"au:"Sergei V. Chekanov""

Jets and Jet Substructure at Future Colliders

Ben Nachman, Salvatore Rappoccio, Nhan Tran, Johan Bonilla, Grigorios Chachamis, Barry M. Dillon, Sergei V. Chekanov, Robin Erbacher, Loukas Gouskos, Andreas Hinzmann, Stefan Höche, B. Todd Huffman, Ashutosh. V. Kotwal, Deepak Kar, Roman Kogler, Clemens Lange, Matt LeBlanc, Roy Lemmon, Christine McLean, Mark S. Neubauer, Tilman Plehn, Debarati Roy, Giordan Stark, Jennifer Roloff, Marcel Vos, Chih-Hsiang Yeh, Shin-Shan Yu

Mar 14, 2022·hep-ph·PDF

Even though jet substructure was not an original design consideration for the Large Hadron Collider (LHC) experiments, it has emerged as an essential tool for the current physics program. We examine the role of jet substructure on the motivation for and design of future energy frontier colliders. In particular, we discuss the need for a vibrant theory and experimental research and development program to extend jet substructure physics into the new regimes probed by future colliders. Jet substructure has organically evolved with a close connection between theorists and experimentalists and has catalyzed exciting innovations in both communities. We expect such developments will play an important role in the future energy frontier physics program.

Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021

Tulika Bose, Antonio Boveia, Caterina Doglioni, Simone Pagan Griso, James Hirschauer, Elliot Lipeles, Zhen Liu, Nausheen R. Shah, Lian-Tao Wang, Kaustubh Agashe, Juliette Alimena, Sebastian Baum, Mohamed Berkat, Kevin Black, Gwen Gardner, Tony Gherghetta, Josh Greaves, Maxx Haehn, Phil C. Harris, Robert Harris, Julie Hogan, Suneth Jayawardana, Abraham Kahn, Jan Kalinowski, Simon Knapen, Ian M. Lewis, Meenakshi Narain, Katherine Pachal, Matthew Reece, Laura Reina, Tania Robens, Alessandro Tricoli, Carlos E. M. Wagner, Riley Xu, Felix Yu, Filip Zarnecki, Amin Aboubrahim, Andreas Albert, Michael Albrow, Wolfgang Altmannshofer, Gerard Andonian, Artur Apresyan, Kétévi Adikle Assamagan, Patrizia Azzi, Howard Baer, Michael J. Baker, Avik Banerjee, Vernon Barger, Brian Batell, Martin Bauer, Hugues Beauchesne, Samuel Bein, Alexander Belyaev, Ankit Beniwal, Mikael Berggren, Prudhvi N. Bhattiprolu, Nikita Blinov, Alain Blondel, Oleg Brandt, Giacomo Cacciapaglia, Rodolfo Capdevilla, Marcela Carena, Cesare Cazzaniga, Francesco Giovanni Celiberto, Cari Cesarotti, Sergei V. Chekanov, Hsin-Chia Cheng, Thomas Y. Chen, Yuze Chen, R. Sekhar Chivukula, Matthew Citron, James Cline, Tim Cohen, Jack H. Collins, Eric Corrigan, Nathaniel Craig, Daniel Craik, Andreas Crivellin, David Curtin, Smita Darmora, Arindam Das, Sridhara Dasu, Annapaola de Cosa, Aldo Deandrea, Antonio Delgado, Zeynep Demiragli, David d'Enterria, Frank F. Deppisch, Radovan Dermisek, Nishita Desai, Abhay Deshpande, Jordy de Vries, Jennet Dickinson, Keith R. Dienes, Karri Folan Di Petrillo, Matthew J. Dolan, Peter Dong, Patrick Draper, Marco Drewes, Etienne Dreyer, Peizhi Du, Florian Eble, Majid Ekhterachian, Motoi Endo, Rouven Essig, Jesse N. Farr, Farida Fassi, Jonathan L. Feng, Gabriele Ferretti, Daniele Filipetto, Thomas Flacke, Karri Folan Di Petrillo, Roberto Franceschini, Diogo Buarque Franzosi, Keisuke Fujii, Benjamin Fuks, Sri Aditya Gadam, Boyu Gao, Aran Garcia-Bellido, Isabel Garcia Garcia, Maria Vittoria Garzelli, Stephen Gedney, Marie-Hélène Genest, Tathagata Ghosh, Mark Golkowski, Giovanni Grilli di Cortona, Emine Gurpinar Guler, Yalcin Guler, C. Guo, Nate Graf, Ulrich Haisch, Jan Hajer, Koichi Hamaguchi, Tao Han, Philip Harris, Sven Heinemeyer, Christopher S. Hill, Joshua Hiltbrand, Tova Ray Holmes, Samuel Homiller, Sungwoo Hong, Walter Hopkins, Shih-Chieh Hsu, Phil Ilten, Wasikul Islam, Sho Iwamoto, Daniel Jeans, Laura Jeanty, Haoyi Jia, Sergo Jindariani, Daniel Johnson, Felix Kahlhoefer, Yonatan Kahn, Paul Karchin, Thomas Katsouleas, Shin-ichi Kawada, Junichiro Kawamura, Chris Kelso, Elham E Khoda, Valery Khoze, Doojin Kim, Teppei Kitahara, Juraj Klaric, Michael Klasen, Kyoungchul Kong, Wojciech Kotlarski, Ashutosh V. Kotwal, Jonathan Kozaczuk, Richard Kriske, Suchita Kulkarni, Jason Kumar, Manuel Kunkel, Greg Landsberg, Kenneth Lane, Clemens Lange, Lawrence Lee, Jiajun Liao, Benjamin Lillard, Lingfeng Li, Shuailong Li, Shu Li, Jenny List, Tong Li, Hongkai Liu, Jia Liu, Jonathan D Long, Enrico Lunghi, Kun-Feng Lyu, Danny Marfatia, Dakotah Martinez, Stephen P. Martin, Navin McGinnis, Karrick McGinty, Krzysztof Mękała, Federico Meloni, Oleksii Mikulenko, Ming Huang, Rashmish K. Mishra, Manimala Mitra, Vasiliki A. Mitsou, Chang-Seong Moon, Alexander Moreno, Takeo Moroi, Gerard Mourou, Malte Mrowietz, Patric Muggli, Jurina Nakajima, Pran Nath, J. Nelson, Matthias Neubert, Laura Nosler, Maria Teresa Núñez Pardo de Vera, Nobuchika Okada, Satomi Okada, Vitalii A. Okorokov, Yasar Onel, Tong Ou, Maksym Ovchynnikov, Rojalin Padhan, Priscilla Pani, Luca Panizzi, Andreas Papaefstathiou, Kevin Pedro, Cristián Peña, Federica Piazza, James Pinfold, Deborah Pinna, Werner Porod, Chris Potter, Markus Tobias Prim, Stefano Profumo, James Proudfoot, Mudit Rai, Filip Rajec, Reese Ramos, Michael J. Ramsey-Musolf, Javier Resta-Lopez, Jürgen Reuter, Andreas Ringwald, Chiara Rizzi, Thomas G. Rizzo, Giancarlo Rossi, Richard Ruiz, L. Rygaard, Aakash A. Sahai, Shadman Salam, Pearl Sandick, Deepak Sathyan, Christiane Scherb, Pedro Schwaller, Leonard Schwarze, Pat Scott, Sezen Sekmen, Dibyashree Sengupta, S. Sen, Anna Sfyrla, Eric Shackelford, T. Sharma, Varun Sharma, Jessie Shelton, William Shepherd, Seodong Shin, Elizabeth H. Simmons, Zoie Sloneker, Carlos Vázquez Sierra, Torbjörn Sjöstrand, Scott Snyder, Huayang Song, Giordon Stark, Patrick Stengel, Joachim Stohr, Daniel Stolarski, Matt Strassler, Nadja Strobbe, Julia Gonski, Rebeca Gonzalez Suarez, Taikan Suehara, Shufang Su, Wei Su, Raza M. Syed, Tim M. P. Tait, Toshiki Tajima, Andy Tang, Xerxes Tata, Teodor Tchalokov, Andrea Thamm, Brooks Thomas, Natalia Toro, Nhan V. Tran, Loan Truong, Yu-Dai Tsai, Eva Tuecke, Nikhilesh Venkatasubramanian, Chris B. Verhaaren, Carl Vuosalo, Xiao-Ping Wang, Xing Wang, Yikun Wang, Zhen Wang, Christian Weber, Glen White, Martin White, Anthony G. Williams, Brady Williams, Mike Williams, Stephane Willocq, Alex Woodcock, Yongcheng Wu, Ke-Pan Xie, Keping Xie, Si Xie, C. -H. Yeh, Ryo Yonamine, David Yu, S. -S. Yu, Mohamed Zaazoua, Aleksander Filip Żarnecki, Kamil Zembaczynski, Danyi Zhang, Jinlong Zhang, Frank Zimmermann, Jose Zurita

Sep 27, 2022·hep-ph·PDF

This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More general explorations), and EF10 (Dark Matter at Colliders). The report includes a general introduction to BSM motivations and the comparative prospects for proposed future experiments for a broad range of potential BSM models and signatures, including compositeness, SUSY, leptoquarks, more general new bosons and fermions, long-lived particles, dark matter, charged-lepton flavor violation, and anomaly detection.

Enhancing the hunt for new phenomena in dijet final-states using anomaly detection filters at the High-Luminosity Large Hadron Collider

Sergei V. Chekanov, Rui Zhang

Aug 4, 2023·hep-ex·PDF

In the realm of dijet searches in high-energy physics, a significant challenge has emerged: with experiments producing more and more data, the traditional methods of using analytic functions to describe dijet mass spectra start to fail. To address this, we suggest the application of an anomaly detection approach to eliminate less interesting background events based on event final states. This method not only bypasses the limitations of conventional background models but also significantly enhances our ability to detect potential signals of new physics. Through simulations that mimic the conditions of the upcoming High-Luminosity Large Hadron Collider, we demonstrate the strength and efficiency of this approach in dealing with large data volumes. The integration of unsupervised machine learning into our experimental framework paves the way for a promising avenue to unveil hidden physics discoveries within the overwhelming influx of data.

ADFilter -- A Web Tool for New Physics Searches With Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks

Sergei V. Chekanov, Wasikul Islam, Rui Zhang, Nicholas Luongo

Sep 4, 2024·hep-ph·PDF

A web-based tool called ADFilter was developed to process collision events using autoencoders based on a deep unsupervised neural network. The autoencoders are trained on a small fraction of either collision data or Standard Model Monte Carlo simulations. The tool calculates loss distributions for input events, helping to determine the degree to which the events can be considered anomalous. It also calculates two-body invariant masses both before and after the autoencoders, as well as cross sections. Real-life examples are provided to demonstrate how the tool can be used to reinterpret existing LHC results with the goal of significantly improving exclusion limits.

Enhancing Sensitivity for Di-Higgs Boson Searches Using Anomaly Detection and Supervised Machine Learning Techniques

Sergei V. Chekanov, Wasikul Islam, Nicholas Luongo

Apr 16, 2025·hep-ph·PDF

This paper explores different strategies for enhancing sensitivity to new heavy resonances that decay into two or more Higgs bosons. This is achieved using two neural network architectures: an unsupervised autoencoder for anomaly detection and a supervised classifier. The autoencoder is trained on a small fraction of Standard Model (SM) Monte Carlo simulated events to calculate the loss distribution for input events, aiding in determining the extent to which events can be considered anomalous. The supervised classifier uses the same inputs but is trained on events simulated using both beyond Standard Model (BSM) and SM processes. By applying selection cuts to the output scores, we compare the sensitivities of the two approaches.

Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021

Sep 27, 2022·hep-ph·PDF