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RIS citation export for TUPOST051: Using Data Intensive Science for Accelerator Optimization

TY  - CONF
AU  - Welsch, C.P.
ED  - Zimmermann, Frank
ED  - Tanaka, Hitoshi
ED  - Sudmuang, Porntip
ED  - Klysubun, Prapong
ED  - Sunwong, Prapaiwan
ED  - Chanwattana, Thakonwat
ED  - Petit-Jean-Genaz, Christine
ED  - Schaa, Volker R.W.
TI  - Using Data Intensive Science for Accelerator Optimization
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - Particle accelerators and light sources are some of the largest, most data intensive, and most complex scientific systems. The connections and relations between machine subsystems are complicated and often nonlinear with system dynamics involving large parameter spaces that evolve over multiple relevant time scales and accelerator systems. In 2017, the Liverpool Centre for Doctoral Training in Data Intensive Science (LIV. DAT) was established. With almost 40 PhD students, the centre is now established as an international hub for training PhD students in data intensive science. This contribution presents results from studies carried out in LIV. DAT into novel high gradient accelerators with a focus on the data science techniques that were used. This includes studies into inverse-designed narrowband THz radiators for ultra-relativistic electrons, simulation of the transverse asymmetry and inhomogeneity on seeded self-modulation of beams in plasma, as well as studies into the physical aspects of collinear laser injection in Trojan Horse laser plasma experiments.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 980
EP  - 982
KW  - plasma
KW  - experiment
KW  - simulation
KW  - electron
KW  - radiation
DA  - 2022/07
PY  - 2022
SN  - 2673-5490
SN  - 978-3-95450-227-1
DO  - doi:10.18429/JACoW-IPAC2022-TUPOST051
UR  - https://jacow.org/ipac2022/papers/tupost051.pdf
ER  -