论文标题
将近似贝叶斯计算与系外行星的泊松类似方法进行比较
Comparing Approximate Bayesian Computation with the Poisson-Likelihood Method for Exoplanet Occurrence Rates
论文作者
论文摘要
我们提出了通过近似贝叶斯计算（ABC）推断出的开普勒系外行星的发生率。通过使用同一行星目录，出色的样本以及与Bryson等人的完整性和可靠性的表征。 （2020），我们能够将ABC结果与流行的泊松类似方法得出的结果进行首次直接比较。 For planets with orbital periods between 50 and 400 days and radii between 0.75 and 2.5 $R_{\oplus}$, we find an integrated occurrence rate $F_{0} = 0.596_{-0.099}^{+0.092}$ planets per GK dwarf star.在针对天体物理误报和错误警报的可靠性纠正后，我们发现$ f_ {0} = 0.421 _ { - 0.072}^{+0.086} $。我们的发现在Bryson等人的1 $σ$中一致。 （2020），表明结果是稳健而不是方法依赖性的。
We present Kepler exoplanet occurrence rates inferred with approximate Bayesian computation (ABC). By using the same planet catalogue, stellar sample, and characterization of completeness and reliability as Bryson et al. (2020), we are able to provide the first direct comparison of results from ABC to those derived with the popular Poisson-likelihood method. For planets with orbital periods between 50 and 400 days and radii between 0.75 and 2.5 $R_{\oplus}$, we find an integrated occurrence rate $F_{0} = 0.596_{-0.099}^{+0.092}$ planets per GK dwarf star. After correcting for reliability against astrophysical false positives and false alarms, we find $F_{0} = 0.421_{-0.072}^{+0.086}$. Our findings agree within 1$σ$ of Bryson et al. (2020), indicating that the results are robust and not method-dependent.
