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CERN Accelerating science

CERN Doctoral Student Program

Darreres entrades:
2021-04-12
21:34
Criticality of fast failures in the High Luminosity Large Hadron Collider / Lindstrom, Bjorn Hans Filip
Each of the two Large Hadron Collider (LHC) beams contain 362 MJ of energy [...]
CERN-THESIS-2020-318 urn:nbn:se:uu:diva-426416 ; ISBN:978-91-513-1081-7 ; oai:DiVA.org:uu-426416 ; diva2:1504630. - Uppsala, Sweden : Acta Universitatis Upsaliensis, 2021-01-05. - 115 p.

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2021-03-23
12:35
Applications of Crystal Collimation to the CERN Large Hadron Collider (LHC) and its High Luminosity Upgrade Project (HL-LHC) / D'Andrea, Marco
Charged particles interacting with materials with a highly ordered structure can experience a variety of coherent processes, among which crystal channeling is of particular interest to applications to high-energy colliders [...]
CERN-THESIS-2021-022 - 144 p.

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2021-03-18
11:46
Methods for the Design and Analysis of Higher-Order Mode Couplers applied to Superconducting Accelerating Structures / Papke, Kai
Higher-order modes (HOMs) may affect beam stability and refrigeration requirements of superconducting proton linacs such as the SPL which is being studied at CERN as a driver for future neutrino programs [...]
CERN-THESIS-2020-308 - 250 p.

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2021-03-09
12:25
Instability and Beam-Beam Study for Multi-TeV PWFA e+e− and γγ Linear Colliders / Chen, Jian Bin Ben
Beam-driven plasma wakefield acceleration (PWFA) is considered as one of the most promising novel acceleration technologies capable of drastically shrinking the footprints of high-energy particle colliders [...]
CERN-THESIS-2020-301 - 132 p.

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2021-03-05
14:18
Development of a beam position monitor for co-propagating electron and proton beams / Senes, Eugenio
Novel acceleration technologies promise a large improvement in particle accelerator performance, but pose a number of technical challenges due to the use of several beams and the beam parameters involved [...]
CERN-THESIS-2020-294 - 140 p.

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2021-02-11
09:52
Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments / Alonso Monsalve, Saul
Deep-learning methods are playing a crucial role in numerous scientific and industrial applications [...]
CERN-THESIS-2020-274 - 189 p.

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2021-02-04
15:18
Modern machine learning in the presence of systematic uncertainties for robust and optimized multivariate data analysis in high-energy particle physics / Wunsch, Stefan
In high energy particle physics, machine learning has already proven to be an indispensable technique to push data analysis to the limits [...]
CERN-THESIS-2021-005 - Karlsruhe : KIT Library, 2021-02-04. - 110 p.

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2021-01-15
15:51
Studies of Breakdown and Pre-Breakdown Phenomena in High Gradient Accelerating Structures / Paszkiewicz, Jan
Vacuum breakdown is a complex process and an important limiting factor of the performance of normal-conducting high-gradient particle accelerators, and can result in loss of luminosity in particle collider applications, as well as damage to accelerating structures [...]
CERN-THESIS-2020-260 - 237 p.

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2021-01-05
15:43
Trigger design studies at future high-luminosity colliders / Bologna, Simone
The LHC will enter in 2026 its high-luminosity phase which will deliver a peak instantaneous luminosity of $7.5 \times 10^{34}$ cm$^{-2}$ s$^{-1}$ and produce events with an average pile-up of 200 [...]
CERN-THESIS-2020-250 - 170 p.

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2021-01-04
09:58
Experimental studies on small diameter carbon dioxide evaporators for optimal Silicon Pixel Detector cooling / Hellenschmidt, Desiree
Since recent years the Large Hadron Collider at CERN and its experiments are the subject of upgrade programs, which are necessary to increase the foreseen collision rates and the amount of data to be gathered for the particle physics community in the future [...]
CERN-THESIS-2020-245 - https://bonndoc.ulb.uni-bonn.de/xmlui/handle/20.500.11811/8860 : bonndoc Publication Server of Bonn University, 2020-12-18. - 269 p.

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