“School of Particles And Accelerator”

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Paper   IPM / Particles And Accelerator / 15121
School of Particles and Accelerator
  Title:   Analytical approaches to the determination of spin-dependent parton distribution functions at NNLO approximation
1.  Maral Salajegheh
2.  Seyed Mohammad Moosavi Nejad
3.  Hamzeh Khanpour
4.  Shahin Atashbar Tehrani
  Status:   Published
  Journal: Phys. Rev. C
  No.:  5, 055201
  Vol.:  97
  Year:  2018
  Supported by:  IPM
In this paper, we present "SMKA18" which is the first set of next-to-next-leading-order (NNLO) spin-dependent parton distribution functions (spin-dependent PDFs) and their uncertainties determined through the Laplace transform technique and Jacobi polynomial approach. Using the Laplace transformations, we present an analytical solution for the spin-dependent Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equations at NNLO approximation. The results shown made use of a wide range of proton g1p(x, Q2), neutron g1n(x, Q2) and deuteron g1d(x, Q2) spin-dependent structure functions dataset including the most recent high-precision measurements from COMPASS16 experiments at CERN which are playing an increasingly important role in global spin-dependent fits. The careful estimations of uncertainties have been performed using the standard "Hessian error" propagation. We compare our results with the available spin-dependent inclusive DIS dataset and other results for the spin-dependent PDFs in literature. The obtained results for the spin-dependent PDFs as well as spin-dependent structure functions are clearly explained both in the small and large values of x.

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