Recovering Velocity Distributions Via Penalized Likelihood
Recovering Velocity Distributions Via Penalized Likelihood
复制标题
通过惩罚似然恢复速度分布
DOI：
10.1086/118467
复制
发表时间：
1996
期刊：
影响因子：
--
通讯作者：
D. Merritt
中科院分区：
文献类型：
--
作者：
D. Merritt
视线速度分布对于解开热恒星系统的动力学至关重要。我们提出了一种基于惩罚似然的新算法，用于从运动学数据中提取N(V)，并对从吸收线谱和从个体速度集提取N(V)的两种算法的性能进行了评估。这两种算法都优于现有的算法，因为即使在数据非常差的情况下，解决方案也几乎是无偏的，需要大量的平滑处理。此外，离散速度算法能够从N(V)的估计中去除已知的测量误差分布。利用形式化方法恢复了半人马座ω球状星团中心附近五个场中恒星的速度分布。
Line-of-sight velocity distributions are crucial for unravelling the dynamics of hot stellar systems. We present a new formalism based on penalized likelihood for deriving such distributions from kinematical data, and evaluate the performance of two algorithms that extract N(V ) from absorption-line spectra and from sets of individual velocities. Both algorithms are superior to existing ones in that the solutions are nearly unbiased even when the data are so poor that a great deal of smoothing is required. In addition, the discrete-velocity algorithm is able to remove a known distribution of measurement errors from the estimate of N(V ). The formalism is used to recover the velocity distribution of stars in five fields near the center of the globular cluster ω Centauri.