Asteroid lightcurve inversion with Bayesian inference

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dc.contributor.author Muinonen, K.
dc.contributor.author Torppa, J.
dc.contributor.author Wang, X-B
dc.contributor.author Cellino, A.
dc.contributor.author Penttilä, A.
dc.date.accessioned 2020-11-27T13:26:01Z
dc.date.available 2020-11-27T13:26:01Z
dc.date.issued 2020-10-13
dc.identifier.citation Muinonen , K , Torppa , J , Wang , X-B , Cellino , A & Penttilä , A 2020 , ' Asteroid lightcurve inversion with Bayesian inference ' , Astronomy & Astrophysics , vol. 642 , 138 . https://doi.org/10.1051/0004-6361/202038036
dc.identifier.other PURE: 156357814
dc.identifier.other PURE UUID: 2b23352b-06ab-4e10-9a10-0446cef9fb37
dc.identifier.other WOS: 000584570600016
dc.identifier.other ORCID: /0000-0001-7403-1721/work/84255645
dc.identifier.other ORCID: /0000-0001-8058-2642/work/84255944
dc.identifier.uri http://hdl.handle.net/10138/322054
dc.description.abstract Context. We assess statistical inversion of asteroid rotation periods, pole orientations, shapes, and phase curve parameters from photometric lightcurve observations, here sparse data from the ESA Gaia space mission (Data Release 2) or dense and sparse data from ground-based observing programs.Aims. Assuming general convex shapes, we develop inverse methods for characterizing the Bayesian a posteriori probability density of the parameters (unknowns). We consider both random and systematic uncertainties (errors) in the observations, and assign weights to the observations with the help of Bayesian a priori probability densities.Methods. For general convex shapes comprising large numbers of parameters, we developed a Markov-chain Monte Carlo sampler (MCMC) with a novel proposal probability density function based on the simulation of virtual observations giving rise to virtual least-squares solutions. We utilized these least-squares solutions to construct a proposal probability density for MCMC sampling. For inverse methods involving triaxial ellipsoids, we update the uncertainty model for the observations.Results. We demonstrate the utilization of the inverse methods for three asteroids with Gaia photometry from Data Release 2: (21) Lutetia, (26) Proserpina, and (585) Bilkis. First, we validated the convex inverse methods using the combined ground-based and Gaia data for Lutetia, arriving at rotation and shape models in agreement with those derived with the help of Rosetta space mission data. Second, we applied the convex inverse methods to Proserpina and Bilkis, illustrating the potential of the Gaia photometry for setting constraints on asteroid light scattering as a function of the phase angle (the Sun-object-observer angle). Third, with the help of triaxial ellipsoid inversion as applied to Gaia photometry only, we provide additional proof that the absolute Gaia photometry alone can yield meaningful photometric slope parameters. Fourth, for (585) Bilkis, we report, with 1-sigma uncertainties, a refined rotation period of (8.5750559 0.0000026) h, pole longitude of 320.6 degrees +/- 1.2 degrees, pole latitude of - 25.6 degrees +/- 1.7 degrees, and the first shape model and its uncertainties from convex inversion.Conclusions. We conclude that the inverse methods provide realistic uncertainty estimators for the lightcurve inversion problem and that the Gaia photometry can provide an asteroid taxonomy based on the phase curves. en
dc.format.extent 19
dc.language.iso eng
dc.relation.ispartof Astronomy & Astrophysics
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject minor planets
dc.subject asteroids: general
dc.subject radiative transfer
dc.subject scattering
dc.subject methods: numerical
dc.subject methods: statistical
dc.subject ATMOSPHERELESS BODIES
dc.subject ROTATIONAL PROPERTIES
dc.subject OPTIMIZATION METHODS
dc.subject PHASE FUNCTION
dc.subject SHAPE
dc.subject PHOTOMETRY
dc.subject PARAMETERS
dc.subject SCATTERING
dc.subject MODELS
dc.subject G(1)
dc.subject 115 Astronomy, Space science
dc.title Asteroid lightcurve inversion with Bayesian inference en
dc.type Article
dc.contributor.organization Department of Physics
dc.contributor.organization Planetary-system research
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1051/0004-6361/202038036
dc.relation.issn 0004-6361
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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