CERN Accelerating science

CMS Theses

უკანასკნელი დამატებები:
2023-06-07
16:03
Search for heavy Higgs bosons in conjunction with neural-network-driven reconstruction and upgrade of the Fast Beam Condition Monitor at the CMS experiment / Rubenach, Jonas
This thesis presents a search for a heavy scalar and a heavy pseudoscalar Higgs boson decaying into a top quark and a top antiquark [...]
CERN-THESIS-2023-066 - Hamburg : Verlag Deutsches Elektronen-Synchrotron DESY, 2023-05-12. - 177 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-06-04
20:32
Probing the Quark Gluon Plasma with B0s and B+ Mesons: Cross Sections in pp and Nuclear Modification Factors in PbPb Collisions / Legoinha, Henrique
The quark gluon plasma (QGP) is one of the most exciting frontiers of particle physics [...]
CERN-THESIS-2023-064 - 89 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-06-04
16:45
Measurement of the properties of the Higgs boson in CMS experiment at the LHC / Mukherjee, Soumya
Since the groundbreaking discovery of the Higgs boson (H) in 2012, the primary focus of the experiments conducted at the Large Hadron Collider (LHC) has been to accurately measure its properties [...]
CERN-THESIS-2023-063 - 297 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-06-03
18:10
Performance of micro-pattern gaseous detectors at the LHC and future collider experiments / Pellecchia, Antonello
CERN-THESIS-2023-062 -


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-30
13:34
Research and Development for the Data, Trigger and Control Card in Preparation for Hi-Lumi LHC / Monk, David Gabriel
When the Large Hadron Collider (LHC) increases its luminosity by an order of magnitude in the coming decade, the experiments that sit upon it must also be upgraded to continue to their physics performance in the increasingly demanding environment [...]
CERN-THESIS-2022-359 CMS-TS-2023-008. - 2023. - 206 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-28
12:00
Searching for Unexpected New Physics at the LHC with Machine Learning / Grosso, Gaia
New Physics Learning Machine (NPLM) is a machine-learning based strategy to detect data departures from a Reference hypothesis (the Standard Model), with no prior bias on the source of the discrepancy responsible for it [...]
CERN-THESIS-2023-055 - 266 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-23
17:30
Search for New Physics in Vector Boson-mediated Electroweak processes with the CMS Experiment at LHC / Piccinelli, Andrea
CERN-THESIS-2023-054 -


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-08
14:49
A Search for Leptoquarks Coupling to $\tau$ Leptons and Bottom Quarks in Proton-Proton Collisions at the CMS Experiment / Neutelings, Izaak
Despite the many remarkable successes of the Standard Model (SM) of particle physics, there are both theoretical and experimental reasons that imply the SM is not the final and most fundamental theory of nature [...]
CERN-THESIS-2022-353 CMS-TS-2023-007. - 180 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-05-07
14:11
Data‐driven background modelling and trigger algorithms for compressed supersymmetry searches with the CMS experiment at the LHC / Zarucki, Mateusz
Supersymmetry (SUSY) is a highly motivated theory that can provide solutions to central issues and open questions of the standard model (SM) of particle physics [...]
CERN-THESIS-2023-047 - 324 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2023-04-28
16:54
Search for Dark Matter produced in association with Monotop in the fully leptonic channel in proton-proton collisions at 13 TeV with the Compact Muon Soleniod experiment / Uniyal, Rishabh
A search for dark matter has been performed using the monotop model, with the dark matter signature in the form of large missing energy, presence of a b-tagged jet and an isolated lepton (electron and muon) [...]
CERN-THESIS-2023-042 - 162 p.


დეტალური ჩანაწერი - მსგავსი ჩანაწერები