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RIS citation export for MOPAB184: Unsupervised Learning Techniques for Tune Cleaning Measurement

TY  - CONF
AU  - Garcia Morales, H.
AU  - Fol, E.
AU  - Tomás García, R.
ED  - Liu, Lin
ED  - Byrd, John M.
ED  - Neuenschwander, Regis T.
ED  - Picoreti, Renan
ED  - Schaa, Volker R. W.
TI  - Unsupervised Learning Techniques for Tune Cleaning Measurement
J2  - Proc. of IPAC2021, Campinas, SP, Brazil, 24-28 May 2021
CY  - Campinas, SP, Brazil
T2  - International Particle Accelerator Conference
T3  - 12
LA  - english
AB  - Precise measurements of tune and its stability are crucial for various optics analyses in the LHC, e.g. for the determination of the beta star using K-modulation. LHC BBQ system provides tune measurements online and stores the tune data. We apply unsupervised machine learning techniques on BBQ tune data in order to provide an automatic outlier detection method for better measurements of tune shifts and unexpected tune jitters.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 624
EP  - 627
KW  - ISOL
KW  - optics
KW  - coupling
KW  - luminosity
KW  - quadrupole
DA  - 2021/08
PY  - 2021
SN  - 2673-5490
SN  - 978-3-95450-214-1
DO  - doi:10.18429/JACoW-IPAC2021-MOPAB184
UR  - https://jacow.org/ipac2021/papers/mopab184.pdf
ER  -