ICALEPCS 2023: 3rd Data Science and Machine Learning Workshop

Session

Project presentations/demos

7 Oct 2023, 12:30

CENTURY CITY CONVENTION CENTRE4 Energy Lane, Century City, Cape Town

5. Neural Networks for Anomaly Detection in LINACs, Injectors, and Transfer Lines

Jon Edelen (Radiasoft)

07/10/2023, 12:30

Maximizing up-time of accelerators relies heavily on the ability to detect and diagnose changes in the machine. The application of machine learning for anomaly detection remains a rich area of research. RadiaSoft has been developing methods for anomaly detection in collaboration with Jefferson Lab, Brookhaven National Lab, and SLAC. Here we provide a survey of recent innovations in anomaly...

6. A Potential of Use of Language Processing in Accelerator Control Systems

Antonin Sulc (DESY)

07/10/2023, 12:50

Particle accelerators rely on complex control systems for their operation. As accelerators grow in scale and complexity, developing and maintaining effective control systems becomes increasingly challenging. In this presentation, we will explore the potential for applying natural language processing (NLP) techniques to improve accelerator operations by closely examining the use of textual...

8. Use of Machine learning for Denoising Beam Profile Measurements

Javier Martinez Samblas

07/10/2023, 13:10

Several CERN accelerators are being equipped with Beam Gas Ionization (BGI) profile monitors using high resolution Timepix3 detectors resulting in very powerful and not destructive measurements [1]
The images produced by these detectors contain the signal from ionization electrons as well as noise coming from different sources (mainly beam losses) and other artifacts like noisy pixels or the...

7. Addressing protein serial crystallography 36 GB/s data-rate challenge with FPGAs and GPUs

Filip Leonarski

07/10/2023, 13:30

Serial crystallography [1] is a technique used at synchrotrons and X-ray free electron lasers to solve protein structures from random still diffraction images of thousands of small crystals. The technique is one of the most data intensive techniques at X-ray facilities. With novel detectors, like the 9 MPixel JUNGFRAU [2] currently commissioned at the Paul Scherrer Institute, it is possible to...

4. Common Problems in Early Stage Projects at the ISIS Neutron and Muon Source

Kathryn Baker

07/10/2023, 13:50

At the ISIS Neutron and Muon Source, we are still relatively early on in our pursuit to integrate machine learning into the operations of the accelerator. Consultation with various teams across the accelerator has highlighted three key areas where machine learning can be leveraged most effectively, namely fault diagnosis and prediction, the use of virtual diagnostics and intelligent control of...

13. Additional presentations and/or discussions

07/10/2023, 14:05