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The influence of space weathering on the observed spectra of C-complex asteroids remains uncertain. This has long hindered our understanding of their composition through telescope observations. Multi-band imaging of Ryugu by ONC-T on Hayabusa2 and that of Bennu by MapCam on OSIRIS-REx found opposite spectral trends of space weathering; Ryugu darkened/reddened while Bennu brightened/blued. How the spectra of Ryugu and Bennu evolved relative to each other would place a constraint for understanding their origins and evolutions. In this study, we compared the space weathering trends on Ryugu and Bennu by applying the results of cross calibration between ONC-T and MapCam. We show that the average Bennu surface is brighter by 18.0 $\pm$ 1.5% at 550 nm and bluer by 0.18 $\pm$ 0.03 $\mu$m$^{-1}$ (480-850 nm slope) than Ryugu. The spectral slopes of surface materials are more uniform on Bennu than on Ryugu at spatial scales $\gtrsim$1 m, but Bennu is more heterogeneous at $\lesssim$1 m. This suggests that lateral mixing due to resurfacing may have been more efficient on Bennu. The reflectance-spectral slope distributions of craters on Ryugu and Bennu appeared to follow two trend lines with an offset before cross calibration, but they converged to a single straight trend without a bend after cross calibration. We show that the spectra of the freshest craters on Ryugu and Bennu are indistinguishable within the uncertainty of cross calibration. These results suggest that Ryugu and Bennu initially had similar spectra before space weathering and that they evolved in completely opposite directions along the same trend line, subsequently evolving into asteroids with different disk-averaged spectra. These findings further suggest that space weathering likely expanded the spectral slope variation of C-complex asteroids, implying that they may have formed from materials with more uniform spectral slopes.

In the context of charge-coupled devices (CCDs), the ultraviolet (UV) region has mostly remained unexplored after the 1990s. Gaia DR3 offers the community a unique opportunity to explore tens of thousands of asteroids in the near-UV as a proxy of the UV absorption. This absorption has been proposed in previous works as a diagnostic of hydration, organics, and space weathering. Aims. In this work, we aim to explore the potential of the NUV as a diagnostic region for primitive asteroids using Gaia DR3. We used a corrective factor over the blue part of Gaia spectra to erase the solar analog selection effect. We identified an artificial relation between the band noise and slope and applied a signal-to-noise ratio (S/N) threshold for Gaia bands. Meeting the quality standards, we employed a Markov chain Monte Carlo (MCMC) algorithm to compute the albedo threshold, maximizing primitive asteroid inclusion. Utilizing one- and two-dimensional (1D and 2D) projections, along with dimensionality-reduction methods (such as PCA and UMAP), we identified primitive asteroid populations. We uncovered: (a) the first observational evidence linking UV absorption to the 0.7 {\mu}m band, tied to hydrated iron-rich phyllosilicates; and (b) a 2D space revealing a split in C-type asteroids based on spectral features, including UV absorption. The computed average depth (3.5 +- 1.0 %) and center (0.70 +- 0.03 {\mu}m) of the 0.7 {\mu}m absorption band for primitive asteroids observed with Gaia is in agreement with the literature values. In this paper, we shed light on the importance of the UV absorption feature to discriminate among different mineralogies (i.e., iron-rich phyllosilicates vs. iron-poor) or to identify taxonomies that are conflated in the visible (i.e., F-types vs. B-types). We have shown that this is a promising region for diagnostic studies of the composition of primitive asteroids., Comment: 14 pages 13 figures, accepted for publication in A&A

Asteroids (162173) Ryugu and (101955) Bennu observed by Hayabusa2 and OSIRIS-REx share many properties, but spectral observations by the telescopic Optical Navigation Camera (ONC-T) and MapCam detected subtle but significant differences, which may reflect differences in their origin and evolution. Comparing these differences on the same absolute scale is necessary for understanding their causes. However, ONC-T and MapCam have a large imager-to-imager systematic error of up to 15% caused by the difference in radiometric calibration targets. To resolve this problem, we cross calibrated albedo and color data between the two instruments using the Moon as the common calibration standard. The images of the Moon taken by ONC-T and MapCam were compared with those simulated using photometry models developed from lunar orbiter data. Our results show that the cross-calibrated reflectance of Ryugu and Bennu can be obtained by upscaling the pre-cross-calibrated reflectance of Bennu by 13.3 +/- 1.6% at b band, 13.2 +/- 1.5% at v band, 13.6 +/- 1.7% at w band, and 14.8 +/- 1.8% at x band, while those for Ryugu are kept the same. These factors compensate for the imager-to-imager bias caused by differences in targets used for radiometric calibration and solar irradiance models used for data reduction. Need for such large upscaling underscore the importance of using the cross-calibrated data for accurately comparing the Ryugu and Bennu data. The uncertainty in these factors show that the reflectance of Ryugu and Bennu can be compared with <2% accuracy after applying our results. By applying our cross calibration, the geometric albedo of Bennu became consistent with those observed by ground-based telescopes and OVIRS. Our result can be simply applied by multiplying a constant to the publicly available data and enables accurate comparison of the optical spectra of Ryugu and Bennu in future studies.

Quaoar is a classical Trans-Neptunian Object (TNO) with an area equivalent diameter of 1,100 km and an orbital semi-major axis of 43.3 astronomical units. Based on stellar occultations observed between 2018 and 2021, an inhomogeneous ring (Q1R, Quaoar's first ring) was detected around this body. Aims. A new stellar occultation by Quaoar was observed on August 9th, 2022 aiming to improve Quaoar's shape models and the physical parameters of Q1R while searching for additional material around the body. Methods. The occultation provided nine effective chords across Quaoar, pinning down its size, shape, and astrometric position. Large facilities, such as Gemini North and the Canada-France-Hawaii Telescope (CFHT), were used to obtain high acquisition rates and signal-to-noise ratios. The light curves were also used to characterize the Q1R ring (radial profiles and orbital elements). Results. Quaoar's elliptical fit to the occultation chords yields the limb with an apparent semi-major axis of $579.5\pm4.0$ km, apparent oblateness of $0.12\pm0.01$, and area-equivalent radius of $543\pm2$ km. Quaoar's limb orientation is consistent with Q1R and Weywot orbiting in Quaoar's equatorial plane. The orbital radius of Q1R is refined to a value of $4,057\pm6$ km. The radial opacity profile of the more opaque ring profile follows a Lorentzian shape that extends over 60 km, with a full width at half maximum (FWHM) of $\sim5$ km and a peak normal optical depth of 0.4. Besides the secondary events related to the already reported rings, new secondary events detected during the August 2022 occultation in three different data sets are consistent with another ring around Quaoar with a radius of $2,520\pm20$ km, assuming the ring is circular and co-planar with Q1R. This new ring has a typical width of 10 km and a normal optical depth of $\sim$0.004. Like Q1R, it also lies outside Quaoar's classical Roche limit., Comment: Accepted for publication in Astronomy & Astrophysics (17-April-2023). 18 pages, 12 figures

In the framework of the Visible NEAs Observations Survey (ViNOS) that uses several telescopes at the Canary Islands observatories since 2018, we observed two super fast rotator NEAs, 2021 NY$_1$ and 2022 AB. We obtained photometry and spectrophotometry of both targets and visible spectroscopy of 2022 AB. Light curves of 2021 NY$_1$ obtained in 4 different nights between Sept. 30 and Oct. 16, 2021 return a rotation period $P=13.3449\pm0.0013$ minutes and a light curve amplitude $A = 1.00$ mag. We found that 2021 NY$_1$ is a very elongated super fast rotator with an axis ratio $a/b \ge 3.6$. We also report colours $(g-r) = 0.664 \pm 0.013$, $(r-i) = 0.186 \pm 0.013$, and $(i-z_s) = -0.117 \pm 0.012$ mag. These are compatible with an S-type asteroid. The light curves of 2022 AB obtained on Jan. 5 and Jan. 8, 2021 show a rotation period $P=3.0304\pm0.0008$ minutes, with amplitudes $A = 0.52$ and $A =0.54$ mag. 2022 AB is also an elongated object with axis ratio $a/b \ge 1.6$. The obtained colours are $(g-r) = 0.400 \pm 0.017$, $(r-i) = 0.133 \pm 0.017$, and $(i-z_s) = 0.093 \pm 0.016$. These colours are similar to those of the X-types, but with an unusually high $(g-r)$ value. Spectra obtained on Jan. 12 and Jan. 14, 2022, are consistent with the reported colours. The spectral upturn over the 0.4 - 0.6 $\mu m $ region of 2022 AB does not fit with any known asteroid taxonomical class or meteorite spectrum, confirming its unusual surface properties., Comment: 9 pages, 7 figures

Relevant information about physical properties of the surface of airless bodies such as porosity, particle size, or roughness can be inferred knowing the dependence of the brightness with illumination and observing geometry. Additionally, this knowledge is necessary to standardize or photometrically correct data acquired under different illumination conditions. In this work we develop a robust, automatic, and efficient photometric modeling methodology which is tested and validated using Bennu images acquired by the camera MapCam from the OSIRIS-REx spacecraft. It consists of a supervised machine learning algorithm through an artificial neural network. Our system provides a more precise modeling for all color filters than the previous procedures which are already published, offering an improvement over this classic approach of up to 14.30%, as well as a considerable reduction in computing time.

The OSIRIS-REx spacecraft encountered the asteroid (101955) Bennu on December 3, 2018, and has since acquired extensive data from the payload of scientific instruments on board. In 2019, the OSIRIS-REx team selected primary and backup sample collection sites, called Nightingale and Osprey, respectively. On October 20, 2020, OSIRIS-REx successfully collected material from Nightingale. In this work, we apply an unsupervised machine learning classification through the K-Means algorithm to spectrophotometrically characterize the surface of Bennu, and in particular Nightingale and Osprey. We first analyze a global mosaic of Bennu, from which we find four clusters scattered across the surface, reduced to three when we normalize the images at 550 nm. The three spectral clusters are associated with boulders and show significant differences in spectral slope and UV value. We do not see evidence of latitudinal non-uniformity, which suggests that Bennu's surface is well-mixed. In our higher-resolution analysis of the primary and backup sample sites, we find three representative normalized clusters, confirming an inverse correlation between reflectance and spectral slope (the darkest areas being the reddest ones) and between b' normalized reflectance and slope. Nightingale and Osprey are redder than the global surface of Bennu by more than $1\sigma$ from average, consistent with previous findings, with Nightingale being the reddest ($S' = (- 0.3 \pm 1.0) \times 10^{- 3}$ percent per thousand angstroms). We see hints of a weak absorption band at 550 nm at the candidate sample sites and globally, which lends support to the proposed presence of magnetite on Bennu.

The first known asteroid with the orbit inside that of Venus is 2020~AV$_{2}$. This may be the largest member of a new population of small bodies with the aphelion smaller than 0.718~au, called Vatiras. The surface of 2020~AV$_{2}$ is being constantly modified by the high temperature, by the strong solar wind irradiation that characterizes the innermost region of the Solar system, and by high-energy micrometeorite impacts. The study of its physical properties represents an extreme test-case for the science of near-Earth asteroids. Here, we report spectroscopic observations of 2020~AV$_{2}$ in the 0.5-1.5~$\mu m$ wavelength interval. These were performed with the Nordic Optical Telescope and the William Herschel Telescope. Based on the obtained spectra, we classify 2020~AV$_{2}$ as a Sa-type asteroid. We estimate the diameter of this Vatira to be $1.50_{-0.65}^{+1.10}$ km by considering the average albedo of A-type and S-complex asteroids ($p_V=0.23_{-0.08}^{+0.11}$), and the absolute magnitude (H=$16.40\pm0.78$ mag). The wide spectral band around 1~$\mu m$ shows the signature of an olivine rich composition. The estimated band centre $BIC = 1.08 \pm 0.02~\mu m$ corresponds to a ferroan olivine mineralogy similar to that of brachinite meteorites., Comment: Accepted for publication in MNRAS. 10 pages, 5 figures

Using images acquired by the Hayabusa/AMICA instrument, along with Lederer et al.'s (2008) ground-based observations, we re-examine Itokawa's disk-integrated phase curve. The AMICA images provide critical opposition measurements (between 0.7deg - 9.3deg phase at 540 nm). Using Hapke's model (2012), we fit the updated phase curves at 5 different wavelengths. Preliminary modeling results show a range of porosity values commensurate with those in the literature (Ostro et al. 2004, Gundlach and Blum, 2012, Kiuchi and Nakamura 2014) based on an impact-generated grain size distribution function and grain size range evaluations from the AMICA data (Yano et al. 2006). This wide range on a global porosity is indicative of a highly variable porosity across the surface. The derived transport mean free path and the generally forward scattering nature of the global regolith are indicative of scattering centers (such as cracks, bubbles, and inclusions) that are small compared to the observational wavelengths. The derived regolith properties are compared with the imaging and sample analysis results, providing a test of the predictive capabilities of global disk-integrated measurements. This work suggests that the sub-pixel grain information could be extracted from the photometry, especially around opposition.