Measurements of transverse energy distributions in Au + Au collisions at s(NN)**(1/2) = 200-GeV.

The STAR collaboration Adams, J. ; Aggarwal, M.M. ; Ahammed, Z. ; et al.
Phys.Rev.C 70 (2004) 054907, 2004.
Inspire Record 653797 DOI 10.17182/hepdata.98621

Transverse energy ($E_T$) distributions have been measured for Au+Au collisions at $\sqrt{s_{NN}}= 200$ GeV by the STAR collaboration at RHIC. $E_T$ is constructed from its hadronic and electromagnetic components, which have been measured separately. $E_T$ production for the most central collisions is well described by several theoretical models whose common feature is large energy density achieved early in the fireball evolution. The magnitude and centrality dependence of $E_T$ per charged particle agrees well with measurements at lower collision energy, indicating that the growth in $E_T$ for larger collision energy results from the growth in particle production. The electromagnetic fraction of the total $E_T$ is consistent with a final state dominated by mesons and independent of centrality.

16 data tables

Typical MIP spectrum. The hits correspond to isolated tracks with p > 1.25 GeV/c which project to EMC towers. The peak corresponds to the energy deposited by non-showering hadrons (MIP peak).

$p/E_{tower}$ spectrum for electron candidates, selected through $dE/dx$ from the TPC, with 1.5 < p < 5.0 GeV/c. A well defined electron peak is observed. The dashed line corresponds to the hadronic background in the $dE/dx$-identified electron sample.

Upper plot: points are measured $p/E_{tower}$ electron peak position as a function of the distance to the center of the tower. The solid line is from a calculation based on a full GEANT simulation of the detector response to electrons. Lower plot: points show measured energy deposited by electrons in the tower as a function of the momentum for distances to the center of the tower smaller than 2.0 cm. The first point is the electron equivalent energy of the minimum ionizing particles. The solid line is a second order polynomial fit of the data.

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