The EXPRES Stellar Signals Project II. State of the Field in Disentangling Photospheric Velocities

TL;DR

The paper reviews 22 methods for disentangling stellar activity signals from exoplanet radial velocity measurements, highlighting current limitations and the need for improved interpretability, data quality, and benchmarking to advance detection capabilities.

Contribution

It provides a comprehensive comparison of diverse methods on the same dataset, revealing their strengths, weaknesses, and the lack of consistent sub-meter-per-second precision.

Findings

Most methods outperform classic decorrelation in RV RMS reduction.

No method consistently achieves sub-meter-per-second RV precision.

Significant disagreement exists between different methods' RV results.

Abstract

Measured spectral shifts due to intrinsic stellar variability (e.g., pulsations, granulation) and activity (e.g., spots, plages) are the largest source of error for extreme precision radial velocity (EPRV) exoplanet detection. Several methods are designed to disentangle stellar signals from true center-of-mass shifts due to planets. The EXPRES Stellar Signals Project (ESSP) presents a self-consistent comparison of 22 different methods tested on the same extreme-precision spectroscopic data from EXPRES. Methods derived new activity indicators, constructed models for mapping an indicator to the needed RV correction, or separated out shape- and shift-driven RV components. Since no ground truth is known when using real data, relative method performance is assessed using the total and nightly scatter of returned RVs and agreement between the results of different methods. Nearly all submitted methods return a lower RV RMS than classic linear decorrelation, but no method is yet consistently reducing the RV RMS to sub-meter-per-second levels. There is a concerning lack of agreement between the RVs returned by different methods. These results suggest that continued progress in this field necessitates increased interpretability of methods, high-cadence data to capture stellar signals at all timescales, and continued tests like the ESSP using consistent data sets with more advanced metrics for method performance. Future comparisons should make use of various well-characterized data sets -- such as solar data or data with known injected planetary and/or stellar signals -- to better understand method performance and whether planetary signals are preserved.