1 code implementation • 29 Apr 2024 • Haoxing Du, Claudius Krause, Vinicius Mikuni, Benjamin Nachman, Ian Pang, David Shih
There have been many applications of deep neural networks to detector calibrations and a growing number of studies that propose deep generative models as automated fast detector simulators.
1 code implementation • 22 Aug 2023 • Ian Pang, John Andrew Raine, David Shih
In this work, we introduce SuperCalo, a flow-based super-resolution model, and demonstrate that high-dimensional fine-grained calorimeter showers can be quickly upsampled from coarse-grained showers.
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.
no code implementations • 25 Oct 2022 • Claudius Krause, Ian Pang, David Shih
CaloFlow is a new and promising approach to fast calorimeter simulation based on normalizing flows.