CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation

Autor: Krause, Claudius, Giannelli, Michele Faucci, Kasieczka, Gregor, Nachman, Benjamin, Salamani, Dalila, Shih, David, Zaborowska, Anna, Amram, Oz, Borras, Kerstin, Buckley, Matthew R., Buhmann, Erik, Buss, Thorsten, Cardoso, Renato Paulo Da Costa, Caterini, Anthony L., Chernyavskaya, Nadezda, Corchia, Federico A. G., Cresswell, Jesse C., Diefenbacher, Sascha, Dreyer, Etienne, Ekambaram, Vijay, Eren, Engin, Ernst, Florian, Favaro, Luigi, Franchini, Matteo, Gaede, Frank, Gross, Eilam, Hsu, Shih-Chieh, Jaruskova, Kristina, Käch, Benno, Kalagnanam, Jayant, Kansal, Raghav, Kim, Taewoo, Kobylianskii, Dmitrii, Korol, Anatolii, Korcari, William, Krücker, Dirk, Krüger, Katja, Letizia, Marco, Li, Shu, Liu, Qibin, Liu, Xiulong, Loaiza-Ganem, Gabriel, Madula, Thandikire, McKeown, Peter, Melzer-Pellmann, Isabell-A., Mikuni, Vinicius, Nguyen, Nam, Ore, Ayodele, Schweitzer, Sofia Palacios, Pang, Ian, Pedro, Kevin, Plehn, Tilman, Pokorski, Witold, Qu, Huilin, Raikwar, Piyush, Raine, John A., Reyes-Gonzalez, Humberto, Rinaldi, Lorenzo, Ross, Brendan Leigh, Scham, Moritz A. W., Schnake, Simon, Shimmin, Chase, Shlizerman, Eli, Soybelman, Nathalie, Srivatsa, Mudhakar, Tsolaki, Kalliopi, Vallecorsa, Sofia, Yeo, Kyongmin, Zhang, Rui

We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of increasing dimensionality, ranging from a few hundred voxels to a few t

Externí odkaz: http://arxiv.org/abs/2410.21611

DeepTreeGAN: Fast Generation of High Dimensional Point Clouds

Autor: Scham, Moritz Alfons Wilhelm, Krücker, Dirk, Käch, Benno, Borras, Kerstin

In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the comple

Externí odkaz: http://arxiv.org/abs/2311.12616

JetFlow: Generating Jets with Conditioned and Mass Constrained Normalising Flows

Autor: Käch, Benno, Krücker, Dirk, Melzer-Pellmann, Isabell, Scham, Moritz, Schnake, Simon, Verney-Provatas, Alexi

Fast data generation based on Machine Learning has become a major research topic in particle physics. This is mainly because the Monte Carlo simulation approach is computationally challenging for future colliders, which will have a significantly high

Externí odkaz: http://arxiv.org/abs/2211.13630

DeepTreeGAN: Fast Generation of High Dimensional Point Clouds

Autor: Scham Moritz A.W., Krücker Dirk, Käch Benno, Borras Kerstin

Publikováno v: EPJ Web of Conferences, Vol 295, p 09010 (2024)

In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the comple

Externí odkaz: https://doaj.org/article/996c1c2439cf43d0add03ff9c7a32037