Context. Asteroid (16) Psyche is the target of the NASA Psyche mission. It is considered one of the few main-belt bodies that could be an exposed proto-planetary metallic core and that would thus be related to iron meteorites. Such an association is however challenged by both its near-and mid-infrared spectral properties and the reported estimates of its density. Aims. Here, we aim to refine the density of (16) Psyche to set further constraints on its bulk composition and determine its potential meteoritic analog. Methods. We observed (16) Psyche with ESO VLT/SPHERE/ZIMPOL as part of our large program (ID 199.C-0074). We used the high angular resolution of these observations to refine Psyche's three-dimensional (3D) shape model and subsequently its density when combined with the most recent mass estimates. In addition, we searched for potential companions around the asteroid. Results. We derived a bulk density of 3.99 ± 0.26 g·cm −3 for Psyche. While such density is incompatible at the 3sigma level with any iron meteorites (∼7.8 g·cm −3 ), it appears fully consistent with that of stony-iron meteorites such as mesosiderites (density ∼4.25 g·cm −3 ). In addition, we found no satellite in our images and set an upper limit on the diameter of any non-detected satellite of 1460 ± 200 m at 150 km from Psyche (0.2% × R Hill , the Hill radius) and 800 ± 200 m at 2,000 km (3% × R Hill ). Conclusions. Considering that the visible and near-infrared spectral properties of mesosiderites are similar to those of Psyche, there is merit to a long-published initial hypothesis that Psyche could be a plausible candidate parent body for mesosiderites.
Context. Adaptive optics (AO) systems greatly increase the resolution of large telescopes, but produce complex point spread function (PSF) shapes, varying in time and across the field of view. The PSF must be accurately known since it provides crucial information about optical systems for design, characterization, diagnostics, and image post-processing. Aims. We develop here a model of the AO long-exposure PSF, adapted to various seeing conditions and any AO system. This model is made to match accurately both the core of the PSF and its turbulent halo.Methods. The PSF model we develop is based on a parsimonious parameterization of the phase power spectral density, with only five parameters to describe circularly symmetric PSFs and seven parameters for asymmetrical ones. Moreover, one of the parameters is the Fried parameter r 0 of the turbulence's strength. This physical parameter is an asset in the PSF model since it can be correlated with external measurements of the r 0 , such as phase slopes from the AO real time computer (RTC) or site seeing monitoring. Results. We fit our model against end-to-end simulated PSFs using the OOMAO tool, and against on-sky PSFs from the SPHERE/ZIMPOL imager and the MUSE integral field spectrometer working in AO narrow-field mode. Our model matches the shape of the AO PSF both in the core and the halo, with a relative error smaller than 1% for simulated and experimental data. We also show that we retrieve the r 0 parameter with sub-centimeter precision on simulated data. For ZIMPOL data, we show a correlation of 97% between our r 0 estimation and the RTC estimation. Finally, MUSE allows us to test the spectral dependency of the fitted r 0 parameter. It follows the theoretical λ 6/5 evolution with a standard deviation of 0.3 cm. Evolution of other PSF parameters, such as residual phase variance or aliasing, is also discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.