The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
@inproceedings{welsch:ipac2021-wepab183,
author = {C.P. Welsch},
title = {{Big Data Techniques for Accelerator Optimization}},
booktitle = {Proc. IPAC'21},
pages = {3039--3041},
eid = {WEPAB183},
language = {english},
keywords = {plasma, laser, experiment, wakefield, radiation},
venue = {Campinas, SP, Brazil},
series = {International Particle Accelerator Conference},
number = {12},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2021},
issn = {2673-5490},
isbn = {978-3-95450-214-1},
doi = {10.18429/JACoW-IPAC2021-WEPAB183},
url = {https://jacow.org/ipac2021/papers/wepab183.pdf},
note = {https://doi.org/10.18429/JACoW-IPAC2021-WEPAB183},
abstract = {{Accelerators and the experiments that they enable are some of the largest, most data-intensive, and most complex scientific systems in existence. The interrelations between machine subsystems are complicated and often nonlinear. The system dynamics involve large parameter spaces that evolve over multiple relevant time scales and accelerator systems. Any accelerator-based experiments and applications are almost always difficult to model. LIV. DAT, the Liverpool Centre for Doctoral Training in Data-intensive science, was established in 2017 as a hub for training students in Big Data science. The centre currently has 36 PhD students that are working across nuclear, particle and astrophysics, as well as in accelerator science. This paper presents results from R&D into betatron radiation models and beam parameter reconstruction for plasma acceleration experiments at FACET-II, simulations for MeV energy gain in dielectric structures driven by a CO₂ laser, and modelling of seeded self-modulation of long elliptical bunches in plasma. It also gives an overview of the training program offered to the LIV. DAT students.}},
}