Data-driven extraction of the substructure of quark and gluon jets in proton-proton and heavy-ion collisions
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 full...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/143273 |
| Summary: | 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. |
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