Searching for hidden particles with the SHiP experiment and development of machine learning methods
Lead Research Organisation:
University of Bristol
Department Name: Physics
Abstract
Using Deep Learning to:
- Generate vast numbers of protons-on-target and simulate the detector response.
- Suppress the large combinatorial muon background
- Generate vast numbers of protons-on-target and simulate the detector response.
- Suppress the large combinatorial muon background
People |
ORCID iD |
Alex Marshall (Student) |
Publications
Ahdida C
(2019)
Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks
in Journal of Instrumentation
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/P006779/1 | 30/09/2017 | 29/09/2024 | |||
2028277 | Studentship | ST/P006779/1 | 30/09/2017 | 29/09/2021 | Alex Marshall |
Description | SHiP |
Organisation | European Organization for Nuclear Research (CERN) |
Country | Switzerland |
Sector | Academic/University |
PI Contribution | SHiP collaboration at CERN |
Collaborator Contribution | Responsible for RPV SUSY sensitivity, muon combinatorial background and fast simulations |
Impact | Paper |
Start Year | 2015 |