no code implementations • 28 Oct 2024 • Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-Gonzalez, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge.
1 code implementation • 28 Oct 2024 • Edward D. Ramirez, Yitian Sun, Matthew R. Buckley, Siddharth Mishra-Sharma, Tracy R. Slatyer
We interpret our best-fit GP in terms of GCE templates consisting of an NFW squared template and a bulge component to determine which bulge models can best describe the fitted GP and to what extent the best-fit GP is described better by an NFW squared template versus a bulge template.
no code implementations • 19 May 2023 • Matthew R. Buckley, Claudius Krause, Ian Pang, David Shih
Simulating particle detector response is the single most expensive step in the Large Hadron Collider computational pipeline.
1 code implementation • 5 May 2023 • Mariel Pettee, Sowmya Thanvantri, Benjamin Nachman, David Shih, Matthew R. Buckley, Jack H. Collins
Large-scale astrophysics datasets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searches.
Supervised Anomaly Detection
Weakly-supervised Anomaly Detection
2 code implementations • 18 Jul 2017 • Pouya Asadi, Matthew R. Buckley, Anthony DiFranzo, Angelo Monteux, David Shih
In this paper we describe a novel, model-independent technique of "rectangular aggregations" for mining the LHC data for hints of new physics.
High Energy Physics - Phenomenology High Energy Physics - Experiment
1 code implementation • 3 Jul 2015 • Daniel Abercrombie, Nural Akchurin, Ece Akilli, Juan Alcaraz Maestre, Brandon Allen, Barbara Alvarez Gonzalez, Jeremy Andrea, Alexandre Arbey, Georges Azuelos, Patrizia Azzi, Mihailo Backović, Yang Bai, Swagato Banerjee, James Beacham, Alexander Belyaev, Antonio Boveia, Amelia Jean Brennan, Oliver Buchmueller, Matthew R. Buckley, Giorgio Busoni, Michael Buttignol, Giacomo Cacciapaglia, Regina Caputo, Linda Carpenter, Nuno Filipe Castro, Guillelmo Gomez Ceballos, Yangyang Cheng, John Paul Chou, Arely Cortes Gonzalez, Chris Cowden, Francesco D'Eramo, Annapaola De Cosa, Michele De Gruttola, Albert De Roeck, Andrea De Simone, Aldo Deandrea, Zeynep Demiragli, Anthony DiFranzo, Caterina Doglioni, Tristan du Pree, Robin Erbacher, Johannes Erdmann, Cora Fischer, Henning Flaecher, Patrick J. Fox, Benjamin Fuks, Marie-Helene Genest, Bhawna Gomber, Andreas Goudelis, Johanna Gramling, John Gunion, Kristian Hahn, Ulrich Haisch, Roni Harnik, Philip C. Harris, Kerstin Hoepfner, Siew Yan Hoh, Dylan George Hsu, Shih-Chieh Hsu, Yutaro Iiyama, Valerio Ippolito, Thomas Jacques, Xiangyang Ju, Felix Kahlhoefer, Alexis Kalogeropoulos, Laser Seymour Kaplan, Lashkar Kashif, Valentin V. Khoze, Raman Khurana, Khristian Kotov, Dmytro Kovalskyi, Suchita Kulkarni, Shuichi Kunori, Viktor Kutzner, Hyun Min Lee, Sung-Won Lee, Seng Pei Liew, Tongyan Lin, Steven Lowette, Romain Madar, Sarah Malik, Fabio Maltoni, Mario Martinez Perez, Olivier Mattelaer, Kentarou Mawatari, Christopher McCabe, Théo Megy, Enrico Morgante, Stephen Mrenna, Siddharth M. Narayanan, Andy Nelson, Sérgio F. Novaes, Klaas Ole Padeken, Priscilla Pani, Michele Papucci, Manfred Paulini, Christoph Paus, Jacopo Pazzini, Björn Penning, Michael E. Peskin, Deborah Pinna, Massimiliano Procura, Shamona F. Qazi, Davide Racco, Emanuele Re, Antonio Riotto, Thomas G. Rizzo, Rainer Roehrig, David Salek, Arturo Sanchez Pineda, Subir Sarkar, Alexander Schmidt, Steven Randolph Schramm, William Shepherd, Gurpreet Singh, Livia Soffi, Norraphat Srimanobhas, Kevin Sung, Tim M. P. Tait, Timothee Theveneaux-Pelzer, Marc Thomas, Mia Tosi, Daniele Trocino, Sonaina Undleeb, Alessandro Vichi, Fuquan Wang, Lian-Tao Wang, Ren-Jie Wang, Nikola Whallon, Steven Worm, Mengqing Wu, Sau Lan Wu, Hongtao Yang, Yong Yang, Shin-Shan Yu, Bryan Zaldivar, Marco Zanetti, Zhiqing Zhang, Alberto Zucchetta
This document is the final report of the ATLAS-CMS Dark Matter Forum, a forum organized by the ATLAS and CMS collaborations with the participation of experts on theories of Dark Matter, to select a minimal basis set of dark matter simplified models that should support the design of the early LHC Run-2 searches.
High Energy Physics - Experiment High Energy Physics - Phenomenology