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arXiv:1509.07512v2 [astro-ph.GA] 8 Dec 2016
Accepted for publication in ApJ.
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EXCITATION MECHANISMS FOR HCN (1–0) AND HCO+(1–0) IN GALAXIES FROM THE GREAT
OBSERVATORIES ALL-SKY LIRG SURVEY1
G. C. Privon2,3. 4, R. Herrero-Illana5, A. S. Evans2,6, K. Iwasawa7, M. A. Perez-Torres5, L. Armus8, T.
D
´
ıaz-Santos8,9 , E. J. Murphy10, S. Stierwalt2, S. Aalto11, J. M. Mazzarella10 , L. Barcos-Mu˜
noz2, H. J. Borish2,
H. Inami13, D.-C. Kim6, E. Treister3, J. A. Surace8, S. Lord14, J. Conway11, D. T. Frayer12, and A. Alberdi5
Accepted for publication in ApJ.
ABSTRACT
We present new IRAM 30m spectroscopic observations of the ∼88 GHz band, including emission
from the CCH (N = 1 →0) multiplet, HCN (J = 1 →0), HCO+(J = 1 →0), and HNC (J = 1 →0),
for a sample of 58 local luminous and ultraluminous infrared galaxies from the Great Observato-
ries All-sky LIRG Survey (GOALS). By combining our new IRAM data with literature data and
Spitzer/IRS spectroscopy, we study the correspondence between these putative tracers of dense gas
and the relative contribution of active galactic nuclei (AGN) and star formation to the mid-infrared
luminosity of each system. We find the HCN (1–0) emission to be enhanced in AGN-dominated sys-
tems (hL′
HCN (1–0)/L′
HCO+(1–0) i= 1.84), compared to composite and starburst-dominated systems
(hL′
HCN (1–0)/L′
HCO+(1–0) i= 1.14, and 0.88, respectively). However, some composite and starburst
systems have L′
HCN (1–0)/L′
HCO+(1–0) ratios comparable to those of AGN, indicating that enhanced
HCN emission is not uniquely associated with energetically dominant AGN. After removing AGN-
dominated systems from the sample, we find a linear relationship (within the uncertainties) between
log10(L′
HCN (1–0)) and log10 (LIR), consistent with most previous findings. L′
HCN (1–0)/LIR , typically in-
terpreted as the dense gas depletion time, appears to have no systematic trend with LIR for our sample
of luminous and ultraluminous infrared galaxies, and has significant scatter. The galaxy-integrated
HCN (1–0) and HCO+(1–0) emission do not appear to have a simple interpretation, in terms of the
AGN dominance or the star formation rate, and are likely determined by multiple processes, including
density and radiative effects.
Subject headings: galaxies: ISM — galaxies: starburst — galaxies: active
1. INTRODUCTION
gprivon@astro-udec.cl
1Based on observations carried out with the IRAM 30m Tele-
scope. IRAM is supported by INSU/CNRS (France), MPG (Ger-
many) and IGN (Spain).
2Department of Astronomy, University of Virginia, Char-
lottesville, VA, USA
3Departamento de Astronom´ıa, Universidad de Concepci´on,
Concepci´on, Chile
4Visiting Graduate Student Research Fellow (2013), NASA
Infrared Processing and Analysis Center, California Institute of
Technology, Pasadena, CA, USA
5Instituto de Astrof´ısica de Andaluc´ıaa-CSIC, Glorieta de la
Astronom´ıa s/n, 18008, Granada, Spain
6National Radio Astronomy Observatory, Charlottesville, VA,
USA
7ICREA and Institut de Ci`encies del Cosmos (ICC), Uni-
versitat de Barcelona (IEEC-UB), Mart´ı i Franqu`es 1, 08028,
Barcelona, Spain
8Spitzer Science Center, California Institute of Technology,
Pasadena, CA, USA
9Universidad Diego Portales, Chile
10 Infrared Processing and Analysis Center, California Insti-
tute of Technology, Pasadena, CA, USA
11 Chalmers University of Technology, Department of Earth
and Space Sciences, Onsala Space Observatory, 43992 Onsala,
Sweden
12 National Radio Astronomy Observatory, Green Bank, WV,
USA
13 National Optical Astronomy Observatory, 950 North
Cherry Avenue, Tucson, AZ 85719, USA
14 The SETI Institute, 189 Bernardo Ave, Suite 100, Mountain
View, CA 94043, USA
Molecular gas is observationally linked to ongoing star
formation through observed correlations between the star
formation rate surface density and the H2surface den-
sity as inferred from CO observations (e.g., Bigiel et al.
2008;Leroy et al. 2012). CO (1–0) has a relatively low
critical density (ncrit ≈2×103cm−3) and so traces the
bulk of the molecular gas. Molecular transitions such
as HCN (1–0) and HCO+(1–0) have critical densities
ncrit ≈3×106cm−3and 2 ×105cm−3, respectively,
at 30 K, and so they are associated with higher density
molecular hydrogen. Early studies found a linear corre-
lation between HCN (1–0) and the infrared luminosity—
LIR[8 −1000 µm]—of galaxies (Solomon et al. 1992;Gao
& Solomon 2004b). This relation, which is tighter than
that for CO (1–0) with LIR, was interpreted as evidence
that HCN (1–0) traces the dense gas directly associ-
ated with star formation. Revisiting the relationship
between SFR and this molecular tracer, Garc´ıa-Burillo
et al. (2012) find LFIR to be a super-linear function of
HCN (1–0), suggesting that there are other physical fac-
tors that are important for the HCN emission.
Calling into question the use of HCN (1–0) as a tracer
of dense gas, several studies of systems hosting active
galactic nuclei (AGN) have found integrated (Graci´a-
Carpio et al. 2006;Krips et al. 2008) and spatially-
resolved enhancements (Kohno et al. 2003;Imanishi et al.
2006,2007,2009;Davies et al. 2012) of HCN (1–0) emis-
sion compared to what is observed in starburst galaxies.
Similar results have been found for HCN (4–3) (Iman-
2 Privon et al.
ishi & Nakanishi 2013,2014). These results suggest that
HCN emission is enhanced in the presence of AGN, po-
tentially invalidating the use of HCN as a tracer of the
dense molecular gas associated with ongoing star forma-
tion, particularly in systems with AGN. However it is
notable that some systems with a known AGN do not
show this enhanced ratio (ARP 299, Imanishi & Nakan-
ishi 2006; I Zw 1, Evans et al. 2006), suggesting the
HCN (1–0) emission enhancement observed in some AGN
hosts may have a more nuanced interpretation.
Modeling by various authors suggests the HCN and
HCO+emission are affected by density, radiative, and
abundance/ionization effects which potentially compli-
cates interpretation of the line ratios in both photon
dominated and X-ray dominated regions (PDR and
XDR, respectively; e.g., Aalto et al. 1994,1995;Huet-
temeister et al. 1995;Lepp & Dalgarno 1996;Meijerink
et al. 2007). The possible influence of the XDR on molec-
ular abundances has been used to argue that elevated
HCN (1–0) is a signpost of an AGN, however Juneau
et al. (2009) and Costagliola et al. (2011) argue the exci-
tation of HCN and HCO+is not solely driven by abun-
dance and so this ratio may not solely trace XDRs. The
relative influence of the other effects (infrared pumping,
source compactness) has not been fully established.
In order to investigate the relation between the pres-
ence and strength of an AGN, and the HCN and HCO+
emission in a large sample of gas-rich galaxies, we have
observed 58 luminous and ultraluminous infrared galax-
ies ((U)LIRGs; LIR >1011 L⊙), selected from the Great
Observatories All-sky LIRG Survey (GOALS; Armus
et al. 2009), with the Institut de Radioastronomie Mil-
lim´etrique (IRAM) 30m Eight Mixer Receiver (EMIR;
Carter et al. 2012). These new observations (Section 2)
of the molecular rotational transitions, HCN (1–0) and
HCO+(1–0), are used in combination with calibrated
AGN strengths determined from Spitzer/IRS (Houck
et al. 2004) spectroscopy of the GOALS sample (Stier-
walt et al. 2013;Inami et al. 2013) to assess the cor-
relation of AGN strength with the global HCN (1–0)
and HCO+(1–0) emission (Section 3). We then dis-
cuss the possible explanations for enhanced HCN (1–0)
(Section 4). Finally, we explore the utility of HCN (1–
0) and HCO+(1–0) as tracers of the mass of dense gas
associated with star formation (Section 5).
The power of this study comes from the increased sam-
ple size of (U)LIRGs with measurements of these lines
and, particularly, from the large number of sources with
measured mid-infrared diagnostic of the relative contri-
butions of AGN and star formation to the infrared lumi-
nosity of each system (a factor of 4 increase over Costagli-
ola et al. 2011). The use of the mid-infrared diagnos-
tics facilitates a good estimation of the importance of
an AGN to the mid-infrared emission (i.e., as opposed
to simply using rudimentary optical “AGN” and “star-
burst” diagnostics to classify systems). This enables a
direct investigation of the global L′
HCN (1–0)/L′
HCO+(1–0)
line ratio (hereafter, HCN/HCO+) as a function of the
contribution of the AGN to the bolometric luminosity.
Throughout the paper we adopt a WMAP-5 cosmol-
ogy (Hinshaw et al. 2009, H0= 70 km s−1Mpc−1,
Ωvacuum = 0.72, Ωmatter = 0.28), with velocities cor-
rected for the 3-attractor model of Mould et al. (2000).
2. SAMPLE, OBSERVATIONS, AND DATA
2.1. GOALS
As noted, the data presented here were obtained as
part of a millimeter survey of (U)LIRGs selected from
GOALS. The GOALS sample as a whole consists of all
the (U)LIRGs from the Revised Bright Galaxy Sample
(RBGS; i.e., 60 µm flux density greater than 5.24 Jy
and LIR >1011 L⊙;Sanders et al. 2003). GOALS15 is
a multi-wavelength survey aimed at understanding the
physical conditions and activity in the most luminous
galaxies in the local Universe. The dataset includes spec-
troscopic and imaging observations in the infrared from
Spitzer (Petric et al. 2011;Inami et al. 2013;Stierwalt
et al. 2013, J. M. Mazzarella et al. in prep) and Herschel
(Diaz-Santos et al. 2013,2014;Lu et al. 2014), GALEX
and HST UV, optical, and near-infrared imaging (How-
ell et al. 2010;Haan et al. 2011;Kim et al. 2013, A.
S. Evans et al. in prep), Chandra X-ray observations
(Iwasawa et al. 2011), and a suite of ground-based radio
and sub-millimeter observations (e.g., Leroy et al. 2011;
Barcos-Mu˜noz et al. 2015, Herrero-Illana et al. in prep).
These observations collectively trace the obscured and
unobscured activity and constrain the structural proper-
ties and merger stages of these systems.
The objects in this study were selected from two por-
tions of GOALS; a high-luminosity sample (LIR ≥1011.4
L⊙) to capture the most extreme star forming systems,
and a sample of LIRGs with LIR ≤1011.4L⊙which were
selected to be isolated or non-interacting, on the basis
of their stellar morphology (Stierwalt et al. 2013). The
combination of these subsets of GOALS ensures this sam-
ple spans the range of LIR and merger stage within the
GOALS sample as a whole.
2.2. Observations and Data Reduction
The IRAM 30m Telescope was used with the EMIR
receiver to observe an 8 GHz instantaneous bandwidth,
tuned to simultaneously capture HCN (J = 1 →0),
HCO+(J = 1 →0), the CCH (N = 1 →0) multiplet, and
HNC (J = 1 →0), thus reducing systematic uncertain-
ties when comparing the fluxes of these lines. The rest
frequencies16 for these transitions are: νrest(HCN (1–0))
= 88.631 GHz, νr est(HCO+(1–0)) = 89.189 GHz, and
νrest(HNC (1–0)) = 90.663 GHz. For CCH, we adopt a
rest frequency which is the simple arithmetic mean of the
individual multiplet frequencies, νrest (CCH) = 87.370
GHz. The beam FWHM for these measurements is
∼28”, corresponding to a linear size of 16.8 kpc at the
mean redshift of our sample – thus we obtain galaxy-
integrated measurements. Observations were done in
wobbler switching mode (∼1′throw, 0.8 s switching) to
improve the baseline calibration. In Table 1we list the
pointing coordinates, assumed redshift, observing year &
month, integration times, system temperatures, and the
backend used, for each source.
Some of our observations use the FTS backend, which
consists of 24 individual fourier transform spectrometer
units. In some scans, the FTS units exhibited gain vari-
ations, resulting in offsets of the baselines for individual
15 http://goals.ipac.caltech.edu
16 obtained from the Splatalogue database:
http://splatalogue.net
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 3
units. For those scans, linear fits were made to the base-
line of each unit (masking out the expected locations of
spectral lines), and the units were corrected to a common
baseline. Scans were combined and exported using the
GILDAS/CLASS software17. Further analysis, includ-
ing a linear baseline subtraction, smoothing, and flux
measurement, was done using the pyspeckit software18
(Ginsburg & Mirocha 2011). The typical velocity reso-
lution of these smoothed data is 60 MHz, corresponding
to roughly 215 km s−1. In Figure 1we show the reduced
spectra for all sources, with the expected positions of the
CCH, HCN (1–0), HCO+(1–0), and HNC (1–0) lines
marked. Lines were identified visually based on cata-
loged optical redshifts and total fluxes were determined
by integrating under the line. IRAS F16164-0746 had
spectra which were clearly shifted from the location ex-
pected based on the cataloged redshift. We measured a
new redshift of 0.0229 for IRAS F16164-0746 compared
to the value from NED, 0.0272.
We determined uncertainties in the fluxes by calcu-
lating the RMS, σch, per channel of width dv, in the
line-free regions of the spectrum and multiplying by the
square root of the number of channels, Nch covered by
each line. We considered a line a detection if the mea-
sured flux exceeded 3σchdv√Nch. For non-detections we
calculated a 3σupper limit by assuming a square line
profile with a width half that of the detected HCN (1–
0) or HCO+(1–0) line, or 200 km s−1if no lines were
detected for that source.
For IRAM 30m observations, temperatures are re-
ported on the T∗
Ascale; these values were converted to
a main beam temperature, Tmb =T∗
A/(Beff /Feff ) us-
ing the main beam efficiency, Beff = 0.81, and a for-
ward efficiency, Fef f = 0.95, both measured by IRAM
staff on 26 August 201319 . We use a Jy/K conversion of
3.906(Fef f /Aeff ) = 6.185, where Aeff = 0.6, to convert
the reported T∗
Avalues to flux densities. Line luminosi-
ties were computed according to Solomon et al. (1992,
their Equation 3), in units of K km s−1pc2.
As noted, the wide EMIR bandwidth enables simul-
taneous measurements of HCN (1–0), HCO+(1–0),
HNC (1–0), and CCH. We had a detection rate of 78%,
76%, 35%, and 37%, for HCN (1–0), HCO+(1–0),
HNC (1–0), and CCH, respectively. For detected lines
the signal-to-noise weighted mean HNC (1–0)/HCN (1–
0) and CCH/HCN (1–0) ratios are 0.5±0.3 and 0.8±0.3,
respectively. One source, NGC 6285 has detected CCH
emission and no detection of HCN (1–0) or HCO+(1–0);
the CCH detection is ∼3.8σand, if confirmed, would be
an interesting and rare example of a source with CCH
brighter than HCN or HCO+. Such elevated CCH emis-
sion may indicate an overabundance of CCH or a lack of
dense molecular gas (Mart´ın et al. 2014). The HCN (1–
0)/HCO+(1–0) ratio is discussed in more detail in Sec-
tion 3. Integrated fluxes (or 3σupper limits) are pro-
vided for all lines, in Table 2, but we limit the analysis
here to the HCN (1–0) and HCO+(1–0) lines. Upper
and lower limits in Figures use these 3σlimits. CO (1–
0) observations were also obtained as part of this pro-
gram; these will be presented in R. Herrero-Illana et al.
17 http://www.iram.fr/IRAMFR/GILDAS
18 http://pyspeckit.bitbucket.org
19 http://www.iram.es/IRAMES/mainWiki/Iram30mEfficiencies
(in prep).
In order to explore the influence of AGN on the
HCN (1–0) and HCO+(1–0) emission, we use the equiv-
alent width (EQW) of the 6.2 µm polycyclic aromatic
hydrocarbon (PAH) measured from Spitzer/IRS low-
resolution observations (Stierwalt et al. 2013). The EQW
of the 6.2µm PAH feature compares the strength of
the PAH emission associated with star formation with
the strength of the mid-infrared continuum (e.g., Genzel
et al. 1998;Armus et al. 2004,2007). The AGN is en-
ergetically more important in systems with lower values
of the PAH EQW. Points in Figures 2–7are color-coded
by their 6.2µm PAH EQW, to show the relationship
between AGN and starburst dominated systems.
In addition to our new measurements, we incorporate
observations from Graci´a-Carpio et al. (2006), Costagli-
ola et al. (2011), and Garc´ıa-Burillo et al. (2012) in our
analysis. The combination of these three samples in-
cludes 63 individual galaxies with measured 6.2µm PAH
EQWs and detections in at least one of HCN (1–0) or
HCO+(1–0), comprising roughly 25% of the objects in
the GOALS sample.
We use LIR measurements from IRAS observations
(Armus et al. 2009). For galaxies in pairs, we assign
a portion of LIR to each component based on their 70
or 24 µm flux ratio, as described by Diaz-Santos et al.
(2013). Measurements of the [C ii] 158 µm line are taken
from Diaz-Santos et al. (2013).
2.2.1. Comparison with Previous Measurements
Several of the sources observed by us have pre-existing
published fluxes in the literature (e.g., Gao & Solomon
2004a;Graci´a-Carpio et al. 2006;Garc´ıa-Burillo et al.
2012). We compared our fluxes with those previous ef-
forts and found good agreement for some sources (e.g.,
ARP 220, VV 114, NGC 0034, IRAS 15107+0724, IRAS
23365+3604), but we measure fluxes for some individual
sources (NGC 2623, NGC 6701, UGC 5101, and NGC
7591) which are factors of 2 −3 higher than those previ-
ously published. There appears to be no trend of these
high fluxes with observing date or observing setup. De-
spite some differences in fluxes for some sources, we find
the HCN/HCO+ratios for those sources are in good
agreement with previously published ratios.
2.3. Distance and Aperture Effects
2.3.1. Source Distance Effects
The 28′′ IRAM 30m beam FWHM covers linear scales
of 6.1−46 kpc for these sources. Thus, these single-dish
observations average together emission from many giant
molecular clouds (GMCs) within each system, likely with
varying physical conditions and environments. This fac-
tor of ∼8 in distance leads to possible concerns about the
effects of beam size on the results, particularly if there
are systematic variations in the GMC properties or en-
vironments as a function of distance from the nuclei.
Previous interferometric observations with ∼5′′ reso-
lution have found the HCN (1–0) and HCO+(1–0) emis-
sion to be unresolved in ULIRGs (Imanishi et al. 2007,
2009). For the sources from their study that overlap
with our sample, we find general agreement between the
fluxes, suggesting the amount of extended flux is mini-
mal and the HCN and HCO+emission is confined to a
4 Privon et al.
84 86 88 90
−1
0
1
2
T∗
A[mK]
NGC 0034
HCN
HCO+
HNC
CCH
84 86 88
0
1
2MCG –02-01-052
84 86 88
0
1
MCG –02-01-051
84 86 88 90
0
2
4
6
8
T∗
A[mK]
IC 1623
80 82 84 86 88
0
1
2MCG –03-04-014
82 84 86 88
0
1
IRAS 01364-1042
84 86 88
0
1
T∗
A[mK]
IC 214
84 86 88 90 92
−1
0
1
2NGC 0958
82 84 86 88 90
−1.0
−0.5
0.0
0.5
1.0ESO 550-IG 025
84 86 88 90 92
0
1
T∗
A[mK]
UGC 03094
84 86 88 90 92
0
1
2
NGC 1797
80 82 84 86 88
−1
0
1
2
3VII Zw 031
80 82 84 86 88
0
1
2
T∗
A[mK]
IRAS F05189-2524
82 84 86 88
0
1
2
IRAS F05187-1017
82 84 86 88 90
−1
0
1
2
IRAS F06076-2139
84 86 88 90 92
νobs [GHz]
−0.5
0.0
0.5
1.0
T∗
A[mK]
NGC 2341
84 86 88 90 92
νobs [GHz]
0
1
NGC 2342
78 80 82 84 86
νobs [GHz]
−0.5
0.0
0.5
1.0IRAS 07251-0248
Figure 1. IRAM 30m EMIR spectra of the systems observed as part of this program, sorted by Right Ascension. In all panels we plot the
observed T∗
Aas a function of the observed frequency. The typical velocity resolution of these smoothed data is 60 MHz, corresponding to
roughly 215 km s−1. Dashed vertical lines mark (from left to right) the expected locations of CCH, HCN (1–0), HCO+(1–0), and HNC (1–
0), based on optical redshifts from NED, except for IRAS F16164-0746, where we have used our new measured redshift. Information on
the observing parameters are provided in Table 1. Integrated fluxes (or upper limits) for each line are given in Table 2.This figure is
continued at the end of the manuscript, in the Figures currently labeled 8–10.
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 5
0 50 100 150 200 250 300 350 400
DL[Mpc]
0.0
0.5
1.0
1.5
2.0
2.5
3.0
L′
HC N /L′
HC O+
This work
Gracia-Carpio+ 2006
Costagliola+ 2011
Garcia-Burillo+ 2012
0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
Figure 2. Ratio of the L′
HCN (1–0) and L′
HCO+(1–0) luminosities
versus luminosity distance. The lack of a significant correlation
suggests our results are not being affected by the distances to each
system. Points are color-coded by the 6.2µm PAH EQW.
region smaller than the 28′′ beam of these IRAM 30m
observations.
In Figure 2we compare the HCN/HCO+ratio with the
luminosity distance; there is no obvious trend with dis-
tance, suggesting that the pro jected beam size is not the
dominant factor in determining the HCN/HCO+ratio in
our sample.
2.3.2. Spitzer vs IRAM 30m Telescope Aperture Comparison
The 6.2µm PAH EQW used to assess the relative dom-
inance of the AGN in the mid-infrared was measured
from a 3.6′′ aperture (Stierwalt et al. 2013). Thus, these
measurements are upper limits to the large-scale influ-
ence of the AGN, and we expect any systematic effect
of this aperture difference between the mid-infrared and
millimeter observations would serve to overestimate the
importance of the AGN.
In other words, we would expect any signature of AGN-
dominated gas to be diluted with increasing source dis-
tance. As will we shown (Section 3), the excitation
of these molecular transitions does not appear to be
solely a function of the AGN strength, thus we con-
clude our results are not being significantly biased by
the mis-match in aperture between the millimeter and
mid-infrared datasets.
3. ENHANCED GLOBAL HCN (1–0) EMISSION DOES NOT
UNIQUELY TRACE AGN ACTIVITY
Some of the initial claims that HCN (1–0) is
enhanced in AGN were supported by plotting the
L′
HCN (1–0)/L′
CO (1–0) and L′
HCO+(1–0)/L′
CO (1–0) ratios as
a function of LIR. In Figure 3we show the HCN (1–
0)/HCO+(1–0) ratio as a function of LIR20 , to compare
20 Here we do not compare with CO (1–0) as this would po-
tentially include molecular gas which is not physically associated
with the regions emitting in HCN (1–0) and HCO+(1–0). For this
study, we rely on the HCN/HCO+ratio alone, to avoid concerns
with mis-matched apertures between the CO (1–0) measurements
1011 1012 1013
LIR [L⊙]
0.0
0.5
1.0
1.5
2.0
2.5
3.0
L′HC N /L′HC O+
This work
Gracia-Carpio+ 2006
Costagliola+ 2011
Garcia-Burillo+ 2012
0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
Figure 3. Ratio of L′
HCN (1–0) to L′
HCO+(1–0) luminosities ver-
sus the total infrared luminosity. Points are color-coded by the
6.2µm PAH EQW.
we previous work. As in previous studies (e.g., Graci´a-
Carpio et al. 2006), we find a relative dearth of sources
at high LIR with low HCN/HCO+.
However, our larger sample also contains a number of
lower LIR systems with HCN/HCO+ratios as high as
those of ULIRGs (>1), which suggests that increasing
LIR (or an associated increase in AGN contribution) may
not be the sole driver of an increase in HCN/HCO+ra-
tios. A Spearman rank correlation analysis is consistent
with the null hypothesis that HCN/HCO+and LIR are
uncorrelated (ρ= 0.021 ±0.178, z-score= 0.057 ±0.494;
Table 3). The coefficients were computed using a Monte
Carlo perturbation and bootstrapping method (with 105
iterations), as described by Curran (2014) and imple-
mented in Curran (2015).
The Spitzer/IRS observations of GOALS systems, pre-
sented by Stierwalt et al. (2013), provide a calibrated
measurement of the AGN contribution to the mid-
infrared emission in each system, via the 6.2µm PAH
EQW. In order to test claims that HCN (1–0) emis-
sion is enhanced in systems with AGN, we explore the
HCN/HCO+ratio as a function of this AGN diagnos-
tic. In Figure 4(Left), we plot HCN/HCO+against the
relative contribution of AGN and star formation to the
infrared luminosity; where lower values of the PAH EQW
indicate the presence of more energetically important
AGN. We consider systems with PAH EQW <0.2µm to
have energetically dominant AGN (LMI R,AGN /LMI R &
60 %;) e.g., Petric et al. 2011), while systems with PAH
EQW >0.55 µm are considered starburst-dominated
(Brandl et al. 2006), and systems with intermediate ra-
tios as composites, where LMI R is the mid-infrared lu-
minosity and LMI R,AGN is the AGN contribution to the
mid-infrared luminosity.
We find that systems dominated by the AGN in the
mid-infrared show elevated HCN/HCO+ratios, with a
signal-to-noise ratio weighted mean ratio of 1.84 ±0.43.
and the HCN (1–0) and HCO+(1–0) (a 30% difference in beam
size).
6 Privon et al.
Starburst dominated systems have a weighted mean ratio
of 0.88 ±0.28, while composite systems have a weighted
mean ratio of 1.14±0.49. However, for systems which ap-
pear to be star formation dominated, this ratio exhibits
significant scatter. Several starburst and composite sys-
tems have HCN/HCO+values which are comparable to
the AGN dominated systems, suggesting that while en-
ergetically dominant AGN are associated with elevated
HCN (1–0) emission alone, the converse is not true: en-
hanced HCN (1–0) emission does not imply the presence
of an AGN. We note that although these starburst and
composite sources with enhanced HCN (1–0) emission
have substantial uncertainties in their HCN/HCO+ra-
tios, it is unlikely that the HCN/HCO+ratio is simulta-
neously overestimated for all six of these HCN-enhanced,
composite/starburst sources.
A Spearman rank correlation analysis shows
HCN/HCO+and the PAH EQW to be moderately
anti-correlated, with ρ=−0.512 ±0.127 and a z-score of
−1.532 ±0.464 (Table 3). In Figure 4(Right) we provide
a “box plot” of the mean ratio, interquartile range, and
full range of the HCN/HCO+values, separated by into
source types based on the PAH EQW. The distributions
of HCN/HCO+for pure starbursts and AGN-dominated
systems show a clear offset, with the AGN-dominated
systems show a relative enhancement of HCN (1–0)
emission over the pure starbursts.
It is worth noting there are fewer AGN-dominated
sources than SB or composite sources; further observa-
tions of low PAH EQW systems would be useful to ensure
the existing objects are representative.
4. WHAT DRIVES THE GLOBAL HCN (1–0)/HCO+(1–0)
RATIO?
In Section 3we demonstrated that globally enhanced
HCN (1–0) emission (relative to HCO+(1–0)) is not
correlated with the presence of an AGN (Figure 4).
Costagliola et al. (2011) found similar results for a
smaller sample of starbursts. Is there a straight-forward
explanation for the observed global HCN (1–0) emis-
sion in local (U)LIRGs? In the following subsections we
explore a series of proposed explanations for enhanced
HCN, including X-ray induced chemistry (Section 4.1),
the presence of a compact, high-density source (Section
4.2), and radiative pumping from absorption of mid-
infrared photons (Section 4.3). We finish by discussing
the possibility that the PAH EQW is not an ideal tracer
of AGN (Section 4.4) and then mention future observa-
tions which could be used to improve our understanding
of HCN enhancements (Section 4.5).
4.1. Comparison of HCN (1–0)/HCO+(1–0) with
X-ray Properties
To consider the possible influence of XDRs resulting
from powerful AGN, we investigated the HCN/HCO+
ratio as a function of X-ray properties, such as the hard-
ness ratio and the total 0.5–10 keV X-ray luminosity,
from Chandra X-ray observations of the GOALS sample
(Iwasawa et al. 2011). The HCN/HCO+ratio showed no
correlation with either the hardness ratio or the X-ray
luminosity, albeit with only ten sources common to both
samples. Additional X-ray observations would be useful
to further investigate the influence of XDRs. However,
based on the currently available X-ray data, it does not
appear that either the hardness of the X-ray spectrum or
the total X-ray luminosity correlate with HCN/HCO+,
suggesting an XDR is not generally a major driver in en-
hancing HCN (1–0), for these systems, possibly because
the XDRs are spatially disconnected from the regions
that dominate the global line luminosity.
A complication is that enhancement from X-rays may
be most effective in obscured AGN and diagnosing this
activity is difficult with observations below 10 keV. Hard
X-ray observations with NuSTAR (Harrison et al. 2013),
though time-consuming, would provide an interesting
test for the presence of obscured AGN in sources with
enhanced HCN emission.
4.2. HCN/HCO+Enhancements Through Source
Compactness
In compact environments HCO+(1–0) appears to
be more susceptible to self-absorption than HCN (1–0)
(Aalto et al. 2015), which would lead to an increase in
the observed HCN/HCO+ratio. To test if elevated ratios
are primarily associated with dense systems, we compare,
in Figure 5, the HCN/HCO+ratio with the [C ii]/LFIR
ratios from the central Herschel spaxel (9′′.4×9′′ .4) as
measured by Diaz-Santos et al. (2013). In local galax-
ies, the [C ii]/LFIR value decreases with increasing LFIR
and dust temperature, Tdust. That the “[C ii] deficit”
tracks Tdust suggests the deficit is the result of compact
nuclear activity. Diaz-Santos et al. (2013) find this trend
of a lower [C ii]/LFIR ratio with decreasing source size
is present when considering only starbursts, suggesting
that the [C ii] deficit is driven by the compactness of the
starburst, rather than dust heated by an AGN.
Therefore, if the HCN (1–0)/HCO+(1–0) ratio is be-
ing driven primarily by the density / compactness of the
starburst, we should see a correlation between the two
quantities. For sources with [C ii]/LFIR >10−3, the
signal-to-noise weighted mean L′
HCN (1–0) to L′
HCO+(1–0)
is 1.0±0.4, while sources with [C ii]/LFIR <10−3
(large [C ii] deficits) have a mean ratio of 1.7±0.5. For-
mally, the ratio does not appear to vary as a function of
[C ii]/LFIR though a Spearman rank analysis suggests a
moderate anti-correlation (ρ=−0.401 ±0.142, z-score=
−1.165 ±0.458; Table 3), though somewhat weaker than
the anti-correlation of HCN/HCO+with PAH EQW.
The majority of sources with [C ii]/LFIR <10−3have
HCN/HCO+ratios >1, consistent with a scenario in
which a compact and dense starburst causes an enhance-
ment of HCN (1–0). On the other hand, a substantial
number of systems without significant [C ii]/LFIR deficits
also have HCN/HCO+>1. For composite and starburst
systems (PAH EQW >0.2µm) higher HCN/HCO+ra-
tios do not appear to be associated with lower [C ii]/LFIR
values. Based on the available data, we cannot directly
link the [C ii] deficit with enhanced HCN (1–0) emission.
It is worth noting that HCN (1–0) can be enhanced
in sources that do not show a strong [C ii] deficit; if
a compact continuum source is surrounded by extended
disk-like star formation, the system may have a “normal”
[C ii]/LFIR ratio, but still show enhanced HCN (1–0)
associated with the compact starburst on scales which
cannot be resolved by Herschel. See Diaz-Santos et al.
(2014) for a discussion on extended [C ii] emission in the
GOALS sample. Assessing the spatial distribution of the
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 7
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
PAH 6.2µm EQW [µm]
0.0
0.5
1.0
1.5
2.0
2.5
3.0
L′
HC N /L′
HC O+
Increasing AGN
dominance
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0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
AGN
(7 sources)
Composite
(15 sources)
Starburst
(20 sources)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
L′
HC N /L′
HC O+
Figure 4. Left: L′
HCN (1–0)/L′
HCO+(1–0) as a function of the 6.2µm PAH EQW from Stierwalt et al. (2013). The points are colored
by their PAH EQW. The symbol shape notes the origin of the millimeter line measurements; circles are new data (see Table 2), diamonds
are from Graci´a-Carpio et al. (2006) and squares are from Costagliola et al. (2011). Right: Box plot showing the median (red line),
interquartile range (boxes) and full range up to 1.5×the interquartile range (IQR; black horizontal lines) for HCN/HCO+of the AGN
dominated, composite, and starburst systems. A flier (a point with a value >1.5×IQR) is plotted with a ’+’ symbol. Upper and
lower limits were not included in the box plot. HCN/HCO+is enhanced for systems which are AGN dominated in the mid-infrared, but
some starburst dominated systems show similarly elevated ratios. Weighted by signal-to-noise ratio, the average ratio for AGN dominated
systems (PAH EQW <0.2µm), pure starbursts (PAH EQW >0.55 µm Brandl et al. 2006), and composite systems (0.2µm < PAH
EQW <0.55 µm) is 1.84, 0.88, and 1.14, respectively.
10−410−310−2
[C II] 158 µm/LF IR
0.0
0.5
1.0
1.5
2.0
2.5
3.0
L′
HC N /L′
HC O+
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0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
Figure 5. A comparison of HCN/HCO+with [C ii]/LFIR, as
a proxy for the compactness of the source. Systems with signif-
icant [C ii] deficits are located towards the left side of the plot.
There is a dearth of sources with low [C ii]/LFIR values and low
HCN/HCO+ratios, but the scatter is significant and some systems
with high [C ii]/LFIR values (less compact starbursts) still show
elevated HCN/HCO+ratios, consistent with the mean of systems
with substantial deficits ([C ii]/LFIR <10−3). However there is
significant scatter. Points are color-coded by the 6.2µm PAH
EQW.
HCN (1–0)/HCO+(1–0) would be a useful comparison
with [C ii]/LFIR– do regions with “normal” [C ii]/LFIR
correspond to regions with low HCN (1–0)/HCO+(1–0)?
A possible concern with the above analysis is that the
LIR, [C ii]/LFIR, and the PAH EQW are all correlated.
Indeed, the LIR, the [C ii] deficit, and the 6.2µm PAH
EQW are interrelated, in that the most luminous sources
tend to have the strongest [C ii] deficits (Diaz-Santos
et al. 2013, because both LIR and [C ii]/LFIR correlate
with the dust temperature;) and lower PAH EQWs (Pet-
ric et al. 2011;Stierwalt et al. 2013). However, the con-
verse is not true; a normal [C ii]/LFIR value does not
guarantee a high PAH EQW. Systems with low or in-
termediate PAH EQWs are distributed across the range
of LIR and [C ii]/LFIR values seen for our sample (e.g.,
Figure 5and Diaz-Santos et al. 2013).. In contrast,
essentially all the high PAH EQW (starburst) systems
have normal [C ii]/LFIR and LIR ∼a few ×1011 L⊙.
Thus, while these quantities are generally related, sys-
tems with low or intermediate PAH equivalent widths
appear to have a range of compactness (as diagnosed
by [C ii]/LFIR) and so the PAH EQW and [C ii] deficit
appear to be semi-independent. That the HCN (1–
0)/HCO+(1–0) ratio does not correlate well with either,
suggests the origin of HCN enhancement cannot be easily
assigned solely to AGN or to the presence of a compact
starburst.
4.3. HCN/HCO+Enhancements Through Mid-infrared
Pumping
The strong mid-infrared continuum present in many
(U)LIRGs may also influence these line ratios. The HCN
molecule has degenerate bending modes in the infrared
and can absorb mid-infrared photons (14 µm) to its first
vibrational state. The transitions have high level energies
(>1000 K) and mid-IR emission with a brightness tem-
perature of at least 100 K is necessary to excite them
(Aalto et al. 2007). A sign that infrared pumping of
HCN is taking place is the presence of line emission from
rotational transitions within the vibrational band (e.g.,
8 Privon et al.
Sakamoto et al. 2010). However, it may be possible for
HCN to be infrared pumped without detectable emission
from these rotational-vibrational lines. When the bright-
ness temperature is close to the lower limit for pumping,
the excitation of the rotational-vibrational line is so low
that it takes a very large column density to result in a
large enough optical depth for this rotational-vibrational
line to be detected.
Several sources in our sample do show evidence for in-
frared absorption at 14 µm which could be associated
with pumping of HCN (Lahuis et al. 2007;Sakamoto
et al. 2010), but none of the starburst systems with en-
hanced HCN emission show 14 µm absorption in the
Spitzer/IRS observations from Inami et al. (2013).
HCO+is similarly susceptible to infrared pumping, via
a∼12 µm line; using the IRS high-resolution spec-
troscopy from Inami et al. (2013) we searched for a
∼12 µm absorption feature in those systems with high
ratios, where we postulated mid-infrared pumping could
be important. We did not find any evidence for HCO+
absorption.
However, it is not clear that existing mid-infrared ob-
servations are sensitive enough to establish firm upper
limits on the importance of infrared pumping. Existing
spectroscopy may not have the sensitivity to identify ab-
sorption which is sufficient to affect level populations.
4.4. Is the PAH EQW A Good Tracer of AGN Strength
An obvious question is whether or not the PAH EQW
is a robust measure of AGN strength in (U)LIRGs. Aalto
et al. (2015) present interferometric observations of sev-
eral objects, including the composite source CGCG 049-
057, one of our sources with enhanced HCN emission.
The HCN (3–2) v2= 0 and HCO+(3–2) lines show ev-
idence for significant self absorption and the HCN (3–2)
v2= 1 ro-vibrational line is detected (consistent with
mid-infrared pumping). Aalto et al. (2015) interpret this
as evidence for a very compact (tens of pc) warm (>100
K) region surrounded by a large envelope of cooler, more
diffuse gas. The total column density through these sys-
tems is likely quite high (>1024 cm−2). If the column
densities are sufficiently high to support mid-infrared
pumping, the optical depths in the infrared may be high
enough that the mid-infrared continuum level does not
trace the intrinsic energy source – thus the PAH EQW
diagnostic may miss highly embedded AGN.
In Section 2.3.2 we note that the PAH EQW is an up-
per limit to the AGN’s influence on large scales, but this
measurement could also be considered as a lower limit to
the AGN’s influence on smaller scales. Thus, consistent
with results of Aalto et al. (2015) for CGCG 047-059,
it is possible that these starburst or composite sources
with high HCN (1–0)/HCO+(1–0) ratios host embed-
ded AGN, and substantial mid-infrared optical depths
result in an under-estimate of the AGN’s influence when
using the PAH EQW.
4.5. Future Observations
Though we have shown in this study that
some starburst-dominated systems have global
L′
HCN (1–0)/L′
HCO+(1–0) ratios in excess of unity,
the starburst-dominated systems outnumber AGN-
dominated systems in the present sample. More
IRAM 30m single-dish observations of AGN-dominated
(U)LIRGs would be useful to study the dense-gas
tracers in that population, particularly to see if
the absence of AGN-dominated sources with low
L′
HCN (1–0)/L′
HCO+(1–0) ratios is truly representative or
merely reflects small number statistics.
Spatially resolved comparisons of the HCN emission
with CO or HCO+have been undertaken for systems
known to host an AGN (e.g., Kohno et al. 2003;Iman-
ishi et al. 2006,2007,2009;Davies et al. 2012;Imanishi &
Nakanishi 2013,2014); it would be instructive to perform
the same exercise on starburst dominated systems. The
Atacama Large Millimeter/sub-millimeter Array is the
natural instrument for this, and such a study could inves-
tigate the spatial variation in the L′
HCN (1–0)/L′
HCO+(1–0)
ratio for starbursts. If the ratio peaks on the nucleus but
is low elsewhere (as in systems with AGN), does that
correspond to a compact mid-infrared emitting region?
Spatially resolving this ratio in starburst systems with
both high and low ratios may enable a separation of the
relative importance of source compactness and/or mid-
infrared pumping, in setting the ratio.
Krips et al. (2008) studied the emission of multiple
HCN and HCO+transitions for twelve systems, find-
ing evidence for systematic differences in the HCN (1–
0)/HCO+(1–0) and HCN (3–2)/HCO+(3–2) ratios be-
tween AGN and starbursts, with AGN having values >2
for both ratios. They also found evidence that the (3–
2)/(1–0) ratio for both HCN and HCO+varies between
AGN and starbursts. The number of GOALS objects
with (3–2) measurements of HCN and HCO+is currently
too small to draw conclusions regarding the (3–2)/(1–0)
ratios as a function of AGN strength, but it would be
possibly illuminating to compare the higher Jupper tran-
sitions with the AGN diagnostic used here.
The discovery of mid-infrared pumping and associated
high-column densities in enhanced HCN sources sug-
gests that even mid-infrared diagnostics such as the PAH
EQW may miss highly embedded AGN. If this is the case,
hard X-ray observations may provide the only conclusive
evidence for AGN in sources with heavily obscured nu-
clei. However, the weakness of the >10 keV X-rays in
ULIRG AGN (e.g., Mrk 231; Teng et al. 2014) may make
these observations difficult with existing facilities.
Finally, the influence of infrared pumping is still uncer-
tain. Future mid-infrared observations of these sources
with The James Webb Space Telescope would provide
tighter constraints on the importance and ubiquity of
mid-infrared pumping, for both HCN and HCO+. See
also Aalto et al. (2007) for a discussion on using re-
solved observations to distinguish mid-infrared pumping
and XDR scenarios.
5. THE RELATIONSHIPS BETWEEN MOLECULAR LINE
LUMINOSITIES, STAR FORMATION RATES, AND GAS
DEPLETION TIMESCALES
5.1. Star Formation Rates
We now turn to the relationship between the HCN (1–
0) emission and the star formation rates in (U)LIRGs.
While HCN (1–0) is generally taken to trace the mass of
dense molecular gas, Mdense , previous studies have found
conflicting results for the relationship between LIR and
L′
HCN (1–0). In Figure 6(Left) we plot the standard re-
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 9
lation between L′
HCN (1–0) and LIR including additional
measurements from Gao & Solomon (2004b, with val-
ues corrected to our assumed cosmology and for the 3-
attractor model of Mould et al. (2000)).
We fit the relationship using a maximum likelihood
technique, considering the errors in both LIR and
L′
HCN (1–0) (e.g., Sec 7 of Hogg et al. 2010). When un-
certainties for mm-line fluxes were not quoted in the lit-
erature, we assume 20%. Uncertainties on the fit pa-
rameters were determined using Markov Chain Monte
Carlo (MCMC) sampling21 and quoted fit parameter un-
certainties are for the 99% confidence interval.
To this point, we have not considered systematic un-
certainties in our new observations, as the simultane-
ous measurement of HCN and HCO+should result
in significantly reduced systematic uncertainties in the
HCN/HCO+ratio,in the HCN/HCO+ratio, compared
to non-simultaneous measurements. However, for the
present comparison of LIR with these lines, the absolute
flux of these lines may be subject to systematic uncer-
tainties. We tested two approaches for dealing with sys-
tematic uncertainties: 1) assigning additional systematic
uncertainties (equal in magnitude to the statistical un-
certainties) to each datapoint22 and fitting the relation-
ship, or 2) including only statistical uncertainties23 and
allowing for additional uncertainties in the fitting pro-
cess. In addition to fitting for the slope and intercept,
we included an additional “nuisance” parameter, f, in
the likelihood function to fit for the fractional amount
by which the uncertainties are underestimated (e.g., due
to not explicitly including systematic uncertainties). Af-
ter the MCMC sampling, we marginalized over fwhen
determining the final uncertainties for the slope and in-
tercept. Both approaches yielded the same results for
the best-fit relations, so we conclude that our fitting pro-
cess appropriately accounts for non-statistical uncertain-
ties and present the numerical results from the latter
approach. For consistency, we show only the statistical
uncertainties for values plotted in Figures 6and 7.
Our best fit relation to our new data combined with the
literature data (omitting both AGN-dominated systems,
in which LIR may not solely trace star formation, and
HCN (1–0) upper limits) between LIR and L′
HCN (1–0) is:
log10 LIR = (1.08+0.18
−0.16) log10 L′
HCN(1−0) + (2.32+1.54
−1.50)
(1)
This fit is shown in Figure 6(Left) as the solid line.
We also fit L′
HCN (1–0)–LIR , fixing the slope to be lin-
ear, which we show in Figure 6(Left) as a dashed
line. The slope of the L′
HCN (1–0)–LIR relation is con-
sistent with being linear at the ∼1.3σlevel. We note
that Garc´ıa-Burillo et al. (2012) found the L′
HCN (1–0)–
LFIR[40 −400 µm] relation to be steeper than linear,
with a slope of 1.23 ±0.05 (68 % confidence interval).
21 Calculated using the emcee python library (Foreman-Mackey
et al. 2013).
22 The values quoted by Garc´ıa-Burillo et al. (2012) already
include systematic uncertainties, so we did not increase the uncer-
tainties on those points.
23 In this case, we reduced the uncertainties on the Garc´ıa-
Burillo et al. (2012) points to remove their estimate for the sys-
tematic uncertainties.
In Figure 6(Right) we perform the same compari-
son, but utilizing L′
HCO+(1–0) instead of L′
HCN (1–0). As
HCO+(1–0) has a higher critical density than CO (1–
0), but lower than HCN (1–0), it is useful to test if it is
also linearly tracked by the SFR. The L′
HCO+(1–0)–LIR
relation is also consistent with linear:
log10 LIR = (0.94+0.25
−0.19) log10 L′
HCO+(1−0) + (3.54+2.18
−2.20)
(2)
Thus, our results are consistent with scenarios in which
the HCN and HCO+emission both trace the dense gas
associated with ongoing star formation, albeit with scat-
ter, likely the result of one or more of the excitation
mechanisms discussed in Section 4.
5.2. The Lack of HCO+Measurements for
non-(U)LIRGs
The inclusion of the Gao & Solomon (2004a) HCN ob-
servations adds in a substantial number of galaxies with
LIR <1011 L⊙, but corresponding HCO+(1–0) obser-
vations are not available. In order to assess the degree
to which these lower-luminosity systems influence our fit-
ting results, we also fit the HCN (1–0)–LIR relation with-
out the points from Gao & Solomon (2004a); this fit is
shown as the dot-dash line in Fig 7(Left) and the best-fit
relation is:
log10 LIR = (1.09+0.48
−0.31) log10 L′
HCN(1−0) + (2.30+3.37
−3.64)
(3)
which is consistent with that for the full dataset.
5.3. Dense Gas Depletion Times
The ratio L′
HCN (1–0)/LIR is often taken as ∝
Mdense/SFR, which corresponds to the depletion time
(τdep) of the dense molecular gas. In Figure 7(Left)
we show L′
HCN (1–0)/LIR as a function of LIR , exclud-
ing sources which are AGN dominated (PAH EQW
<0.2µm). As in Figure 6(Left), we include ob-
servations from Gao & Solomon (2004a). The mean
log10(L′
HCN (1–0)/LIR ) = 1 ×10−3with a RMS scatter
of 0.22 dex. The AGN and starburst dominated sys-
tems (as traced by the 6.2 µm PAH feature) have similar
L′
HCN (1–0)/LIR ratios.
Similarly, L′
HCO+(1–0)/LIR shows no obvious trend
with LIR, but has substantial scatter. The mean
log10(L′
HCO+(1–0)/LIR ) = 1 ×10−3with a RMS scat-
ter of 0.19 dex.
The significant scatter in L′
HCN (1–0)/L′
HCO+(1–0) can
plausibly be attributed to the influence of multiple ex-
citation mechanisms for these dense gas tracers, as de-
scribed above. These observations are consistent with
a scenario in which molecular abundance (Lepp & Dal-
garno 1996), density (Meijerink et al. 2007), and radia-
tive effects (Aalto et al. 1995) all influence the global
HCN (1–0) emission, obscuring a simple link between
L′
HCN (1–0) and the mass of dense gas directly associated
with ongoing star formation. Stated differently, the con-
version factor between L′
HCN (1–0) (or L′
HCO+(1–0)) and
10 Privon et al.
1071081091010
L′HC N [K km s−1pc2]
109
1010
1011
1012
LIR [L⊙]
Best fit
Linear slope
Best fit (no GS2004)
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Gao & Solomon 2004
Garcia-Burillo+ 2012
0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
1071081091010
L′HC O+[K km s−1pc2]
109
1010
1011
1012
LIR [L⊙]
Best fit
Linear Slope
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0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
Figure 6. LIR plotted as a function of L′
HCN (1–0) (Left) and L′
HCO+(1–0) (right). The points are color-coded by 6.2 µm EQW. The
solid lines in the left and right panels denote the best fit relations of equations 1and 2, respectively, while the dashed lines show the relation
if we fix the slope to be linear. The fits do not include upper limits, but the (solid and dashed) fits to the LIR–L′
HCN (1–0) relation (left)
includes the data from Gao & Solomon (2004b), corrected to our cosmology. In the left panel, we show a fit excluding the Gao & Solomon
(2004b) points, as the dot-dash line. We find a slope consistent with being linear, when considering LIR (L′
HCN (1–0)) (Equation 1),
consistent with Gao & Solomon (2004b). For LIR (L′
HCO+(1–0)) we find a slope consistent with a linear relation (Equation 2). The fits
do not include upper limits or AGN-dominated systems (PAH EQW <0.2µm).
1010 1011 1012
LIR [L⊙]
10−4
10−3
L′HC N /LIR [K km s−1pc2L⊙
−1]
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Gao & Solomon 2004
Garcia-Burillo+ 2012
0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
1010 1011 1012
LIR [L⊙]
10−4
10−3
L′HC O+/LIR [K km s−1pc2L⊙
−1]
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Garcia-Burillo+ 2012
0
0.2
0.4
0.6
0.8
PAH 6.2µm EQW [µm]
Figure 7. Left: L′
HCN (1–0)/LIR versus LIR. The Gao & Solomon (2004a) points have been corrected to the cosmology assumed here.
Right: L′
HCO+(1–0)/LIR versus LIR. Points are color-coded by the 6.2µm PAH EQW. We see no clear trend of the gas depletion time
with LIR.
Mdense likely depends on the relative HCN–H2abun-
dance in addition to the overall density, excitation source
(PDR vs XDR), and influence of infrared pumping. A
better understanding of the processes in (U)LIRGs con-
tributing to L′
HCN (1–0) and L′
HCO+(1–0) are needed to
determine if the scatter in Figure 7is due to differences
in the consumption rates of molecular gas or a vary-
ing L′
HCN (1–0)–Mdense conversion factor. Future obser-
vations (Section 4.5), coupled with improved modeling,
should be able to discriminate between these scenarios
for the HCN and HCO+emission in (U)LIRGs.
6. SUMMARY
We make use of new measurements of the putative
high density gas tracers HCN (1–0) and HCO+(1–0)
in a sample of local (U)LIRGs. A comparison between
the ratios of these lines and the 6.2µm PAH EQW
mid-infrared AGN indicator suggests enhancements in
the global HCN (1–0) emission (relative to HCO+(1–
0)) does not uniquely trace the presence of an energeti-
cally dominant AGN. While we find enhanced HCN (1–0)
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 11
emission relative to HCO+(1–0) in ob jects hosting dom-
inant AGN, we find the same magnitude of enhancement
is also possible for systems which are dominated by star
formation. The HCN (1–0) and HCO+(1–0) emission
does not seem to be driven by a single process. It is likely
that their emission is determined by the interplay of ra-
diation field, gas column, and gas density. This hampers
a simple interpretation of the line ratio. Existing data
on the X-ray and mid-infrared properties of these sys-
tems are not complete or deep enough (respectively) for
us to prefer one of XDRs or mid-infrared pumping as the
mechanism for enhancing the HCN (1–0) emission.
We compare the HCN (1–0) emission with the star
formation rate (LIR) and find a linear relationship, con-
sistent with some previous studies (e.g., Solomon et al.
1992;Gao & Solomon 2004b). However, our result is
also consistent with a superlinear relationship, within our
99% confidence interval, analogous to the recent study
utilizing LFIR, by Garc´ıa-Burillo et al. (2012). The large
scatter in the L′/LIR ratios is consistent with a scenario
in which these dense gas tracers can be influenced by
density effects, infrared pumping, and/or XDRs. This
potentially complicates the determination of global dense
gas masses and dense gas depletion times.
We thank the anonymous referee for their careful read-
ing of our manuscript and for their helpful comments and
suggestions, which improved the paper.
G.C.P. and A.S.E. were supported by the NSF grant
AST 1109475, and by NASA through grants HST-
GO10592.01-A and HST-GO11196.01-A from the Space
Telescope Science Institute, which is operated by the
Association of Universities for Research in Astronomy,
Inc., under NASA contract NAS5-26555. G.C.P. and
E.T. were supported by the CONICYT Anillo project
ACT1101 (EMBIGGEN). G.C.P. was also supported
by a Visiting Graduate Research Fellowship at the In-
frared Processing and Analysis Center / Caltech and by
a FONDECYT Postdoctoral Fellowship (No. 3150361).
This work was supported in part by National Science
Foundation Grant No. PHYS-1066293 and the hospi-
tality of the Aspen Center for Physics. G.C.P. acknowl-
edges the hospitality of the National Socio-environmental
Synthesis Center (SESYNC), where portions of this
manuscript were written. A.S.E. was also supported
by the Taiwan, R.O.C. Ministry of Science and tech-
nology grant MoST 102-2119-M-001-MY3. KI acknowl-
edges support by the Spanish MINECO under grant
AYA2013-47447-C3-2-P and MDM-2014-0369 of ICCUB
(Unidad de Excelencia “Mar´ıa de Maeztu”). RHI,
MAPT, and AA also acknowledge support from the
Spanish MINECO through grant AYA2012-38491-C02-
02. E.T. was also supported by the Center of Excellence
in Astrophysics and Associated Technologies (PFB 06)
and by the FONDECYT regular grant 1120061.
This research has made use of the NASA/IPAC Ex-
tragalactic Database (NED) which is operated by the
Jet Propulsion Laboratory, California Institute of Tech-
nology, under contract with the National Aeronautics
and Space Administration. This research also made use
of Astropy, a community-developed core Python pack-
age for Astronomy (The Astropy Collaboration et al.
2013), the cubehelix python library24, and NASA’s As-
trophysics Data System. The Spitzer Space Telescope
is operated by the Jet Propulsion Laboratory, Califor-
nia Institute of Technology, under NASA contract 1407.
G.C.P. thanks Ina Evans for a critique of the comments
of an earlier version of this manuscript.
Facility: IRAM:30m (EMIR, WIMA, FTS)
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HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 13
Table 1
IRAM 30m Observing Log
Source J2000 RA J2000 Dec zObs Month tint Tsys Backend
[deg] [deg] [YYYY-MM] [min] [K]
NGC 0034 2.77729 –12.10775 0.0200 2011-09 276 116 WILMA
MCG –02-01-052 4.70904 –10.36246 0.0274 2011-12 127 89 FTS
MCG –02-01-051 4.71208 –10.37672 0.0270 2011-12 277 90 FTS
IC 1623 16.94804 –17.50721 0.0205 2011-12 95 88 FTS
MCG –03-04-014 17.53733 –16.85272 0.0342 2011-12 223 86 FTS
IRAS 01364-1042 24.72050 –10.45317 0.0487 2011-09 117 98 WILMA
IC 214 33.52279 +5.17367 0.0300 2011-12 244 84 FTS
NGC 0958 37.67858 –2.93905 0.0193 2012-10 61 139 FTS
ESO 550-IG 025 65.33333 –18.81094 0.0321 2013-08 298 105 WILMA
UGC 03094 68.89096 +19.17172 0.0247 2012-10 224 126 FTS
NGC 1797 76.93690 –8.01911 0.0149 2012-10 184 113 FTS
VII Zw 031 79.19333 +79.67028 0.0540 2010-06 42 137 WILMA
IRAS F05189-2524 80.25612 –25.36261 0.0435 2011-12 297 107 FTS
IRAS F05187-1017 80.27728 –10.24619 0.0283 2011-12 138 88 FTS
IRAS F06076-2139 92.44088 –21.67325 0.0376 2013-08 127 107 WILMA
NGC 2341 107.30000 +20.60278 0.0174 2014-03 61 89 FTS
NGC 2342 107.32525 +20.63622 0.0174 2012-10 326 107 FTS
IRAS 07251-0248 111.90646 –2.91503 0.0876 2013-08 255 113 WILMA
NGC 2623 129.60045 +25.75461 0.0185 2010-06 42 200 WILMA
IRAS 09111-1007W 138.40167 –10.32500 0.0564 2013-08 318 103 WILMA
IRAS 09111-1007E 138.41167 –10.32231 0.0550 2011-09 117 98 WILMA
UGC 05101 143.96500 +61.35328 0.0394 2010-06 191 116 WILMA
CGCG 011-076 170.30095 –2.98396 0.0247 2012-10 163 123 FTS
IRAS F12224-0624 186.26621 –6.68103 0.0257 2012-10 92 135 FTS
CGCG 043-099 195.46167 +4.33333 0.0374 2011-09 116 98 WILMA
ESO 507-G 070 195.71812 –23.92158 0.0215 2011-12 180 110 FTS
NGC 5104 200.34627 +0.34248 0.0186 2012-10 153 121 FTS
IC 4280 203.22212 –24.20720 0.0165 2012-10 132 145 FTS
NGC 5257 204.97042 +0.84058 0.0227 2014-03 132 104 FTS
NGC 5258 204.98854 +0.82989 0.0226 2011-12 180 88 FTS
UGC 08739 207.30800 +35.25730 0.0172 2012-10 102 111 FTS
NGC 5331 208.06750 +2.10156 0.0330 2013-08 286 98 WILMA
CGCG 247-020 214.93007 +49.23666 0.0258 2014-03 122 153 FTS
IRAS F14348-1447 219.40975 –15.00633 0.0830 2011-09 223 139 WILMA
CGCG 049-057 228.30455 +7.22556 0.0127 2012-10 71 116 FTS
NGC 5936 232.50360 +12.98953 0.0134 2012-10 91 123 FTS
ARP 220 233.73854 +23.50323 0.0181 2010-06 53 159 WILMA
IRAS F16164-0746 244.79913 –7.90078 0.0229 2011-12 201 94 FTS
CGCG 052-037 247.73545 +4.08292 0.0248 2012-10 214 113 FTS
IRAS F16399-0937 250.66754 –9.72067 0.0270 2011-12 191 91 FTS
NGC 6285 254.59998 +58.95594 0.0186 2011-12 127 82 FTS
NGC 6286 254.63146 +58.93673 0.0185 2011-12 53 79 FTS
IRAS F17138-1017 259.14900 –10.34439 0.0175 2011-12 149 102 FTS
UGC 11041 268.71599 +34.77625 0.0161 2012-09 41 101 FTS
CGCG 141-034 269.23598 +24.01704 0.0199 2012-10 61 109 FTS
IRAS 18090+0130 272.91004 +1.52782 0.0293 2013-08 286 94 WILMA
NGC 6701 280.80208 +60.65312 0.0132 2012-10 163 165 FTS
NGC 6786 287.72500 +73.40992 0.0250 2011-09 265 95 WILMA
UGC 11415 287.76833 +73.42556 0.0252 2011-09 287 92 WILMA
ESO 593-IG 008 288.62950 –21.31897 0.0487 2011-09 53 120 WILMA
NGC 6907 306.27750 –24.80893 0.0106 2012-09 102 171 FTS
IRAS 21101+5810 317.87667 +58.38422 0.0398 2013-08 308 89 WILMA
ESO 602-G 025 337.85621 –19.03454 0.0247 2012-10 142 125 FTS
UGC 12150 340.30077 +34.24918 0.0216 2012-10 81 100 FTS
IRAS F22491-1808 342.95567 –17.87357 0.0760 2011-12 158 111 FTS
CGCG 453-062 346.23565 +19.55198 0.0248 2012-10 122 96 FTS
NGC 7591 349.56777 +6.58579 0.0165 2012-10 101 102 FTS
IRAS F23365+3604 354.75542 +36.35250 0.0645 2011-09 32 87 WILMA
Note. — Col 1: Source name, Col 2: Right Ascension, Col 3: Declination, Col 4: redshift, Col
5: Year and month of observation, Col 6: Total on-source time, Col 7: System temperature, Col
8: Backend used for measurements (either the Fourier Transform Spectrometer (FTS; Klein et al.
2012) or the Wideband Line Multiple Autocorrelator (WILMA)).
14 Privon et al.
Table 2
IRAM 30m Fluxes
Source Σ Tmbdv (CCH) Σ Tmb dv (HCN (1–0)) Σ Tmb dv (HCO+(1–0)) Σ Tmb dv (HNC (1–0))
[K km s−1] [K km s−1] [K km s−1] [K km s−1]
NGC 0034 <0.35 0.71 ±0.12 1.14 ±0.15 <0.44
MCG –02-01-052 <0.33 0.57 ±0.13 <0.27 <0.26
MCG –02-01-051 <0.23 0.17 ±0.05 0.30 ±0.07 <0.16
IC 1623 1.40 ±0.14 1.51 ±0.15 4.00 ±0.15 0.64 ±0.13
MCG –03-04-014 0.48 ±0.12 0.94 ±0.12 0.93 ±0.09 0.38 ±0.12
IRAS 01364-1042 <0.46 <0.71 <0.45 <0.54
IC 214 <0.15 0.36 ±0.10 0.56 ±0.12 <0.14
NGC 0958 <0.42 <0.71 <0.58 <0.69
ESO 550-I G025 <0.35 0.45 ±0.11 0.36 ±0.11 <0.39
UGC 03094 0.63 ±0.12 <0.42 0.74 ±0.14 <0.41
NGC 1797 <0.37 0.72 ±0.17 0.55 ±0.12 <0.43
VII Zw 031 <1.00 <0.98 1.26 ±0.40 <0.96
IRAS F05189-2524 <0.24 0.73 ±0.13 0.55 ±0.13 0.39 ±0.11
IRAS F05187-1017 0.49 ±0.12 0.75 ±0.11 0.76 ±0.14 <0.18
IRAS F06076-2139 <0.60 1.05 ±0.20 <0.59 <0.50
NGC 2341 0.65 ±0.21 <0.35 <0.43 <0.60
NGC 2342 0.55 ±0.11 0.68 ±0.11 0.75 ±0.13 <0.22
IRAS 07251-0248 <0.41 0.35 ±0.11 <0.33 <0.40
NGC 2623 <1.27 2.62 ±0.48 2.40 ±0.54 <1.23
IRAS 09111-1007W <0.36 0.60 ±0.08 0.83 ±0.16 <0.25
IRAS 09111-1007E 0.66 ±0.16a<0.36 <0.41 <0.35
UGC 05101 0.99 ±0.20 2.17 ±0.20 1.25 ±0.17 0.92 ±0.20
CGCG 011-076 <0.51 1.09 ±0.15 1.20 ±0.17 <0.35
IRAS F12224-0624 <0.69 <0.55 <0.67 <0.66
CGCG 043-099 <0.55 <0.54 <0.53 <0.53
ESO 507-G 070 <0.48 1.22 ±0.19 1.87 ±0.21 0.49 ±0.13
NGC 5104 <0.67 1.23 ±0.22 0.74 ±0.20 <0.41
IC 4280 0.55 ±0.15 0.95 ±0.21 1.17 ±0.23 0.57 ±0.18
NGC 5257 <0.29 0.39 ±0.10 0.46 ±0.09 0.37 ±0.11
NGC 5258 <0.20 0.43 ±0.10 0.53 ±0.07 0.30 ±0.08
UGC 08739 <0.51 1.30 ±0.17 0.94 ±0.19 0.88 ±0.19
NGC 5331 <0.31 0.67 ±0.10 0.45 ±0.10 <0.43
CGCG 247-020 <0.38 0.96 ±0.15 0.57 ±0.12 0.35 ±0.09
IRAS F14348-1447 <0.46 <0.52 <0.37 <0.51
CGCG 049-057 1.57 ±0.36 3.21 ±0.32 1.48 ±0.20 1.70 ±0.28
NGC 5936 <0.48 1.21 ±0.16 0.81 ±0.11 <0.46
ARP 220 4.37 ±0.62 12.15 ±0.75 6.02 ±0.74 7.85 ±0.60
IRAS F16164-0746 0.65 ±0.12 0.54 ±0.11 0.93 ±0.12 0.32 ±0.09
CGCG 052-037 0.57 ±0.12 0.67 ±0.12 0.74 ±0.10 0.73 ±0.13
IRAS F16399-0937 0.66 ±0.14 0.77 ±0.10 0.68 ±0.10 0.38 ±0.11
NGC 6285 0.38 ±0.10 <0.36 <0.25 <0.35
NGC 6286 0.93 ±0.20 1.63 ±0.22 1.67 ±0.21 <0.40
IRAS F17138-1017 1.01 ±0.17 0.83 ±0.10 1.03 ±0.12 0.47 ±0.11
UGC 11041 <0.50 1.51 ±0.26 1.49 ±0.20 <0.59
CGCG 141-034 <0.51 1.01 ±0.20 <0.49 <0.69
IRAS 18090+0130 <0.30 0.67 ±0.10 0.78 ±0.11 0.28 ±0.08
NGC 6701 <0.48 2.77 ±0.22 2.26 ±0.22 1.16 ±0.22
NGC 6786 0.30 ±0.10 0.51 ±0.08 0.56 ±0.11 0.35 ±0.09
UGC 11415 <0.36 <0.28 0.54 ±0.12 <0.22
ESO 593-IG 008 <0.77 <0.98 <1.22 <1.05
NGC 6907 <0.83 2.29 ±0.31 1.27 ±0.27 <0.65
IRAS 21101+5810 0.47 ±0.11 0.53 ±0.09 0.33 ±0.08 <0.22
ESO 602-G 025 <0.57 0.84 ±0.21 0.75 ±0.12 0.74 ±0.20
UGC 12150 0.69 ±0.15 1.36 ±0.17 1.59 ±0.14 0.51 ±0.14
IRAS F22491-1808 <0.83 <0.82 <0.73 <0.71
CGCG 453-062 0.74 ±0.14 0.97 ±0.16 0.48 ±0.16 <0.42
NGC 7591 1.37 ±0.20 1.35 ±0.18 0.69 ±0.13 0.68 ±0.20
IRAS F23365+3604 <0.58 0.81 ±0.27 1.28 ±0.27 <0.88
Note. — Col 1: Source name, Col 2: CCH (N = 1 →0) flux with 1σerrors, Col 3: HCN (J = 1 →0) flux with 1σ
errors, Col 4: HCO+(J = 1 →0) flux with 1σerrors, Col 5: HNC (J = 1 →0) flux with 1σerrors. The quoted upper
limits are 3σ.
aThough formally a detection (>3σ), this CCH flux appears to be spurious as the signal at the location of CCH is
significantly broader than would be expected.
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 15
Table 3
Spearman Rank Coefficients
Quantities ρ z-score
L′
HCN (1–0)/L′
HCO+(1–0) vs log10(LIR /L⊙) (Figure 3) 0.021 ±0.178 0.057 ±0.494
L′
HCN (1–0)/L′
HCO+(1–0) vs 6.2µm PAH EQW (Figure 4, Left) −0.512 ±0.127 −1.532 ±0.464
L′
HCN (1–0)/L′
HCO+(1–0) vs log10([C ii]/LFIR) (Figure 5)−0.401 ±0.142 −1.165 ±0.458
Note. — Spearman rank coefficients for several relationships discussed in the text along with z-
scores. Quantities and their 68% confidence intervals were computed according to the Monte Carlo
perturbation plus bootstrapping method (1e5 iterations) discussed by Curran (2014) and using the
associated code (Curran 2015). Upper and lower limits for L′
HCN (1–0)/L′
HCO+(1–0) were not included
when computing these coefficients.
16 Privon et al.
86 88 90 92
−4
−2
0
2
4
6
8
T∗
A[mK]
NGC 2623
HCN
HCO+
HNC
CCH
80 82 84 86 88
0
1
2IRAS 09111-1007W
80 82 84 86 88
−0.6
−0.4
−0.2
0.0
0.2
0.4
0.6IRAS 09111-1007E
82 84 86 88 90
0
1
2
3
T∗
A[mK]
UGC 05101
84 86 88 90 92
−1
0
1
2
CGCG 011-076
84 86 88 90 92
−1
0
1
2IRAS F12224-0624
82 84 86 88 90
−0.5
0.0
0.5
1.0
T∗
A[mK]
CGCG 043-099
84 86 88 90
0
1
2
ESO 507-G 070
84 86 88 90 92
−1
0
1
2
NGC 5104
84 86 88 90 92
−1
0
1
2
T∗
A[mK]
IC 4280
84 86 88 90 92
−0.5
0.0
0.5
1.0NGC 5257
82 84 86 88 90
0
1
2NGC 5258
84 86 88 90 92
−1
0
1
2
3
T∗
A[mK]
UGC 08739
82 84 86 88 90
0
1
NGC 5331
84 86 88 90 92
0
1
2
CGCG 247-020
78 80 82 84 86
νobs [GHz]
−1
0
1
T∗
A[mK]
IRAS F14348-1447
84 86 88 90 92
νobs [GHz]
−1
0
1
2
3
4
5
6
7
CGCG 049-057
84 86 88 90 92
νobs [GHz]
−1
0
1
2
3
4
5NGC 5936
Figure 8. Figure 1Continued
HCN (1–0) and HCO+(1–0) in GOALS (U)LIRGs 17
84 86 88 90 92
−4
0
4
8
12
16
20
T∗
A[mK]
Arp220
HCN
HCO+
HNC
CCH
82 84 86 88
−1
0
1
2IRAS F16164-0746
84 86 88 90 92
0
1
2CGCG 052-037
82 84 86 88
0
1
2
T∗
A[mK]
IRAS F16399-0937
82 84 86 88 90
−0.6
−0.4
−0.2
0.0
0.2
0.4
0.6NGC 6285
82 84 86 88 90
0
1
2
3NGC 6286
84 86 88 90 92
0
1
2
T∗
A[mK]
IRAS F17138-1017
84 86 88 90 92
−1
0
1
2
3
4UGC 11041
84 86 88 90 92
−1
0
1
2
CGCG 141-034
82 84 86 88 90
0
1
2
T∗
A[mK]
IRAS 18090+0130
84 86 88 90 92
−1
0
1
2
3
4
5
6
7
NGC 6701
82 84 86 88 90
0
1
2
NGC 6786
82 84 86 88 90
0
1
T∗
A[mK]
UGC 11415
82 84 86 88
−1
0
1
2
3ESO 593-IG 008
84 86 88 90 92
−1
0
1
2
3
4
5
6
7
NGC 6907
82 84 86 88 90
νobs [GHz]
0
1
T∗
A[mK]
IRAS 21101+5810
84 86 88 90 92
νobs [GHz]
0
1
2ESO 602-G 025
84 86 88 90 92
νobs [GHz]
0
1
2
3
4UGC 12150
Figure 9. Figure 1Continued
