EKO是一个开源的Python库，专注于解决不极化部分子分布函数的DGLAP方程到NNLO。其特色在于计算独立于边界条件的演化算子，方便快速地应用于多种初始PDF的演化。另一方面，文章还展示了全球QCD分析在极化反物质方面的新进展，通过最新的RHIC STAR数据首次从数据驱动的角度提取了非零的极化轻夸克海不对称性。
EKO: Evolution Kernel Operators
https://arxiv.org/pdf/2202.02338.pdf
abstract: We present a new QCD evolution library for unpolarized parton distribution functions: EKO. The program solves DGLAP equations up to next-to-next-to-leading order. The unique feature of EKO is the computation of solution operators, which are independent of the boundary condition, can be stored and quickly applied to evolve several initial PDFs. The EKO approach combines the power of N -space solutions with the flexibility of a x-space delivery, that allows for an easy interface with existing codes. The code is fully open source and written in Python, with a modular structure in order to facilitate usage, readability and possible extensions. We provide a set of benchmarks with similar available tools, finding good agreement.
Polarized Antimatter in the Proton from Global QCD Analysis
https://arxiv.org/pdf/2202.03372.pdf
abstract: We present a global QCD analysis of spin-dependent parton distribution functions (PDFs) that includes the latest polarized W -lepton production data from the STAR collaboration at RHIC. These data allow the first data-driven extraction of a nonzero polarized light quark sea asymmetry ∆ ̄u−∆ ̄d within a global QCD framework with minimal theoretical assumptions. Within our simultaneous extraction of polarized PDFs, unpolarized PDFs, and pion and kaon fragmentation functions, we also extract a self-consistent set of antiquark polarization ratios ∆ ̄u/ ̄u and ∆ ̄d/ ̄d.
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