Drift effects and the cosmic ray density gradient in a solar rotation period: First observation with the Global Muon Detector Network (GMDN)

We present for the first time hourly variations of the spatial density gradient of 50 GeV cosmic rays within a sample solar rotation period in 2006. By inversely solving the transport equation, including diffusion, we deduce the gradient from the anisotropy that is derived from the observation made by the Global Muon Detector Network (GMDN). The anisotropy obtained by applying a new analysis method to the GMDN data is precise and free from atmospheric temperature effects on the muon count rate recorded by ground based detectors. We find the derived north-south gradient perpendicular to the ecliptic plane is oriented toward the Helioshperic Current Sheet (HCS) (i.e. southward in the toward sector of the Interplanetary Magnetic Field (IMF) and northward in the away sector). The orientation of the gradient component parallel to the ecliptic plane remains similar in both sectors with an enhancement of its magnitude seen after the Earth crosses the HCS. These temporal features are interpreted in terms of a local maximum of the cosmic ray density at the HCS. This is consistent with the prediction of the drift model for the $A<0$ epoch. By comparing the observed gradient with the numerical prediction of a simple drift model, we conclude that particle drifts in the large-scale magnetic field play an important role in organizing the density gradient, at least in the present $A<0$ epoch. We also found that corotating interaction regions did not have such a notable effect. Observations with the GMDN provide us with a new tool for investigating cosmic ray transport in the IMF.Comment: 35 pages, 10 figures, submitted to the Astrophysical Journa

Constraints on the χ_(c1) versus χ_(c2) polarizations in proton-proton collisions at √s = 8 TeV

The polarizations of promptly produced χ_(c1) and χ_(c2) mesons are studied using data collected by the CMS experiment at the LHC, in proton-proton collisions at √s=8  TeV. The χ_c states are reconstructed via their radiative decays χ_c → J/ψγ, with the photons being measured through conversions to e⁺e⁻, which allows the two states to be well resolved. The polarizations are measured in the helicity frame, through the analysis of the χ_(c2) to χ_(c1) yield ratio as a function of the polar or azimuthal angle of the positive muon emitted in the J/ψ → μ⁺μ⁻ decay, in three bins of J/ψ transverse momentum. While no differences are seen between the two states in terms of azimuthal decay angle distributions, they are observed to have significantly different polar anisotropies. The measurement favors a scenario where at least one of the two states is strongly polarized along the helicity quantization axis, in agreement with nonrelativistic quantum chromodynamics predictions. This is the first measurement of significantly polarized quarkonia produced at high transverse momentum

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives