AI 中文总结
本研究针对将AGN反馈纳入宇宙学模拟的计算难题，基于RAiSE模型提出分析框架，揭示两种反馈机制的空间分布差异，发现其加热率可抵消多数星系团的辐射冷却，为下一代模拟提供基础。
AI 中文摘要
将真实的活动星系核（AGN）反馈纳入宇宙学流体动力学模拟仍是一项重大挑战，因为在宇宙时标上解析喷流能量的空间耦合在计算上是不可行的。我们提出了一种分析框架，可预测瓣状AGN反馈能量的径向和极角依赖性，从而为喷流反馈提供了一种基于物理的、计算高效的处理方案。该框架建立在半解析环境射电AGN（RAiSE）动力学模型之上，我们的方法通过两种不同机制追踪射电源的后AGN喷流阶段演化：受侵蚀作用的浮力上升气泡，以及激波壳中扫积气体的引力坍缩。我们发现，这两种反馈机制在10个代表性星系团环境中产生了截然不同的空间分布：浮力气泡优先在核心半径附近的陡峭密度梯度中沉积能量，而坍缩的激波气体壳则在更平缓的星系团核心内驱动加热。弱的、短寿命的AGN爆发（功率Q<10³⁷瓦，持续时间t_on<10百万年）将能量沉积限制在星系团内部10千秒差距范围内；持续时间更长的事件（t_on≥100百万年）在30千秒差距内沉积的注入能量不到1%。我们发现，当工作周期为0.08<δ≤1时，多次爆发的时间平均加热率足以抵消除最高密度星系团核心（100千秒差距以内）外所有区域的辐射冷却。该框架为构建各向异性、基于物理的喷流反馈模型提供了可扩展的基础，可纳入下一代宇宙学模拟中。
英文摘要
Integrating realistic active galactic nucleus (AGN) feedback into cosmological hydrodynamical simulations remains a major challenge as resolving the spatial coupling of jet energy over cosmic timescales is computationally prohibitive. We present an analytic framework that predicts the radial and polar-angle dependence of feedback energy from lobed AGNs, enabling a physically motivated, computationally efficient prescription for jet feedback. Built upon the Radio AGN in Semi-analytic Environments (RAiSE) dynamical model, our approach tracks the post-AGN jet phase evolution of radio sources through two distinct mechanisms: buoyantly rising bubbles subject to ablation, and the gravitational collapse of swept-up gas in the shocked shell. We find that these two feedback mechanisms produce strongly contrasting spatial distributions across ten representative cluster environments. Buoyant bubbles preferentially deposit energy in steep density gradients near the core radius, while the collapsing shocked gas shell drives heating within flatter cluster cores. Weak, short-lived AGN outbursts ($Q<10^{37}$ W and $t_{\rm on}<10$ Myr) confine their energy deposition to the inner 10 kpc of the cluster; longer-lived events ($t_{\rm on} \geqslant 100$ Myr) deposit less than 1% of their injected energy within 30 kpc. We find that time-averaged heating rates across multiple outbursts are sufficient to offset radiative cooling in all but the highest density cluster cores (within 100 kpc) for duty cycles of $0.08< δ\leqslant 1$. This framework provides a scalable basis for modelling anisotropic, physically motivated jet feedback that can be incorporated into next-generation cosmological simulations.
Comments15 pages, 9 figures, 2 tables; accepted in MNRAS
