In this paper, we investigate the differential cross-sections of the inclusive jet and dijet productions of the ZEUS collaboration data at the center-of-mass energies of ∼300GeV and 319GeV using the k _t and (z, k _t )-factorizations with the different unintegrated and double-unintegrated parton-distribution functions (UPDFs and DUPDFs), respectively. The KaTie event generator is used to calculate the differential cross-sections of the UPDFs, while for the input DUPDFs, the calculations are directly performed by evaluating the corresponding matrix elements. We check the effects of choosing the different implementations of angular or strong ordering constraints using the UPDFs and the corresponding DUPDFs of the Kimber–Martin–Ryskin (KMR), the leading-order (LO), and next-to-leading-order (NLO) Martin–Ryskin–Watt (MRW) approaches. The impacts of choosing the virtualities or in the differential cross-section predictions for the ZEUS experimental data are also investigated. It is observed that, as one would expect, the application of (z, k _t )-factorization is better than the k _t -factorization framework for predictions of high-virtuality Q ² with respect to the ZEUS collaboration data, and also that the results of the KMR and LO-MRW UPDFs and DUPDFs are reasonably close to each other and, in general, can describe the data. It is also observed that only in the case of k _t -factorization does the inclusion of the Born level make our results overshoot the inclusive jet experimental data.

在本文中，我们使用k _t和 ( z , k _t )-分别具有不同的未积分和双未积分部分分布函数（UPDF 和 DUPDF）的分解。KaTie 事件生成器用于计算 UPDF 的差分横截面，而对于输入 DUPDF，则通过评估相应的矩阵元素直接进行计算。我们使用 UPDF 和 Kimber-Martin-Ryskin (KMR)、前导 (LO) 和次前导 ( NLO) Martin-Ryskin-Watt (MRW) 方法。选择虚拟性或还研究了 ZEUS 实验数据的差分横截面预测。观察到，正如人们所预期的那样，对于 ZEUS 协作数据的高虚拟性Q ²预测，( z , k _t )-分解的应用优于k _{t -}分解框架，并且KMR 和 LO-MRW UPDF 和 DUPDF 的结果彼此相当接近，并且通常可以描述数据。还观察到，只有在k _t分解的情况下，包含 Born 水平才会使我们的结果超过包含的喷射实验数据。