Speaker
Description
The long-range ($|\Delta\eta| \gt 2$) near-side ($\Delta\phi\approx0$) ridge structure in a two-particle correlation analysis has been observed in heavy ion collision, which was well-explained by the hydrodynamic models based on the quark-gluon plasma (QGP) effect. However, even though small systems such as pp and pPb collisions cannot have enough density and temperature to create the QGP matter, the ridge phenomenon appeared in high multiplicity events of small systems, which is controversial in the hydrodynamic models. Among numerous models to explain this phenomenon in small systems, the Momentum Kick Model (MKM) can give a description of it via a kinematic process where the high-momentum jet particles transfer their momentum to the medium partons called a ``kick" process, leading to collective motion which becomes the ridge phenomenon in the MKM. The MKM has been applied to various experimental data, such as the STAR and the PHENIX, and has shown good agreement. Furthermore, since the ridge yields are dependent on multiplicity in high-energy collision experiments, C. Y. Wong built a multiplicity dependence on the MKM through an impact parameter and applied it to the CMS data for pp collisions at $\sqrt{s}=7$ TeV.
Recently, the CMS Collaboration measured the ridge yields along the different $p_T$ and multiplicity ranges for pp collisions at $\sqrt{s}=13$ TeV. To verify the MKM with multiplicity dependence, we expand the model analysis at 7 TeV to those at 13 TeV and provide the theoretical basis on two questions raised by the CMS Collaboration; the linearity of the ridge yield with multiplicity and the prominence at the middle $p_T$ range. Moreover, the CMS Collaboration suggested that the ridge structure does not have the collision energy dependence for pp collisions by comparing the ridge yields at 7 TeV with those at 13 TeV. From this surmise, we predict the future ridge behavior of the LHC Run3 at $\sqrt{s}=5.3$ and $8.5$ TeV.
| Category | Theory |
|---|---|
| Collaboration (if applicable) | Inha University |
