“School of Particles%20And%20Accelerator”
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| Paper IPM / Particles%20And%20Accelerator / 15121 |
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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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