In 2026, the European Space Agency’s PLATO mission will launch to find Earth-like planets around Sun-like stars, but it cannot yet measure the ages of those planetary systems to the required 10% accuracy because current stellar models are too imprecise. This project will fix that by gathering ultra-precise data on 20 benchmark stars—measuring their mass, radius, and luminosity directly from binary systems and white-dwarf companions. The team will then use Bayesian statistics and machine learning to calibrate the next generation of stellar evolution models, plugging the gap that currently prevents PLATO from fulfilling its core mission. If successful, the improved models will allow astronomers to reliably age-date exoplanet systems across the Galaxy, transforming our understanding of how planetary systems—including potentially habitable ones—form and evolve over billions of years. The work is fundamental science: it will not change daily life directly, but it will sharpen the tools used by every stellar astrophysicist and Galactic archaeologist interpreting data from Gaia, WEAVE, and 4MOST. Citizen scientists with small telescopes can also contribute by observing benchmark eclipsing binaries.
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The PLATO mission is on-schedule to launch in 2026 with the goal to study the evolution of planetary systems in our Galaxy, including Earth-like planets orbiting in the habitable zone of Sun-like stars. With the stellar models currently available, the mission cannot yet deliver on the specified requirement to measure the age of these planetary systems to an accuracy of 10%. This is why hundreds of researchers are currently working on new stellar models for the PLATO mission. The PLATO "Benchmark star" work package that I co-lead has the responsibility to deliver the new data for benchmark stars that is needed to validate and calibrate the next generation of stellar models. This project will apply methods that I have developed in recent years to measure the properties stars in exoplanet and binary systems to generate accurate fundamental data for Sun-like stars of lasting value and unprecedented precision. These high-quality data will be used with advanced Bayesian and machine-learning techniques that we will develop to calibrate the new physics in the next generation of stellar evolution models. These improved stellar models will be needed so that the PLATO mission can deliver on its goal to study the evolution of exoplanet systems in our Galaxy. The outcomes of this project will benefit all areas of stellar astrophysics and Galactic research, particularly those that rely on stellar models to interpret data from surveys such as Gaia, WEAVE, 4MOST, etc. The main objectives of this project are: i. to create a library of high-quality spectra for 20 stars with direct and precise mass, radius and luminosity measurements to calibrate mixing and diffusion effects in stellar models; ii. to characterise white-dwarf companions on wide orbits to PLATO targets that will be used for end-to-end tests of the age estimates from asteroseismology; iii. to use advanced statistical methods to fully exploit the high-precision data now available for stars in eclipsing binary systems combined with asteroseismology to calibrate new physics in the next generation of stellar models. This project will benefit from support by members of PLATO stellar and exoplanet science teams and the PLATO ground-based observing programme. This project also enables citizen scientists with access to small (~0.4-m) telescopes to make a useful contribution to the PLATO mission by observing benchmark eclipsing binary systems.
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