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Gaia is an astrometric mission that will be launched in 2013 and set on L2 point of Lagrange. It will observe a large number of Solar System Objets (SSO) down to magnitude 20. The Solar System Science goal is to map thousand of Main Belt asteroids (MBAs), Near Earth Objects (NEOs) (including comets) and also planetary satellites with the principal purpuse of orbital determination (better than 5 mas astrometric precision), determination of asteroid mass, spin properties and taxonomy. Besides, Gaia will be able to discover a few objects, in particular NEOs in the region down to the solar elongation 45{deg} which are harder to detect with current ground-based surveys. But Gaia is not a follow-up mission and newly discovered objects can be lost if no ground-based recovery is processed. The purpose of this study is to quantify the impact of Gaia data for the known NEAs population and to show how to handle the problem of these discoveries when faint number of observations and thus very short arc is provided.
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Gaia is an astrometric mission that will be launched in spring 2013. There are many scientific outcomes from this mission and as far as our Solar System is concerned, the satellite will be able to map thousands of main belt asteroids (MBAs) and near-Earth objects (NEOs) down to magnitude < 20. The high precision astrometry (0.3-5 mas of accuracy) will allow orbital improvement, mass determination, and a better accuracy in the prediction and ephemerides of potentially hazardous asteroids (PHAs). We give in this paper some simulation tests to analyse the impact of Gaia data on known asteroids orbit, and their value for the analysis of NEOs through the example of asteroid (99942) Apophis. We then present the need for a follow-up network for newly discovered asteroids by Gaia, insisting on the synergy of ground and space data for the orbital improvement.
We seek evidence of the Yarkovsky effect among Near Earth Asteroids (NEAs) by measuring the Yarkovsky-related orbital drift from the orbital fit. To prevent the occurrence of unreliable detections we employ a high precision dynamical model, including the Newtonian attraction of 16 massive asteroids and the planetary relativistic terms, and a suitable astrometric data treatment. We find 21 NEAs whose orbital fits show a measurable orbital drift with a signal to noise ratio (SNR) greater than 3. The best determination is for asteroid (101955) 1999 RQ36, resulting in the recovery of one radar apparition and an orbit improvement by two orders of magnitude. In addition, we find 16 cases with a lower SNR that, despite being less reliable, are good candidates for becoming stronger detections in the future. In some cases it is possible to constrain physical quantities otherwise unknown by means of the detected orbital drift. Furthermore, the distribution of the detected orbital drifts shows an excess of retrograde rotators that can be connected to the delivery mechanism from the most important NEA feeding resonances and allows us to infer the distribution for NEAs obliquity. We discuss the implications of the Yarkovsky effect for impact predictions. In particular, for asteroid (29075) 1950 DA our results favor a retrograde rotation that would rule out an impact in 2880.
The cryogenic WISE mission in 2010 was extremely sensitive to asteroids and not biased against detecting dark objects. The albedos of 428 Near Earth Asteroids (NEAs) observed by WISE during its fully cryogenic mission can be fit quite well by a 3 parameter function that is the sum of two Rayleigh distributions. The Rayleigh distribution is zero for negative values, and follows $f(x) = x exp[-x^2/(2sigma^2)]/sigma^2$ for positive x. The peak value is at x=sigma, so the position and width are tied together. The three parameters are the fraction of the objects in the dark population, the position of the dark peak, and the position of the brighter peak. We find that 25.3% of the NEAs observed by WISE are in a very dark population peaking at $p_V = 0.03$, while the other 74.7% of the NEAs seen by WISE are in a moderately dark population peaking at $p_V = 0.168$. A consequence of this bimodal distribution is that the Congressional mandate to find 90% of all NEAs larger than 140 m diameter cannot be satisfied by surveying to H=22 mag, since a 140 m diameter asteroid at the very dark peak has H=23.7 mag, and more than 10% of NEAs are darker than p_V = 0.03.
The Yarkovsky effect is a thermal process acting upon the orbits of small celestial bodies, which can cause these orbits to slowly expand or contract with time. The effect is subtle (da/dt ~ 10^-4 au/My for a 1 km diameter object) and is thus generally difficult to measure. We analyzed both optical and radar astrometry for 600 near-Earth asteroids (NEAs) for the purpose of detecting and quantifying the Yarkovsky effect. We present 247 NEAs with measured drift rates, which is the largest published set of Yarkovsky detections. This large sample size provides an opportunity to examine the Yarkovsky effect in a statistical manner. In particular, we describe two independent population-based tests that verify the measurement of Yarkovsky orbital drift. First, we provide observational confirmation for the Yarkovsky effects theoretical size dependence of 1/D, where D is diameter. Second, we find that the observed ratio of negative to positive drift rates in our sample is 2.34, which, accounting for bias and sampling uncertainty, implies an actual ratio of $2.7^{+0.3}_{-0.7}$. This ratio has a vanishingly small probability of occurring due to chance or statistical noise. The observed ratio of retrograde to prograde rotators is two times lower than the ratio expected from numerical predictions from NEA population studies and traditional assumptions about the sense of rotation of NEAs originating from various main belt escape routes. We also examine the efficiency with which solar energy is converted into orbital energy and find a median efficiency in our sample of 12%. We interpret this efficiency in terms of NEA spin and thermal properties.
We present here VRI spectrophotometry of 39 near-Earth asteroids (NEAs) observed with the Sutherland, South Africa, node of the Korea Microlensing Telescope Network (KMTNet). Of the 39 NEAs, 19 were targeted, but because of KMTNets large 2 deg by 2 deg field of view, 20 serendipitous NEAs were also captured in the observing fields. Targeted observations were performed within 44 days (median: 16 days, min: 4 days) of each NEAs discovery date. Our broadband spectrophotometry is reliable enough to distinguish among four asteroid taxonomies and we were able to confidently categorize 31 of the 39 observed targets as either a S-, C-, X- or D-type asteroid by means of a Machine Learning (ML) algorithm approach. Our data suggest that the ratio between stony S-type NEAs and not-stony (C+X+D)-type NEAs, with H magnitudes between 15 and 25, is roughly 1:1. Additionally, we report ~1-hour light curve data for each NEA and of the 39 targets we were able to resolve the complete rotation period and amplitude for six targets and report lower limits for the remaining targets.
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