Conveners
ML Workshop: II session
- Teresa Montaruli (Universite de Geneve (CH))
The Bert pretraining paradigm has proven to be highly effective in many domains including natural language processing, image processing and biology. To apply the Bert paradigm the data needs to be described as a set of tokens, and each token needs to be labelled. To date the Bert paradigm has not been explored in the context of HEP. The samples that form the data used in HEP can be described...
We present a novel approach for directly generating full events at detector-level from parton-level information, leveraging cutting-edge machine learning techniques. To address the challenge of multiplicity variations between parton and reconstructed object spaces, we employ transformers, score-based models and normalizing flows. Our method tackles the inherent complexities of the stochastic...
A dedicated experimental search for a muon electric dipole moment (EDM) is being set up at Paul Scherrer Institute. This experiment will search for a muon EDM signal with a final precision of \SI{6e-23}{e \cdot cm} using the frozen-spin technique, improving the current experimental limit by 3 orders of magnitude. To achieve the precision objective, it is important to optimize the setup to...
In this talk, we address the challenge of optimizing detector design for advanced tasks in high energy particle physics. Our goal is to develop differentiable pipelines for the optimization of typical metrics sought out in particle physics applications. The approach is tailored with a focus on several critical design aspects, including optimizing detector performance, enhancing sensitivity to...
The dynamic aperture is defined as the region of phase space where the particle motion in circular particle accelerators remains bounded over a fixed and large number of turns. Understanding the key features of this concept offers insight into non-linear beam dynamics and factors affecting beam lifetime in accelerators, which are pivotal for the operation of machines like the CERN Large Hadron...
