CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation

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.

DeepTreeGANv2: Iterative Pooling of Point Clouds

2 code implementations • 24 Nov 2023 • Moritz Alfons Wilhelm Scham, Dirk Krücker, Kerstin Borras

In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors.

Physics Validation of Novel Convolutional 2D Architectures for Speeding Up High Energy Physics Simulations

no code implementations • 19 May 2021 • Florian Rehm, Sofia Vallecorsa, Kerstin Borras, Dirk Krücker

Our results demonstrate a high physics accuracy and further consolidate the use of GANs for fast detector simulations.

3D Architecture Image Generation

Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case

no code implementations • 18 Mar 2021 • Florian Rehm, Sofia Vallecorsa, Vikram Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker

We employ the novel Intel low precision optimization tool (iLoT) for quantization and compare the results to the quantized model from TensorFlow Lite.

Deep Learning Generative Adversarial Network +1