Co-financed by:
Name
QML-HEP: Exploring quantum machine learning as a tool for present and future high-energy colliders
Code
CERN/FIS-COM/0004/2021
Beneficiary Entity
LIP - Laboratório de Instrumentação e Física Experimental de Partículas
Project summary
...
Support under
Reforçar a investigação, o desenvolvimento tecnológico e a inovação
Region of Intervention
...
Funding
Total eligible cost
€ 30,000.00
EU financial support
Funding for LIP
€ 0.00
€ 30,000.00
National public financial support
€ 30.000
Dates
Approval
Start
2022-02-01
End
2023-08-31
Acknowledgements
Versão Extensa: Este trabalho é financiado por fundos nacionais através da FCT - Fundação para a Ciência e a Tecnologia, I.P., no âmbito do projeto CERN/FIS-COM/0004/2021
Versão Resumida: OE,FCT-Portugal, CERN/FIS-PAR/0004/2021
Publications
Fitting a Collider in a Quantum Computer: Tackling the Challenges of Quantum Machine Learning for Big Datasets | Article in international journal (with direct contribution from team) | published |
Presentations
Artificial Intelligence and Machine Learning for Collider and Beyond the Standard Model Physics | Seminar |
CERN and particle physics: challenges and opportunities | Presentation in national conference |
ChatGPT: desafios e oportunidades na ótica da comunicação de ciência | Presentation in national conference |
Machine learning as a tool for high energy physics | Seminar |
Machine learning as a tool for particle physics in collider experiments | Seminar |
Rare production and decay processes in the top quark sector | Oral presentation in international conference |
Theses
Anomaly detection as a quality control tool in an industrial context | ||
Application of quantum computing to quantum chromodynamics |
Team
Ana Paula Pereira Peixoto |
Henrique Manuel Peixoto Carvalho |
Maria Gabriela Jordão Oliveira |
Maria Inês Abreu Julião Ochoa de Castro |
Miguel Caçador Peixoto |
Miguel Correia dos Santos Crispim Romão |
Nuno Filipe da Silva Fernandes de Castro |
Tiago Dias do Vale |
Tiago Vieira de Castro Martins Antão |