2026-09-20T22:20:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1432732022-06-16T03:19:06Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Lee, Yen-Jie
Roland, Gunther
Ying, Yueyang
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-06-15T13:08:53Z
2022-06-15T13:08:53Z
2022-02
2022-02-22T18:32:07.722Z
https://hdl.handle.net/1721.1/143273
The modification of quark- and gluon-initiated jets in the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the size of the modifications differs between theoretical models. Therefore a fully data-driven technique is crucial for an unbiased extraction of the quark and gluon jet spectra and substructure. We demonstrate a fully data-driven method for separating quark and gluon contributions to jet observables using a statistical technique called topic modeling. We will also demonstrate that jet substructures, such as jet shapes and jet fragmentation function, could be extracted using this data-driven method. This proof-of-concept study is based on proton-proton and heavy-ion collision events from the PYQUEN generator with statistics accessible in Run 4 of the Large Hadron Collider. These results suggest the potential for an experimental determination of quark- and gluon-jet spectra and their substructures.
M.Eng.
Massachusetts Institute of Technology
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Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Data-driven extraction of the substructure of quark and gluon jets in proton-proton and heavy-ion collisions
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
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unknown
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<Abstract>The modification of quark- and gluon-initiated jets in the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the size of the modifications differs between theoretical models. Therefore a fully data-driven technique is crucial for an unbiased extraction of the quark and gluon jet spectra and substructure. We demonstrate a fully data-driven method for separating quark and gluon contributions to jet observables using a statistical technique called topic modeling. We will also demonstrate that jet substructures, such as jet shapes and jet fragmentation function, could be extracted using this data-driven method. This proof-of-concept study is based on proton-proton and heavy-ion collision events from the PYQUEN generator with statistics accessible in Run 4 of the Large Hadron Collider. These results suggest the potential for an experimental determination of quark- and gluon-jet spectra and their substructures.</Abstract>
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