Session

Machine learning and automatic tuning

WG13
6 Mar 2025, 16:10
300 (EPOCHAL)

300

EPOCHAL

Tsukuba, Japan

Presentation materials

There are no materials yet.
Vaihabi Gawas (CERN)
06/03/2025, 16:10
Invited Oral Presentation
Jiaqi Fan (IHEP)
06/03/2025, 16:40
Invited Oral Presentation
Verena Kein (CERN)
06/03/2025, 17:10
Invited Oral Presentation
Nikita Kuklev (FNAL)
07/03/2025, 09:00
Invited Oral Presentation
Satya Sai Jagabathuni (European Organization for Nuclear Research)
07/03/2025, 09:30
WG13 : Machine learning and automatic tuning
Invited Oral Presentation

The FCC-ee collider requires strong focusing and small beam sizes at the interaction point (IP) to achieve its unprecedented luminosity. Magnet misalignments and gradient errors will perturb the optics at the IP, leading to beam size growth, and making it difficult to reach the collider’s luminosity goals. Therefore, tuning tools are essential for correcting these aberrations during operation....

Daniel Ratner (SLAC National Accelerator Laboratory)
07/03/2025, 10:00
Invited Oral Presentation
Gaku Mitsuka (KEK)
07/03/2025, 10:50
Invited Oral Presentation
Eiad Hamwi (Cornell Univ.)
07/03/2025, 11:20
Invited Oral Presentation
Verena Kain (European Organization for Nuclear Research)
WG13 : Machine learning and automatic tuning
Invited Oral Presentation

The Future Circular Collider (FCC) study at CERN is developing designs for the next generation particle colliders to follow on from the Large Hadron Collider after its High-Luminosity phase. A new tunnel of about 90 km circumference would Initially house an electron-positron collider, the FCC-ee, with a research programme of 15 years followed by a hadron collider, the FCC-hh, with a programme...

Satya Sai Jagabathuni (CERN)
Invited Oral Presentation
Building timetable...