CERN Accelerating science

CERN Students Projects

უკანასკნელი დამატებები:
2018-12-10
13:54
Two Graphical User Interfaces for ISS / Baader, Edith Franziska
The ISOLDE Solenoidal Spectrometer (ISS) is one of the experiments of the HIE-ISOLDE section. [...]
CERN-STUDENTS-Note-2018-221.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-12-06
14:58
A Deep Neural Network capable of discriminating between jets coming from the decay of longitudinally and transversely polarized W or Z bosons with a large Lorentz boost / De Boer, Jan (University of Copenhagen (DK))
The amount of data that will come available from the future High Luminosity Large Hadron Collider enables precision studies to look for deviations from Standard Model expectations. [...]
CERN-STUDENTS-Note-2018-220.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-12-04
14:11
Possible Improvements of the Signal Selections in ATLAS for Dark Matter Production in association with Heavy Flavour Quarks / Ruimi, Ophir Moshe (CERN)
During this Summer Student Programme at CERN I had the opportunity to join the DM+HF ATLAS group working on WIMPs pair production associated with heavy flavour (bottom and top) quarks, arising from proton-proton collisions at the LHC [...]
CERN-STUDENTS-Note-2018-219.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-12-03
15:53
Measuring the Ratio of σ(ttH)/σ(ttZ) in the ttH multilepton channel with the ATLAS detector / Halser, Lea
At the Large Hadron Collider (LHC) at CERN protons are collided with a center of mass energy (CME) up to 13 TeV. [...]
CERN-STUDENTS-Note-2018-218.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-12-03
15:45
Cross Validation Improvements in TMVA  / Uzair, Mohammad
TMVA is a machine learning framework primarily targeted at enabling physics  research and is distributed as part of ROOT. This project sets out to improve the  validation tools, and cross validation of TMVA. Cross validation is an important tool for making the most out of limited data sets trading increased data efficiency for decreased computation efficiency. This is relevant to HEP applications since  experiments are limited by the prohibitive cost of running detector and reconstruction simulation. Tasks include: implement and evaluate the performance of different cross validation splitting functions; extend the current implementation to seamlessly handle nested cross validation; evaluate and compare the performance of the TMVA implementation to industry standard libraries using physics datasets; parallelise training and evaluation.   
CERN-STUDENTS-Note-2018-217.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-12-03
09:49
sTGC Testing for ATLAS’ New Small Wheel at McGill University and CERN / Formenti, Lia Frances
ATLAS’ muon small wheel must be replaced to improve muon track reconstruction and the forward muon trigger as the LHC tends towards higher collision rates. [...]
CERN-STUDENTS-Note-2018-216.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-11-27
13:40
H2 Delay Wire Chamber Efficiency and Electron-Pion Separation in a CMS HGCal Prototype / Adi, Wihan
Currently CMS is developing the High Granularity Calorimeter (HGCal) as part of its HL-LHC upgrade and for this various CMS calorimeter prototypes are tested in test beam experiments. [...]
CERN-STUDENTS-Note-2018-215.
- 2018.

დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-11-19
15:48
Work Project Report / Ottimo, Alberto
The current LHCb detector uses both hardware and software for its High Level Trigger. [...]
CERN-STUDENTS-Note-2018-214.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-11-19
14:38
Background measurements and simulation for CODEX-b / Lee, Jongho
CODEX-b is a newly proposed detector [1] to be housed inside the existing LHCb cavern that will search for weakly interacting long-lived particles, predicted in many extensions of the Standard Model. [...]
CERN-STUDENTS-Note-2018-213.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2018-11-19
13:23
Control system for the ALPHA-g apparatus vacuum heaters / Svazas, Erikas
ALPHA collaboration studies the fundamental symmetries between matter and antimatter, or more precisely between hydrogen and its antimatter counterpart antihydrogen. [...]
CERN-STUDENTS-Note-2018-212.
- 2018.
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დეტალური ჩანაწერი - მსგავსი ჩანაწერები