Nuclear structure functions at a future electron-ion collider
Nuclear structure functions at a future electron-ion collider
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DOI：
10.1103/physrevd.96.114005
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发表时间：
2017-08
影响因子：
5
通讯作者：
E. Aschenauer;S. Fazio;M. Lamont;H. Paukkunen;Pia Zurita Brookhaven National Laboratory;U. Jyvaskyla;Helsinki Institute of Physics
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文献类型：
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作者：
E. Aschenauer;S. Fazio;M. Lamont;H. Paukkunen;Pia Zurita Brookhaven National Laboratory;U. Jyvaskyla;Helsinki Institute of Physics
重核部分子结构的定量知识目前仅限于相当大的动量分数x值，在低分辨率尺度Q2下，x ≤ 10-2的实验约束特别缺乏。这与自由质子的结构形成鲜明对比，自由质子的结构已经在深度非弹性散射（DIS）测量中以微扰分辨率尺度探测到x = 10-5。电子离子对撞机（EIC）的建设与各种各样的核操作的可能性，将允许一个探索低x区域更详细。在本文中，我们模拟提取的核结构函数的测量包容性和魅力约化截面在EIC。基于最近的EPPS 16分析，通过直接分析核部分子分布函数的次领先阶全局拟合中的模拟数据来研究潜在的约束。一个特别强调的是放在研究的影响EIC将提取核胶子部分子分布函数，部分子分量最容易在低Q2的非线性效应。与目前的知识相比，我们发现胶子部分子分布函数可以在EIC处测量，并且不确定性大大降低。
The quantitative knowledge of heavy nuclei’s partonic structure is currently limited to rather large values of momentum fraction x—robust experimental constraints below x∼10-2 at low resolution scale Q2 are particularly scarce. This is in sharp contrast to the free proton’s structure which has been probed in Deep Inelastic Scattering (DIS) measurements down to x∼10-5 at perturbative resolution scales. The construction of an electron-ion collider (EIC) with a possibility to operate with a wide variety of nuclei, will allow one to explore the low-x region in much greater detail. In the present paper we simulate the extraction of the nuclear structure functions from measurements of inclusive and charm reduced cross sections at an EIC. The potential constraints are studied by analyzing simulated data directly in a next-to-leading order global fit of nuclear Parton Distribution Functions based on the recent EPPS16 analysis. A special emphasis is placed on studying the impact an EIC would have on extracting the nuclear gluon parton distribution function, the partonic component most prone to nonlinear effects at low Q2. In comparison to the current knowledge, we find that the gluon parton distribution function can be measured at an EIC with significantly reduced uncertainties.