论文标题
情节流出反馈对恒星多样性和恒星形成效率的影响
The impact of episodic outflow feedback on stellar multiplicity and the star formation efficiency
论文作者
论文摘要
材料上的材料上的材料伴随着流出的发射。观察结果表明,积聚,因此也流出是情节性的。但是,情节流出反馈对核心尺度的影响尚不清楚。我们已经对湍流密度$ 1 \,\ mathrm {m} _ {\ odot} $核心进行了88个平滑的粒子流体动力模拟,以研究情节流出反馈对恒星多重性和星形形成效率(SFE)的影响。原恒星由水槽颗粒表示,该粒子使用子网格模型捕获恒星的演化,内盘进化,情节积聚和流出的发射。通过比较带有或没有情节流出反馈的模拟,我们表明,流出反馈的模拟再现了年轻恒星种群的二进制统计数据,包括单打,二进制文件,三元组等的相对比例以及具有$ q \ geq QUQ 0.95 $ Q \ geq的双二元的高发生率;没有流出反馈的模拟没有。夹带因子(总流出质量和最初弹出质量之间的比率)通常为$ \ sim 7 \ pm 2 $,但是如果核心中形成的总恒星总质量很低,并且/或流出发作很少,则可能会更高。通过减少形成的恒星的平均质量和形成的恒星数,流出反馈将SFE降低了约2倍(与不包括流出反馈的模拟相比)。
The accretion of material onto young protostars is accompanied by the launching of outflows. Observations show that accretion, and therefore also outflows, are episodic. However, the effects of episodic outflow feedback on the core-scale are not well understood. We have performed 88 Smoothed Particle Hydrodynamic simulations of turbulent dense $1 \, \mathrm{M}_{\odot}$ cores, to study the influence of episodic outflow feedback on the stellar multiplicity and the star formation efficiency (SFE). Protostars are represented by sink particles, which use a sub-grid model to capture stellar evolution, inner-disc evolution, episodic accretion and the launching of outflows. By comparing simulations with and without episodic outflow feedback, we show that simulations with outflow feedback reproduce the binary statistics of young stellar populations, including the relative proportions of singles, binaries, triples, etc. and the high incidence of twin binaries with $q\geq 0.95$; simulations without outflow feedback do not. Entrainment factors (the ratio between total outflowing mass and initially ejected mass) are typically $\sim 7\pm 2$, but can be much higher if the total mass of stars formed in a core is low and/or outflow episodes are infrequent. By decreasing both the mean mass of the stars formed and the number of stars formed, outflow feedback reduces the SFE by about a factor of 2 (as compared with simulations that do not include outflow feedback).