J/A+A/699/A175ivo://CDS.VizieR/J/A+A/699/A175doi:10.26093/cds/vizier/bc-nv/lbhfCDSPalamakumbure L.Syrjaenen S.A.I.Korda D.Kohout T.Klami A.2026-08-03T06:55:31Z2025-07-09T07:28:49ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frsolar-systemasteroidsastronomical-modelsThe surfaces of airless planetary bodies, such as S-type asteroids, undergo space weathering (SW) due to exposure to the interplanetary environment, resulting in alterations to their reflectance spectral features (e.g., spectral slope, albedo, and absorption band characteristics). This study aims to estimate the surface age of S-, Sq-, and Q-type asteroids as a function of SW agents and dose by employing machine learning models. Two models were developed: an ensemble model (combining a CNN, gradient-boosting regressor, K-nearest neighbor, extratree regressor, and random forest regressor) and a Gaussian process (GP) model. Both models were trained on published reflectance spectra of olivine, pyroxene, their mixtures, and chondritic meteorites, using SW conditions as independent variables and surface age at 1 AU as the dependent variable. Given the limited dataset, k-fold cross-validation was employed for model training. The models were further validated by applying them to S-, Sq-, and Q-type asteroids, evaluating their ability to capture two key trends: the SW progression across chondritic S-type asteroids and the relationship between asteroid size and surface age. Both models successfully identify relatively fresh surfaces in Q-type asteroids and mature surfaces in S-type asteroids, as well as younger surface ages for asteroids with diameters less than 5 km. However, the GP model exhibits higher variability in predictions for the asteroid dataset. While both models effectively capture relative surface age trends, limitations in data availability between 10^3^ and 10^7^ years hinder precise predictions of asteroid surface ages. These models have significant potential for future applications, such as determining the surface age for individual asteroids and identifying asteroid families, offering valuable tools for advancing our understanding of asteroid evolution and SW processes.2025A&A...699A.175Phttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/699/A175CatalogResearchIsServedByTAP VizieR generic servicerelated-toB/astorb : Orbits of Minor Planets (Bowell+, 2014-)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/699/A175https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/699/A175http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/699/A175https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/699/A175https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/699/A175http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/699/A175GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapdefaultJ/A+A/699/A175/tableb1Predicted and the corrected surface age for these asteroidsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintNoAsteroid numbermeta.id;meta.mainintn_No[*] * Near Earth Asteroidsmeta.notecharType[Q S Sq] Asteroid typesrc.classcharT-1AU1H^+^ irradiation age, surface age at 1AU, Ensemble model1000yrtime.age;meta.modelledfloate_T-1AU1H^+^ irradiation age, surface age at 1AU error, Ensemble model1000yrstat.errorfloatT-cor1H^+^ irradiation age, corrected surface age with the distance, Ensemble model1000yrpos.distance;time.age;meta.modelledfloate_T-cor1H^+^ irradiation age, corrected surface age with the distance error, Ensemble model1000yrstat.errorfloatT-1AU2H^+^ irradiation age, surface age at 1AU, Gaussian (GP) model1000yrtime.age;meta.modelledfloate_T-1AU2H^+^ irradiation age, surface age at 1AU error, Gaussian (GP) model1000yrstat.errorfloatT-cor2H^+^ irradiation age, corrected surface age with the distance, Gaussian (GP) model1000yrpos.distance;time.age;meta.modelledfloate_T-cor2H^+^ irradiation age, corrected surface age with the distance error, Gaussian (GP) model1000yrstat.errorfloatT-1AU3Laser irradiation age, surface age at 1AU, Ensemble model1e+09yrtime.age;meta.modelledfloate_T-1AU3Laser irradiation age, surface age at 1AU error, Ensemble model1e+09yrstat.errorfloatT-cor3Laser irradiation age, corrected surface age with the distance, Ensemble model1e+09yrpos.distance;time.age;meta.modelledfloate_T-cor3Laser irradiation age, corrected surface age with the distance error, Ensemble model1e+09yrstat.errorfloatT-1AU4Laser irradiation age, surface age at 1AU, Gaussian (GP) model1e+09yrtime.age;meta.modelledfloate_T-1AU4Laser irradiation age, surface age at 1AU error, Gaussian (GP) model1e+09yrstat.errorfloatT-cor4Laser irradiation age, corrected surface age with the distance, Gaussian (GP) model1e+09yrpos.distance;time.age;meta.modelledfloate_T-cor4Laser irradiation age, corrected surface age with the distance error, Gaussian (GP) model1e+09yrstat.errorfloat