论文标题
宇宙学模拟预测,尽管有效反馈
Cosmological simulations predict that AGN preferentially live in gas-rich, star-forming galaxies despite effective feedback
论文作者
论文摘要
活性银河核(AGN)的负反馈是在绝大多数现代星系演化模型中淬灭大型星系的主要机制。但是,缺乏直接的观察性证据表明AGN反馈会导致人口量表的淬火。研究表明,发光的AGN优先位于气体富含气体和星形的星系中,这种观察有时被认为是张力,具有负AGN反馈图片。我们研究了三个当前的宇宙学模拟(Illustristng,Eagle和Simba),以及用于分子氢气质量的后加工模型,并进行了与观察者使用的测试相似的测试。我们发现模拟预测:(i)AGN光度与分子气体分数或SSFR之间没有强烈的负趋势; (ii)高亮度($ l_ {bol}> 10^{44} $ erg/s)和高埃德丁顿比(> 1%)AGN优先位于具有高分子气体级数和SSFR的星系中; (iii)AGN宿主星系的气体耗尽和淬火的部分低于非活动星系的对照样品。这三个发现与$ z = 0 $和$ z = 2 $的观察样本有定性协议,并表明这种结果与存在强大的AGN反馈的存在并不紧张,我们使用的所有模拟都需要产生逼真的大型星系。但是,我们还发现模拟预测之间的可量化差异,这可以使我们能够在观察中测试不同的亚网格反馈模型。
Negative feedback from active galactic nuclei (AGN) is the leading mechanism for the quenching of massive galaxies in the vast majority of modern galaxy evolution models. However, direct observational evidence that AGN feedback causes quenching on a population scale is lacking. Studies have shown that luminous AGN are preferentially located in gas-rich and star-forming galaxies, an observation that has sometimes been suggested to be in tension with a negative AGN feedback picture. We investigate three of the current cosmological simulations (IllustrisTNG, EAGLE and SIMBA) along with post-processed models for molecular hydrogen gas masses and perform similar tests to those used by observers. We find that the simulations predict: (i) no strong negative trends between AGN luminosity and molecular gas fraction or sSFR; (ii) both high-luminosity ($L_{bol}>10^{44}$ erg/s) and high-Eddington ratio (>1%) AGN are preferentially located in galaxies with high molecular gas fractions and sSFR; and (iii) that the gas-depleted and quenched fractions of AGN host galaxies are lower than a control sample of non-active galaxies. These three findings are in qualitative agreement with observational samples at $z=0$ and $z=2$ and show that such results are not in tension with the presence of strong AGN feedback, which all simulations we employ require to produce realistic massive galaxies. However, we also find quantifiable differences between predictions from the simulations, which could allow us to observationally test the different subgrid feedback models.