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Hanpu Jiang

Publications and source records attributed to Hanpu Jiang.

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Mini-jet Clustering Algorithm Using Transverse-momentum Seeds in High-energy Nuclear Collisions

We propose an algorithm to detect mini-jet clusters in high-energy nuclear collisions, by selecting a high-transverse-momentum ($p_T$) particle as a seed and assigning a clustering radius ($R$) in the pseudorapidity and azimuthal-angle space. Our PYTHIA simulations for $p$+$p$ collisions show that a scheme with a seeding $p_T$ of around 0.5 GeV/$c$ and $R$ of approximately 0.6 satisfactorily identifies mini-jet clusters. The correlation between clusters obtained in PYTHIA calculations using the algorithm exhibits the proper behavior of hard-scattering-like processes, suggesting its usefulness in isolating mini-jet-like clusters from non-hard-scattering soft processes when applied to actual nuclear-collision data, thereby allowing a closer examination of both the mini-jet and the soft mechanisms.

physics.data-an

On the clustering properties of produced particles in high-energy $pp$ collisions

Minijets provide useful information on parton interactions in the low transverse-momentum (low-$p_T$) region. Because minijets produce clusters, we study the clustering properties of produced particles in high-energy $pp$ collisions as a first step to identify minijets. We develop an algorithm to find clusters by using the k-means clustering method, in conjunction with a k-number (cluster number) selection principle in the space of pseudorapidity and azimuthal angles. We test the clustering algorithm using events generated by PYTHIA 8.1, for $pp$ collision at $\sqrt{s}=200$ GeV. We find that clustering of low-$p_T$ hadrons occurs in high multiplicity events. However similar clustering properties are also present for particles produced randomly in a finite pseudorapidity and azimuthal angle space. To distinguish the dynamics from random generations of events, it is necessary to examine the correlation between particles and between clusters. We find that the correlations between clusters may provide a useful tool to distinguish the underlying dynamics of the reaction mechanism.

hep-ph