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Spin asymmetries for events with high p_T hadrons in DIS and an evaluation of the gluon polarization

SMC Collaboration, B. Adeva

TL;DR

This work measures longitudinal spin asymmetries in deep inelastic scattering of polarized muons on polarized nucleons with two high-$p_T$ hadrons in the final state to tag Photon-Gluon Fusion (PGF). It employs two PGF-enrichment strategies, including a neural-network classifier, to maximize PGF purity and extract the gluon polarization $\frac{\Delta G}{G}$ from LO QCD expressions that couple $\Delta G$ to PGF, while using $A_1$ for $\Delta q/q$ and MC-generated partonic asymmetries. The resulting value, $\frac{\Delta G}{G} = -0.20 \pm 0.28\,({\rm stat}) \pm 0.10\,({\rm syst})$ at $\langle\eta\rangle \approx 0.07$, indicates no strong evidence for a sizable gluon polarization within the experimental uncertainties. The study highlights the trade-off between efficiency and purity in PGF tagging and demonstrates the benefit of neural-network-based selection for improving statistical precision in spin-structure measurements.

Abstract

We present a measurement of the longitudinal spin cross section asymmetry for deep inelastic muon-nucleon interactions with two high transverse momentum hadrons in the final state. Two methods of event classification are used to increase the contribution of the Photon Gluon Fusion process to above 30%. The most effective one, based on a neural network approach, provides the asymmetries A_p(lN->lhhX)=0.030+/-0.057+/-0.010 and A_d(lN->lhhX)=0.070+/-0.076+/-0.010. From these values we derive an averaged gluon polarization delta(G)/G=-0.20+/-0.28+/-0.10 at an average fraction of nucleon momentum carried by gluons eta=0.07.

Spin asymmetries for events with high p_T hadrons in DIS and an evaluation of the gluon polarization

TL;DR

This work measures longitudinal spin asymmetries in deep inelastic scattering of polarized muons on polarized nucleons with two high- hadrons in the final state to tag Photon-Gluon Fusion (PGF). It employs two PGF-enrichment strategies, including a neural-network classifier, to maximize PGF purity and extract the gluon polarization from LO QCD expressions that couple to PGF, while using for and MC-generated partonic asymmetries. The resulting value, at , indicates no strong evidence for a sizable gluon polarization within the experimental uncertainties. The study highlights the trade-off between efficiency and purity in PGF tagging and demonstrates the benefit of neural-network-based selection for improving statistical precision in spin-structure measurements.

Abstract

We present a measurement of the longitudinal spin cross section asymmetry for deep inelastic muon-nucleon interactions with two high transverse momentum hadrons in the final state. Two methods of event classification are used to increase the contribution of the Photon Gluon Fusion process to above 30%. The most effective one, based on a neural network approach, provides the asymmetries A_p(lN->lhhX)=0.030+/-0.057+/-0.010 and A_d(lN->lhhX)=0.070+/-0.076+/-0.010. From these values we derive an averaged gluon polarization delta(G)/G=-0.20+/-0.28+/-0.10 at an average fraction of nucleon momentum carried by gluons eta=0.07.

Paper Structure

This paper contains 12 sections, 6 equations, 6 figures, 4 tables.

Figures (6)

  • Figure 1: Lowest order diagrams for DIS $\gamma^{\ast}$ absorption: a) leading process (LP), b) gluon radiation (QCD-C), c) photon-gluon fusion (PGF).
  • Figure 2: Distribution of vertices along the beam axis. Points correspond to the proton data from 1993 and the histogram to the corresponding MC simulation.
  • Figure 3: The $x$ and $Q^2$ distributions for the proton case: points correspond to the data and histograms to the Monte Carlo simulation.
  • Figure 4: Distributions of longitudinal momentum and scattering angle for the hadron with the highest $p_T$. Points correspond to the proton data collected in 1993, histograms to the Monte Carlo simulations with the modified fragmentation function.
  • Figure 5: Comparison of purity and efficiency for the selection methods based on the cut on $\sum p_T^2$ and the NN response. Simulations correspond to the proton sample.
  • ...and 1 more figures