TY - JOUR
T1 - Using machine learning to classify the diffuse interstellar bands
AU - Baron, Dalya
AU - Poznanski, Dovi
AU - Watson, Darach
AU - Yao, Yushu
AU - Cox, Nick L.J.
AU - Prochaska, J. Xavier
N1 - Publisher Copyright:
© 2015 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Using over a million and a half extragalactic spectra from the Sloan Digital Sky Survey 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 five strong DIBs. Furthermore, we find a pair of DIBs, 5925.9 and 5927.5 Å, 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 dependence, we study how DIBs follow their local environment. We thus obtain six groups of weak DIBs, four of which are tightly associated with C2 or CN absorption lines.
AB - Using over a million and a half extragalactic spectra from the Sloan Digital Sky Survey 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 five strong DIBs. Furthermore, we find a pair of DIBs, 5925.9 and 5927.5 Å, 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 dependence, we study how DIBs follow their local environment. We thus obtain six groups of weak DIBs, four of which are tightly associated with C2 or CN absorption lines.
KW - Dust, extinction
KW - ISM: general
KW - ISM: lines and bands
KW - ISM: molecules
KW - Surveys
KW - Techniques: spectroscopic
UR - http://www.scopus.com/inward/record.url?scp=84938252061&partnerID=8YFLogxK
U2 - 10.1093/mnras/stv977
DO - 10.1093/mnras/stv977
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AN - SCOPUS:84938252061
SN - 0035-8711
VL - 451
SP - 332
EP - 352
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
IS - 1
ER -