Synthetic disk-integrated absorption lines isolating stellar granulation for high-precision RV studies

Abstract

We present a novel method for constructing high-accuracy, time-varying disk-integrated stellar absorption line profiles that isolate the effects of granulation alone. This framework provides an effectively unlimited supply of physically consistent training data, offering a unique opportunity to study granulation-driven velocity variability with no contamination from other stellar processes or instrumental systematics. Our interpolation scheme enables accurate profile generation at arbitrary limb angles and successfully reproduces observed disk integrated solar bisector shapes from IAG spectra. Using four Fe I lines (525.0, 615.2, 617.3, and 627.1 nm), we produce 1000 model star disk-integrated realisations per line and find an isolated granulation-induced RV scatter of 0.16-0.21 m s^-1. Using our synthetic profiles and assuming infinite signal-to-noise, we find strong correlations between various line-shape metrics and convective blueshift, demonstrating that line-shape diagnostics can, in principle, trace granulation effects. Equivalent width proves the strongest diagnostic, achieving up to 60% scatter reduction. However, the strength of all simple line shape diagnostics rapidly diminishes once photon noise is injected. Even when artificially boosting the signal to represent a spectrum containing ~1000 spectral lines, the achievable improvement with these metrics remains below 10% at typical signal-to-noise ratios. Our results highlight the need for more robust, noise-resilient diagnostics and position our synthetic dataset as a valuable testbed for developing and benchmarking such methods.

Figures (12)

• Figure 1: First three eigenprofiles (principal components) of each component profile (left column) and the associated coefficients and their variation with limb angle (right column) for FeI 617.3nm. The circular points show results for the training set of limb angles from which the interpolation is based on.
• Figure 2: Model fits to the parameters required to build skewed Gaussian distributions for both the GT filling factors (left column) and the ratio OGR/IgL filling factors (right column) for FeI 617.3nm. The black crosses show the best fit parameters to the test-set distributions, and the black line is the model fit to these data. The colored circles show best fit parameters to the validation-set distributions, these values are not included in the fitting. Note that for the GT filling factor distribution the scale parameter is normalised by the location parameter. This is not the case for the OGR/IgL filling factor distribution.
• Figure 3: Histograms of GT filling factors and OGR/IgL ratio filling factors for the validation set of angles for FeI 617.3nm. Overplotted in black are the predicted skewed Gaussian distributions using parameters derived through the interpolation procedure using a seperate set of training angles. These Gaussians are not fit to the data shown and serve as a test of whether distributions at the validation angles are being correctly captured.
• Figure 4: Fe617.3 nm bisectors from an example sample pulled from the interpolation method at each validation limb angle. Bisectors from the validation time series are overplotted. The interpolation and validation sample at each angle are of equal size. In an attempt to mitigate overlap, we alternate plotting interpolated and validation bisectors. The intensity values have been normalised in each case by the maximum intensity value in the validation sample at the relevant angle.
• Figure 5: An example stellar grid with enlarged tiles and slight inclination for demonstrative purposes. The left hand plot shows the line of sight stellar rotational velocity at each tile, including differential rotation. The middle plot shows the projected area of each tile. Note that these are enlarged tiles, hence the inflated area values. The rightmost plot shows the limb angle at each tile.