Techniques d'observation spectroscopique d'astéroïdes

CHAPTER 4. SPECTRAL ANALYSIS TECHNIQUES 67
O : 3628 - Very rounded and deep, "bowl" shape absorption feature at 1 µm as well as a
significant absorption feature at 2 µm.
Q : 1862, 3753, 5660 - Distinct 1 µm absorption feature with evidence of another feature near
1.3 µm; a 2 µm feature exists with varying depths between objects.
R : 349 - Deep 1 and 2 µm features; the 1 µm feature is much narrower than a Q type, but
slightly broader than a V type.
S : 5, 14, 20 - Moderate 1 and 2 µm features; the 2 µm feature may vary in depth between
objects.
Sa : 984, 5261 - Has a deep and extremely broad absorption band at 1 µm; has similar features
to A types but is less red.
tel-00785991, version 1 - 7 Feb 2013
Sq : 3, 11, 43 - Has a wide 1 µm absorption band with evidence of a feature near 1.3 µm like
the Q type, except the 1 µm feature is more shallow for the Sq.
Sr : 237, 808, 1228 - Has a fairly narrow 1 µm feature similar to but more shallow than an R
type as well as a 2 µm feature.
Sv : 2965, 4451 - Has a very narrow 1 µm absorption band similar to but more shallow than a
V type as well as a 2 µm feature.
T : 96, 308, 773 - Linear with moderate to high slope and often gently concaving down.
V : 4, 1929, 2851 - Very strong and very narrow 1 µm absorption and as well as a strong 2 µm
absorption feature.
X : 22, 87, 153 - Linear with medium to high slope.
Xc : 21, 97, 739 - Low to medium slope and slightly curved and concave downward.
Xe : 64, 77, 3103 - Low to medium slope similar to either Xc or Xk type, but with an absorption
band feature shortward of 0.55 µm.
Xk : 56, 110, 337 - Slightly curved and concave downward similar to Xc type but with a faint
feature between 0.8 to 1 µm.
Ld : 279, 3734 - Diverged to L and D classes.
Sk : 3, 6585 - Diverged to the S and Sq classes.
Sl : 17, 30 - Merged with the S class.
The classification of an asteroid spectrum in Bus-DeMeo taxonomy can be done via MIT-
SMASS online tool 1 .
The G-mode is a multivariate statistical clustering method that allows us to classify a statistical
sample consisting of N elements with M variables. The parameter G is the analog of
the distance in a NxM space. This statistical distance between an object and a taxonomic class
shows the similarities of the characteristics of this object to those of its class [Barucci et al.,
1 http://smass.mit.edu/busdemeoclass.html