Identifying activity induced RV periodicities and correlations using Central Line Moments

J. R. Barnes, S. V. Jeffers, C. A. Haswell, M. Damasso, F. Del Sordo, F. Liebing, M. Perger, G. Anglada-Escudé
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Abstract

The radial velocity (RV) method of exoplanet detection requires mitigation of nuisance signals arising from stellar activity. Using analytic cool and facular spot models, we explore the use of central line moments (CLMs) for recovering and monitoring rotation induced RV variability. Different spot distribution patterns, photosphere-spot contrast ratios and the presence or absence of the convective blueshift lead to differences in CLM signals between M dwarfs and G dwarfs. Harmonics of the rotation period are often recovered with the highest power in standard periodogram analyses. By contrast, we show the true stellar rotation may be more reliably recovered with string length minimisation. For solar minimum activity levels, recovery of the stellar rotation signal from CLMs is found to require unfeasibly high signal-to-noise observations. The stellar rotation period can be recovered at solar maximum activity levels from CLMs for reasonable cross-correlation function (CCF) signal-to-noise ratios $> 1000 - 5000$. The CLMs can be used to recover and monitor stellar activity through their mutual correlations and correlations with RV and bisector inverse span. The skewness of a CCF, a measure of asymmetry, is described by the third CLM, $M_3$. Our noise-free simulations indicate the linear RV vs $M_3$ correlation is up to 10 per cent higher than the RV vs bisector inverse span correlation. We find a corresponding $\sim 5$ per cent increase in linear correlation for CARMENES observations of the M star, AU Mic. We also assess the effectiveness of the time derivative of the second CLM, $M_2$, for monitoring stellar activity.
利用中心线矩识别活动诱发的 RV 周期性和相关性
探测系外行星的径向速度(RV)方法需要减少恒星活动产生的干扰信号。我们利用分析冷斑和面斑模型,探索了利用中心线矩(CLM)来恢复和监测旋转引起的径向速度变异性。不同的光斑分布模式、光球-光斑对比度以及是否存在对流蓝移导致了 M 矮星和 G 矮星之间 CLM 信号的差异。在标准的周期图分析中,旋转周期的谐波通常能以最高的功率恢复。相比之下,我们的研究表明,用弦长度最小化方法可以更可靠地恢复真正的恒星自转。在太阳活动最低水平时,从CLMs 中恢复恒星自转信号需要难以想象的高信噪比观测。在太阳活动水平最大时,CLMs 的信噪比为 1000 - 5000 美元,可以通过合理的交叉相关函数(CCF)恢复恒星自转周期。CLMs可以通过它们之间的相互关系以及与RV和双矢量反演的关系来恢复和监测恒星活动。第三个CLM,即$M_3$,描述了CCF的偏斜度(一种不对称度量)。我们的无噪声模拟表明,RV 与 $M_3$ 的线性相关性比 RV 与 bisector 的反相关性高 10%。我们发现,CARMENES观测到的M星AU Mic的线性相关性也相应地提高了5%。我们还评估了第二个CLM的时间导数$M_2$对监测恒星活动的有效性。
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