begin{equation} \tau_N = \frac{1}{d_0} \sum_k p_{T,k} \cdot \text{min}\{ \Delta R_{1,k}, \Delta R_{2,k}, …, \Delta
@ -664,8 +679,14 @@ softdropmass window is used. If both of them pass, the one with higher $p_t$ is
## DeepAK8
The DeepAK8 tagger uses a deep neural network (DNN) to identify decays originating in a vector boson. It is supposed
to give better efficiencies than the older N-Subjettiness method.
The DeepAK8 tagger [@DEEP_BOOSTED] uses a deep neural network (DNN) to identify decays originating in a vector boson. It
claims to reduce the background rate by up to a factor of ~10 with the same signal efficiency compared to
non-machine-learning approaches like the N-Subjettiness method. This is supported by [@fig:ak8_eff], showing a
comparision of background and signal efficiency of the DeepAK8 tagger, with, between others, the $\tau_{21}$ tagger also
used in this analysis.
![Comparison of tagger efficiencies, showing, between others, the DeepAK8 and $\tau_{21}$ tagger used in this analysis.
Taken from [@DEEP_BOOSTED]](./figures/deep_ak8.pdf){#fig:ak8_eff width=80%}
The DNN has two input lists for each jet. The first is a list of up to 100 constituent particles of the jet, sorted by
decreasing $p_t$. A total of 42 properties of the particles such es $p_t$, energy deposit, charge and the
@ -700,6 +721,9 @@ around the resonance nominal mass is chosen. The significance is then calculated
discriminant of the two taggers and then plotted in dependence on the minimum resp. maximum allowed value of the
discriminant to pass the selection for the deep boosted resp. the N-subjettiness tagger.
The optimization process is done using only the data from year 2018, assuming the taggers have similar performances on
the data of the different years.
\begin{figure}
\begin{minipage}{0.5\textwidth}
\includegraphics{./figures/sig-db.pdf}
@ -731,13 +755,12 @@ for all masspoints of the decay to qW and qZ and for both datasets used, the one
2017 and 2018.
To extract the signal from the background, its cross section limit is calculated using a frequentist asymptotic limit
calculator. It uses the fit that was performed to the simulated samples to calculate expected limits for all the
available masspoints and then a fit to the actual data to determine an observed limit. If there's no resonance of the
q\* particle in the data, the observed limit should lie within the $2\sigma$ environment of the expected limit. After
that, the crossing of the theory line, representing the cross section limits expected, if the q\* particle would exist,
and the observed data is calculated, to have a limit of mass up to which the existence of the q\* particle can be
excluded. To find the uncertainty of this result, the crossing of the theory line plus, respectively minus, its
uncertainty with the observed limit is also calculated.
calculator. It performs a shape analysis of the dijet invariant mass spectrum to determine an expected and an observed
limit. If there's no resonance of the q\* particle in the data, the observed limit should lie within the $2\sigma$
environment of the expected limit. After that, the crossing of the theory line, representing the cross section limits
expected, if the q\* particle would exist, and the observed data is calculated, to have a limit of mass up to which the
existence of the q\* particle can be excluded. To find the uncertainty of this result, the crossing of the theory line
plus, respectively minus, its uncertainty with the observed limit is also calculated.
## Uncertainties
@ -773,7 +796,7 @@ lowest possible mass of the q\* particle, by finding the crossing of the theory
limit. In [@fig:res2016] it can be seen, that the observed limit in the region where theory and observed limit cross is
very high compared to when using the N-subjettiness tagger. Therefore the two lines cross earlier, which results in
lower exclusion limits on the mass of the q\* particle causing the deep boosted tagger to perform worse than the
N-subjettiness tagger in regards of establishing those limits as can be seen in {@tbl:res2016}. The table also shows the
N-subjettiness tagger in regards of establishing those limits as can be seen in [@tbl:res2016]. The table also shows the
upper and lower limits on the mass found by calculating the crossing of the theory plus resp. minus its uncertainty. Due
to the theory and the observed limits line being very flat in the high TeV region, even a small uncertainty of the
theory can cause a high difference of the mass limit.
@ -891,8 +914,6 @@ working but should have been applied to the combined dataset.
Recently, some issues with the training of the deep boosted tagger used in this analysis were also found, which might
explain, why it didn't perform much better in general.
![Comparision of deep boosted and N-subjettiness tagger in the high purity category using the data from year 2018.
](./figures/limit_comp_2018.pdf){#fig:comp_2018}
\begin{figure}
\begin{minipage}{0.5\textwidth}
@ -906,6 +927,10 @@ decay to qZ}
\label{fig:limit_comp}
\end{figure}
![Comparision of deep boosted and N-subjettiness tagger in the high purity category using the data from year 2018.
](./figures/limit_comp_2018.pdf){#fig:comp_2018 width=60%}
\clearpage
\newpage

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@ -115,7 +115,18 @@
\begin{document}
\maketitle
\begin{abstract}
Abstract.
A search for an excited quark state, called q*, is presented using data
recorded by CMS during the years 2016, 2017 and 2018. By analysing its
decay channels to qW and qZ, a minimum mass of 6.1 TeV resp. 5.5 TeV is
established. This limit is about 1 TeV higher than the limits found by a
previous research of data collected by CMS in 2016
\autocite{PREV_RESEARCH}, excluding the q* particle up to a mass of 5.0
TeV resp. 4.7 TeV. Also a comparison of the new DeepAK8
\autocite{DEEP_BOOSTED} and the older N-subjettiness \autocite{TAU21}
tagger is conducted, showing that the newer DeepAK8 tagger is currently
approximately at the same level as the N-subjettiness tagger, but has
the potential to further improve in performance.
\end{abstract}
\begin{abstract}
Abstract 2.
@ -485,17 +496,29 @@ LHC, the integrated luminosity is introduced as \(L_{int} = \int L dt\).
The data used in this thesis was recorded by the Compact Muon Solenoid
(CMS). It is one of the four main experiments at the Large Hadron
Collider. It can detect all elementary particles of the standard model
except neutrinos. For that, it has an onion like setup. The particles
produced in a collision first go through a tracking system. They then
pass an electromegnetic as well as a hadronic calorimeter. This part is
surrounded by a superconducting solenoid that generates a magenetic
field of 3.8 T. Outside of the solenoid are big muon chambers. In 2016
the CMS captured data of a integrated luminosity of
\(\SI{35.92}{\per\femto\barn}\). In 2017 it collected
\(\SI{41.53}{\per\femto\barn}\) and in 2018
\(\SI{59.74}{\per\femto\barn}\). Therefore the combined dataset of all
three years has a total integrated luminosity of
\(\SI{137.19}{\per\femto\barn}\).
except neutrinos. For that, it has an onion like setup, as can be seen
in fig.~\ref{fig:cms_setup}. The particles produced in a collision first
go through a tracking system. They then pass an electromegnetic as well
as a hadronic calorimeter. This part is surrounded by a superconducting
solenoid that generates a magenetic field of 3.8 T. Outside of the
solenoid are big muon chambers. In 2016 the CMS captured data of an
integrated luminosity of \(\SI{37.80}{\per\femto\barn}\). In 2017 it
collected \(\SI{44.98}{\per\femto\barn}\) and in 2018
\(\SI{63.67}{\per\femto\barn}\). Of that data, in 2016
\(\SI{35.92}{\per\femto\barn}\), in 2017 \(\SI{41.53}{\per\femto\barn}\)
and in 2018 \(\SI{59.74}{\per\femto\barn}\) were usable for research.
Therefore the combined integrated luminosity of data usable for research
is \(\SI{137.19}{\per\femto\barn}\).
\begin{figure}
\hypertarget{fig:cms_setup}{%
\centering
\includegraphics{./figures/cms_setup.png}
\caption{The setup of the Compact Muon Solenoid showing its onion like
structure, the different detector parts and where different particles
are detected \autocite{CMS_PLOT}.}\label{fig:cms_setup}
}
\end{figure}
\hypertarget{coordinate-conventions}{%
\subsubsection{Coordinate conventions}\label{coordinate-conventions}}
@ -572,10 +595,9 @@ tracks.
Outside of the solenoid there is only the muon system. It consists of
three types of gas detectors, the drift tubes, cathode strip chambers
and resistive plate chambers. The system is divided into a barrel part
and two endcaps. Together they cover \(0 < |\eta| < 2.4\). The muons are
the only detected particles, that can pass all the other systems without
a significant energy loss.
and resistive plate chambers. It covers a total of \(0 < |\eta| < 2.4\).
The muons are the only detected particles, that can pass all the other
systems without a significant energy loss.
\hypertarget{the-trigger-system}{%
\subsubsection{The Trigger system}\label{the-trigger-system}}
@ -650,9 +672,9 @@ random soft \enquote{ghosts}. Taken from
}
\end{figure}
fig.~\ref{fig:antiktcomparison} clearly shows, that the jets
reconstructed using the anti-\(k_t\) algorithm are closest to having a
cone like shape and are so fucking beautiful.
Fig.~\ref{fig:antiktcomparison} shows, that the jets reconstructed using
the anti-\(k_t\) algorithm have the clearest cone like shape and is
therefore chosen for this thesis.
\newpage
@ -668,22 +690,24 @@ quark and a vector boson with the vector boson then decaying
hadronically will be investigated. This is the second most probable
decay of the q* particle and easier to analyse than the dominant decay
to a quark and a gluon. Therefore it is a good choice for this research.
The data studied was collected by the CMS experiment in the years 2016,
2017 and 2018. It is analysed with the Particle Flow algorithm to
reconstruct jets and all the other particles forming during the
collision. The jets are then clustered using the anti-\(k_t\) algorithm
with the distance parameter R being 0.8.
To find the signal events, described in sec.~\ref{sec:qs}, in the data,
this thesis looks at the dijet invariant mass distribution. The only
background considered is the QCD background described in
The decay q* \(\rightarrow\) qV + q \(\rightarrow q\bar{q}\) + q results
in two jets, because the decay products of the heavy vector boson are
highly boosted, causing them to be very close together and therefore be
reconstructed as one jet. The dijet invariant mass of those two jets,
which is identical to the mass of the q* particle, is reconstructed. The
only background considered is the QCD background described in
sec.~\ref{sec:qcdbg}. A selection using different kinematic variables as
well as a tagger to identify jets from the decay of a vector boson is
introduced to reduce the background and increase the sensitivity for the
signal. After that, it will be looked for a peak in the dijet invariant
mass distribution at the resonance mass of the q* particle.
The data studied were collected by the CMS experiment in the years 2016,
2017 and 2018. They are analysed with the Particle Flow algorithm to
reconstruct jets and all the other particles forming during the
collision. The jets are then clustered using the anti-\(k_t\) algorithm
with the distance parameter R being 0.8.
The analysis will be conducted with two different sets of data. First,
only the data collected by CMS in 2016 will be used to compare the
results to the previous analysis \autocite{PREV_RESEARCH}. Then the
@ -1006,14 +1030,14 @@ possible is achieved.
\hypertarget{n-subjettiness}{%
\subsection{N-Subjettiness}\label{n-subjettiness}}
The N-subjettiness \(\tau_N\) is a jet shape parameter designed to
identify boosted hadronically-decaying objects. When a vector boson
decays hadronically, it produces two quarks each causing a jet. But
because of the high mass of the vector bosons, the particles are highly
boosted and appear, after applying a clustering algorithm, as just one.
This algorithm now tries to figure out, whether one jet might consist of
two subjets by using the kinematics and positions of the constituent
particles of this jet. The N-subjettiness is defined as
The N-subjettiness \autocite{TAU21} \(\tau_N\) is a jet shape parameter
designed to identify boosted hadronically-decaying objects. When a
vector boson decays hadronically, it produces two quarks each causing a
jet. But because of the high mass of the vector bosons, the particles
are highly boosted and appear, after applying a clustering algorithm, as
just one. This algorithm now tries to figure out, whether one jet might
consist of two subjets by using the kinematics and positions of the
constituent particles of this jet. The N-subjettiness is defined as
\begin{equation} \tau_N = \frac{1}{d_0} \sum_k p_{T,k} \cdot \text{min}\{ \Delta R_{1,k}, \Delta R_{2,k}, …, \Delta
R_{N,k} \} \end{equation}
@ -1039,9 +1063,24 @@ with higher \(p_t\) is chosen.
\hypertarget{deepak8}{%
\subsection{DeepAK8}\label{deepak8}}
The DeepAK8 tagger uses a deep neural network (DNN) to identify decays
originating in a vector boson. It is supposed to give better
efficiencies than the older N-Subjettiness method.
The DeepAK8 tagger \autocite{DEEP_BOOSTED} uses a deep neural network
(DNN) to identify decays originating in a vector boson. It claims to
reduce the background rate by up to a factor of \textasciitilde10 with
the same signal efficiency compared to non-machine-learning approaches
like the N-Subjettiness method. This is supported by
fig.~\ref{fig:ak8_eff}, showing a comparision of background and signal
efficiency of the DeepAK8 tagger, with, between others, the
\(\tau_{21}\) tagger also used in this analysis.
\begin{figure}
\hypertarget{fig:ak8_eff}{%
\centering
\includegraphics[width=0.8\textwidth,height=\textheight]{./figures/deep_ak8.pdf}
\caption{Comparison of tagger efficiencies, showing, between others, the
DeepAK8 and \(\tau_{21}\) tagger used in this analysis. Taken from
\autocite{DEEP_BOOSTED}}\label{fig:ak8_eff}
}
\end{figure}
The DNN has two input lists for each jet. The first is a list of up to
100 constituent particles of the jet, sorted by decreasing \(p_t\). A
@ -1095,6 +1134,10 @@ two taggers and then plotted in dependence on the minimum resp. maximum
allowed value of the discriminant to pass the selection for the deep
boosted resp. the N-subjettiness tagger.
The optimization process is done using only the data from year 2018,
assuming the taggers have similar performances on the data of the
different years.
\begin{figure}
\begin{minipage}{0.5\textwidth}
\includegraphics{./figures/sig-db.pdf}
@ -1135,10 +1178,9 @@ and qZ and for both datasets used, the one from 2016 und the combined
one of 2016, 2017 and 2018.
To extract the signal from the background, its cross section limit is
calculated using a frequentist asymptotic limit calculator. It uses the
fit that was performed to the simulated samples to calculate expected
limits for all the available masspoints and then a fit to the actual
data to determine an observed limit. If there's no resonance of the q*
calculated using a frequentist asymptotic limit calculator. It performs
a shape analysis of the dijet invariant mass spectrum to determine an
expected and an observed limit. If there's no resonance of the q*
particle in the data, the observed limit should lie within the
\(2\sigma\) environment of the expected limit. After that, the crossing
of the theory line, representing the cross section limits expected, if
@ -1199,8 +1241,8 @@ limit cross is very high compared to when using the N-subjettiness
tagger. Therefore the two lines cross earlier, which results in lower
exclusion limits on the mass of the q* particle causing the deep boosted
tagger to perform worse than the N-subjettiness tagger in regards of
establishing those limits as can be seen in \{tbl.~\ref{tbl:res2016}\}.
The table also shows the upper and lower limits on the mass found by
establishing those limits as can be seen in tbl.~\ref{tbl:res2016}. The
table also shows the upper and lower limits on the mass found by
calculating the crossing of the theory plus resp. minus its uncertainty.
Due to the theory and the observed limits line being very flat in the
high TeV region, even a small uncertainty of the theory can cause a high
@ -1357,16 +1399,6 @@ Recently, some issues with the training of the deep boosted tagger used
in this analysis were also found, which might explain, why it didn't
perform much better in general.
\begin{figure}
\hypertarget{fig:comp_2018}{%
\centering
\includegraphics{./figures/limit_comp_2018.pdf}
\caption{Comparision of deep boosted and N-subjettiness tagger in the
high purity category using the data from year
2018.}\label{fig:comp_2018}
}
\end{figure}
\begin{figure}
\begin{minipage}{0.5\textwidth}
\includegraphics{./figures/limit_comp_w.pdf}
@ -1379,6 +1411,16 @@ decay to qZ}
\label{fig:limit_comp}
\end{figure}
\begin{figure}
\hypertarget{fig:comp_2018}{%
\centering
\includegraphics[width=0.6\textwidth,height=\textheight]{./figures/limit_comp_2018.pdf}
\caption{Comparision of deep boosted and N-subjettiness tagger in the
high purity category using the data from year
2018.}\label{fig:comp_2018}
}
\end{figure}
\clearpage
\newpage

View File

@ -10,13 +10,13 @@
\contentsline {subsection}{\numberline {3.1}Large Hadron Collider}{7}{subsection.3.1}%
\contentsline {subsection}{\numberline {3.2}Compact Muon Solenoid}{7}{subsection.3.2}%
\contentsline {subsubsection}{\numberline {3.2.1}Coordinate conventions}{8}{subsubsection.3.2.1}%
\contentsline {subsubsection}{\numberline {3.2.2}The tracking system}{8}{subsubsection.3.2.2}%
\contentsline {subsubsection}{\numberline {3.2.2}The tracking system}{9}{subsubsection.3.2.2}%
\contentsline {subsubsection}{\numberline {3.2.3}The electromagnetic calorimeter}{9}{subsubsection.3.2.3}%
\contentsline {subsubsection}{\numberline {3.2.4}The hadronic calorimeter}{9}{subsubsection.3.2.4}%
\contentsline {subsubsection}{\numberline {3.2.5}The solenoid}{9}{subsubsection.3.2.5}%
\contentsline {subsubsection}{\numberline {3.2.6}The muon system}{9}{subsubsection.3.2.6}%
\contentsline {subsubsection}{\numberline {3.2.7}The Trigger system}{9}{subsubsection.3.2.7}%
\contentsline {subsubsection}{\numberline {3.2.8}The Particle Flow algorithm}{9}{subsubsection.3.2.8}%
\contentsline {subsubsection}{\numberline {3.2.5}The solenoid}{10}{subsubsection.3.2.5}%
\contentsline {subsubsection}{\numberline {3.2.6}The muon system}{10}{subsubsection.3.2.6}%
\contentsline {subsubsection}{\numberline {3.2.7}The Trigger system}{10}{subsubsection.3.2.7}%
\contentsline {subsubsection}{\numberline {3.2.8}The Particle Flow algorithm}{10}{subsubsection.3.2.8}%
\contentsline {subsection}{\numberline {3.3}Jet clustering}{10}{subsection.3.3}%
\contentsline {section}{\numberline {4}Method of analysis}{12}{section.4}%
\contentsline {subsection}{\numberline {4.1}Signal and Background modelling}{12}{subsection.4.1}%
@ -27,12 +27,12 @@
\contentsline {section}{\numberline {6}Jet substructure selection}{20}{section.6}%
\contentsline {subsection}{\numberline {6.1}N-Subjettiness}{20}{subsection.6.1}%
\contentsline {subsection}{\numberline {6.2}DeepAK8}{21}{subsection.6.2}%
\contentsline {subsection}{\numberline {6.3}Optimization}{21}{subsection.6.3}%
\contentsline {section}{\numberline {7}Signal extraction}{22}{section.7}%
\contentsline {subsection}{\numberline {6.3}Optimization}{22}{subsection.6.3}%
\contentsline {section}{\numberline {7}Signal extraction}{23}{section.7}%
\contentsline {subsection}{\numberline {7.1}Uncertainties}{23}{subsection.7.1}%
\contentsline {section}{\numberline {8}Results}{23}{section.8}%
\contentsline {subsection}{\numberline {8.1}2016}{23}{subsection.8.1}%
\contentsline {section}{\numberline {8}Results}{24}{section.8}%
\contentsline {subsection}{\numberline {8.1}2016}{24}{subsection.8.1}%
\contentsline {subsubsection}{\numberline {8.1.1}Previous research}{24}{subsubsection.8.1.1}%
\contentsline {subsection}{\numberline {8.2}Combined dataset}{25}{subsection.8.2}%
\contentsline {subsection}{\numberline {8.3}Comparison of taggers}{25}{subsection.8.3}%
\contentsline {section}{\numberline {9}Summary}{29}{section.9}%
\contentsline {subsection}{\numberline {8.2}Combined dataset}{26}{subsection.8.2}%
\contentsline {subsection}{\numberline {8.3}Comparison of taggers}{28}{subsection.8.3}%
\contentsline {section}{\numberline {9}Summary}{30}{section.9}%