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The LHC Beam Gas Vertex Detector - a Non-Invasive Profile Monitor for High Energy Machines

The Beam Gas Vertex (BGV) monitor is being developed as part of the High Luminosity LHC project with the aim of providing measurements with less than 5% error on the beam size with an integration time of 5 minutes. It will be the only instrument capable of non-invasive beam size measurement througho...

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Detalles Bibliográficos
Autores principales: Vlachos, Sotiris, Alexopoulos, Andreas, Barchel, Colin, Bay, Aurelio, Blanc, Frederic, Bravin, Enrico, Bregliozzi, Giuseppe, Chritin, Nicolas, Dehning, Bernd, Ferro-Luzzi, Massimiliano, Giani, Sebastiana, Giovannozzi, Massimo, Girard, Olivier, Greim, Roman, Haefeli, Guido, Hopchev, Plamen, Jacobsson, Richard, Jensen, Lars, Jones, Robert, Kain, Verena, Kim, T, Karpinski, Waclaw, Kuonen, Axel, Matev, Rosen, Nakada, Tatsuya, Rihl, Mariana, Salustino Guimaraes, Valdir, Schael, Stefan, Schneider, Olivier, Schultz von Dratzig, A, Schwering, Georg, Tobin, Mark, Veness, Raymond, Veyrat, Quentin, Wlochal, Michael, Würkner, Benedikt, Xu, Zhirui
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:https://dx.doi.org/10.18429/JACoW-IBIC2017-WE3AB1
http://cds.cern.ch/record/2661463
Descripción
Sumario:The Beam Gas Vertex (BGV) monitor is being developed as part of the High Luminosity LHC project with the aim of providing measurements with less than 5% error on the beam size with an integration time of 5 minutes. It will be the only instrument capable of non-invasive beam size measurement throughout the LHC acceleration cycle with high intensity physics beams. A prototype BGV monitor has been installed in the LHC since 2016. Particles emerging from beam-gas interactions are recorded by 2 planes of scintillating fibre detectors. Based on vertex reconstruction of the detected tracks, this monitor allows non-invasive measurement of beam profiles with bunch-by-bunch resolution. A dedicated computer farm performs track reconstruction and event analysis on-line so that real-time beam profile measurements can be provided. Data taken in 2016 and 2017 will be presented that demonstrate the power of the method.