New Model Selection Criterion Developed for Multidimensional Gaussian Processes in Radial Velocity Analysis
Astronomers have developed a new information criterion, MGIC_rv, to compare multidimensional Gaussian Process models used to separate stellar activity noise from planetary signals in radial velocity data. Classical model comparison methods cannot be directly applied when these models involve different combinations of time series, making indicator selection difficult. The new metric provides a principled, quantitative framework that could improve the reliability of exoplanet detection from radial velocity surveys.
A team led by Dr. Oscar Barragán has introduced MGIC_rv, an information criterion designed specifically for comparing multidimensional Gaussian Process (multi-GP) regression models in the context of radial velocity (RV) exoplanet searches. Multi-GP regression is a standard technique for jointly modeling stellar activity indicators alongside RV measurements to disentangle astrophysical noise from genuine planetary signals, but selecting which combination of activity indicators best constrains the stellar component has lacked a rigorous statistical framework. MGIC_rv addresses this gap by combining the conditional RV likelihood with an effective parameter count that reflects the regularization the multi-GP model imposes on the RV component. The authors demonstrate that the criterion is both quantitative and robust for model comparison purposes. Importantly, the criterion is formulated generally and is not restricted to RV analysis — it applies to any multi-GP problem where inference is focused on one specific observable within a larger set of jointly modeled time series. The paper has been accepted for publication in Monthly Notices of the Royal Astronomical Society (MNRAS) Letters.
What's missing
Comparisons against Bayesian evidence (marginal likelihood) or cross-validation benchmarks on benchmark RV datasets are not detailed in the abstract.
What different sources said
- arXiv physicsCenter
A Model Selection Criterion for Multidimensional Gaussian Processes: Application to Radial Velocities
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