IPPL is a C++ library to develop performance portable code for fully Eulerian, Lagrangian or hybrid Eulerian-Lagrangian methods.
Python 3 codes for beam optics measurements and corrections in circular particle accelerators
Code for the paper "Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning"
Python version of Simulated Commissioning toolkit for synchrotrons (https://github.com/ThorstenHellert/SC).
Calculate various beam optics functions from TfsDataframes
FPGA embedded multicore processing of an iterative deconvolution method based on sparse data representation aimed at online reconstruction of energy in particle accelerators
I/O functionality for turn-by-turn BPM measurements data from different particle accelerators
MAD-X Example Study Scripts (MESS), for your everyday use
A python framework for particle accelerator simulations
Links in the endnotes of "Beams - The Story of Particle Accelerators and the Science They Discover" published by Springer
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