Journal ArticleDOI

# A 10 kpc SCALE SEYFERT GALAXY OUTFLOW: HST/COS OBSERVATIONS OF IRAS F22456–5125

01 Jun 2012-The Astrophysical Journal (IOP Publishing Ltd.)-Vol. 751, Iss: 2, pp 107

AbstractWe present analysis of the UV spectrum of the low-z AGN IRAS F22456?5125 obtained with the Cosmic Origins Spectrograph on board the Hubble Space Telescope. The spectrum reveals six main kinematic components, spanning a range of velocities of up to 800?km?s?1, which for the first time are observed in troughs associated with C II, C IV, N V, Si II, Si III, Si IV, and S IV. We also obtain data on the O VI troughs, which we compare to those available from an earlier Far Ultraviolet Spectroscopic Explorer epoch. Column densities measured from these ions allow us to derive a well-constrained photoionization solution for each outflow component. Two of these kinematic components show troughs associated with transitions from excited states of Si II and C II. The number density inferred from these troughs, in combination with the deduced ionization parameter, allows us to determine the distance to these outflow components from the central source. We find these components to be at a distance of ~10?kpc. The distances and the number densities derived are consistent with the outflow being part of a galactic wind.

Topics: , Galaxy (52%), Active galactic nucleus (52%), Quasar (52%), Luminosity (51%)

### 1. INTRODUCTION

• In Section 3, the authors detail the computation of the column densities associated with every species.
• The reduced spectrum with its original 5 Details on CALCOS can be found in the COS Data Handbook.
• In Figure 1, the authors show the majority of the spectrum on which they identified major intrinsic absorption features associated with the outflow.

### 2.1. Identification of Spectral Features

• These components, spanning a total velocity range of 800 km s−1, were detected in O vi, C iii, and several lines of the Lyman series (Lyβ to Lyη).
• While the absorption troughs associated with the higherionization lines generally exhibit broader profiles, the authors observe a 1:1 kinematic correspondence between the core of these components and the narrower features associated with the lowerionization species of the outflow.
• Given the significantly broad range of velocities covered by the components and their net kinematic separations, such a match is not likely to occur by chance.
• This argues in favor of a scenario where the troughs of the different ionic species detected in a given kinematic component are generated in the same region.
• Nevertheless, given the selfblending of these features in the strongest lines (e.g., O vi) and the absence of apparent change between the FUSE and COS observations, the authors will use the labeling of components as defined in Dunn et al. (2010).

### 2.2. Deconvolution of the COS Spectrum

• Detailed analysis of the on-orbit COS line-spread function (LSF) revealed the presence of broadened wings that scatter a significant part of the continuum flux inside the absorption troughs (see Kriss et al. 2011 for details).
• This continuum leaking is particularly strong for narrow absorption troughs (FWHM ∼50 km s−1) in which this effect may significantly affect the estimation of the true column density by artificially increasing the residual intensity observed inside the troughs.
• Adopting the procedure described in Kriss et al. (2011), the authors deconvolve the spectrum obtained for each grating in 50 Å intervals using the wavelength-dependent LSFs and an IDL implementation of the stsdas Richardson–Lucy (RL) “lucy” algorithm (G. Schneider & B. Stobie 2011, private communication).
• The main effect of the deconvolution is illustrated in Figure 2, in which the authors clearly see that the deconvolved spectrum shows significantly deepened intrinsic Lyα absorption troughs and produces a square, black bottom for the saturated interstellar line C ii λ1334.532.
• In order to decrease these effects, the authors modified the RL algorithm by forcing the deconvolved spectrum to have an LSF satisfying the sampling theorem.

### 2.3. Unabsorbed Emission Model

• The unabsorbed emission model F0(λ) of IRAS F22456− 5125 is constructed in a similar manner to the one described in detail for IRAS F04250−5718 in Paper I, in which the authors consider three main sources of emission: a continuum, a broad emission line (BEL) component, and a narrow emission line (NEL) component.
• The NEL component of each line of a doublet is fit by a single narrower Gaussian (FWHM ∼ 600 km s−1) centered around the rest wavelength of each line, with the separation of the two Gaussians fixed to the velocity difference between the doublet lines.
• A normalized spectrum is then obtained by dividing the data with the emission model.

### 3.1. Methodology

• The column density associated with a given ionic species detected in the outflow is determined by modeling the residual intensity in the normalized data of the absorption troughs.
• The authors use these three models in order to account for possible inhomogeneities in the absorber (see Section 6), which cause the apparent strength ratio Ra = τi/τj of two lines i, j from a given ion to deviate from the expected laboratory ratio 1995; Hamann 1997; Arav et al. 1999).
• For singlet lines the authors will generally only derive a lower limit on the column density using the AOD method.
• In the following subsections, the authors use the term (non-black) saturation to qualify Notes.

### 3.2. Column Density Measurements

• Computed ionic column densities are determined using the deconvolved line profiles presented in Figure 3 and the ionic transition properties reported in Table 1.
• The computed column densities are reported in Table 2 for the three absorber models when possible.
• The adopted values shown in the last column of Table 2 are the ones used in the photoionization analysis.
• When available, the authors choose to use the value reported in the PC column as the measurement and use the PL measurement and error as the upper error in order to account for the possible inhomogeneities in the absorbing material distribution.
• If only the AOD determination is available, the authors will consider the reported value minus the error as a lower limit unless they have evidence suggesting a high covering.

### 3.2.8. The Density Diagnostic Lines

• Using the oscillator strengths from NIST for the quoted transitions (rated either B+ or C in the database), the authors find that the relative strength order of the lines matches the observed residual flux for the λλ1190.42, 1193.28, and 1260.37 lines and the weak detection of the λ1304.37 transition.
• While this could be due to a blend, the narrowness of the trough and its location away from any known ISM lines do not support this scenario.
• The column density derived using the PL absorber model is 2.5 times larger than the one assuming the PC model, potentially suggesting an underestimation of the column density when using the PC model.
• While the authors observe a small increase of the derived columns using this PC model, the ratio of column density between the resonance and excited states remains identical (as expected given the similar residual flux inside the C ii and C ii* troughs), strengthening the density diagnostic obtained from these lines.

### 4. PHOTOIONIZATION ANALYSIS OF THE ABSORBERS

• In order to derive the physical properties of each kinematic component of the outflow, the authors solve the ionization equilibrium equations using version c08.00 of the spectral synthesis code Cloudy (last described by Ferland et al. 1998).
• The authors model each absorber by a plane-parallel slab of gas of constant hydrogen number density (nH) and assume solar elemental abundances as given in Cloudy.
• The COS observations show a wealth of absorption lines compared to the earlier FUSE observations discussed in Dunn et al. (2010).
• The authors prefer this formalism to the traditional definition of χ2 since it preserves the multiplicative nature of the errors when dealing with logarithmic values.

### 4.1. Troughs T 2 and T 3

• The physical parameters of component T 2 are constrained by 10 ionic column densities, eight from COS data along with H i and C iii from FUSE data (keeping in mind that the latter have been obtained at a different epoch).
• For component T 3, the authors have column density measurements for seven ions in the COS spectrum, along with H i and C iii from FUSE data and an upper limit on Si ii due to non-detection of the stronger lines in the COS spectrum (see Section 3.2.8).
• This solution fits all the lines within a factor of ∼3 (see Table 4).
• The constraints on the (NH, UH) parameter space for trough T 4 are presented in Figure 11.
• While the saturation observed in the troughs of several ions limits the analysis of the physical properties of the gas, the estimated (NH, UH) solution is able to reproduce most of the ionic columns to within a factor of two.

### 5. ABSORBER DISTANCE AND ENERGETICS

• The label SI corresponds to the single-ionization model, while TIlo and TIhi are the low- and high-ionization phases of the two-ionization model of the absorber.
• To these two kinematic components from the central source.
• Using the derived ionization parameter of that phase, this density implies a distance of R 10.3+5.1−1.6 kpc, where the errors are conservatively computed from the ne range allowed by the Si ii*/Si ii ratio and the error on the ionization parameter.
• This situation is nonphysical since for the inferred temperature of the absorbing gas (T ∼ 104 K) the velocity width of the outflow (Δv 50 km s−1) is at least 10 times larger than the sound speed, and therefore the outflowing material cannot Note.
• The authors note, however, that, using the definition of the filling factor (f = NH/(nHΔR)), this instantaneous mass flow rate relates to the average mass flow rate defined in Equation (7) by the relation ṀTi,ins = ṀTi /(ΔR/R).

### 6. DISCUSSION AND CONCLUSIONS

• The authors analyzed the physical properties of the UV outflow of IRAS F22456−5125 based on high-S/N COS observations.
• Dunn et al. (2010) analyzed that ASCA and XMM-Newton spectra of IRAS F22456−5125 do not reveal any evidence for an X-ray warm absorption edge; however, the limited S/N in these data can still allow the presence of a warm phase with significant column density.
• These observations suggest a model where the low-ionization phase is formed by relatively small, discrete clumps of denser material embedded in a lowerdensity, higher-ionization phase as suggested by Hamann (1998) and Gabel et al. (2005b).
• Comparing the properties of the outflow present in IRAS F22456−5125 and the bona fide AGN outflow observed in NGC 3783 reveals a more complex situation.
• B.B. also thanks S. Penton for the introduction to the HST/COS pipeline.

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The Astrophysical Journal, 751:107 (15pp), 2012 June 1 doi:10.1088/0004-637X/751/2/107
C
A 10 kpc SCALE SEYFERT GALAXY OUTFLOW: HST/COS
OBSERVATIONS OF IRAS F224565125
Benoit C. J. Borguet
1
, Doug Edmonds
1
, Nahum Arav
1
, J ay Dunn
2
, and Gerard A. Kriss
3,4
1
Department of Physics, Virginia Tech, Blacksburg, VA 24061, USA; benbo@vt.edu
2
Augusta Perimeter College, Atlanta, GA, USA
3
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
4
Center for Astrophysical Sciences, Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA
Received 2012 January 6; accepted 2012 March 25; published 2012 May 11
ABSTRACT
We present analysis of the UV spectrum of the low-z AGN IRAS F224565125 obtained with the Cosmic Origins
Spectrograph on board the Hubble Space Telescope. The spectrum reveals six main kinematic components, spanning
a range of velocities of up to 800 km s
1
, which for the ﬁrst time are observed in troughs associated with C ii,Civ,
N v,Siii,Siiii,Siiv, and S iv. We also obtain data on the O vi troughs, which we compare to those available from an
earlier Far Ultraviolet Spectroscopic Explorer epoch. Column densities measured from these ions allow us to derive
a well-constrained photoionization solution for each outﬂow component. Two of these kinematic components show
troughs associated with transitions from excited states of Si ii and C ii. The number density inferred from these
troughs, in combination with the deduced ionization parameter, allows us to determine the distance to these outﬂow
components from the central source. We ﬁnd these components to be at a distance of 10 kpc. The distances and
the number densities derived are consistent with the outﬂow being part of a galactic wind.
Key words: galaxies: active line: formation quasars: absorption lines quasars: individual (IRAS
F224565125)
Online-only material: color ﬁgures, ﬁgure set
1. INTRODUCTION
Mass outﬂows are detected in the UV spectra of more than
50% of low-redshift active galactic nuclei (AGNs), mainly
Seyfert galaxies, e.g., Crenshaw et al. (1999), Kriss et al.
(2002), Dunn et al. (2007), and Ganguly & Brotherton (2008).
These outﬂows are observed as narrow absorption lines (a few
hundred km s
1
in width) blueshifted with respect to the AGN
systemic redshift.
In this paper, we determine the ionization equilibrium, dis-
tance, mass ﬂow rate, and kinetic luminosity of the UV outﬂow
observed in the luminous Seyfert 1 galaxy IRAS F224565125
(z = 0.1016; Dunn et al. 2010). The bolometric luminosity
of this object, L
bol
= 10
45.6
erg s
1
(see Section 4), places it
at the Seyfert/quasar border deﬁned to be 10
12
L
, where L
is the luminosity of the Sun (Soifer et al. 1987). Several ab-
sorption systems are resolved in the UV spectrum in ﬁve main
kinematic components ranging in velocity from 20 km s
1
to
820 km s
1
. A detailed analysis of the physical properties of
the UV absorber determined from Far Ultraviolet Spectroscopic
et al. (2010). These authors report a lower limit on the distance
R of the absorbing material from the central source of 20 kpc
using photoionization timescale arguments.
In 2010 June we observed IRAS F224565125 with the
Cosmic Origins Spectrograph (COS) on board the Hubble Space
Telescope (HST) as part of our program aiming at determining
the cosmological impact of AGN outﬂows (PI: Arav, PID:
11686). The high signal-to-noise spectrum obtained reveals the
presence of absorption troughs associated with high-ionization
species (C iv,Nv,Ovi,Siiv, and S iv), as well as lower ones
(Si ii,Siiii,Cii), thus increasing the number of constraints
on the photoionization analysis of the absorber compared
to Dunn et al. (2010). We also identify absorption troughs
corresponding to excited states of Si ii and C ii associated with
two kinematic components of the UV outﬂow. The population of
the excited state relative to the resonance counterpart provides
an indirect measurement of the number density of the gas
producing the lines (Osterbrock & Ferland 2006). These number
densities allow us to determine reliable distances to these two
components and hence derive their mass ﬂow rates and kinetic
luminosities.
The plan of the paper is as follows: in Section 2, we present
the COS observations of IRAS F224565125, as well as the
reduction of the data and identiﬁcation of the spectral features
within the COS range. In Section 3, we detail the computation
of the column densities associated with every species. We
present the photoionization analysis of the outﬂow components
in Section 4 and report the derived distance, mass ﬂow rate, and
kinetic luminosity in Section 5. We conclude the paper by a
discussion of our results in Section 6. This paper is the second
of a series and the reader will be referred to Edmonds et al.
(2011, hereafter Paper I) for further details on the techniques
used throughout the paper.
2. HST/COS OBSERVATIONS AND DATA REDUCTION
We observed IRAS F224565125 using the COS instrument
(Osterman et al. 2011) on board the HST in 2010 June using both
medium-resolution (Δλ/λ 18,
000) far ultraviolet gratings
G130M and G160M. Sub-exposures of the target were obtained
for each grating through the Primary Science Aperture using
different central wavelength settings in order to minimize the
impact of the instrumental features and to ﬁll the gap between
detector segments, providing a continuous coverage over the
spectral range between roughly 1135–1795 Å. We obtained a
total integration time of 15,056 s and 11,889 s for the G130M
and G160M gratings, respectively.
1
Copyright by the IOP PUBLISHING LTD. Benoit C. J. Borguet et al. 2012. " a 10 kpc scale seyfert galaxy outflow: hst/cos
observations of iras f22456-5125," ApJ 751 107 doi:10.1088/0004-637X/751/2/107

The Astrophysical Journal, 751:107 (15pp), 2012 June 1 Borguetetal.
Figure 1. Full FUV spectrum of IRAS F224565125 obtained by COS. The major absorption troughs related to the intrinsic absorber are labeled. The green line
represents our ﬁt to the non-absorbed emission model (see Section 2.3).
(A color version and the complete ﬁgure set (23 images) of this ﬁgure are available in the online journal.)
The data sets processed through the standard CALCOS
5
ﬂat-ﬁelded and combined together using the COADD_X1D
6
IDL pipeline developed by the COS GTO team (see Danforth
et al. 2010 for details). The reduced spectrum with its original
5
Details on CALCOS can be found in the COS Data Handbook.
6
The routine can be found at http://casa.colorado.edu/danforth/science/
cos/costools.html.
2kms
1
oversampling has an overall signal-to-noise ratio
(S/N) 15 pixel
1
in most of the continuum region. Typical
errors in the wavelength calibration are less than 15 km s
1
.In
Figure 1, we show the majority of the spectrum on which we
identiﬁed major intrinsic absorption features associated with
the outﬂow. The COS FUV spectrum of IRAS F224565125
is presented in greater detail along with the identiﬁcation of
most absorption features (interstellar, intergalactic, and intrinsic
lines) in the online version of Figure 1.
2

The Astrophysical Journal, 751:107 (15pp), 2012 June 1 Borguetetal.
Figure 2. Illustration of the necessity of using a deconvolution algorithm when dealing with COS data (see the text for details). Troughs associated with the intrinsic
absorber signiﬁcantly deepen while the saturated interstellar C ii line exhibits the expected squared black bottom p roﬁle. The main difference between the deconvolved
spectrum using the RL method and the modiﬁed RL algorithm respecting the sampling theorem is the signiﬁcant reduction of oscillations due to the total deconvolution
process performed in RL, even more so when considering a high number of iterations.
(A color version of this ﬁgure is available in the online journal.)
2.1. Identiﬁcation of Spectral Features
Using archived FUSE spectra, Dunn et al. (2007, 2010)
reported the ﬁrst detection of ﬁve distinct kinematic components
with centroid velocities v
1
=−800 km s
1
, v
2
=−610 km s
1
,
v
3
=−440 km s
1
, v
4
=−320 km s
1
, v
5
=−130 km s
1
and FWHM [50, 200] km s
1
associated with an intrinsic UV
outﬂow in IRAS F224565125. These components, spanning a
total velocity range of 800 km s
1
, were detected in O vi,Ciii,
and several lines of the Lyman series (Lyβ to Lyη). Using the
kinematic pattern reported by Dunn et al. (2010) as a template,
we identify absorption features in our COS spectrum related to
both low-ionization (C ii,Siii,Siiii) and high-ionization species
(Si iv,Siv,Civ,Nv,Ovi), as well as in the Lyα transition.
Absorption troughs from the metastable level C ii* λ1335.704
are detected in components 2 and 3, and troughs from metastable
Si ii* λλ1264.738 and 1194.500 are detected in component 2.
While the absorption troughs associated with the higher-
ionization lines generally exhibit broader proﬁles, we observe
a 1:1 kinematic correspondence between the core of these
components and the narrower features associated with the lower-
ionization species of the outﬂow. Given the signiﬁcantly broad
range of velocities covered by the components and their net
kinematic separations, such a match is not likely to occur by
chance. This argues in favor of a scenario where the troughs
of the different ionic species detected in a given kinematic
component are generated in the same region. This observation
is strengthened by the fact that most of the troughs have a line
proﬁle similar to that of the non-blended N v λ1238.820 line
when properly scaled.
The high S/N of our COS observations (S/N 40 per
resolution element on most of the spectral coverage) reveals
the presence of kinematic substructures in several components
of the outﬂow compared to the lower-S/N FUSE observations
(S/N 7; Dunn et al. 2010). Nevertheless, given the self-
blending of these features in the strongest lines (e.g., O vi) and
the absence of apparent change between the FUSE and COS
observations, we will use the labeling of components as deﬁned
in Dunn et al. (2010). We will, however, separate their trough
5 into low- and high-velocity components given the apparent
difference in ionization suggested by the presence of a stronger
Si iii in subcomponent 5A
(v
5A
=−40 km s
1
) than in 5B
(v
5B
=−130 km s
1
) relative to the higher-ionization lines
(C iv,Nv,Ovi; see Figure 3). Most of our analysis in this
paper concentrates on components 2 and 3 of the outﬂow, for
which absorption features associated with an excited state have
been detected.
2.2. Deconvolution of the COS Spectrum
Detailed analysis of the on-orbit COS line-spread function
(LSF) revealed the presence of broadened wings that scatter
a signiﬁcant part of the continuum ﬂux inside the absorption
troughs (see Kriss et al. 2011 for details). This continuum
leaking is particularly strong for narrow absorption troughs
(FWHM 50 km s
1
) in which this effect may signiﬁcantly
affect the estimation of the true column density by artiﬁcially
increasing the residual intensity observed inside the troughs.
Given the overall good S/N of our data, we can correct the
effect of the poor LSF by deconvolving the COS spectrum.
Adopting the procedure described in Kriss et al. (2011), we
deconvolve the spectrum obtained for each grating in 50 Å
intervals using the wavelength-dependent LSFs and an IDL
implementation of the stsdas Richardson–Lucy (RL) “lucy”
algorithm (G. Schneider & B. Stobie 2011, private commu-
nication). The main effect of the deconvolution is illustrated in
Figure 2, in which we clearly see that the deconvolved spectrum
shows signiﬁcantly deepened intrinsic Lyα absorption troughs
and produces a square, black bottom for the saturated interstellar
line C ii λ1334.532.
However, the main drawback of the deconvolution algorithms
commonly used, such as the RL algorithm, is a signiﬁcant
increase of the noise in the deconvolved spectrum due to the
fact that these techniques try to perform a total deconvolution of
the data, i.e., in which the LSF of the deconvolved spectrum is
a Dirac delta function, violating the Shannon sampling theorem
3

The Astrophysical Journal, 751:107 (15pp), 2012 June 1 Borguetetal.
Figure 3. Normalized absorption line proﬁle of the metal lines associated with the outﬂow in IRAS F224565125. The line proﬁles have been deconvolved using
the modiﬁed RL algorithm described in Section 2.2 and rebinned to a common 5kms
1
dispersion velocity scale. For doublets, we overplot the expected residual
intensity in the strongest component based on the residual ﬂux observed in the weakest component assuming an AOD absorber model. For C iv we only plot that
quantity in regions free of self-blending (mainly T 3; see the text).
(A color version of this ﬁgure is available in the online journal.)
(see Magain et al. 1998 for a thorough discussion of these
issues). In order to decrease these effects, we modiﬁed the RL
algorithm by forcing the deconvolved spectrum to have an LSF
satisfying the sampling theorem. We choose the deconvolved
LSFtobeaGaussianwitha2pixelFWHM(5kms
1
given the COS detector sampling). This operation prevents the
appearance of strong unwanted oscillations since we force the
maximum resolution that can be achieved in the deconvolved
data to agree with the sampling theorem. The deconvolved
spectrum produced by this modiﬁed RL algorithm is similar to
the one obtained by the traditional RL algorithm (see Figure 2),
the main difference being the signiﬁcant decrease of the high
frequencies and high-amplitude features artiﬁcially generated
by RL deconvolution with a high number of iterations. In our
analysis, we will derive the column density for each ionic
species using the spectrum deconvolved with the modiﬁed RL
algorithm, allowing us to derive more accurate column densities
associated with the narrow absorption components observed in
IRAS F224565125.
2.3. Unabsorbed Emission Model
The unabsorbed emission model F
0
(λ) of IRAS F22456
5125 is constructed in a similar manner to the one described
in detail for IRAS F042505718 in Paper I, in which we
consider three main sources of emission: a continuum, a broad
emission line (BEL) component, and a narrow emission line
(NEL) component. Adopting a single power law (PL) F (λ) =
F
1150
(λ/1150)
α
to describe the deredenned (E(B V ) =
0.01035; Schlegel et al. 1998) continuum emission, we obtain
4

The Astrophysical Journal, 751:107 (15pp), 2012 June 1 Borguetetal.
a reduced χ
2
red
= 1.413 over emission/absorption line free
regions of the rest wavelength spectrum ([1115, 1130] Å,
[1340,1360] Å, and [1455,1475] Å) with α =−1.473 ± 0.068
and F
1150
= 2.13010
14
± 0.003310
14
erg cm
2
Å
1
s
1
.
Prominent BEL features observed in the spectrum (Lyα,Civ,
O vi) are ﬁt using two broad Gaussians of FWHM 9000 and
2000 km s
1
. The NEL component of each line of a doublet is ﬁt
by a single narrower Gaussian (FWHM 600 km s
1
) centered
around the rest wavelength of each line, with the separation of
the two Gaussians ﬁxed to the velocity difference between the
doublet lines. The NEL of the strong Lyα lineisbestﬁtbytwo
Gaussians of FWHM 1200 and 400 km s
1
. The remaining
weaker emission features in the spectrum (Si iv+O iv,Cii,Nv,
O i, etc.) are modeled by a smooth cubic spline ﬁt. A normalized
spectrum is then obtained by dividing the data with the emission
model. We present our best ﬁt to the unabsorbed spectrum of
IRAS F224565125 in Figure 1.
3. COLUMN DENSITY DETERMINATION
3.1. Methodology
The column density associated with a given ionic species
detected in the outﬂow is determined by modeling the residual
intensity in the normalized data of the absorption troughs.
Assuming a single homogeneous emission source F
0
(v) and
a one-dimensional spatial distribution of optical depth across
the emission source τ
i
(x,v), we can express the intensity F
i
(v)
observed for a line i as (Arav et al. 2005)
F
i
(v) = F
0
(v)
1
0
e
τ
i
(x,v)
dx, (1)
where v is the radial velocity of the outﬂow and the spatial
extension of the emission source is normalized to 1. Once the
optical depth solution τ
i
(x,v) is derived at a given radial veloc-
ity, we link the observed residual intensity I
i
(v) = F
i
(v)/F
0
(v)
to the ionic column density using the relation
N
ion
(v) =
3.8 × 10
14
f
i
λ
i
τ
i
(v)(cm
2
km
1
s), (2)
where f
i
, λ
i
, and τ
i
(v) are the oscillator strength, the rest
wavelength, and the average optical depth across the emission
source of line i (see Paper I), respectively.
We consider here the three absorber models (i.e., optical depth
distributions) discussed in Paper I: the apparent optical depth
(AOD), partial covering (PC), and PL models. We use these three
models in order to account for possible inhomogeneities in the
absorber (see Section 6), which cause t he apparent strength ratio
R
a
= τ
i
j
of two lines i, j from a given ion to deviate from the
expected laboratory ratio R
l
= λ
i
f
i
j
f
j
(e.g., Wampler et al.
1995; Hamann 1997;Aravetal.1999). Wherever possible we
derive these three optical depth solutions for ions with multiple
transitions. However, as mentioned in Paper I, we consider the
results obtained with the PL model performed on doublets with
caution given its increased sensitivity to the S/N, which can
lead to severe overestimation of the underlying column density
(Arav et al. 2005). For singlet lines we will generally only derive
a lower limit on the column density using the AOD method. This
lower limit will be considered a measurement in cases where the
singlet line is associated with a kinematic component for which
other multiplets do not show signs of saturation. In the following
subsections, we use the term (non-black) saturation to qualify
Tab le 1
Atomic Data for the Observed Transitions
Ion E
low
a
λ
i
b
g
low
c
f
i
d
(cm
1
)(Å)
H i 0.00 1215.670 2 0.4164
C ii 0.00 1334.532 2 0.1290
C ii* 63.42 1335.704
e
4 0.1277
C iv 0.00 1548.202 2 0.1900
C iv 0.00 1550.774 2 0.0952
N v 0.00 1238.821 2 0.1560
N v 0.00 1242.804 2 0.0780
O vi 0.00 1031.912 2 0.1330
O vi 0.00 1037.613 2 0.0660
Si ii 0.00 1190.416 2 0.2770
Si ii 0.00 1193.280 2 0.5750
Si ii* 287.24 1194.500 4 0.7370
Si ii 0.00 1260.422 2 1.2200
Si ii* 287.24 1264.730 4 1.0900
Si ii 0.00 1304.370 2 0.0928
Si ii 0.00 1526.720 2 0.1330
Si iii 0.00 1206.500 1 1.6700
Si iv 0.00 1393.760 2 0.5130
Si iv 0.00 1402.770 2 0.2550
S iv 0.00 1062.656 2 0.0500
Notes.
a
Lower-level energy.
b
Wavelength of the transition.
c
Statistical weight.
d
Oscillator strength. We use the oscillator strengths from the National Institute
of Standards and Technology (NIST) database, except for S iv, for which we
use the value reported in Hibbert et al. (2002).
e
Blend of two transitions; we report the sum of the oscillator strength and the
weighted average of λ
i
.
absorption troughs of doublets in which R
a
= τ
i
j
< 0.75 R
l
,
where τ
i
and τ
j
are the AOD of the strongest and the weakest
component of the doublet, respectively.
3.2. Column Density Measurements
Computed ionic column densities are determined using the
deconvolved line proﬁles presented in Figure 3 and the ionic
transition properties reported in Table 1. The computed column
densities are reported in Table 2 for the three absorber models
when possible. The adopted values shown in the last column
of Table 2 are the ones used in the photoionization analysis.
When available, we choose to use the value reported in the PC
column as the measurement and use the PL measurement and
error as the upper error in order to account for the possible
inhomogeneities i n the absorbing material distribution. If only
the AOD determination is available, we will consider the
reported value minus the error as a lower limit unless we have
evidence suggesting a high covering.
3.2.1. H
i
The spectral coverage of the COS G130M and G160M
gratings only allows us to cover the Lyα line that shows a deep
and smooth proﬁle in which the different kinematic components
blend. The absence of higher-order Lyman series lines restricts
us to put a lower limit on the H i column density by applying
the AOD method to the Lyα proﬁle.
A better constraint on the H i column density is determined
by using higher-order Ly-series lines from earlier FUSE data
(Dunn et al. 2010). In Figure 4, we compare the 2010 June
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