Description of the DES_Asteroid_taxonomy bundle V1.0
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Bundle Generation Date: 2024-03-13
Peer Review: 2024_Asteroid_Review
Discipline node: Small Bodies Node


Content description for the DES_Asteroid_taxonomy bundle
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While proper orbital elements are currently available for more than 1 million asteroids,
taxonomical information is still lagging behind.  Surveys like SDSS-MOC4 provided 
preliminary information for more than 100,000 objects (DeMeo and Carry 2013), but many 
asteroids still lack even a basic taxonomy. 

In this study, we use Dark Energy Survey (DES; Dark Energy Survey Collaboration et al. 
2016) data to provide additional information on a set of more data to provide new 
information on asteroid physical properties. Two data sets can be obtained from DES data.  
In the first, we compute gri slope and i-z colors.  In this domain, the taxonomic 
classification scheme of DeMeo and Carry (2013) can be applied, but the number of 
asteroids for which such data can be computed is limited.  
We also obtained a larger data base of DES g-r and g-i colors, with the limitation that a 
much more limited taxonomic analysis, just based on complexes  rather than classes, can be 
performed in this space. 
After eliminating asteroids with large errors in gri slope (larger than 10%/100nm) and 
with errors in the colors i-z, g-r, and g-i larger than 0.1 magnitudes, we obtained two 
data sets with 16517 and 58116 asteroids, respectively.  By cross-correlating the new DES 
database with other databases (Carvano et al. 2010, DeMeo and Carry 2013, and Popescu et 
al. 2018), we investigate how asteroid taxonomy is reflected in DES data.  While the 
resolution of DES data is not sufficient to distinguish between different asteroid 
taxonomies within the complexes, except for V-type objects, it can provide information on 
whether an asteroid belongs to the C- or S-complex.  

Here, supervised machine learning methods optimized through the use of genetic algorithms 
were used to predict the labels of more than 68000  asteroids with no prior taxonomic 
information.  Using a high-quality, limited set of asteroids with data on gri slopes and 
i-z colors, we detected 409 new possible V-type asteroids.  Their orbital distribution is 
highly consistent with that of other known V-type objects (Carruba et al. 2023).

The format of the des_gri_iz.csv database is the asteroid identification, its gri slope, 
its i-z color, and a label which is 0 for a C-complex asteroid, 1, for a S-complex one, 
and 2 for a V-type.  
The des_gr_gi.csv dataset has a similar format but with the colors g-r and g-i instead of 
the gri slope and i-z color.  
Finally, the format of the v_types_pred.csv database is identification, proper a,e, and 
sin(i), and absolute magnitudes. 
Details of the procedures used to obtain the data sets can be found in Carruba et al. (2023).


Caveats to the data user
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None.