2019A&A...632A..84F


Query : 2019A&A...632A..84F

2019A&A...632A..84F - Astronomy and Astrophysics, volume 632A, 84-84 (2019/12-0)

Learning mid-IR emission spectra of polycyclic aromatic hydrocarbon populations from observations.

FOSCHINO S., BERNE O. and JOBLIN C.

Abstract (from CDS):


Context. The James Webb Space Telescope (JWST) will deliver an unprecedented quantity of high-quality spectral data over the 0.6-28µm range. It will combine sensitivity, spectral resolution, and spatial resolution. Specific tools are required to provide efficient scientific analysis of such large data sets.
Aims. Our aim is to illustrate the potential of unsupervised learning methods to get insights into chemical variations in the populations that carry the aromatic infrared bands (AIBs), more specifically polycyclic aromatic hydrocarbon (PAH) species and carbonaceous very small grains (VSGs).
Methods. We present a method based on linear fitting and blind signal separation (BSS) for extracting representative spectra for a spectral data set. The method is fast and robust, which ensures its applicability to JWST spectral cubes. We tested this method on a sample of ISO-SWS data, which resemble most closely the JWST spectra in terms of spectral resolution and coverage.
Results. Four representative spectra were extracted. Their main characteristics appear consistent with previous studies with populations dominated by cationic PAHs, neutral PAHs, evaporating VSGs, and large ionized PAHs, known as the PAHx population. In addition, the 3µm range, which is considered here for the first time in a BSS method, reveals the presence of aliphatics connected to neutral PAHs. Each representative spectrum is found to carry second-order spectral signatures (e.g., small bands), which are connected with the underlying chemical diversity of populations. However, the precise attribution of theses signatures remains limited by the combined small size and heterogeneity of the sample of astronomical spectra available in this study.
Conclusions. The upcoming JWST data will allow us to overcome this limitation. The large data sets of hyperspectral images provided by JWST analysed with the proposed method, which is fast and robust, will open promising perspectives for our understanding of the chemical evolution of the AIB carriers.

Abstract Copyright: © S. Foschino et al. 2019

Journal keyword(s): ISM: lines and bands - ISM: molecules - infrared: ISM - photon-dominated region - methods: statistical

Simbad objects: 27

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Number of rows : 27
N Identifier Otype ICRS (J2000)
RA
ICRS (J2000)
DEC
Mag U Mag B Mag V Mag R Mag I Sp type #ref
1850 - 2024
#notes
1 NAME W 3A 02219+6125 HII 02 25 44.6 +62 06 11           ~ 8 0
2 IRAS 03260+3111 mul 03 29 10.4 +31 21 59           ~ 16 0
3 NAME Orion Bright Bar reg 05 35 22.30 -05 24 33.0           ~ 874 0
4 NGC 2023 RNe 05 41 37.9 -02 15 52           ~ 635 1
5 HD 44179 pA* 06 19 58.2185496 -10 38 14.706068 9.51 9.33 9.02     B9Ib/II 765 0
6 PN Vo 1 PN 06 59 26.4167860656 -79 38 47.118534828           [WC10] 100 0
7 M 82 AGN 09 55 52.430 +69 40 46.93 9.61 9.30 8.41     ~ 5860 6
8 ESO 95-1 HII 12 09 01.260 -63 15 59.63     16.00     ~ 95 2
9 WRAY 15-1269 PN 14 59 53.4819371136 -54 18 07.521138792 12.12 12.17 11.64 11.63   [WC11] 248 0
10 IRAS 15384-5348 HII 15 42 17.787 -53 58 30.88           ~ 39 1
11 RCW 97 HII 15 53 05.0 -54 35 24           ~ 157 0
12 NAME Ophiuchus Molecular Cloud SFR 16 28 06 -24 32.5           ~ 3631 1
13 CD-42 11721 Be* 16 59 06.7629322176 -42 42 08.404228224 12.16 12.28 11.00     B0IVe 168 0
14 CPD-56 8032 PN 17 09 00.9291677740 -56 54 47.868280757 11.24 11.48 11.04 11.067   [WC11] 267 0
15 IRAS 17279-3350 HII 17 31 18.0 -33 52 50           ~ 23 0
16 GAL 009.62+00.19 HII 18 06 13.9 -20 31 44           ~ 209 0
17 NGC 6618 OpC 18 20 47 -16 10.3           ~ 1615 0
18 RAFGL 2194 Y*O 18 34 25.18 -07 54 46.1           ~ 28 0
19 RAFGL 5541 Y*O 18 52 50.26 +00 55 29.6           ~ 117 1
20 HD 184738 PN 19 34 45.2337620448 +30 30 58.950651240   10.41 10.44     [WC9] 952 0
21 SH 2-87 bub 19 46 20.69 +24 35 15.4           ~ 158 2
22 NAME SH 2-106 IR Y*O 20 27 26.502 +37 22 42.03           ~ 163 1
23 NGC 7023 RNe 21 01 36.9 +68 09 48           ~ 702 0
24 NAME Cave Nebula RNe 22 13 27 +70 15.3           ~ 55 0
25 SH 2-138 HII 22 32 45.7 +58 28 20           ~ 112 2
26 IC 1470 HII 23 05 09.9 +60 14 31   11.5       ~ 174 2
27 SH 2-159 Y*O 23 15 31.2384366062 +61 07 10.181362705           ~ 180 2

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