PDFxTMDLib：一种高性能的C++库，用于平行动量依赖部分子分布函数
PDFxTMDLib: A High-Performance C++ Library for Collinear and Transverse Momentum Dependent Parton Distribution Functions
AI总结：
PDFxTMDLib是一种高性能C++库，用于支持平行和横动量依赖部分子分布函数，提供更灵活的定制和更高的计算性能。
摘要：
平行部分子分布函数（cPDFs）和横动量依赖分布（TMDs）对于高能物理中计算横截面至关重要，特别是在平行和kt因子化框架中。目前有两种库，如LHAPDF和TMDLib，用于获得这些物理对象。然而，这两个库都存在局限性，尤其是对于TMDs，例如定制和扩展受限。用户只能使用这些库提供的实现，无法轻松支持非常规PDFs。此外，目前没有标准的TMD库提供一致的QCD耦合评估框架或研究分布水平的不确定性——这些功能对于现象学研究中的诊断和比较分析至关重要。为了解决这些不足，我们引入PDFxTMDLib，一种现代的C++库，旨在提供稳健且灵活的解决方案。该库支持平行PDFs和TMDs，同时允许更大的定制。它还为支持更高阶分布打开了可能性。在本文中，我们描述了PDFxTMDLib的结构。我们还通过将其集成到PYTHIA蒙特卡洛事件生成器中计算Drell-Yan横截面来展示其有效性和性能。此外，将PDFxTMDLib获得的PDFs与LHAPDF和TMDLib的比较证实了PDFxTMDLib结果的可靠性。
英文摘要：
Collinear parton distribution functions (cPDFs) and transverse momentum dependent distributions (TMDs) are essential for calculating cross sections in high-energy physics, particularly within collinear and kt-factorization frameworks. Currently, there exists two libraries, such as LHAPDF and TMDLib, to obtain these physical objects. However, there are limitations in both libraries, especially for TMDs, such as restricted customization and extensibility. Users are limited to the implementations provided by these libraries and cannot easily support unconventional PDFs. Moreover, no standard TMD library currently provides a consistent framework for QCD coupling evaluation or for studying uncertainties at the distribution level--features that are important for diagnostic and comparative analyses in phenomenological research. To address these shortcomings, we introduce PDFxTMDLib, a modern C++ library designed to offer a robust and flexible solution. This library supports both collinear PDFs and TMDs while allowing greater customization. It also opens the way to support higher-order distributions. In this article, we describe the structure of PDFxTMDLib. We also demonstrate its validity and performance by integrating it into the PYTHIA Monte Carlo event generator to compute Drell-Yan cross sections. Additionally, comparisons of PDFs obtained from PDFxTMDLib with those from LHAPDF and TMDLib confirm the reliability of PDFxTMDLib's results.
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