SciPost Submission Page
Normalizing Flows for High-Dimensional Detector Simulations
by Florian Ernst, Luigi Favaro, Claudius Krause, Tilman Plehn, David Shih
Submission summary
| Authors (as registered SciPost users): | Luigi Favaro · Claudius Krause · Tilman Plehn |
| Submission information | |
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| Preprint Link: | scipost_202312_00040v1 (pdf) |
| Code repository: | https://github.com/heidelberg-hepml/CaloINN |
| Date submitted: | 2023-12-22 12:53 |
| Submitted by: | Favaro, Luigi |
| Submitted to: | SciPost Physics |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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Abstract
Whenever invertible generative networks are needed for LHC physics, normalizing flows show excellent performance. A challenge is their scaling to high-dimensional phase spaces. We investigate their performance for fast calorimeter shower simulations with increasing phase space dimension. In addition to the standard architecture we also employ a VAE to compress the dimensionality. Our study provides benchmarks for invertible networks applied to the CaloChallenge.
Current status:
In refereeing