论文标题
非线性Gribov-Levin-Ryskin-Mueller-QIU演化方程的数值评估
Numerical evaluation of the nonlinear Gribov-Levin-Ryskin-Mueller-Qiu evolution equations for nuclear parton distribution functions
论文作者
论文摘要
我们首次研究核部分分布函数（NPDFS）的非线性GLR-MQ演化方程，以实现近代领先的订单准确度，并量化Gluon重组对小$ x $的影响。使用NCTEQ15 NPDFS作为输入，我们确认非线性校正对小$ x \ sillesim 10^{ - 3} $的重要性，其幅度随着$ x $的减少而增加，原子数$ $ a $的增加。我们发现，在$ x = 10^{ - 5} $中，对于重核，在向上从$ q_0 = 2 $ gev到$ q = 10 $ gev之后，Quark Singlet $ω（x，q^2）$和GluOon $ G（X，x，Q^2）$分布将分别减少9-15 $％。从$ q_0 = 10 $ gev到$ q = 2 $ gev，相对效果要强得多，在那里我们发现$ω（x，q^2）$被抑制了40％，而$ g（x，q^2）$提高了140％。这些趋势传播到$ f_2^a（x，q^2）$核结构功能和$ f_l^a（x，q^2）$纵向结构函数，在向下进化后，该功能分别降低了45％，并增强了80％。我们的分析表明，在$ f_l^a（x，q^2）$中，非线性效应最为明显，并且对于重核而言，在$ x \ sim 10^{ - 3} $中已经相当大。我们已经检查了我们的结论非常弱取决于输入NPDF的选择。特别是，使用EPPS21 NPDF作为输入，我们获得了定量相似的结果。
We numerically study for the first time the nonlinear GLR-MQ evolution equations for nuclear parton distribution function (nPDFs) to next-to-leading order accuracy and quantify the impact of gluon recombination at small $x$. Using the nCTEQ15 nPDFs as input, we confirm the importance of the nonlinear corrections for small $x \lesssim 10^{-3}$, whose magnitude increases with a decrease of $x$ and an increase of the atomic number $A$. We find that at $x=10^{-5}$ and for heavy nuclei, after the upward evolution from $Q_0=2$ GeV to $Q=10$ GeV, the quark singlet $Ω(x,Q^2)$ and the gluon $G(x,Q^2)$ distributions become reduced by $9-15$%, respectively. The relative effect is much stronger for the downward evolution from $Q_0=10$ GeV to $Q=2$ GeV, where we find that $Ω(x,Q^2)$ is suppressed by 40%, while $G(x, Q^2)$ is enhanced by 140%. These trends propagate into the $F_2^A(x,Q^2)$ nuclear structure function and the $F_L^A(x,Q^2)$ longitudinal structure function, which after the downward evolution become reduced by 45% and enhanced by 80%, respectively. Our analysis indicates that the nonlinear effects are most pronounced in $F_L^A(x,Q^2)$ and are already quite sizable at $x \sim 10^{-3}$ for heavy nuclei. We have checked that our conclusions very weakly depend on the choice of input nPDFs. In particular, using the EPPS21 nPDFs as input, we obtain quantitatively similar results.
