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Future colliders for early-career researchers (Belgium and the Netherlands)

12–13 Sept 2024
Ghent
Europe/Brussels timezone

Contribution List

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3. Poster session and social event
12/09/2024, 17:00
11. Introduction
Andrea García Alonso (Nikhef)
13/09/2024, 09:10
12. Current physics landscape and motivation for future colliders
Dr Wouter Waalewijn (University of Amsterdam)
13/09/2024, 09:30
13. Overview of future colliders options
Dr Clara Nellist (University of Amsterdam)
13/09/2024, 10:00
14. Summary of ECFA-wide event on future colliders
Dr Armin Ilg (University of Zurich)
13/09/2024, 11:10
16. Impact on future colliders on society and sustainability
Prof. Jorgen D' Hondt (VU Brussel)
13/09/2024, 11:30
15. Past and current national HEP involvement
Prof. Antonio Pellegrino (University of Groningen)
13/09/2024, 13:30
17. Dutch view on involvement and interests in future colliders
Prof. Tristan du Pree (University of Twente)
13/09/2024, 13:45
18. Belgian view on involvement and interests in future colliders
Kirill Skovpen (Ghent University)
13/09/2024, 14:15
22. National funding structure and plans for future collider R&D
Dr Mara Senghi Soares (Vrije Universiteit Amsterdam)
13/09/2024, 15:15
20. Future colliders panel discussion
Armin Ilg (University of Zurich), Clara Nellist (University of Amsterdam), Jorgen D' Hondt (VU Brussel), Mara Senghi Soares (Vrije Universiteit Amsterdam)
13/09/2024, 15:45
5. Conclusions and next steps
Marion Missio (Nikhef - Radboud University)
13/09/2024, 16:45
19. Belgian funding structure and plans for future collider R&D
2. Belgium and Dutch involvements
24. Characterization of analogue MAPS fabricated in 65 nm technology for the ALICE ITS3
Eduardo Ploerer (UZH/VUB)

CMOS Monolithic Active Pixel Sensors (MAPS) have become a prominent technology choice for tracking and vertexing detectors in high-energy physics experiments over the last decades. The ALICE ITS3 project foresees the use of ultra-light MAPS, developed in the 65 nm imaging process, for the vertex detector in the ALICE experiment at the LHC to improve the vertexing performance drastically. This...
21. Future colliders panel discussion
1. Introduction
23. Jet Flavour Tagging at FCC-ee with a Transformer-based Neural Network: DeepJetTransformer
Kunal Gautam (VUB [BE]/UZH [CH])

Jet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, DeepJetTransformer, is presented, which exploits a transformer-based neural network that is substantially faster to train.

The DeepJetTransformer network uses information from particle flow-style objects and secondary vertex reconstruction as is standard for $b$- and $c$-jet identification...
4. People and money session
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