J/MNRAS/489/4389 JINGLE V Dust properties of nearby galaxies (Lamperti+, 2019)
JINGLE - V. Dust properties of nearby galaxies derived from hierarchical
Bayesian SED fitting.
Lamperti I., Saintonge A., De Looze I., Accurso G., Clark C.J.R.,
Smith M.W.L., Wilson C.D., Brinks E., Brown T., Bureau M., Clements D.L.,
Eales S., Glass D.H.W., Hwang H.S., Lee J.C., Lin L., Michalowski M.J.,
Sargent M., Williams T.G., Xiao T., Yang C.
<Mon. Not. R. Astron. Soc., 489, 4389-4417 (2019)>
=2019MNRAS.489.4389L 2019MNRAS.489.4389L (SIMBAD/NED BibCode)
ADC_Keywords: Galaxies ; Interstellar medium ; Models
Keywords: dust, extinction - galaxies: evolution - galaxies: ISM -
submillimetre: ISM
Abstract:
We study the dust properties of 192 nearby galaxies from the JINGLE
survey using photometric data in the 22-850µm range. We derive the
total dust mass, temperature T, and emissivity index β of the
galaxies through the fitting of their spectral energy distribution
(SED) using a single modified blackbody model (SMBB). We apply a
hierarchical Bayesian approach that reduces the known degeneracy
between T and β. Applying the hierarchical approach, the strength
of the T-β anticorrelation is reduced from a Pearson correlation
coefficient R=-0.79 to R=-0.52. For the JINGLE galaxies we measure
dust temperatures in the range 17-30K and dust emissivity indices
β in the range 0.6-2.2. We compare the SMBB model with the broken
emissivity law modified blackbody (BMBB) and the two modified
blackbody (TMBB) models. The results derived with the SMBB and TMBB
are in good agreement, thus applying the SMBB, which comes with fewer
free parameters, does not penalize the measurement of the cold dust
properties in the JINGLE sample. We investigate the relation between T
and β and other global galaxy properties in the JINGLE and
Herschel Reference Survey (HRS) sample. We find that β correlates
with the stellar mass surface density (R=0.62) and anticorrelates with
the HI mass fraction (MHI/M*, R=-0.65), whereas the dust
temperature correlates strongly with the star formation rate
normalized by the dust mass (R=0.73). These relations can be used to
estimate T and β in galaxies with insufficient photometric data
available to measure them directly through SED fitting.
Description:
The 192 galaxies in the JINGLE sample have stellar masses in the range
logM*/M☉=9-11.3 and are in the redshift range 0.01<z<0.05. The
targets were selected from the H-ATLAS survey (Eales et al.
2010PASP..122..499E 2010PASP..122..499E; Maddox et al. 2018ApJS..236...30M 2018ApJS..236...30M, Cat.
J/ApJS/236/30) with the requirement to have a detection ≥3σ in
the 250 and 350µm SPIRE bands. Additionally, they have been
selected to have a flat logarithmic stellar mass distribution. Due to
these requirements, they are mainly main-sequence star-forming
galaxies with -1.5<logSFR<1.5[M☉/yr]. A detailed description of
the selection criteria is provided in Saintonge et al.
(2018MNRAS.481.3497S 2018MNRAS.481.3497S, Cat. J/MNRAS/481/3497). Most of the JINGLE
objects are late-type galaxies, with only seven classified as
early-type galaxies.
A detailed description of the JINGLE photometric data set is given in
Smith et al. (2019MNRAS.486.4166S 2019MNRAS.486.4166S, Cat. J/MNRAS/486/4166) and De Looze
et al. (2020MNRAS.496.3668D 2020MNRAS.496.3668D).
To describe the far-infrared and sub-millimetre SED we adopt the three
models employed by Gordon et al. (2014ApJ...797...85G 2014ApJ...797...85G) for the SED fit
of the Magellanic Clouds: single modified blackbody (SMBB), broken
emissivity law modified blackbody (BMBB), and two modified blackbody
(TMBB). The results of the hierarchical fit using the SMBB, BMBB and
TMBB models are given in Tables E1, E2 and E3 respectively.
File Summary:
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FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
tablee1.dat 60 192 Result parameters from the hierarchical SED
fitting using the SMBB model
tablee2.dat 83 192 Result parameters from the hierarchical SED
fitting using the BMBB model
tablee3.dat 81 192 Result parameters from the hierarchical SED
fitting using the TMBB model
tablee4.dat 89 35 Results of the analysis of the correlation
between dust emissivity index β and
combinations of other galaxy properties
tablee5.dat 90 35 Results of the analysis of the correlation
between dust temperature Tdust and
combinations of other galaxy properties
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See also:
J/ApJS/236/30 : Herschel-ATLAS (H-ATLAS) DR2 (Maddox+, 2018)
Byte-by-byte Description of file: tablee1.dat
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Bytes Format Units Label Explanations
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1- 3 I3 --- ID [0/192] JINGLE ID
5- 23 A19 --- Name SDSS name (JHHDDSS.ss+DDMMSS.s)
25- 28 F4.2 [Msun] logMc Logarithm of dust mass from the SMBB model
30- 33 F4.2 [Msun] e_logMc Error on logMc
35- 39 F5.2 K Tc Dust temperature from the SMBB model
model
41- 44 F4.2 K e_Tc Error on Tc
46- 49 F4.2 --- betac Emissivity index from the SMBB model
51- 54 F4.2 --- e_betac Error on betac
56- 60 F5.2 --- lnL Natural logarithm of the likelihood of the
SMBB model fit
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Byte-by-byte Description of file: tablee2.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 3 I3 --- ID [0/192] JINGLE ID
5- 23 A19 --- Name SDSS name (JHHDDSS.ss+DDMMSS.s)
25- 28 F4.2 [Msun] logMc Logarithm of dust mass from the BMBB model
30- 33 F4.2 [Msun] e_logMc Error on logMc
35- 39 F5.2 K Tc Dust temperature from the BMBB model
41- 44 F4.2 K e_Tc Error on Tc
46- 49 F4.2 --- beta1 Emissivity index (for wavelengths
<λbreak) from the BMBB model
51- 54 F4.2 --- e_beta1 Error on beta1
56- 59 F4.2 --- beta2 Emissivity index (for wavelengths
>λbreak) from the BMBB model
61- 64 F4.2 --- e_beta2 Error on beta2
66- 71 F6.2 um lambdab Wavelength of the break (λbreak)
from the BMBB model
73- 77 F5.2 um e_lambdab Error on lambdab
79- 83 F5.2 --- lnL Natural logarithm of the likelihood of the
BMBB model fit
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Byte-by-byte Description of file: tablee3.dat
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Bytes Format Units Label Explanations
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1- 3 I3 --- ID [0/192] JINGLE ID
5- 23 A19 --- Name SDSS name (JHHDDSS.ss+DDMMSS.s)
25- 28 F4.2 [Msun] logMc Logarithm of the dust mass of the cold
component from the TMBB model
30- 33 F4.2 [Msun] e_logMc Error on logMc
35- 39 F5.2 K Tc Dust temperature of the cold component
from the TMBB model
41- 44 F4.2 K e_Tc Error on Tc
46- 49 F4.2 --- betac Emissivity index of the cold component
from the TMBB model (1)
51- 54 F4.2 --- e_betac Error on betac
56- 59 F4.2 [Msun] logMw Logarithm of the dust mass of the warm
component from the TMBB model
61- 64 F4.2 [Msun] e_logMw Error on logMw
66- 70 F5.2 K Tw Dust temperature of the warm component
from the TMBB model
72- 75 F4.2 K e_Tw Error on Tw
77- 81 F5.2 --- lnL Natural logarithm of the likelihood of the
TMBB model fit
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Note (1): The emissivity index of the warm component has been fixed to
βw=1.5
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Byte-by-byte Description of file: tablee4.dat
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Bytes Format Units Label Explanations
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1 I1 --- Nparam [2/3] Number of parameters considered for the
correlation analysis between β and
other properties
3- 6 F4.2 --- alogM* ? Multiplicative coefficient for logM* of the
best polynomial expression to estimate
β (1)
8- 11 F4.2 --- e_alogM* ? Error on alogM*
13- 17 F5.2 --- alogSFR ? Multiplicative coefficient for logSFR of
the best polynomial expression to estimate
β (1)
19- 22 F4.2 --- e_alogSFR ? Error on alogSFR
24- 28 F5.2 --- alogarea ? Multiplicative coefficient for logarea of
the best polynomial expression to estimate
β (1)
30- 33 F4.2 --- e_alogarea ? Error on alogarea
35- 38 F4.2 --- ametal ? Multiplicative coefficient for 12+log(O/H)
of the best polynomial expression to estimate
β (1)
40- 43 F4.2 --- e_ametal ? Error on ametal
45- 49 F5.2 --- alogMd ? Multiplicative coefficient for logMdust of
the best polynomial expression to estimate
β (1)
51- 54 F4.2 --- e_alogMd ? Error on alogMd
56- 60 F5.2 --- alogMHI ? Multiplicative coefficient for logMHI of the
best polynomial expression to estimate
β (1)
62- 65 F4.2 --- e_alogMHI ? Error on alogMHI
67- 72 F6.2 --- inter Intercept of the best polynomial expression to
estimate β (parameter b) (1)
74- 77 F4.2 --- e_inter Error on inter
79- 84 F6.2 --- BIC Bayesian Information Criterion
(Schwarz, 1978AnSta...6..461S 1978AnSta...6..461S) (G1)
86- 89 F4.2 --- R Pearson correlation coefficient
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Note (1): Coefficients aj of the best polynomial expression
β(x1,...,xk)=Σj=1kajlog(xj)+b, to estimate the
dust emissivity index β using combinations of two or three
galaxy properties
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Byte-by-byte Description of file: tablee5.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1 I1 --- Nparam [2/3] Number of parameters considered for the
correlation analysis between Tdust and other
properties
3- 7 F5.2 --- alogM* ? Multiplicative coefficient for logM* of the
best polynomial expression to estimate
Tdust (1)
9- 12 F4.2 --- e_alogM* ? Error on alogM*
14- 17 F4.2 --- alogSFR ? Multiplicative coefficient for logSFR of the
best polynomial expression to estimate
Tdust (1)
19- 22 F4.2 --- e_alogSFR ? Error on alogSFR
24- 28 F5.2 --- alogarea ? Multiplicative coefficient for logarea of
the best polynomial expression to estimate
Tdust (1)
30- 33 F4.2 --- e_alogarea ? Error on alogarea
35- 39 F5.2 --- ametal ? Multiplicative coefficient for 12+log(O/H)
of the best polynomial expression to estimate
Tdust (1)
41- 44 F4.2 --- e_ametal ? Error on ametal
46- 50 F5.2 --- alogMd ? Multiplicative coefficient for logMdust of
the best polynomial expression to estimate
Tdust (1)
52- 55 F4.2 --- e_alogMd ? Error on alogMd
57- 61 F5.2 --- alogMHI ? Multiplicative coefficient for logMHI of the
best polynomial expression to estimate
Tdust (1)
63- 66 F4.2 --- e_alogMHI ? Error on alogMHI
68- 72 F5.2 --- inter Intercept of the best polynomial expression to
estimate Tdust (parameter b) (1)
74- 77 F4.2 --- e_inter Error on inter
79- 85 F7.2 --- BIC Bayesian Information Criterion
(Schwarz, 1978AnSta...6..461S 1978AnSta...6..461S) (G1)
87- 90 F4.2 --- R Pearson correlation coefficient
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Note (1): Coefficients aj of the best polynomial expression
Tdust(x1,...,xk)=Σj=1kajlog(xj)+b, to estimate the
dust temperature using combinations of two or three galaxy properties
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Global Notes:
Note (G1): The Bayesian Information Criterion (Schwarz 1978AnSta...6..461S 1978AnSta...6..461S) is
defined as : BIC=-2ln(L)+qln(m), where L is the likelihood, q is the
number of free parameters of the model, and m is the number of data
points (wavebands)
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History:
From electronic version of the journal
References:
Saintonge et al., Paper I 2018MNRAS.481.3497S 2018MNRAS.481.3497S, Cat. J/MNRAS/481/3497
Smith et al., Paper II 2019MNRAS.486.4166S 2019MNRAS.486.4166S, Cat. J/MNRAS/486/4166
De Looze et al., Paper IV 2020MNRAS.496.3668D 2020MNRAS.496.3668D
(End) Ana Fiallos [CDS] 17-Jan-2023