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Michele Faucci Giannelli (Istituto Nazionale di Fisica Nucleare), Rui Zhang30/05/2023, 11:00
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Benno Käch (Deutsches-Elektronen Synchrotron (DESY))30/05/2023, 11:30
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Federico Andrea Guillaume Corchia (Istituto Nazionale di Fisica Nucleare)30/05/2023, 12:00
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30/05/2023, 12:30
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Federico Andrea Guillaume Corchia (Istituto Nazionale di Fisica Nucleare), Lorenzo Rinaldi (Istituto Nazionale di Fisica Nucleare)
The simulation of electromagnetic and hadronic interactions in calorimeters is a very demanding process, both in terms of time and computing resources. A novel technique based on Generative Adversarial Networks (GANs) may benefit from a more efficient use of computing resources, although initial training could be computationally demanding. Nowadays and in the near future we expect to have more...
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Vinicius Mikuni (LBNL)
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Benno Käch (Deutsches-Elektronen Synchrotron (DESY))
We propose the application of our previously published Cross AtteNtion meAn-fielD mAtching CANADA-GAN for generating particle showers in high-granularity datasets. Results are presented for dataset 2 and 3. Point cloud generative models are known to benefit from higher granularity, making these datasets well-suited for high-granularity calorimeters. Although the regular architecture of the...
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