arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2502.08798astro-ph.HE
收藏

修改的强子相互作用与超高能宇宙线观测的未来

Modified Hadronic Interactions and the future of UHECR observations

Jan Ebr, Jiří Blažek, Jakub Vícha, Tanguy Pierog, Eva Santos, Petr Trávníček, Nikolas Denner, Ralf Ulrich

AI总结:

该研究通过构建在加速器数据约束下轻微修改最高能量强子相互作用的UHECR模拟库,系统探索了能同时解释奥格观测站μ子含量和簇射最大深度结果的参数组合,为未来观测站设计提供了量化强子模型不确定性的有力工具。

摘要:

来自多个实验的数据表明,当前蒙特卡洛模拟中使用的相互作用模型不能正确重现超高能宇宙线(UHECR)产生的空气簇射中的强子相互作用。我们创建了一个大型UHECR模拟库,其中最高能量下的相互作用以各种方式被轻微修改——但始终在加速器数据的约束范围内,不随能量发生任何突变,也不假设任何特定机制或在超高能量下引入戏剧性的新物理。皮埃尔·奥格观测站的最新结果表明,需要改变模型对地面μ子含量和簇射纵向发展最大深度的预测。在我们的参数空间中,我们找到了与这一分析一致的修改组合,然而对UHECR簇射的一致描述仍然难以实现。不过,我们的模拟库提供了强子相互作用建模自由度的真实表示,并为量化各种预测的不确定性提供了机会。这对于未来观测站的设计尤其有价值,因为强子模型通常被用作性能预测的输入。我们在几个选定的示例上展示了这一强大能力。

英文摘要:

Data from multiple experiments suggest that the current interaction models used in Monte Carlo simulations do not correctly reproduce the hadronic interactions in air showers produced by ultra-high-energy cosmic rays (UHECR). We have created a large library of UHECR simulations where the interactions at the highest energies are slightly modified in various ways - but always within the constraints of the accelerator data, without any abrupt changes with energy and without assuming any specific mechanism or dramatically new physics at the ultra-high energies. Recent results of the Pierre Auger Observatory indicate a need for a change in the prediction of the models for both the muon content at ground and the depth of the maximum of longitudinal development of the shower. In our parameter space, we find combinations of modifications that are in agreement with this analysis, however a consistent description of UHECR showers remains elusive. Our library however provides a realistic representation of the freedom in the modeling of the hadronic interactions and offers an opportunity to quantify uncertainties of various predictions. This can be particularly valuable for the design of future observatories where hadronic models are often used as input for the prediction of the performance. We demonstrate this powerful capability on several selected examples.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑