Comparison of Diffuse Infrared and Far-Ultraviolet emission in the Large Magellanic Cloud: The Data
aa r X i v : . [ a s t r o - ph . GA ] A p r Comparison of Diffuse Infrared and Far-Ultravioletemission in the Large Magellanic Cloud: The Data
Gautam Saikia a, ∗ , P. Shalima b , Rupjyoti Gogoi a , Amit Pathak a a Department of Physics, Tezpur University, Napaam-784028, India b Regional Institute of Education Mysore, Mysuru, Karnataka-570001, India
Abstract
Dust scattering is the main source of diffuse emission in the far-ultraviolet(FUV). For several locations in the Large Magellanic Cloud (LMC),
Far Ultra-violet Spectroscopic Explorer (FUSE) satellite has observed diffuse radiation inthe FUV with intensities ranging from 1000 - 3 × photon units and dif-fuse fraction between 5% - 20% at 1100 ˚A. Here, we compare the FUV diffuseemission with the mid-infrared (MIR) and far-infrared (FIR) diffuse emissionobserved by the Spitzer Space Telescope and the
AKARI satellite for the samelocations. The intensity ratios in the different MIR and FIR bands for each ofthe locations will enable us to determine the type of dust contributing to thediffuse emission as well as to derive a more accurate 3D distribution of stars anddust in the region, which in turn may be used to model the observed scatteringin the FUV. In this work we present the infrared (IR) data for two differentregions in LMC, namely N11 and 30 Doradus. We also present the FUV ∼ IRcorrelation for different infrared bands.
Keywords:
ISM: dust, infrared: ISM, Magellanic Clouds ∗ Corresponding author
Email address: [email protected] (Gautam Saikia)
Preprint submitted to Planetary and Space Science Journal July 2, 2018 . Introduction
Interstellar dust grains scatter and absorb incident radiation. A combinationof the two processes is called extinction (Trumpler 1930)[1]. These dust prop-erties are all wavelength dependent as well as dependent on the compositionand sizes of the grains. The scattered component is observed as diffuse emis-sion in the optical and ultraviolet (UV). The absorbed fraction is re-emitted asdiffuse radiation in the mid-infrared (MIR) or far-infrared (FIR) depending onthe dust temperature (Draine 2003)[2]. Dust also is an important agent in thefluid dynamics, chemistry, heating, cooling, and even ionization balance in someinterstellar regions, with a major role in the process of star formation. Despitethe importance of dust, determination of the physical properties of interstellardust grains has been a challenging task. The infrared (IR) emission from dustdepends not only on the amount of dust present, but also on the rate at whichit is heated by starlight.The spectral properties of the IR emission from dust allow one to infer thecomposition of the dust, the size distribution of the dust particles, the intensityof the starlight that is heating the dust, and the total mass of dust. The dustscattered UV radiation has been observed in several regions in the Galaxy andbeyond by probes like
GALEX , FUSE etc. It has been found to be associatedwith regions of thin sheets of material close to hot UV emitting stars (Sujathaet al. 2005)[3]. In the MIR we can observe emission from PAH molecules as wellas from tiny solid grains which have sizes starting from a few tens of Angstroms.PAH molecules can be detected in the
Spitzer µ m band. These are associatedwith colder dust clouds. The small solid grains are known as VSGs (Very SmallGrains) and can be excited to very high temperatures, resulting in detectableemission in the Spitzer µ m band (Wu et al. 2005)[4]. This VSG emissionis seen to be associated with locations close to hot UV emitting stars like HIIregions, just like the dust scattered UV radiation. However, the behaviour ofthe PAH emission in cluster environments has not yet been studied well (Murata2t al. 2015)[5]. This is mainly due to sparse filter sampling at 8 – 24 µ m inthe Spitzer Space Telescope (Werner et al. 2004)[6]. In contrast, the Japanese
AKARI satellite (Murakami et al. 2007)[7] has continuous wavelength coverageat 2 – 24 µ m with nine photometric bands in the Infrared Camera ( IRC ; Onakaet al. 2007)[8].The Magellanic Clouds are the nearest extragalactic systems and thereforeoffer an opportunity for the study of extragalactic abundances (Pagel et al.1978)[9]. Four types of objects are available for studies of this sort: normalstars, supernova remnants, planetary nebulae and HII regions. The Large Mag-ellanic Cloud (LMC) provides a nearby, ideal laboratory to study the influenceof massive stars on dust properties because it has a nearly face-on orientation,mitigating the confusion and extinction along the Galactic plane. It is at aknown distance, ∼
50 kpc (Feast 1999)[10], so stars can be resolved and studiedin conjunction with the interstellar gas and dust (Stephens et al. 2014)[11]. TheLMC is located at a high latitude ( ∼ ; Putman et al. 1998)[12] and hence itis not much affected by extinction from the Milky Way (MW) dust. For thesereasons, the LMC has been targeted by every space-based IR observatory tostudy dust properties and calibrate dust emission as star formation indicators.The first report of Spitzer Space Telescope observations of an LMC H II com-plex was made by Gorjian et al. (2004)[13] for LHA120-N206 (N206 for short;designation from Henize 1956)[14]; its dust emission was qualitatively comparedwith that of the Orion Nebula. Subsequently, the entire LMC was surveyed by
Spitzer in the Legacy program Surveying the Agents of a Galaxy’s Evolution(SAGE; Meixner et al. 2006)[15]. More recently, the
AKARI space telescopehas been instrumental in observing the LMC.Oestreicher & Schmidt-Kaler (1996)[16] states that not only dust cloud prop-erties, but also the distribution of the dust itself is important for understandingthe structure and dynamics of the LMC. The highest reddening occurs in the re-gions of 30 Doradus and the supershell LMC 2 where color excess E B − V reaches3 maximum of 0.29. The lowest reddening is observed in the region of supershellLMC 4 with E B − V = 0.06. The HII region N11 also shows a high reddeningwith E B − V up to 0.24.Therefore by studying locations which have observations in the FUV and theMIR, we can hope to identify the particular grain population responsible for theobserved emission. We should expect to find a better correlation between theUV and 24 µ m intensities near hot O and B-type stars compared to the UV –8 µ m correlation. Here, we compare the FUV diffuse emission with the MIRdiffuse emission observed by the Spitzer Space Telescope and the MIR and FIRdiffuse emission observed by
AKARI telescope for the same locations.
2. Observations and Data Analysis
We have selected a list of 81 LMC locations observed by the
FUSE
UVtelescope as published in Pradhan et al. (2010)[17]. Among these 81 locations,43 were available in the
Spitzer and
AKARI archives and have been consideredfor this work. These 43 locations include 15
Spitzer observations (8 µ m and 24 µ m) and 28 AKARI observations (15 µ m, 24 µ m and 90 µ m). The 8 µ m datahave been taken from observations by Spitzer Infrared Array Camera (IRAC) which is a four-channel infrared camera that provides simultaneous images atfour wavelengths 3.6 µ m, 4.5 µ m, 5.8 µ m and 8 µ m. All four detector arraysin the camera are 256 ×
256 pixels in size, with a pixel size of 1 . ′′ × . ′′ .We have taken 15 of the 43 locations containing 24 µ m data from observationsby Multiband Imaging Photometer for Spitzer (MIPS) which produced imagingand photometry in three broad spectral bands in the FIR (128 ×
128 pixels at24 µ m, 32 ×
32 pixels at 70 µ m, 2 ×
20 pixels at 160 µ m).The 15 µ m data have been taken from AKARI Infrared Camera (IRC) whichmakes observations using three independent camera systems:
NIR (1.7 – 5.5 µ m), MIR-S (5.8 – 14.1 µ m) and MIR-L (12.4 – 26.5 µ m). We have used4 KARI MIR-L (12.4 - 26.5 µ m) camera for 15 and 24 µ m observations. Thiscamera takes data in multiple wavelengths in the 12.4 - 26.5 µ m range fromwhich we have selected only 15 µ m and 24 µ m. The same camera has beenused for all locations in Table 2. I refers to intensity at 15 µ m wavelength,similarly for I , I and I . We have taken 28 locations having the 24 µ m datafrom AKARI IRC . The 24 µ m band of Spitzer (128 ×
128 pixels) has a differentresolution as compared to the
AKARI (256 ×
256 pixels) 24 µ m and the con-cerned locations are different as we did not find any location with overlapping Spitzer and
AKARI µ m data. One of the advantages of the IRC was thatit was able to observe 10 square arcmin at a time because of large size detectorarrays (512 ×
412 pixels for
NIR , 256 ×
256 pixels for
MIR ). We have alsoused 28 locations observed by the
AKARI Far-Infrared Surveyor (FIS) whichwas the instrument chiefly intended to make an all-sky survey at far-infraredwavelengths. The
FIS had effectively four observation bands:
N60 (50 – 80 µ m), WIDE-S (60 – 110 µ m), WIDE-L (110 – 180 µ m) and N160 (140 – 180 µ m). We have used data taken by AKARI FIS WIDE-S centred at 90 µ m andhaving an array format of 15 × Figure 1:
LMC images taken by the
Spitzer Space Telescope at 8 µ m (left) showingthe N11 and the AKARI satellite at 24 µ m (right) showing the 30 Doradus inthe mid-IR with our locations represented in red circles and squares.5ur locations were generally around well studied targets in the LMC such asthe 30 Doradus (Tarantula Nebula) and N11 [Figure1] which are HII regions inthe LMC. We have used aperture photometry technique in order to determinethe intensity values for all the 43 locations and the results are tabulated in Table1 and Table 2. Table 1 contains 15 Spitzer locations while Table 2 contains 28
AKARI locations. The aperture size while calculating the intensity values hasbeen taken as 30 ′′ × ′′ which is the same as the aperture size of the LWRS ,the instrument onboard the
FUSE telescope, whose data we have used in thiswork (Pradhan et al. 2010)[17]. The coordinates used are galactic longitude (gl)and galactic latitude (gb). The intensities ( I , I , I , I ) are in units of MJysr − . The Henize numbers for the locations have been taken from the catalogueby Henize (1956)[14]. The other details have been taken from astronomicaldatabases NED and
SIMBAD . Table 1:
Details of
Spitzer observations
Target Name gl gb I I Henize No./Comments(MJy sr − ) (MJy sr − )SNR0449-693 280.9115 -35.8492 0.90 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± able 2: Details of
AKARI observations
Target Name gl gb I I I
90 Henize No./Comments(MJy sr −
1) (MJy sr −
1) (MJy sr − ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
3. Results and Discussion
We have calculated the rank correlations among the intensity values for FUVand the five IR wavelengths that we have observed. The rank correlation is animportant statistical tool to study the relation between two quantities. Highervalue of rank correlation coefficient signifies better agreement between the twoquantities. The rank correlation coefficient is inside the interval [-1,1] and takesthe value 1 if the agreement between the two rankings is perfect (the two rank-ings are the same), 0 if the rankings are completely independent and -1 if thedisagreement between the two rankings is perfect (one ranking is the reverse ofthe other).We have used the Spearman’s (rho) rank correlation which is a particular7ase of the general correlation coefficient. For a sample of size n, the n rawscores X i , Y i are converted to ranks x i , y i and ρ is computed from: ρ = 1 − d i n ( n − d i = x i - y i , is the difference between ranks.The probability or the standard error of the coefficient ( σ ) is given as: σ = 0 . p ( n − σ , more is the reliability in the observedvalue of rank correlation.The far-ultraviolet (FUV) intensity values are taken from FUSE observations(Pradhan et al. 2010)[17]. The
FUSE spacecraft included three apertures: the
HIRS (1 . ′′ × ′′ ), the MDRS (4 ′′ × ′′ ), and the LWRS (30 ′′ × ′′ ), all ofwhich obtained data simultaneously. Only the LWRS , with its relatively largefield of view, was useful for diffuse observations. Murthy & Sahnow (2004)[18]have described the analysis of the background observations, and Pradhan et al.(2010)[17] have followed their method of extraction of diffuse surface brightnessfrom the
FUSE spectra. The
FUSE spectrum is treated as a broadband pho-tometric observation and the spectra is collapsed into two wavelength bandsper detector, excluding the terrestrial airglow lines (primarily Ly β ). This re-sults in seven wavelength bands with effective wavelengths at 1004 ˚A(1A1),1058 ˚A(1A2), 1117 ˚A(1B1), 1157 ˚A(1B2), 1159 ˚A(2A1), 1112 ˚A(2A2) and 1056˚A(2B1) (Pradhan et al. 2010)[17].The correlations for Spitzer
IR data at 8 µ m and 24 µ m with FUSE
FUVare shown in Table 3. The corresponding
Spitzer-FUSE correlation graphs areshown in Figure 2. We have also calculated the correlations separately for N11and the results are presented in Table 4. The corresponding N11 correlation8raphs are shown in Figure 3. The correlations for
AKARI
IR data at 15 µ m,24 µ m and 90 µ m with FUSE
FUV are shown in Table 5. The corresponding
AKARI-FUSE correlation graphs are shown in Figure 4. We have also calcu-lated the correlations separately for the 30 Doradus region in the LMC and theresults are given in Table 6. The corresponding 30 Doradus graphs are shownin Figure 5.
Table 3:
Correlations for all 15
Spitzer locations
IR-FUV Rank correlation Probability I ∼ fuv1A1 0.764 0.001 I ∼ fuv1A2 0.610 0.015 I ∼ fuv1B1 0.752 0.001 I ∼ fuv1B2 0.739 0.002 I ∼ fuv2A1 0.817 0.000 I ∼ fuv2A2 0.696 0.004 I ∼ fuv2B1 0.682 0.005 I ∼ fuv1A1 0.314 0.254 I ∼ fuv1A2 0.357 0.191 I ∼ fuv1B1 0.439 0.101 I ∼ fuv1B2 0.464 0.081 I ∼ fuv2A1 0.442 0.098 I ∼ fuv2A2 0.478 0.071 I ∼ fuv2B1 0.485 0.066 Stephens et al. (2014)[11] states that the PAH mass fraction increases signifi-cantly toward molecular clouds except when there is a very strong radiation fieldsince PAHs are likely being destroyed in such a field. The PAH mass fraction9 U V . µ m ( A ) I µ m Rank Correlation = 0.764N11 0.1 1 10 100 0.1 1 10 100 U V . µ m ( A ) I µ m Rank Correlation = 0.314N11
Figure 2:
Correlations plotted for the 15
Spitzer locations (Table 3)increases as one leaves the central OB association. On the other hand, the VSGmass fraction increases at locations of an enhanced radiation field. Expandingbubbles may be launching dust at velocities that can cause big grains to shatterinto VSGs causing 24 µ m emission (Stephens et al. 2014)[11]. From Table 3, the Spitzer correlations for all 15 locations taken together show that the emissionat 8 µ m is better correlated to the FUV as compared to the emission at 24 µ mcontrary to our assumptions. This may be because these 15 locations contain amixture of both hot and relatively cold regions of the LMC. Hot regions referto the HII regions. The cold regions refer to the general diffuse ISM. This is10 able 4: Correlations for the 6 ‘N11’
Spitzer locations
IR-FUV Rank correlation Probability I ∼ fuv1A1 0.828 0.041 I ∼ fuv1A2 0.657 0.156 I ∼ fuv1B1 0.657 0.156 I ∼ fuv1B2 0.714 0.110 I ∼ fuv2A1 0.885 0.018 I ∼ fuv2A2 0.828 0.041 I ∼ fuv2B1 0.885 0.018 I ∼ fuv1A1 0.885 0.018 I ∼ fuv1A2 0.771 0.072 I ∼ fuv1B1 0.771 0.072 I ∼ fuv1B2 0.828 0.041 I ∼ fuv2A1 0.942 0.004 I ∼ fuv2A2 0.885 0.018 I ∼ fuv2B1 0.942 0.004 supported by the fact that we get a different correlation trend once we separatethe N11 HII region from the other locations (Table 4). In this case we see thatat each FUV wavelength, the 24 µ m emission is marginally better correlated tothe FUV as compared to the 8 µ m emission. This supports the existing theorythat the 24 µ m VSG emission is seen to be associated with locations close to thehot UV emitting stars like HII regions, same as the dust scattered UV radiation.The 24 µ m emission is known to be dominated by warm dust emission fromVSGs, which are mainly heated by young massive stars. Results by Spitzer (Wu 2005[4]; Perez- Gonzalez et al. 2006[19]; Calzetti et al. 2007[20]) haveshown that the 24 µ m luminosity is one of the best Star Formation Rate (SFR)indicators. IRAS and
ISO observations have proved that the FIR luminosityis also a good SFR tracer because of the emission peak around 60 µ m of dustheated by star formation, thus the 70 µ m emission must be closely related tostar formation activities and should have tight and linear correlation with 24 µ mwarm dust emission (Zhu et al. 2008)[21]. As seen from Table 5, the AKARI µ m, 24 µ m and 90 µ m show a good correlation with one another which showsthey are associated with VSGs from similar hot environments. This becomes11 U V . µ m ( A ) I µ m Rank Correlation = 0.828 0.1 1 10 100 0.1 1 10 100 U V . µ m ( A ) I µ m Rank Correlation = 0.885
Figure 3:
Correlations plotted for the N11
Spitzer locations (Table 4)more prominent when we take into consideration the 30 Doradus HII region(Table 6) which clearly gives us better correlation values among the 15 µ m, 24 µ m and 90 µ m emissions. The correlations between 15 µ m and FUV seem tobe better in the HII 30 Doradus region as compared to when all hot and coldregions are considered together. Also, the 24 µ m and 90 µ m correlations withFUV are better when we consider all 28 AKARI locations as compared to whenwe consider only 30 Doradus. The FUV/IR(90 µ m) ratio is a measure of theoptical depth of the medium. We see that the average FUV/IR(90 µ m) valuein 30 Doradus is 0 . µ m) value in12 able 5: Correlations for all 28
AKARI locations
IR-FUV Rank correlation Probability I ∼ I I ∼ I I ∼ I I ∼ fuv1A1 0.493 0.007 I ∼ fuv1A2 0.586 0.001 I ∼ fuv1B1 0.668 0.000 I ∼ fuv1B2 0.630 0.000 I ∼ fuv2A1 0.574 0.001 I ∼ fuv2A2 0.626 0.000 I ∼ fuv2B1 0.571 0.001 I ∼ fuv1A1 0.561 0.001 I ∼ fuv1A2 0.657 0.000 I ∼ fuv1B1 0.707 2.544e-05 I ∼ fuv1B2 0.687 5.288e-05 I ∼ fuv2A1 0.639 0.000 I ∼ fuv2A2 0.658 0.000 I ∼ fuv2B1 0.596 0.001 I ∼ fuv1A1 0.644 0.000 I ∼ fuv1A2 0.620 0.000 I ∼ fuv1B1 0.753 3.674 I ∼ fuv1B2 0.724 1.31e-05 I ∼ fuv2A1 0.697 3.70e-05 I ∼ fuv2A2 0.709 2.37e-05 I ∼ fuv2B1 0.672 8.79e-05 N11 which is lower at 0 . µ m) ratio.
4. Conclusions • In this work, we compare the two regions N11 (Table 4) and 30 Doradus(Table 6) in the LMC and observe better FUV ∼ IR correlations for N11( ∼ ∼ • We observe higher FUV/IR(90 µ m) ratio for 30 Doradus in comparisonto N11, which may indicate low extinction and/or more number of starsbeing unaffected by interstellar dust.13 able 6: Correlations for the 8 ‘30 Doradus’
AKARI locations
IR-FUV Rank correlation Probability I ∼ I I ∼ I I ∼ I I ∼ fuv1A1 0.514 0.191 I ∼ fuv1A2 0.071 0.866 I ∼ fuv1B1 0.523 0.182 I ∼ fuv1B2 0.452 0.260 I ∼ fuv2A1 0.523 0.182 I ∼ fuv2A2 0.523 0.182 I ∼ fuv2B1 0.452 0.260 I ∼ fuv1A1 0.431 0.286 I ∼ fuv1A2 0.000 1.000 I ∼ fuv1B1 0.452 0.260 I ∼ fuv1B2 0.428 0.289 I ∼ fuv2A1 0.500 0.207 I ∼ fuv2A2 0.452 0.260 I ∼ fuv2B1 0.428 0.289 I ∼ fuv1A1 0.419 0.301 I ∼ fuv1A2 0.047 0.910 I ∼ fuv1B1 0.452 0.260 I ∼ fuv1B2 0.404 0.319 I ∼ fuv2A1 0.500 0.207 I ∼ fuv2A2 0.452 0.260 I ∼ fuv2B1 0.404 0.319 •
30 Doradus is a very complex region with a high density of stars andtherefore more starlight, as FUV can be contributed by unresolved stars. • There is also a possibility of destruction of VSGs (24 µ m emission) in 30Doradus. Thus lower emission at 24 µ m band.We will try to model both the regions theoretically by using suitable dustmixtures. For 30 Doradus one needs to use a special dust mixture and N11 canbe modelled by using a Milky Way type of dust mixture. We plan to use thestellar/diffuse fraction which was presented by Pradhan et al. (2010)[17] andpostulate if the stellar component of the FUV is higher in 30 Doradus or not.14 cknowledgements This work is based in part on observations made with the
Spitzer Space Tele-scope , which is operated by the Jet Propulsion Laboratory, California Instituteof Technology under a contract with NASA. This work is based on observationswith
AKARI , a JAXA project with the participation of ESA. This research hasmade use of the
NED and the
SIMBAD databases.AP acknowledges financial support from SERB DST FAST TRACK grant(SERB/ F/5143/20132014) and support from the DST JSPS grant (DST/INT/JSPS/P-189/2014). RG and AP thank the Inter-University Centre for Astron-omy and Astrophysics, Pune for associateship. PS would like to thank TezpurUniversity for their support and hospitality that allowed for completion of thiswork.
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Li, Correlations between Mid-Infrared,Far-Infrared, H α , and FUV Luminosities for Spitzer SWIRE Field Galax-ies, 686 (2008) 155171. doi:10.1086/591121.18 U V . µ m ( A ) I µ m Rank Correlation = 0.49330D 0.01 0.1 1 10 100 1000 10000 0.01 0.1 1 10 100 1000 10000 U V . µ m ( A ) I µ m Rank Correlation = 0.56130D 0.01 0.1 1 10 100 1000 10000 0.01 0.1 1 10 100 1000 10000 U V . µ m ( A ) I µ m Rank Correlation = 0.64430D
Figure 4:
Correlations plotted for the 28
AKARI locations (Table 5)19 U V . µ m ( A ) I µ m Rank Correlation = 0.514 0.01 0.1 1 10 100 1000 10000 0.01 0.1 1 10 100 1000 10000 U V . µ m ( A ) I µ m Rank Correlation = 0.431 0.01 0.1 1 10 100 1000 10000 0.01 0.1 1 10 100 1000 10000 U V . µ m ( A ) I µ m Rank Correlation = 0.419
Figure 5:
Correlations plotted for the 30 Doradus