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Register a new userThe Ch-class asteroids: Connecting a visible taxonomic class to a 3-{mu}m band shape
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Asteroids belonging to the Ch spectral taxonomic class are defined by the presence of an absorption near 0.7 {mu}m, which is interpreted as due to Fe-bearing phyllosilicates. Phyllosilicates also cause strong absorptions in the 3-{mu}m region, as do other hydrated and hydroxylated minerals and H2O ice. Over the past decade, spectral observations have revealed different 3-{mu}m band shapes the asteroid population. Although a formal taxonomy is yet to be fully established, the Pallas-type spectral group is most consistent with the presence of phyllosilicates. If Ch class and Pallas type are both indicative of phyllosilicates, then all Ch-class asteroids should also be Pallas-type. In order to test this hypothesis, we obtained 42 observations of 36 Ch-class asteroids in the 2- to 4-{mu}m spectral region. We found that 88% of the spectra have 3-{mu}m band shapes most consistent with the Pallas-type group. This is the first asteroid class for which such a strong correlation has been found. Because the Ch class is defined by the presence of an absorption near 0.7 {mu}m, this demonstrates that the 0.7-{mu}m band serves not only as a proxy for the presence of a band in the 3-{mu}m region, but specifically for the presence of Pallas-type bands. There is some evidence for a correlation between band depth at 2.95 {mu}m and absolute magnitude and/or albedo. However, we find only weak correlations between 2.95-{mu}m band depth and semi-major axis. The connection between band depths in the 0.7- and 3-{mu}m regions is complex and in need of further investigation.
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We present here a new method to model the shape of the 3-{mu}m absorption band in the reflectance spectra of meteorites and small bodies. The band is decomposed into several OH/H2O components using Exponentially Modified Gaussian (EMG) profiles, as well as possible organic components using Gaussian profiles when present. We compare this model to polynomial and multiple Gaussian profile fits and show that the EMGs model returns the best rendering of the shape of the band, with significantly lower residuals. We also propose as an example an algorithm to estimate the error on the band parameters using a bootstrap method. We then present an application of the model to two spectral analyses of smectites subjected to different H2O vapor pressures, and present the variations of the components with decreasing humidity. This example emphasizes the ability of this model to coherently retrieve weak bands that are hidden within much stronger ones.
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