ICALEPCS 2021: 2nd Data Science and Machine Learning Workshop

Session

Project Presentations

15 Oct 2021, 14:10

Remote

9. LSTM model for the automatic LHC collimator alignment

Gabriella Azzopardi (CERN)

15/10/2021, 14:10

A collimation system is installed in the Large Hadron Collider (LHC) to protect its sensitive equipment from unavoidable beam losses. An alignment procedure determines the settings of each collimator, by moving the collimator jaws towards the beam until a characteristic loss pattern, consisting of a sharp rise followed by a slow decay, is observed in downstream beam loss monitors. This...

10. Report on the Artificial Intelligence workshop at EuXFEL

Danilo Ferreira de Lima

15/10/2021, 14:35

Experiments at large scale facilities like the European X-ray Free Electron Laser (EuXFEL) generate data at a very large rate, leading experimentalists with data samples potentially including millions of unlabelled images and instrument scientists with online monitoring of data from different sources. The analysis and understanding of such data need to cope with the high data rate, both to...

11. Automatic Serial Femtosecond Crystallography online analysis with Reinforcement Learning

Danilo Ferreira De Lima (Ruprecht Karls Universitaet Heidelberg (DE))

15/10/2021, 14:50

Data analysis pipelines typically require experiment- or data-dependent parameters to be tuned. Serial Femtosecond Crystallography (SFX) is a powerful technique that allow to disclose structural information in a time-resolved fashion. We present here an attempt of tuning the parameters of a software tool widely used for SFX data analysis, CrystFEL, using a model-free actor-critic Reinforcement...

12. Report on LEAPS Integrated Platform workshop

Marco Calvi (PSI)

15/10/2021, 15:10

13. Machine Learning for the Tune Estimation in the LHC

Leander Grech (University of Malta (MT))

15/10/2021, 15:30

The betatron tune in the Large Hadron Collider (LHC) is measured using a Base-Band
Tune (BBQ) system. The processing of these BBQ signals is often perturbed by 50 Hz noise harmonics
present in the beam. This causes the tune measurement algorithm, currently based on peak detection,
to provide incorrect tune estimates during the acceleration cycle with values that oscillate...

15. Peek to some recent ML Activities at DESY

Raimund Kammering (DESY)

15/10/2021, 15:50

DESY hosts a huge number of complex facilities like PETRA, FLASH and the European XFEL but also some smaller scale test facilities. At many of these facilities, the usage of ML techniques and approaches has strongly increased in the last years. This talk will give a brief overview about the some of this ongoing activities within the machine division at DESY.

16. Machine Learning for Failure Detection on RF Cavities

Antonin Sulc (DESY)

15/10/2021, 16:00

In this talk, we are going to show you the most recent activities in failure detection on the RF cavities at XFEL, mostly for quench detection and predictive maintenance. We show that a two-layer recurrent neural network can be trained to classify the behaviour of the signals that we record about the cavities and even with relatively inaccurate labelling achieve convincing results to detect...

14. Discussion