Heavy quarkonium 2S states in light-front quark model

We study the charmonium 2S states $\psi'$ and $\eta_c'$, and the bottomonium 2S states $\Upsilon'$ and $\eta_b'$, using the light-front quark model and the 2S state wave function of harmonic oscillator as the approximation of the 2S quarkonium wave function. The decay constants, transition form factors and masses of these mesons are calculated and compared with experimental data. Predictions of quantities such as Br$(\psi' \to \gamma \eta_c')$ are made. The 2S wave function may help us learn more about the structure of these heavy quarkonia.Comment: 5 latex pages, final version for journal publicatio

Three-dimensional parton distribution functions g1Tg_{1T} and h1L⊥h_{1L}^\perp in the polarized proton-antiproton Drell-Yan process

We present predictions of the unweighted and weighted double spin asymmetries related to the transversal helicity distribution $g_{1T}$ and the longitudinal transversity distribution $h_{1L}^\perp$, two of eight leading-twist transverse momentum dependent parton distributions (TMDs) or three-dimensional parton distribution functions (3dPDFs), in the polarized proton-antiproton Drell-Yan process at typical kinematics on the Facility for Antiproton and Ion Research (FAIR). We conclude that FAIR is ideal to access the new 3dPDFs towards a detailed picture of the nucleon structure.Comment: 6 latex pages, 5 figures, version for publication in EPJ

Using ensemble-mean climate scenarios for future crop yield projections: a stochastic weather generator

Using climate scenarios from only 1 or a small number of global climate models (GCMs) in climate change impact studies may lead to biased assessment due to large uncertainty in climate projections. Ensemble means in impact projections derived from a multi-GCM ensemble are often used as best estimates to reduce bias. However, it is often time consuming to run process-based models (e.g. hydrological and crop models) in climate change impact studies using numerous climate scenarios. It would be interesting to investigate if using a reduced number of climate scenarios could lead to a reasonable estimate of the ensemble mean. In this study, we generated a single ensemble-mean climate scenario (En-WG scenario) using ensemble means of the change factors derived from 20 GCMs included in CMIP5 to perturb the parameters in a weather generator, LARS-WG, for selected locations across Canada. We used En-WG scenarios to drive crop growth models in DSSAT ver. 4.7 to simulate crop yields for canola and spring wheat under RCP4.5 and RCP8.5 emission scenarios. We evaluated the potential of using the En-WG scenario to simulate crop yields by comparing them with crop yields simulated with the LARS-WG generated climate scenarios based on each of the 20 GCMs (WG scenarios). Our results showed that simulated crop yields using the En-WG scenarios were often close to the ensemble means of simulated crop yields using the 20 WG scenarios with a high probability of outperforming simulations based on a randomly selected GCM. Further studies are required, as the results of the proposed approach may be influenced by selected crop types, crop models, weather generators, and GCM ensembles