Blind search for activity-sensitive lines in the near-infrared using HARPS and NIRPS observations of Proxima and Gl 581
Bibliographic record
Abstract
Context. Stellar activity variability is one of the main obstacles to the detection of Earth-like planets using the radial velocity (RV) method. Aims. The aim of this work is to measure the effect of activity in the spectra of M dwarfs and detect activity-sensitive lines in the near-infrared (NIR) to help improve exoplanet detection and characterisation and contribute to further stellar activity analysis in the NIR. Methods. We took advantage of the simultaneous observations of HARPS and the newly commissioned NIRPS spectrograph to carry out a blind search of the most activity-sensitive spectral lines in the NIR using NIRPS spectra and known activity indicators in the optical from HARPS as a reference. We analysed the spectra of Proxima (M5.5V) and Gl 581 (M3V), two M dwarfs with different activity levels and internal structures. Spectral lines were identified for both stars and their profiles were fitted using different models. Results. We found hundreds of lines sensitive to activity for both stars; the Proxima spectra were more affected. For Proxima, around 32% of the identified lines can be used to measure the rotation period of the star, while for Gl 581 the numbers drops to 1%. The fraction of lines sensitive to activity increases with increasing line depth for both stars. A list of 17 lines with rotation period detection for both stars is provided. Conclusions. Stellar activity is able to affect a significant number of spectral lines in the NIR, and methods should be developed to mitigate those effects at the spectral level. The line distortions detected here are expected to come mainly from the flux effect due to temperature contrasts between active regions and the quiet photosphere; however, we cannot rule out the possibility that core-emission from chromospheric activity or Zeeman splitting are also affecting some lines. The new line lists presented here can be used to improve the RV extraction and the detection of RV variability due to stellar activity signals, and to help false positive detection and the modelling of activity variability, thereby enhancing exoplanet detection in the NIR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".