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Register a new userThe Albedo Distribution of Near Earth Asteroids
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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.
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In the framework of a 30-night spectroscopic survey of small near-Earth asteroids (NEAs) we present new results regarding the identification of olivine-rich objects. The following NEAs were classified as A-type using visible spectra obtained with 3.6 m NTT telescope: (293726) 2007 RQ17, (444584) 2006 UK, 2012 NP, 2014 YS34, 2015 HB117, 2015 LH, 2015 TB179, 2015 TW144. We determined a relative abundance of $5.4% $ (8 out of 147 observed targets) A-types at hundred meter size range of NEAs population. The ratio is at least five times larger compared with the previously known A-types, which represent less than $sim1%$ of NEAs taxonomically classified. By taking into account that part of our targets may not be confirmed as olivine-rich asteroids by their near-infrared spectra, or they can have a nebular origin, our result provides an upper-limit estimation of mantle fragments at size ranges bellow 300m. Our findings are compared with the battered-to-bits scenario, claiming that at small sizes the olivine-rich objects should be more abundant when compared with basaltic and iron ones.
Recent lunar crater studies have revealed an asymmetric distribution of rayed craters on the lunar surface. The asymmetry is related to the synchronous rotation of the Moon: there is a higher density of rayed craters on the leading hemisphere compared with the trailing hemisphere. Rayed craters represent generally the youngest impacts. The purpose of this paper is to test the hypotheses that (i) the population of Near-Earth asteroids (NEAs) is the source of the impactors that have made the rayed craters, and (ii) that impacts by this projectile population account quantitatively for the observed asymmetry. We carried out numerical simulations of the orbital evolution of a large number of test particles representing NEAs in order to determine directly their impact flux on the Moon. The simulations were done in two stages. In the first stage we obtained encounter statistics of NEAs on the Earths activity sphere. In the second stage we calculated the direct impact flux of the encountering particles on the surface of the Moon; the latter calculations were confined within the activity sphere of the Earth. A steady-state synthetic population of NEAs was generated from a debiased orbital distribution of the known NEAs. We find that the near-Earth asteroids do have an asymmetry in their impact flux on the Moon: apex-to-antapex ratio of 1.32 +/- 0.01. However, the observed rayed crater distributions asymmetry is significantly more pronounced: apex-to-antapex ratio of 1.65 +/- 0.16. Our results suggest the existence of an undetected population of slower (low impact velocity) projectiles, such as a population of objects nearly coorbiting with Earth; more observational study of young lunar craters is needed to secure this conclusion.
The distribution of solar system absolute magnitudes ($H$) for the near-Earth asteroids (NEAs) observable near opposition -- i.e. Amors, Apollos, and Atens ($A^3$) -- is derived from the set of ALL currently known NEAs. The result is based only on common sense assumptions of uniformly random distributions and that the orbital phase space and $H$-magnitude distribution of known NEAs is representative of the total population. There is no population or other modeling and no assumption on albedo except in interpreting the result as a size-frequency distribution (SFD). The analysis is based on the 18355 $A^3$ NEAs cataloged by the MPC as of June 2018. The observations from 9 of the top programs (in terms of number of distinct NEAs observed) and the smaller but deeper DECam NEO Survey are used, comprising 74696 measurements of 13466 NEAs observed within 30 deg of opposition. The only parameter in the analysis is an estimate of the detection magnitude limits for each program. A single power-law slope for the cumulative distribution, $log(N<H)=0.50pm0.03H$, for $H < 27$ is found with no evidence for additional structure. A turn-over fainter than 27th magnitude may occur, but the population of known NEAs is dropping off rapidly because they are difficult to detect and so possibly is a completeness effect. Connecting to the nearly complete census of the brightest/biggest NEAs (diameter $> {sim}2$Km) provides a normalization that estimates ${sim}10^8 A^3$ NEAs with $H < {sim}27$ corresponding to NEAs greater than ${sim}10$m in diameter for reasonable typical albedos. Restricting the analysis to Earth crossing asteroids (10839 known, 7336 selected, 36541 observed) produces the same power-law slope.
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.
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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