探索 f(Q,L_m) 引力中的观测约束与宇宙学动力学
Exploring the Observational Constraints and Cosmological Dynamics in f(Q,L_m) Gravity
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- Indian Institute of Engineering Science and Technology（印度工程科学技术学院）
- Lovely Professional University（洛维专业大学）
- Khazar University（哈扎尔大学）
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中文总结 AI 辅助
本文通过动力学系统分析研究f(Q,L_m)引力的线性和非线性模型，发现其临界点能重现从物质主导到加速膨胀的宇宙演化序列，且与CC+BAO、DESI DR II和Pantheon+数据兼容，为晚期宇宙加速提供了可行替代框架。
中文摘要 AI 辅助
我们探索了 $f(Q,\mathcal{L}_m)$ 引力的两种情形：线性引力模型和非线性引力模型。动力学系统分析为所提出的线性和非线性物质-几何耦合模型各确定了两个临界点。这些平衡点对应于宇宙演化的不同阶段。根据模型参数的不同，所得临界点成功再现了观测到的宇宙演化序列，从减速的物质主导宇宙到当前加速膨胀的时期。有效状态方程参数（$\omega_{\text{eff}}$）和减速参数（$q$）表现出从减速膨胀到加速膨胀的平滑过渡，线性模型的过渡时期约为 $N_{\text{tr}} \approx -0.27$，非线性模型约为 $N_{\text{tr}} \approx -0.32$，与晚期宇宙加速一致。由CC+BAO、DESI DR II和Pantheon$^+$数据集得出的统计约束为模型参数（$\alpha, \beta, \gamma, H_0$）提供了最佳拟合值，显示出与当前宇宙学观测的兼容性。分析采用赤池信息准则（AIC）和贝叶斯信息准则（BIC）来评估模型性能。我们的结果表明，$f(Q,\mathcal{L}_m)$ 引力为解释晚期加速提供了一个可行的替代框架，其丰富的动力学特征值得在即将到来的高精度巡天背景下进一步探索。
英文摘要
We explore two scenarios of $f(Q,\mathcal{L}_m)$ gravity: linear and non-linear gravity models. The dynamical system analysis identifies two critical points for each of the proposed linear and nonlinear matter--geometry coupling models. These equilibrium points correspond to distinct phases of cosmic evolution. Depending on the model parameters, the resulting critical points successfully reproduce the observed sequence of cosmic evolution, from a decelerated matter-dominated Universe to the present epoch of accelerated expansion. The effective equation of state parameter ($ω_{\text{eff}}$) and the deceleration parameter ($q$) exhibit smooth transitions from decelerated to accelerated expansion, with transition epochs around $N_{\text{tr}} \approx -0.27$ for linear Model and $N_{\text{tr}} \approx -0.32$ for non-linear Model, consistent with late-time cosmic acceleration. Statistical constraints derived from CC+BAO, DESI DR II, and Pantheon$^+$ datasets provide best-fit values for the model parameters ($α, β, γ, H_0$), showing compatibility with current cosmological observations. The analysis employs Akaike (AIC) and Bayesian (BIC) information criteria to evaluate model performance. Our results demonstrate that $f(Q,\mathcal{L}_m)$ gravity provides a viable alternative framework for explaining late-time acceleration, with rich dynamical features that merit further exploration in view of upcoming high-precision surveys.
