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We present the first ever measurements of femtoscopic correlations between the K0 S and K± particles. The analysis was performed on the data from Pb–Pb collisions at √sNN = 2.76 TeV measured by the ALICE experiment. The observed femtoscopic correlations are consistent with final-state interactions proceeding via the a0(980) resonance. The extracted kaon source radius and correlation strength parameters for K0 SK− are found to be equal within the experimental uncertainties to those for K0 SK+. Comparing the results of the present study with those from published identical-kaon femtoscopic studies by ALICE, mass and coupling parameters for the a0 resonance are tested. Our results are also compatible with the interpretation of the a0 having a tetraquark structure instead of that of a diquark
This letter presents the first measurement of jet mass in Pb–Pb and p–Pb collisions at sNN=2.76 TeV and sNN=5.02 TeV, respectively. Both the jet energy and the jet mass are expected to be sensitive to jet quenching in the hot Quantum Chromodynamics (QCD) matter created in nuclear collisions at collider energies. Jets are reconstructed from charged particles using the anti-kT jet algorithm and resolution parameter R=0.4. The jets are measured in the pseudorapidity range |ηjet|<0.5 and in three intervals of transverse momentum between 60 GeV/c and 120 GeV/c. The measurement of the jet mass in central Pb–Pb collisions is compared to the jet mass as measured in p–Pb reference collisions, to vacuum event generators, and to models including jet quenching. It is observed that the jet mass in central Pb–Pb collisions is consistent within uncertainties with p–Pb reference measurements. Furthermore, the measured jet mass in Pb–Pb collisions is not reproduced by the quenching models considered in this letter and is found to be consistent with PYTHIA expectations within systematic uncertainties.
The second and the third order anisotropic flow, V2 and V3, are mostly determined by the corresponding initial spatial anisotropy coefficients, ε2 and ε3, in the initial density distribution. In addition to their dependence on the same order initial anisotropy coefficient, higher order anisotropic flow, Vn (n > 3), can also have a significant contribution from lower order initial anisotropy coefficients, which leads to mode-coupling effects. In this Letter we investigate the linear and non-linear modes in higher order anisotropic flow Vn for n = 4, 5, 6 with the ALICE detector at the Large Hadron Collider. The measurements are done for particles in the pseudorapidity range |η| < 0.8 and the transverse momentum range 0.2 < pT < 5.0 GeV/c as a function of collision centrality. The results are compared with theoretical calculations and provide important constraints on the initial conditions, including initial spatial geometry and its fluctuations, as well as the ratio of the shear viscosity to entropy density of the produced system.
Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.