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The total charm-quark production cross section per unit of rapidity dσ(cc)/dy, and the fragmentation fractions of charm quarks to different charm-hadron species f(c → hc), are measured for the first time in p–Pb collisions at √sNN = 5.02 TeV at midrapidity (−0.96 < y < 0.04 in the centre-ofmass frame) using data collected by ALICE at the CERN LHC. The results are obtained based on all the available measurements of prompt production of ground-state charm-hadron species: D0, D+,D+s, and J/ψ mesons, and Λ+cand Ξ0cbaryons. The resulting cross section is dσ(cc)/dy = 219.6±6.3 (stat.)+10.5−11.8(syst.)+7.6−2.9(extr.)±5.4 (BR)±4.6 (lumi.)±19.5 (rapidity shape) +15.0 (Ω0c) mb, which is consistent with a binary scaling of pQCD calculations from pp ollisions. The measured fragmentation fractions are compatible with those measured in pp collisions at √s = 5.02 and 13 TeV, showing an increase in the relative production rates of charm baryons with respect to charm mesons in pp and p–Pb collisions compared with e+e − and e−p collisions. The pT-integrated nuclear modification factor of charm quarks, RpPb(cc) = 0.91±0.04 (stat.) +0.08 −0.09 (syst.) +0.04 −0.03 (extr.)±0.03 (lumi.), is found to be consistent with unity and with theoretical predictions including nuclear modifications of the parton distribution functions.
This work aims to differentiate strangeness produced from hard processes (jet-like) and softer processes (underlying event) by measuring the angular correlation between a high-momentum trigger hadron (h) acting as a jet-proxy and a produced strange hadron (φ(1020) meson). Measuring h–φ correlations at midrapidity in p–Pb collisions at √sNN = 5.02 TeV as a function of event multiplicity provides insight into the microscopic origin of strangeness enhancement in small collision systems. The jet-like and the underlying-event-like strangeness production are investigated as a function of event multiplicity. They are also compared between a lower and higher momentum region. The evolution of the per-trigger yields within the near-side (aligned with the trigger hadron) and away-side (in the opposite direction of the trigger hadron) jet is studied separately, allowing for the characterization of two distinct jet-like production regimes. Furthermore, the h–φ correlations within the underlying event give access to a production regime dominated by soft production processes, which can be compared directly to the in-jet production. Comparisons between h–φ and dihadron correlations show that the observed strangeness enhancement is largely driven by the underlying event, where the φ/h ratio is significantly larger than within the jet regions. As multiplicity increases, the fraction of the total φ(1020) yield coming from jets decreases compared to the underlying event production, leading to high-multiplicity events being dominated by the increased strangeness production from the underlying event
The production of K∗(892)± meson resonance is measured at midrapidity (|y|<0.5) in Pb-Pb collisions at sNN−−−√=5.02 TeV using the ALICE detector at the LHC. The resonance is reconstructed via its hadronic decay channel K∗(892)±→K0Sπ±. The transverse momentum distributions are obtained for various centrality intervals in the pT range of 0.4-16 GeV/c. The reported measurements of integrated yields, mean transverse momenta, and particle yield ratios are consistent with previous ALICE measurements for K∗(892)0. The pT-integrated yield ratio 2K∗(892)±/(K++K−) in central Pb-Pb collisions shows a significant suppression (9.3σ) relative to pp collisions. Thermal model calculations overpredict the particle yield ratio. Although both simulations consider the hadronic phase, only HRG-PCE accurately represents the measurements, whereas MUSIC+SMASH tends to overpredict them. These observations, along with the kinetic freeze-out temperatures extracted from the yields of light-flavored hadrons using the HRG-PCE model, indicate a finite hadronic phase lifetime, which increases towards central collisions. The pT-differential yield ratios 2K∗(892)±/(K++K−) and 2K∗(892)±/(π++π−) are suppressed by up to a factor of five at pT<2 GeV/c in central Pb-Pb collisions compared to pp collisions at s√= 5.02 TeV. Both particle ratios and are qualitatively consistent with expectations for rescattering effects in the hadronic phase. The nuclear modification factor shows a smooth evolution with centrality and is below unity at pT>8 GeV/c, consistent with measurements for other light-flavored hadrons. The smallest values are observed in most central collisions, indicating larger energy loss of partons traversing the dense medium.
The production of K∗(892)± meson resonance is measured at midrapidity (|y|<0.5) in Pb-Pb collisions at sNN−−−√=5.02 TeV using the ALICE detector at the LHC. The resonance is reconstructed via its hadronic decay channel K∗(892)±→K0Sπ±. The transverse momentum distributions are obtained for various centrality intervals in the pT range of 0.4-16 GeV/c. The reported measurements of integrated yields, mean transverse momenta, and particle yield ratios are consistent with previous ALICE measurements for K∗(892)0. The pT-integrated yield ratio 2K∗(892)±/(K++K−) in central Pb-Pb collisions shows a significant suppression (9.3σ) relative to pp collisions. Thermal model calculations overpredict the particle yield ratio. Although both simulations consider the hadronic phase, only HRG-PCE accurately represents the measurements, whereas MUSIC+SMASH tends to overpredict them. These observations, along with the kinetic freeze-out temperatures extracted from the yields of light-flavored hadrons using the HRG-PCE model, indicate a finite hadronic phase lifetime, which increases towards central collisions. The pT-differential yield ratios 2K∗(892)±/(K++K−) and 2K∗(892)±/(π++π−) are suppressed by up to a factor of five at pT<2 GeV/c in central Pb-Pb collisions compared to pp collisions at s√= 5.02 TeV. Both particle ratios and are qualitatively consistent with expectations for rescattering effects in the hadronic phase. The nuclear modification factor shows a smooth evolution with centrality and is below unity at pT>8 GeV/c, consistent with measurements for other light-flavored hadrons. The smallest values are observed in most central collisions, indicating larger energy loss of partons traversing the dense medium.
Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at s√=13 TeV and p−Pb collisions at sNN−−−√=5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle Δφ and pseudorapidity separation Δη for pairs of primary charged particles within the pseudorapidity interval |η|<0.9 and the transverse-momentum interval 1<pT<4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6<|Δη|<1.8) in various high-multiplicity event classes using the low-multiplicity template fit method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.
The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.
Dielectrons are unique observables in ultra-relativistic heavy-ion collisions. Thanks to their penetrating nature, they carry information from all stages of the collision and can provide knowledge about pre-equilibirium dynamics, QGP temperature and transport coefficients, and chiral symmetry restoration. On the other hand, experimental challenges are enormous because production cross sections are small and the signal of interest is eclipsed by a huge combinatorial and physics background from light- and heavy-flavour hadron decays. In this talk the status of dielectron measurements with ALICE is shown and the perspectives with the recently installed and planned ALICE detector upgrades are discussed.
The inclusive production of the charm-strange baryon Ω0c is measured for the first time via its semileptonic decay into Ω−e+νe at midrapidity (|y| < 0.8) in proton–proton (pp) collisions at the centre-of-mass energy √s = 13 TeV with the ALICE detector at the LHC. The transverse momentum (pT) differential cross section multiplied by the branching ratio is presented in the interval 2 < pT < 12 GeV/c. The branching-fraction ratio BR(Ω0c → Ω−e+νe)/BR(Ω0c → Ω−π+) is measured to be 1.12 ± 0.22 (stat.) ± 0.27 (syst.). Comparisons with other experimental measurements, as well as with theoretical calculations, are presented.
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.