Using machine learning to classify the diffuse interstellar bands
  Using over a million and a half extragalactic spectra we study the
correlations of the Diffuse Interstellar Bands (DIBs) in the Milky Way. We
measure the correlation between DIB strength and dust extinction for 142 DIBs
using 24 stacked spectra in the reddening range E(B-V) < 0.2, many more lines
than ever studied before. Most of the DIBs do not correlate with dust
extinction. However, we find 10 weak and barely studied DIBs with correlations
that are higher than 0.7 with dust extinction and confirm the high correlation
of additional 5 strong DIBs. Furthermore, we find a pair of DIBs, 5925.9A and
5927.5A which exhibits significant negative correlation with dust extinction,
indicating that their carrier may be depleted on dust. We use Machine Learning
algorithms to divide the DIBs to spectroscopic families based on 250 stacked
spectra. By removing the dust dependency we study how DIBs follow their local
environment. We thus obtain 6 groups of weak DIBs, 4 of which are tightly
associated with C2 or CN absorption lines.
