Abstract

Sivers effect for gluons is connected to gluon orbital angular momentum which may be the missing part of the nucleon spin puzzle. We present a method of extraction of Sivers effect for gluons from COMPASS SIDIS data on transversely polarised target. In order to access the Sivers effect for gluons photon-gluon fusion (PGF) process is used. To enhance the fraction of PGF in the sample high-pT hadron pair events are selected. The method is based on a assumption that there are 3 processes contributing to the muon-nucleon scattering: PGF, leading process and QCD Compton process. Then one performs a weighting procedure which enables to extract the asymmetries for the 3 contributing processes simultaneously. In order to do that a neural network trained by a Monte Carlo to assign to each event 3 probabilities corresponding to the 3 processes is needed. Finaly we show results of Sivers effect for gluons extraction on COMPASS data with transversely polarised deuteron target. A PGF sinΦ 2h –Φ S = −0.14 ± 0.15 (stat.) at ‹XG › = 0.126.

Highlights

  • In the paper we present the extraction of the Sivers effect for gluons

  • The method enables us to separate the Sivers effect comming from the Photon-Gluon Fusion (PGF) and quark-originated processes in leading order

  • MC is used to train a Neural Network and we demonstrate the validation of this training

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Summary

Introduction

In the paper we present the extraction of the Sivers effect for gluons. The method enables us to separate the Sivers effect comming from the Photon-Gluon Fusion (PGF) and quark-originated processes in leading order. MC is used to train a Neural Network and we demonstrate the validation of this training.

The measurement of Sivers asymmetry
Extraction of Sivers asymmetry on gluons from measured asymmetry
Binning in the Sivers angle
Monte Carlo simulation and Neural Network training
Comparison of MC with real data
Neural Network training
Validation of the method using Monte Carlo
Particle identification
Kinematic cuts
Polarisation of the target
Final results
Systematic error due to MC
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