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Asteroid phase curves from ATLAS dual-band photometry

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arxiv 2009.05129 v1 pith:347PXDDK submitted 2020-09-10 astro-ph.EP

classification astro-ph.EP
keywords phasecurvesasteroidasteroidsabsolutetaxonomicderivemagnitudes
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abstract

Asteroid phase curves are used to derive fundamental physical properties through the determination of the absolute magnitude H. The upcoming visible Legacy Survey of Space and Time (LSST) and mid-infrared Near-Earth Object Surveillance Mission (NEOSM) surveys rely on these absolute magnitudes to derive the colours and albedos of millions of asteroids. Furthermore, the shape of the phase curves reflects their surface compositions, allowing for conclusions on their taxonomy. We derive asteroid phase curves from dual-band photometry acquired by the Asteroid Terrestrial-impact Last Alert System telescopes. Using Bayesian parameter inference, we retrieve the absolute magnitudes and slope parameters of 127,012 phase curves of 94,777 asteroids in the photometric $H, G_1, G_2$- and $H, G^*_{12}$-systems. The taxonomic complexes of asteroids separate in the observed $G_1, G_2$-distributions, correlating with their mean visual albedo. This allows for differentiating the X-complex into the P-, M-, and E-complexes using the slope parameters as alternative to albedo measurements. Further, taxonomic misclassifications from spectrophotometric datasets as well as interlopers in dynamical families of asteroids reveal themselves in $G_1, G_2$-space. The $H, G^*_{12}$-model applied to the serendipitous observations is unable to resolve target taxonomy. The $G_1, G_2$ phase coefficients show wavelength-dependency for the majority of taxonomic complexes. Serendipitous asteroid observations allow for reliable phase curve determination for a large number of asteroids. To ensure that the acquired absolute magnitudes are suited for colour computations, it is imperative that future surveys densely cover the opposition effects of the phase curves, minimizing the uncertainty on H. The phase curve slope parameters offer an accessible dimension for taxonomic classification.

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