In this paper, we employ parametrization techniques within the framework of $f(T)$ gravity to investigate the deceleration parameter (DP), a key quantity characterizing the universe’s expansion dynamics. By analyzing the DP, we gain valuable insights into the nature of cosmic constituents and their impact on the universe’s evolution. We utilize a combination of observational data, including 31 Cosmic Chronometers (CC) measurements, 1048 Type Ia Supernovae (SNIa), 17 Baryon Acoustic Oscillation (BAO) measurements, Cosmic Microwave Background (CMB), 162 Gamma Ray Bursts (GRB), and 24 observations of compact radio quasars (Q). We employ the Markov chain Monte Carlo (MCMC) sampling technique to estimate the best-fit range of model parameters. Cosmological and cosmographic parameters are investigated, and their implications in the context of cosmology have been discussed. We also analyze the statefinder and $\mathrm{\text{Om}}$ diagnostic to gain deeper insights into the universe’s behavior. Furthermore, we conduct statistical analyses to compare our model with the standard $\mathrm{\Lambda }$CDM model. Our investigation also includes the study of physical parameters, providing comprehensive insights into the cosmological behavior within the $f(T)$ gravity framework. The results and comparisons presented in this work contribute to a deeper understanding of the universe’s dynamics and provide valuable implications for the cosmological model under consideration.

在本文中，我们在以下框架内采用参数化技术：$F（\mathrm{时间}）$重力来研究减速参数（DP），这是表征宇宙膨胀动力学的关键量。通过分析 DP，我们获得了关于宇宙成分的性质及其对宇宙演化的影响的宝贵见解。我们利用观测数据的组合，包括 31 个宇宙天文台 (CC) 测量、1048 个 Ia 型超新星 (SNIa)、17 个重子声振荡 (BAO) 测量、宇宙微波背景 (CMB)、162 个伽马射线爆发 (GRB) 和24 次紧凑射电类星体观测 (Q)。我们采用马尔可夫链蒙特卡罗（MCMC）采样技术来估计模型参数的最佳拟合范围。研究了宇宙学和宇宙学参数，并讨论了它们在宇宙学背景下的含义。我们还分析了 statefinder 和$\mathrm{\text{唵}}$诊断以更深入地了解宇宙的行为。此外，我们还进行统计分析，将我们的模型与标准进行比较$\mathrm{\Lambda }$清洁发展机制模型。我们的研究还包括物理参数的研究，为宇宙学行为提供全面的见解$F（\mathrm{时间}）$重力框架。这项工作中提出的结果和比较有助于更深入地了解宇宙动力学，并为正在考虑的宇宙学模型提供有价值的启示。