Cargando…
Analysis, and machine learning anomaly detection of the VELO-LHCb calibration
Silicon detectors are an extraordinary piece of equipment that has become the cornerstone of research in modern high energy physics. They are becoming increasingly useful in medical research as well. LHCbs VELO detector is itself, a microstrip silicon vertex detector. It is the heart of LHCb spectro...
Autor principal: | Majewski, Maciej |
---|---|
Lenguaje: | eng |
Publicado: |
2019
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/1337/1/012006 http://cds.cern.ch/record/2827296 |
Ejemplares similares
-
Development of the LHCb VELO monitoring software platform
por: Majewski, Maciej
Publicado: (2017) -
Machine Learning in Velo LHCb monitoring and calibration in Run I and II
por: Majewski, Maciej Witold
Publicado: (2019) -
Parallel Hough transform for track detection in LHCb's VELO Pixel detector
por: Ebert, Matthias
Publicado: (2014) -
C/VHDL Codesign for LHCb VELO zero suppression algorithms
por: Muecke, Manfred
Publicado: (2005) -
Network anomaly detection: a machine learning perspective
por: Bhattacharyya, Dhruba Kumar
Publicado: (2013)