MSK ML Meeting

Meeting Organization:

bi-weekly starting on the 15.02.2023 14:00
On-site: Seminar room 55a - 110
Zoom: (https://desy.zoom.us/j/96646780409?pwd=Rlk3dkZUQ2pITjc4NFRhNTFsZ0txQT09, Meeting-ID: 966 4678 0409, Kenncode: 160564)
next meetings dates:
- 07.06..2023
- 21.06.2023
- 05.07.2023
subscription E-mail: mskipcml@desy.de

Ideas

Who	Application	Method

Jannis Luebsen Julien Branlard	Cavity Piezo tuning	Bayesian Optimization
Marie Kristin Czwalinna Lukas Mueller	Drift Compensation with Beam-Based Feedbacks problem: distributed feedback loops in a coupled system. current implementation is too simple, static and prone to errors because it does not account for dynamic coupling between loops.	1st approach: model based learning algorithm	link in confluence: https://confluence.desy.de/x/Eca7EQ
Marie Kristin Czwalinna +?	Electron Bunch Trajectory Optmization & Feedback problem: current implementation is not suited for a dynamic system and uses a too simple error estimation.	ideas: RL algorithm (beam optics model could be included) or safe bayesian optimization	link in confluence: https://confluence.desy.de/x/Dca7EQ
Seyednima Omidsajedi	Simulation and control of charged particle beam dynamics using Polynomial Neural Networks (PNN)	idea: Implementation of the target NN on FPGA Main quiestion: How to convert PNN to CNN?
Jan Kaiser	Fast linear particle simulation for machine learning applications	Cheetah Python package	https://github.com/desy-ml/cheetah
Jan Kaiser	Reinforcement learning for particle accelerator optimisation (transverse beam parameter tuning at ARES)	Reinforcement learning, domain randomisation, differential actions, logarithmic rewards, TD3, PPO	https://proceedings.mlr.press/v162/kaiser22a.html
Jan Kaiser	Virtual LPS diagnostics at EuXFEL with adaptive resolution	Supervised learning, neural networks
Jannis Luebsen	Tuning of the LbSync System and Cavity Piezo Tuning	Multi-Information Source Bayesian Optimization
Maximilian Schuette Arne Gruenhagen	Data collection in DOOCS	DxMAF python tool	https://gitlab.desy.de/msk-ipc/dxmaf
Arne Gruenhagen	Laser Oscillator Fault detection and Diagnosis	Feature Extraction and Fault analysis
Lynda Boukela	Quench detection at the EuXFEL	Anomaly detection, Residuals, Clustering

Schedule

When	Who	Topic	Information
26 Apr 2023	Seyednima Omidsajedi	Simulation and control of charged particle	References Polynomial Neural Networks and Taylor maps for Dynamical Systems Simulation and Learning (https://arxiv.org/abs/1912.09986) Matrix Lie Maps and Polynomial Neural Networks for Solving Differential Equations (https://arxiv.org/abs/1908.06088) Physics-based deep neural networks for beam dynamics in charged particle accelerators (https://arxiv.org/abs/2007.03555)
07 Jun 2023	Vahid Rahmani
21 Jun 2023	Jannis Luebsen	Tuning of the LbSync System
05 Jul 2023	Bianca Veglia	ID Gap Compensation and Extremum Seeking at PETRA III

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MSK ML Meeting