Revisiting Ca II Activity Indices in FGK Stars: Systematic Biases in Infrared Triplet Measurements
Xiaozhen Yang, Xiaoting Fu, Mingjie Jian, Jingkun Zhao, Hailong Yuan, Zhongrui Bai, Mengxin Wang, Yiqiao Dong, Mingkuan Yang, Ziyue Jiang, Qian Liu, Ganyu Li, Haotong Zhang

TL;DR
This study investigates the systematic negative biases in Ca II infrared triplet activity indices in FGK stars, attributing them mainly to underestimation of line core depths by photospheric templates and exploring mitigation strategies.
Contribution
It identifies the primary cause of negative Ca II IRT residuals as missing chromospheric structure in templates and proposes empirical adjustments to improve measurement accuracy.
Findings
Negative biases are mainly due to underestimated IRT core depths in templates.
Empirical increase in microturbulent velocity partially mitigates the bias.
Different synthesis configurations show systematic offsets but maintain strong linear correlations.
Abstract
Synthetic-template subtraction is widely used to measure chromospheric activity in large spectroscopic surveys. However, many solar-like FGK stars show systematically negative Ca II infrared triplet (IRT) residual indices, implying that the observed line cores are deeper than those predicted by parameter-matched templates. We investigate this effect using solar-like stars from LAMOST DR9, MaStar, and XSL DR3, measuring activity indices (R+) for both the Ca II H&K and IRT lines in a uniform framework. We find that observational effects, including atmospheric-parameter offsets, treatment of the instrumental line-spread function, and propagated measurement uncertainties, contribute to scatter but do not explain the systematic negative bias in R+_IRT. The results instead suggest that the negative bias most likely arises because photospheric templates underestimate the depth of the IRT…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
