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We present the first measurement of midrapidity vector meson phi production in Au+Au collisions at RHIC (sqrt[sNN]=130 GeV) from the STAR detector. For the 11% highest multiplicity collisions, the slope parameter from an exponential fit to the transverse mass distribution is T=379±50(stat)±45(syst) MeV, the yield dN/dy=5.73±0.37(stat)±0.69(syst) per event, and the ratio N phi /Nh- is found to be 0.021±0.001(stat)±0.004(syst). The measured ratio N phi /Nh- and T for the phi meson at midrapidity do not change for the selected multiplicity bins.
We report first results on elliptic flow of identified particles at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV using the STAR TPC at RHIC. The elliptic flow as a function of transverse momentum and centrality differs significantly for particles of different masses. This dependence can be accounted for in hydrodynamic models, indicating that the system created shows a behavior consistent with collective hydrodynamical flow. The fit to the data with a simple model gives information on the temperature and flow velocities at freeze-out.
The minimum-bias multiplicity distribution and the transverse momentum and pseudorapidity distributions for central collisions have been measured for negative hadrons ( h-) in Au+Au interactions at sqrt[sNN] = 130 GeV. The multiplicity density at midrapidity for the 5% most central interactions is dNh-/d eta | eta = 0 = 280±1(stat)±20(syst), an increase per participant of 38% relative to pp-bar collisions at the same energy. The mean transverse momentum is 0.508±0.012 GeV/c and is larger than in central Pb+Pb collisions at lower energies. The scaling of the h- yield per participant is a strong function of pperp. The pseudorapidity distribution is almost constant within | eta |<1.
We report the first measurement of inclusive antiproton production at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV by the STAR experiment at RHIC. The antiproton transverse mass distributions in the measured transverse momentum range of 0.25<pperp<0.95 GeV/c are found to fall less steeply for more central collisions. The extrapolated antiproton rapidity density is found to scale approximately with the negative hadron multiplicity density.
Effect of event selection on jetlike correlation measurement in d+Au collisions at √sNN = 200 GeV
(2015)
Dihadron correlations are analyzed in √sNN = 200 GeV d + Au collisions classified by forward charged particle multiplicity and zero-degree neutral energy in the Au-beam direction. It is found that the jetlike correlated yield increases with the event multiplicity. After taking into account this dependence, the non-jet contribution on the away side is minimal, leaving little room for a back-to-back ridge in these collisions.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
Mid-rapidity transverse mass spectra and multiplicity densities of charged and neutral kaons are reported for Au + Au collisions at √sNN = 130 GeV at RHIC. The spectra are exponential in transverse mass, with an inverse slope of about 280 MeV in central collisions. The multiplicity densities for these particles scale with the negative hadron pseudo-rapidity density. The charged kaon to pion ratios are K+/π− = 0.161± 0.002(stat) ± 0.024(syst) and K−/π− = 0.146± 0.002(stat) ± 0.022(syst) for the most central collisions. The K+/π− ratio is lower than the same ratio observed at the SPS while the K−/π− is higher than the SPS result. The ratios are enhanced by about 50% relative to p + p and p¯ + p collision data at similar energies.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.