Characterizing the Molecular Interstellar Medium in ... - Caltech

Characterizing the Molecular
Interstellar Medium in Galaxies using
Archival Herschel Data
Naseem Rangwala
University of Colorado - Boulder
NASA Ames Research Center
Main Collaborators: Jason Glenn (CU)
Julia Kamenetzky (CU)
Phil Maloney (CU)
This work is supported by a NASA ADAP grant

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Outline
Description of the program
Goals
Sample
Methodology/Pipeline
Preliminary Results (spectra, modeling results,
CO SLEDs etc.)
Conclusions

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Description of our Archival Program
Archival (publicly available) survey using photometric and
spectroscopic data of all the galaxies (~300) observed with Herschel-
SPIRE’s Fourier Transform Spectrometer (FTS).

Flux [Jy]
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•
50
40
30
20
10
CO (43)
CI (10)
CH
CH
CO (54)
CO (65)
HCN 87
HCO+ 87
H2O +
H2O +
H2O 211202
HCN 98
HCO+ 98
CO (76)
CI (21)
CH +
HCN 109
HCO+ 109
NH2 OH +
CO (87)
NH2 OH +
HCN 1110
NH
HCO+ 1110
H2O 202111
NH
OH +
CO (98)
HCN 1211
HCO+ 1211
H2O 312303
H2O 111000
H2O +
H2O +
HCN 1312
CO (109)
H2O 312221
HCO+ 1312
H2O 321312
H2O 422413
NH3 H2O 220211
HF
HCN 1413
HCO+ 1413
CO (1110)
HCN 1514
HCO+ 1514
CO (1211)
H2O 523514
HCN 1615
HCO+ 1615
NH2 NH2 NII
CH
CH
CO (1312)
HCN 1716
HCO+ 1716
0
670 µm
SPIRE-FTS spectrum of Arp 220
300 µm
600 800 1000
rest [GHz]
1200 1400
Continuous spectral coverage
spectral resolution = 1.44 GHz
•
•
Rangwala et al. (2011)
several molecular and atomic species
190 µm
CO rotational transitions from J = 4-3 to 13-12

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•
Description of our Archival Program
Archival (publicly available) survey using photometric and
spectroscopic data of all the galaxies (~300) observed with Herschel-
SPIRE’s Fourier Transform Spectrometer (FTS).
This sample spans a wide range in the far-infrared luminosity (L FIR)
and galaxy types.

N
SPIRE- FTS Archival Sample
80
60
40
20
Full Sample
with CO J = 76
LIRG
0
8 9 10 11
Log LFIR (Lsun) 12 13 14
•Ntot
~ 300 (AGN = 78, Ellipticals = 32)
•168/227
galaxies have CO J = 7-6 detection
•redshift
up to z = 0.2
ULIRG
HLIRG

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•
•
•
Description of our Archival Program
Archival (publicly available) survey using photometric and
spectroscopic data of all the galaxies (~300) observed with Herschel-
SPIRE’s Fourier Transform Spectrometer (FTS).
This sample span a wide range in the far-infrared luminosity (L FIR)
and galaxy types.
CO spectral line energy distributions (SLEDs) from these spectra
will be uniformly re-reduced, re-calibrated and modeled to estimate
the physical conditions and reservoir of the molecular gas
Application of consistent methodology for data reduction and
modeling across the entire sample will enable accurate comparison
between different galaxies

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Goals of the Program
Determine the molecular gas (and dust) properties as a function of
L FIR and galaxy type (starburst, AGN, disks and ellipticals)
Address the origin of the excitation of warm molecular gas of
varying L FIR: Star-Formation vs AGN?
Compare the gas excitation and dust properties of the local IR
luminous galaxies to high-z submm galaxies.
Explore *Total* L CO - L FIR Relation
Direct measurement of [CO/H 2] abundance for warm molecular
gas.
Substantial public database of legacy value for nearby galaxies

Normalized Luminosity
10 7
10 6
CO SLED: diagnostic for
Star Formation Vs AGN?
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
J upper
Mrk 231 (AGN)
Arp 220 (Starburst)
M82 (Starburst)
Mid- to High-J CO traces warm gas and dominates the CO luminosity and cooling

•
•
•
•
•
•
Goals of the Program
Determine the molecular gas (and dust) properties as a function of
L FIR and galaxy type (starburst, AGN, disks and ellipticals)
Address the origin of the excitation of warm molecular gas of
varying L FIR: Star-Formation Vs AGN?
Compare the gas excitation and dust properties of the local IR
luminous galaxies to high-z submm galaxies.
Explore *Total* L CO - L FIR Relation
Direct measurement of [CO/H 2] abundance for warm molecular
gas.
Substantial public database of legacy value for nearby galaxies

Herschel!
Archive!
Literature!
data!!
!
Pipeline Schematic
SPIRE!
Photometry!
and!
Spectrum!
Photometry!data:!!
10!–!850!µm!
Dust!SED!Modeling!
and!Likelihood!
analysis!
Probability!
Distributions:!!
Tdust,''τ,'&'β'
Dust:!
Temperature,!optical!
depth,!FIR!
luminosity!and!Mass!
Spectrum:!
Additional!
Reprocessing!for!
extended!sources!
Literature!
lowJJ!CO!
extinction correction
Line!Fitter!!
(Integrated!
Fluxes!in!Jy!
km/s!)!
CO!SLEDs!!
J!=!1J0!to!!
J!=!13J12!
Modeling!CO!and!
Likelihood!
analysis!
Probability!
Distributions:!T,#
n,#P,!NCO,$&$Mgas$
Molecular!Gas:!
Temperature!
Density!
Mass!
Luminosity!
Pipeline developed by
J. Kamenetzky
L CO /L FIR
CO#Excitation:
PDR,#cosmic
rays,#XDR,
Mechanical
energy

DATA

Flux (Jy)
600
400
200
0
CO (43)
CI (10)
CO (54)
CO (65)
M82 (Starburst)
CO (76)
CI (21)
CO (87)
CO (98)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0008]
This survey will focus only on CO, CI and NII lines. CO and CI for
characterizing molecular gas and NII as a star formation tracer
CO (109)
CO (1110)
CO (1211)
NII 205
CO (1312)
CO (1413)

Flux (Jy)
12
10
8
6
4
2
0
CO (43)
CI (10)
CO (54)
NGC 6240 (LIRG/AGN)
CO (65)
CO (76)
CI (21)
CO (87)
CO (98)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0243]
CO (109)
CO (1110)
CO (1211)
NII 205
CO (1312)
CO (1413)

Flux (Jy)
10
8
6
4
2
0
CO (43)
CI (10)
CO (54)
MRK 231 (ULIRG/AGN)
CO (65)
CO (76)
CI (21)
CO (87)
CO (98)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0418]
CO (109)
CO (1110)
CO (1211)
NII 205
CO (1312)
CO (1413)

UGC 05101
(LIRG/AGN)
Flux (Jy)
10
8
6
4
2
0
CO (43)
CI (10)
CO (54)
CO (65)
CO (76)
CI (21)
CO (87)
CO (98)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0393]
CO (109)
CO (1110)
CO (1211)
NII 205
CO (1312)
CO (1413)

Modeling and
Preliminary Results

ladder
FTS
Ground
JCMT
Z−spec
10 12 14
–47–
I (K km s −1 )
10 5
10 4
10 3
10 2
Non-LTE Radiative Transfer Modeling Arp
this work
ground−based
T = 1350 K, V = 350 km s −1
T = 50 K, V = 500 km s −1
0 5 10 15
J upper
cted luminosity distribution of the CO ladder from J = 1-0
of J = 10-9 line, which is blended withawaterline. The
urements and the blue triangles are average line fluxes from
lso shown for comparison are new measurements by Z-spec
del fit to the observed CO line temperatures. There are two
m component (dotted line) traced by the mid-J to high-J
hed line) traced by the low-J lines.
%$ #
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•
•
% #
10.0
Mid- to high-J CO are tracing warm
1.0
%#
deling of CO: Likelihood distributions for gas kinetic temand
pressure. The blue line represents the cold component
g low-J transitions and the red line represents the warm
from modeling the mid-J to high-J transitions.
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•
gas
low-J CO are tracing cold molecular
gas.
ARP220 − CO ladder
0 2 4 6 8 10 12 14
J upper
T kin(warm CO) = T kin(warm H 2)
M gas(warm) ~ 10% M gas(cold)
L
CO (cold) ~ 8% Total L CO
! $
L [x 10 6 L Sun]
0.1
FTS
Ground
JCMT
Z−spec
–47–
220
L [x 10 6 L Sun]
10.0
1.0
0.1
ARP220 − CO ladder
FTS
Ground
JCMT
Z−spec
0 2 4 6 8 10 12 14
J upper
–47–
I (K km s −1 )
10 5
10 4
10 3
10 2
this work
ground−based
T = 1350 K, V = 350 km s −1
T = 50 K, V = 500 km s −1
0 5 10 15
J upper
Fig. 5.— Left: Extinction corrected luminosity distribution of the CO ladder from J = 1-0
to J = 13-12 with the exception of J = 10-9 line, which is blended withawaterline. The
black solid circles are FTS measurements and the blue triangles are average line fluxes from
ground-based measurements. Also shown for comparison are new measurements by Z-spec
and JCMT. Right: Non-LTE model fit to the observed CO line temperatures. There are two
temperature components: a warm component (dotted line) traced by the mid-J to high-J
lines and a cold component (dashed line) traced by the low-J lines.
%&#" ' !" %%
! $
%$#
%#
%#
Fig. 6.— Radiative transfer modeling of CO: Likelihood distributions for gas kinetic temperature,
density, column density and pressure. The blue line represents the cold component
at 50 K obtained from modeling low-J transitions and the red line represents the warm
component at 1350 K obtained from modeling the mid-J to high-J transitions.
I (K km s −1 )
10 5
10 4
10 3
10 2
this work
ground−based
T = 1350 K, V = 350 km s −1
T = 50 K, V = 500 km s −1
0 5 10 15
J upper
Fig. 5.— Left: Extinction corrected luminosity distribution of the CO ladder from J = 1-0
to J = 13-12 with the exception of J = 10-9 line, which is blended withawaterline. The
black solid circles are FTS measurements and the blue triangles are average line fluxes from
ground-based measurements. Also shown for comparison are new measurements by Z-spec
and JCMT. Right: Non-LTE model fit to the observed CO line temperatures. There are two
temperature components: a warm component (dotted line) traced by the mid-J to high-J
lines and a cold component (dashed line) traced by the low-J lines.
%&#" ' !" %%
%$#
•Radiative(Transfer(code(maintained(by!Phil!Maloney
cooling rate = 22 L /M
%#
%#
Fig. 6.— Radiative transfer modeling of CO: Likelihood distributions for gas kinetic temperature,
density, column density and pressure. The blue line represents the cold component
at 50 K obtained from modeling low-J transitions and the red line represents the warm
component at 1350 K obtained from modeling the mid-J to high-J transitions.
Rangwala et al. (2011)

Arp 220: Excitation source of warm
molecular gas
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Observed ratio: Total L CO/L FIR ~ 10 -4
[T, n(H 2)] cold = [50 K, 1000 cm -3 ] and [T, n(H 2)] warm = [1350
K, 1000 cm -3 ]
This ratio along with tight constraints on T kin and n(H 2)
rules out PDRs, XDRs and Cosmic ray models
Require a non-ionizing source of energy: A small fraction
of mechanical energy from supernovae and stellar winds
can satisfy a cooling rate = 22 L /M
Similar method has been successfully applied in cases NGC 1068 (Spinoglio et
al. 2012; Hailey-Dunsheath et al. 2012), M82 (Kamenetzky et al. 2012), NGC
4038/39 (Schirm et al. in prep.) and Cloverleaf (Bradford et al. 2009)

3 4 5 6
Log 10 n(H 2) (cm 3 )
5 6 7 8
Log 10 Pressure (K cm 3 )
I CO (K km s 1 )
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
18 19 20 21 22 23
Log10 NCO (cm 2 0.0
)
10000
1000
2
Log10 N[H2] [cm ]
23 24 25 26 27 28
0 2 4 6 8 10 12 14
J upper
•
•
•
Cold
Warm
Total
Preliminary
NGC6240: CO Modeling
T kin(warm CO) ~ 1580 K
T kin(cold CO) ~ 50
0.2
0.2
cooling rate ~ 35 L/M 0.0 0.0
10 100 1000
Log10 Tkin (K)
Marginalized Likellihood
1.0
0.8
0.6
0.4
Cold
Warm
Marginalized Likellihood
1.0
0.8
0.6
0.4
2 3 4 5 6
Log 10 n(H 2) (cm 3 )
Marginalized Likellihood
Marginalized Likellihood
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
Cold
Warm
10 100 1000
Log 10 T kin (K)
0.0
1.0 0.8 0.6 0.4 0.2 0.0
Log10 ff
2
Log10 N[H2] [cm ]
23 24 25 26 27 28
18 19 20 21 22 23
Log10 NCO (cm 2 0.0
)
1.0 1.0 Cold
Marginalized Likellihood
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
0.0
2 3 4 5 6
Log 10 n(H 2) (cm 3 )
Marginalized Likellihood
1.0
0.8
0.6
3 4 5 6 7 8
Log 10 Pressure (K cm 3 )
Marginalized Likellihood
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
Cold
Warm
10 100 1000
Log 10 T kin (K)
0.0
1.0 0.8 0.6 0.4 0.2 0.0
Log10 ff
Marginalized Likellihood
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
I CO (K km s 1 )
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
2
Log10 N[H2] [cm ]
23 24 25 26 27 28
18 19 20 21 22 23
Log10 NCO (cm 2 0.0
)
10000
1000
2 3 4 5 6
Log10 n(H2) (cm 3 0.0
)
1.0
0.8
0.6
0.4
0.2
3 4 5 6 7 8
Log10 Pressure (K cm 3 0.0
)
Marginalized Likellihood
1.0
0.8
Cold
Warm
Total
0 2
0.6
4 6 8
Jupper 10 12 14
I CO (K km s 1 )
0.4
0.2
2
Log10 N[H2] [cm ]
23 24 25 26 27 28
18 19 20 21 22 23
Log10 NCO (cm 2 0.0
)
10000
1000
Cold
Warm
Total
0 2 4 6 8 10 12 14
J upper

3 4 5 6
Log 10 n(H 2) (cm 3 )
4 5 6 7 8
Log 10 Pressure (K cm 3 )
I CO (K km s 1 )
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
0.0
1000
100
10
•
•
•
2
Log10 N[H2] [cm ]
21.0 21.5 22.0 22.5 23.0 23.5
17.5 18.0 18.5 19.0 19.5 20.0
Log 10 N CO (cm 2 )
Cold
Warm
Total
0 2 4 6 8 10 12 14
J upper
Preliminary
M82: CO Modeling Results
T kin (warm CO) ~ 500 K = T kin (warm H 2 )
T kin(cold CO) ~ 35 K
cooling rate ~ 1.4 L /M
Marginalized Likellihood
ikellihood
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
Cold
Warm
10 100 1000
Log 10 T kin (K)
Marginalized Likellihood
ikellihood
1.0
0.8
0.6
0.4
0.2
Marginalized Likellihood
Marginalized Likellihood
2 3 4 5 6
Log10 n(H2) (cm 3 0.0
)
1.0
0.8
1.0
0.8
0.6
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
Cold
Warm
10 100 1000
Log 10 T kin (K)
0.0
3.0 2.5 2.0 1.5 1.0 0.5 0.0
Log10 ff
s 1 )
Marginalized Likellihood
1000
100
1.0
0.8
0.6
0.4
0.2
0.0
2
Log10 N[H2] [cm ]
21.0 21.5 22.0 22.5 23.0 23.5
17.5 18.0 18.5 19.0 19.5 20.0
Log 10 N CO (cm 2 )
Cold
Warm
Total
Marginalized Likellihood
Marginalized Likellihood
1.0
0.8
0.6
0.4
0.2
2 3 4 5 6
Log10 n(H2) (cm 3 0.0
)
1.0
0.8
0.6
0.4
0.2
0.0
0.8
0.8
3 4 5 6 7 8
Marginalized Likellihood
Log10 Pressure (K cm 3 )
0.6
Marginalized Likellihood
1.0
0.4
0.2
0.0
1.0
0.8
0.6
0.4
0.2
Cold
Warm
10 100 1000
Log 10 T kin (K)
0.0
3.0 2.5 2.0 1.5 1.0 0.5 0.0
Log10 ff
Marginalized Likellihood
Marginalized Likellihood
1.0
0.6
0.4
0.2
I CO (K km s 1 )
Marginalized Likellihood
1000
100
1.0
0.8
0.6
0.4
0.2
0.0
10
2 3 4 5 6
Log10 n(H2) (cm 3 0.0
)
1.0
0.8
0.6
0.4
0.2
3 4 5 6 7 8
Log10 Pressure (K cm 3 0.0
)
2
Log10 N[H2] [cm ]
21.0 21.5 22.0 22.5 23.0 23.5
17.5 18.0 18.5 19.0 19.5 20.0
Log 10 N CO (cm 2 )
Marginalized Likellihood
1.0
Cold
Warm
Total
0.8
0 2 4 6 8 10 12 14
Jupper 0.6
I CO (K km s 1 )
1000
100
0.4
0.2
0.0
10
2
Log10 N[H2] [cm ]
21.0 21.5 22.0 22.5 23.0 23.5
17.5 18.0 18.5 19.0 19.5 20.0
Log 10 N CO (cm 2 )
Cold
Warm
Total
0 2 4 6 8 10 12 14
J upper

CO SLEDs
Normalized Luminosity
10 7
10 6
0 115 230 345 461 576 691 806 922 1037 1152 1267 1382 1497 1611
Mrk 231 (AGN)
UGC05101 (AGN)
Arp 220 (ULIRG/starburst)
M82 (starburst)
NGC7552 (barred spiral)
Milky Way
Frequency (GHz)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Jupper Using a large sample we will establish if the shape and brightness of
the CO SLED in galaxies can be used as a diagnostic between dominant
sources of energy affecting their molecular ISM and star formation.

Dust Modeling
Arp220
NGC 6240
S( )= Nbb(1 e
0
e hc
kT 1
)(c/ ) 3
+ Npl ↵ e ( / c) 2

•
•
•
•
•
Conclusions
Molecular gas and dust survey of nearby galaxies using
Herschel-SPIRE.
Systematic re-processing and modeling; Pipeline is almost
complete.
Previous studies have shown that the high-J CO lines are tracing
the warm molecular ISM and dominate the CO luminosity and
hence the cooling.
Observed L CO/L FIR combined with physical properties of the
molecular gas will enable us to constrain the dominant power
source (AGN or SF (PDR, XDR, shocks etc. )) in these galaxies.
Investigate global properties of the molecular gas and dust as
function of L FIR and galaxy types.

Extra Slides

Arp 220: Excitation source of warm
molecular gas
•
•
•
!44B444
!4B444
!B444
4B!44
4B4!4
4B44!
Observed ratio: Total L CO/L FIR ~ 10 -4
This ratio along with tight constraints on T kin and n(H 2)
rules out PDRs, XDRs and Cosmic rays
Require a non-ionizing source of energy: Mechanical
energy from supernovae and stellar winds to satisfy a
cooling rate = 20 L /M
/E?@A/0)F7+/+ /12 /+F 3
, -./01/23/4 & 5
567/8 4
(a)
3456+,780
&!!!!
&
%
$
#
"
!
4
%1"
$12
$1"
"12
"1"
"12
$1"
9:+;& +;$ "=
9:+;2 &=
9:+;! 2=
9:+;? !=
9>+;% $=
9:+;# ?=
9:+;@ #=
!"" #"" $""" $%"" $&"" $!""
'()*+,-./0
5(678-9:;*'-,:88-?67
9:+;$$ $"=
9:+;$% $$=
A>>+; < B $ < B "=
9:+;$< $%=
UGC05101 - Two-Component Radiative Transfer Modeling
Model Fit
Temperature
PDR Models
567/9:0!" !!3;9:0% $3
%B4
ARP220
$B4
M82
#B4
-678
9:+3
;6

UGC 05101
(LIRG/AGN)
Flux [Jy]
3456+,780
10
8
6
4
2
0
%1"
$12
$1"
"12
"1"
"12
$1"
(a)
9:+;&+;$"=
(b)
Flux (Jy)
10
8
6
4
2
0
9:+;2&=
CO (43)
CI (10)
CO (54)
9:+;!2=
CO (65)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0393]
Herschel SPIRE-FTS Spectrum of UGC05101
600 800 1000 1200 1400 1600
rest [GHz]
9:+;?!=
9>+;%$=
CO (76)
CI (21)
9:+;#?=
CO (87)
9:+;@#=
CO (98)
!"" #"" $""" $%"" $&"" $!""
'()*+,-./0
CO (109)
9:+;$"@=
CO (1110)
9:+;$$$"=
CO (1211)
9:+;$%$$=
NII 205
CO (1312)
A>>+; < B $ < B "=
9:+;$

Normalized Luminosity
10 7
10 6
CO SLED: diagnostic for
Star Formation Vs AGN?
Mrk 231 (AGN)
Arp 220 (Starburst)
M82 (Starburst)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Using a large sample Jupper we will establish if the
shape and brightness of the CO SLED in
galaxies can be used as a diagnostic between
dominant sources of energy affecting their
molecular ISM and star formation.
•
•
•
Models have suggested that
the shape of the CO SLEDs can
be used to discriminate
between SF and AGN [e.g. Spaans
& Meijerink (2008); Lagos et al. (2012)].
Observations:
Starburst - CO SLEDs turn
over after J = 6-5 e.g.
Arp220 [Rangwala et al. (2011)] and
M82 [Panuzzo, Rangwala et al. (2010);
Kamenetzky et al. 2012 (incl. N. Rangwala)].
Similar turn over observed in
high-z submm galaxies [Bothwell
et al. (2013)].
AGN: CO SLED remains flat
after J = 6-5 [e.g.,Van der werf et al.
(2010)]

L CO (65) (L sun)
10 10
10 9
10 8
10 7
10 6
10 5
10 4
cena
10 10
LCO - LFIR relation
NGC1365NE
NGC1365SW
ngc1068
ngc1266
NGC253 m82 ngc4038overlap
NGC1222 ngc4038
m83
10 11
Mrk273
arp220
UGC05101
Mrk231
NGC6240
IRAS090223615
IRASF172070014
Arp299A
Arp299B Arp299C
L FIR (L sun)
10 12
SMMJ2135
10 13
HLSW01
Riechers
GN20
Cloverleaf
APM08279
10 14

log 10 L CO (65) (K km s 1 pc 2 )
12
11
10
9
8
7
6
cena
L CO - L FIR relation
SMMJ2135
Mrk273
arp220
UGC05101
NGC1365NE
NGC1365SW
ngc1068
m82 ngc4038overlap
m83 ngc4038
Mrk231
NGC6240
IRAS090223615
IRASF172070014
Arp299A
Arp299B Arp299C
ngc1266
NGC253
NGC1222
HLSW01 Cloverleaf
Riechers
GN20
APM08279 MM18423
5
9 10 11 12
log10 LFIR (Lsun) 13 14 15

3060 M. S. Bothwell et al.
4.3 The L ′ CO –LFIR correlation
A useful quantity to measure for our sample of SMGs is the efficiency
with which their molecular gas is being converted into stars.
The SFE is sometimes defined as SFR/M(H2) – the inverse of the gas
depletion time – but here we take the approach of parameterizing
this as a ratio of observable quantities: LFIR and L ′ CO(1−0) .
There has been debate, in recent years, as to the value of the
slope of the L ′ CO(1−0) − LFIR relation. Whereas, earlier we discussed
the difference in slopes between the various transitions observed
(in order to derive the median SLED), here we present the relation
between the derived 12CO J = 1–0 luminosity and LFIR – a relation
which describes, in observable terms, the relationship between the
luminosity due to star formation and the total gas content. (Section
2.1.1 contains a discussion of the uncertainties inherent to deriving
IR luminosities for sources such as ours.)
In their study of 12 SMGs, Greve et al. (2005) found a slope of
the relation between LFIR and L ′ CO(1−0) of 0.62 ± 0.08 fit a combined
sample of lower redshift LIRGs, ULIRGs and SMGs – identical to
the slope derived for the local LIRGs/ULIRGs alone. The small
number of galaxies in Greve et al. (2005), however, prevented a full
investigation of the SFE slopes within the SMG population itself.
Some recent authors, however, have found the slope to be closer to
linear – Genzel et al. (2010) found that a slope of 0.87 ± 0.09 fits a
combined sample of SMGs across a wide range of redshifts.
Fig. 6 shows the L ′ CO−LFIR relation for our sample of SMGs.
Included in the plot are data points for local (U)LIRGs, as measured
by Sanders, Scoville & Soifer (1991) and Solomon et al.
(1997). We also show three power-law fits to the local (U)LIRGs
alone, the SMGs alone and the combined sample. We find the
SMGs to lie slightly above the best-fitting (sub-linear) line for local
(U)LIRGs, necessitating a steeper slope. The power-law fit to the
local (U)LIRGs alone has a slope of 0.79 ± 0.08, while the fit to
the combined sample of SMGs and (U)LIRGs has a slope of 0.83 ±
0.09. It can also be seen that a fit to the SMG sample alone has
an even steeper slope of 0.93 ± 0.14 – very close to linear – although,
within the uncertainty, this is consistent with the slope for
the combined samples. These results are in good agreement with
Figure 6. The SFE, L ′ CO versus LFIR. Included in the plot are two samples
of local ULIRGs, and the J = (1–0) SMG observations of Ivison et al.
(2011). Best-fitting slopes to the SMGs alone, the local ULIRGs alone and
all three combined samples are overplotted. They have slopes of 0.93 ±
0.14, 0.79 ± 0.08 and 0.83 ± 0.09, respectively.
L CO - L FIR relation
most previous findings; the near-linear slopes (which agree well
with those found by Genzel et al. 2010) would imply a roughly
constant gas depletion time-scale across the entire range of far-IR
luminosities shown here.
However, we caution that our analysis requires extrapolating from
high-Jup 12 CO transitions to 12 CO (1–0). Ivison et al. (2010) have
undertaken a similar analysis based solely on directly observed
12 CO (1–0) observations and homogeneously derived far-IR lumi-
nosities and conclude that the L ′ CO(1−0) −LFIR relation has a slope
substantially below unity. We therefore suggest that it is difficult to
draw any strong conclusions from high-Jup observations about the
gas depletion time-scales of the different populations or the form of
the Kennicutt–Schmidt relation in these galaxies, as these are too
uncertain without brightness temperature ratio measurements for
individual sources.
4.4 Molecular gas masses
Part of the power of observations of 12CO emission from highredshift
galaxies is that they provide a tool to derive the mass of
the reservoir of molecular gas in these systems. This is of critical
importance because this reservoir is the raw material from which
the future stellar mass in these systems is formed. Along with the
existing stellar population, it therefore gives some indication of
the potential stellar mass of the resulting galaxy at the end of the
starburst phase (subject, of course, to the unknown contribution
from in-falling and out-flowing material).
Estimating the mass of H2 from the measured L ′ CO requires two
steps. First, luminosities originating from higher transitions (Jup ≥
2) must be transformed to an equivalent 12CO J = 1–0 luminosity,
using a brightness ratio. We have derived the necessary brightness
ratios using our composite SLED as discussed in Section 3 above.
Once an L ′ CO(1−0) has been determined, it must be converted into
an H2 mass by adopting a conversion factor α: M(H2) = αL ′ CO ,
where α is in units of M⊙ (K km s−1 pc2 ) −1 (when discussing α
hereafter, we omit these units for the sake of brevity). This can then
be converted to a total gas mass, including He, Mgas = 1.36 M(H2).
There is a large body of work, both observational and theoretical,
dedicated to determining the value – and ascertaining the metallicity
or environmental dependence – of α (e.g. Young & Scoville
1991; Solomon & Vanden Bout 2005; Liszt, Pety & Lucas 2010;
Bolatto et al. 2011; Genzel et al. 2012; Narayanan et al. 2011; Papadopoulos
et al. 2012). While secular discs such as the Milky Way
have a relatively ‘high’ value of α ∼ 3–5, using this value for the
gas in nuclear discs/rings within merging systems and starbursts at
z ∼ 0 leads to the molecular gas mass sometimes exceeding their
dynamical masses. As such, a lower value – motivated by a radiative
transfer model of the 12CO kinematics – is typically used
for the intense nuclear starbursts in the most IR-luminous local
systems: α ∼ 0.8, with a range of 0.3–1.3 (Downes & Solomon
1998). However, some recent results have suggested that this value
might, in fact, underestimate the true value in high-redshift SMGs.
Bothwell et al. (2010) found that applying the canonical ULIRG
value to two z ∼ 2 SMGs resulted in gas fractions of

Flux (Jy)
•
•
50
40
30
20
10
0
670 µm
CO (43)
CI (10)
SPIRE-FTS spectrum of Arp 220
CO (54)
CO (65)
CO (76)
CI (21)
CO (87)
CO (98)
600 800 1000 1200 1400 1600
rest (GHz) [used z = 0.0181]
Continuous spectral coverage
spectral resolution = 1.44 GHz
•
•
CO (109)
300 µm
CO (1110)
CO (1211)
NII 205
CO (1312)
CO (1413)
190 µm
several molecular and atomic species
CO rotational transitions from J = 4-3 to 13-12