基于恒星库MILES的光吸收线指数的经验标定
Empirical calibrations of optical absorption line indices based on the stellar library MILES
摘要：
吸收线指数的恒星星族模型是分析恒星星族谱的重要工具。它们是最准确的模拟，通过经验校准的吸收线指数与恒星参数有效温度，金属丰度，和表面重力，所谓的拟合函数。在这里，我们提出了新的经验拟合函数的25个光学舔吸收线指数的基础上，新的恒星库英里。与Lick/IDS库相比，主要的改进是更好地采样恒星参数空间，通常更高的信噪比和仔细的通量校准。事实上，我们发现MILES中单个指数测量的误差比Lick/IDS中的小得多。相反，我们发现最终拟合函数和数据之间的残差的均方根主要由恒星参数的误差。我们提供了拟合函数的舔/IDS和MILES光谱分辨率，并比较我们的结果与其他拟合函数在文献中。在线提供Fortran 90代码，以简化恒星星族模型的实现。我们进一步计算了Lick/IDS系统与通量校准系统之间的折射率测量的偏移。为此，我们使用三个库MILES、STELDIE和STELIB。我们发现，在某些情况下，偏移是可以忽略不计的，最值得注意的是广泛使用的指数Hbeta，Mgb，Fe 5270和Fe 5335。然而，在许多情况下，通量校准库和Lick/IDS之间的差异是显着的偏移取决于索引强度。有趣的是，对于大量的索引，三个库之间没有普遍的一致性，这阻碍了Lick/IDS和通量校准系统之间的通用偏移的推导。
英文摘要：
Stellar population models of absorption line indices are an important tool for the analysis of stellar population spectra. They are most accurately modelled through empirical calibrations of absorption line indices with the stellar parameters effective temperature, metallicity, and surface gravity, the so-called fitting functions. Here we present new empirical fitting functions for the 25 optical Lick absorption line indices based on the new stellar library MILES. The major improvements with respect to the Lick/IDS library are the better sampling of stellar parameter space, a generally higher signal- to-noise, and a careful flux calibration. In fact we find that errors on individual index measurements in MILES are considerably smaller than in Lick/IDS. Instead we find the rms of the residuals between the final fitting functions and the data to be dominated by errors in the stellar parameters. We provide fitting functions for both Lick/IDS and MILES spectral resolutions, and compare our results with other fitting functions in the literature. A Fortran 90 code is available online in order to simplify the implementation in stellar population models. We further calculate the offsets in index measurements between the Lick/IDS system to a flux calibrated system. For this purpose we use the three libraries MILES, ELODIE, and STELIB. We find that offsets are negligible in some cases, most notably for the widely used indices Hbeta, Mgb, Fe5270, and Fe5335. In a number of cases, however, the difference between flux calibrated library and Lick/IDS is significant with the offsets depending on index strengths. Interestingly, there is no general agreement between the three libraries for a large number of indices, which hampers the derivation of a universal offset between the Lick/IDS and flux calibrated systems.
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