Transversity measurements at HERMES

Azimuthal single-spin asymmetries (SSA) in semi-inclusive electroproduction of charged pions in deep-inelastic scattering (DIS) of positrons on a transversely polarised hydrogen target are presented. Azimuthal moments for both the Collins and the Sivers mechanism are extracted. In addition the subleading-twist contribution due to the transverse spin component from SSA on a longitudinally polarised hydrogen target is evaluated.Comment: to appear in the proceedings of the XIII International Workshop on Deep Inelastic Scattering (DIS 2005

Analysis and Processing of Irregularly Distributed Point Clouds

We address critical issues arising in the practical implementation of processing real point cloud data that exhibits irregularities. We develop an adaptive algorithm based on Learning Theory for processing point clouds from a stationary sensor that standard algorithms have difficulty approximating. Moreover, we build the theory of distribution-dependent subdivision schemes targeted at representing curves and surfaces with gaps in the data. The algorithms analyze aggregate quantities of the point cloud over subdomains and predict these quantities at the finer level from the ones at the coarser level

Transverse spin effects of sea quarks in unpolarized nucleons

We calculate the non-zero Boer-Mulders functions of sea quarks inside the proton in a meson-baryon fluctuation model. The results show that the transverse spin effects of sea quarks in an unpolarized nucleon are sizable. Using the obtained antiquark Boer-Mulders functions, we estimate the $\cos 2 \phi$ asymmetries in the unpolarized $pp$ and $p D$ Drell-Yan processes at FNAL E866/NuSea experiments. The prediction for the $\cos 2 \phi$ asymmetries in the unpolarized $pp$ Drell-Yan process at the BNL Relativistic Heavy Ion Collider (RHIC) is also given.Comment: 7 pages, 5 figures, to appear in Physical Review

New insight on the Sivers transverse momentum dependent distribution function

Polarised Semi-Inclusive Deep Inelastic Scattering (SIDIS) processes allow to study Transverse Momentum Dependent partonic distributions (TMDs), which reveal a non trivial three dimensional internal structure of the hadrons in momentum space. One of the most representative of the TMDs is the so-called Sivers function that describes the distribution of unpolarized quarks inside a transversely polarized proton. We present a novel extraction of the Sivers distribution functions from the most recent experimental data of HERMES and COMPASS experiments. Using suitable parametrizations, within the TMD factorization scheme, and a simple fitting strategy, we also perform a preliminary exploration of the role of the proton sea quarks.Comment: Talk delivered by M. Boglione at SPIN2010, September 27-October 2, 2010, Juelich, Germany. Left panel of Fig. 5 replace

Asymmetries involving dihadron fragmentation functions: from DIS to e+e- annihilation

Using a model calculation of dihadron fragmentation functions, we fit the spin asymmetry recently extracted by HERMES for the semi-inclusive pion pair production in deep-inelastic scattering on a transversely polarized proton target. By evolving the obtained dihadron fragmentation functions, we make predictions for the correlation of the angular distributions of two pion pairs produced in electron-positron annihilations at BELLE kinematics. Our study shows that the combination of two-hadron inclusive deep-inelastic scattering and electron-positron annihilation measurements can provide a valid alternative to Collins effect for the extraction of the quark transversity distribution in the nucleon.Comment: 11 pages, RevTeX style, 6 figures in eps forma

Deeply Learning Deep Inelastic Scattering Kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods

Deeply Learning Deep Inelastic Scattering Kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron-proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables $Q^2$ and $x$. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.Comment: 16 pages, 8 figures. v3 journal versio

EXTERNAL WORK BILATERAL SYMMETRY DURING INCREMENTAL CYCLING EXERCISE

The aim of the present study was to compare the bilateral external work and torque at four stages of an incremental maximal cycling. Eleven cyclists were evaluated on a cycle ergometer. Four stages of the incremental cycling workload were defined as 60, 75, 90 and 100% of maximal oxygen uptake (VO2Max). Pedal forces and kinematics variables were measured through each stage. Crank torque and external work were computed (both sides). Crank work and torque increased throughout the incremental test. There were no differences between legs in relation to work and torque at the crank. The high variability of force symmetry between subjects, and between days may indicate the difference of our results compared to previous studies

Constraints on the gluon Sivers distribution via transverse single spin asymmetries at midrapidity in p(transv. polarized) p -> pi^0 X processes at BNL RHIC

We consider the recent RHIC data on the transverse single spin asymmetry (SSA) A_N, measured in p(transv. polarized) p -> pi^0 X processes at mid-rapidity by the PHENIX collaboration. The measurement is consistent with a vanishing SSA. We analyze this experimental information within a hard scattering approach based on a generalized QCD factorization scheme, with unintegrated, transverse momentum dependent (TMD), parton distribution and fragmentation functions. It turns out that, in the kinematical region of the data, only the gluon Sivers effect could give a large contribution to A_N; its vanishing value is thus an indication about the possible size of the gluon Sivers function (GSF). Approximate upper limits on its magnitude are derived. Additional constraints obtained combining available parameterizations of the quark Sivers function and the Burkardt sum rule (BSR) for the Sivers distributions are also discussed.Comment: RevTeX, 8 pages, 2 ps figures; v2: few clarifying comments, a "note added in proof" and some references added; version published in Phys. Rev.