Exploring the Fundamental Mechanism in Driving Highest-velocity Ionized Outflows in Radio AGNs_2

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Article
Exploring the Fundamental Mechanism in Driving
Highest-velocity Ionized Outflows in Radio AGNs
Ashraf Ayubinia 1,2,3*, Yongquan Xue 1,2*, Jong-Hak Woo 3, Huynh Anh Nguyen Le1,2, Zhicheng He1,2,Halime
Miraghaei4, Xiaozhi Lin1,2
1CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science
and Technology of China, Hefei 230026, China
2School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China
3Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
4
Research Institute for Astronomy and Astrophysics of Maragha (RIAAM), University of Maragheh, Maragheh, Iran
*ayubinia@mail.ustc.edu.cn, xuey@ustc.edu.cn
Abstract:
We investigate the ionized gas kinematics relationship with X-ray, radio and accreting properties
using a sample of 348 nearby (
z<
0.4) SDSS-FIRST-X-ray detected AGNs. X-ray properties of our sample
are obtained from XMM-
Newton
,
Swi f t
and
Chandra
observations. We unveil the ionized gas outflows in
our sample manifested by the non-gravitational broad component in [O III]
λ
5007Å emission line profiles.
From the comparison of the correlation of non-parametric outflow velocities (i.e., the velocity width, the
maximal velocity of outflow and line dispersion) with X-ray luminosity and radio luminosity, we find
that outflow velocities have similarly positive correlations with both X-ray and radio luminosity. After
correcting for the gravitational component, we find that the [O III] velocity dispersion normalized by
stellar mass also increases with both X-ray luminosity and radio luminosity. We also find that for a given
X-ray (radio) luminosity, radio (X-ray) luminous AGNs have higher outflow velocities than non-radio
(non-X-ray) luminous AGNs. Therefore, we find no clear preference between X-ray luminosity and radio
luminosity in driving high-velocity ionized outflows and conclude that both AGN activity and small-scale
jets contribute comparably. Moreover, there is no evidence that our obscured AGNs are preferentially
associated with higher velocity outflows. Finally, we find a turning point around log
(λEdd)' −
1.3 when
we explore the dependency of outflow velocity on Eddington ratio. It can be interpreted considering
the role of high radiation pressure (log
(λEdd)&−
1.3) in drastic reduction in the covering factor of the
circumnuclear materials.
Keywords:
Active galactic nuclei; Supermassive black holes; Kinematics and dynamics kinematics and
dynamics
1. Introduction
The coevolution of supermassive black holes and their host-galaxies is usually invoked
to explain the well-known correlation of black hole mass (M
BH
) with bulge mass [
1
,
2
] and
stellar velocity dispersion of the host-galaxy [
3
,
4
]. These black holes grow through the feeding
on circumnuclear materials and are visible as active galactic nuclei (AGNs). The outgoing
emission spanning the entire electromagnetic spectrum is the product of accretion. The energy
released effectively couples to the material in the host-galaxy and impacts on the environment
of the black hole (namely, AGN feedback), from small to large scales. However, it is still not
well understood how AGN feedback affects the interstellar medium (ISM) of the host-galaxy
and more dedicated models and observations are required [5–8].
Journal Not Specified 2022,1, 0. https://doi.org/10.3390/1010000 https://www.mdpi.com/journal/notspecified
arXiv:2210.02828v1 [astro-ph.GA] 6 Oct 2022
Journal Not Specified 2022,1, 0 2 of 23
Multi-phase outflows, frequently detected in local and high redshift galaxies, are capable
of interacting with ISM and hence, they are one of the fundamental tracers of AGN feedback
(see Fabian [
9
] for a review). A wide range of studies invoked the negative feedback scenario
to explain the suppression of star formation (SF) by AGN-driven outflows in which powerful
outflows heat [
10
] or sweep up gas reservoirs from the host-galaxy [
11
] and reduce SF activity
[
12
]. However, some studies found evidence of positive feedback in which AGN-driven
outflows trigger local SF through the compression of ISM [
13
,
14
] and/or providing physical
conditions for SF occurring within outflows [
15
]. Most recently, Bessiere and Almeida [
16
] put
up a scenario in which quasar-driven outflows can simultaneously produce both modes of
feedback.
There is no clear mechanism for driving galactic-scale outflows. In luminous AGNs
accreting close to Eddington limit, it is believed that the strong radiation pressure pushes
the gas away from the nuclear region and forms the observed outflows (so-called radiative
or quasar-mode feedback). However, an alternative feedback mechanism, so-called radio or
kinetic mode feedback, is in favour of radio galaxies with relativistic jets usually hosted by
massive elliptical galaxies. According to this scenario, low-luminosity AGNs are radiatively
inefficient to expel gas to large scales, instead, radio jets that carry much of the energy output
in form of kinetic energy, can be effective enough to impact on ISM and drive outflows.
Particularly, young radio jets with low to moderate radio power (L
1.4 GHz .
10
25
W Hz
−1
)
can penetrate into ISM and alter gas kinematics. Higher power radio jets are presumed to be
highly collimated that pierce the ISM without disturbing gas significantly (see the discussion
in Wylezalek and Morganti [17]). However, the fact is that the observational disentanglement
of different modes of AGN feedback is not straightforward.
Recent observational studies have tried to shed light on the link between outflows and
radio emission [
18
–
20
]. However the results are not unanimous. Mullaney et al. [
21
] ana-
lyzed the [O III]
λ
5007Å profile for a large sample of nearby AGNs and found that AGNs with
L
1.4 GHz >
10
23
W Hz
−1
are much more likely to exhibit extremely broad [O III]
λ
5007Å lines
compared to weak radio AGNs. They concluded that in comparison with [O III]
λ
5007Å lu-
minosity, radio luminosity has the most profound effect on the disturbing gas kinematics in
radio AGNs. Moreover, recent integral field spectroscopy observations found evidence of
enhanced line widths in AGNs that host low-power jets with low inclination with respect to the
galaxy disc, suggestive of strong interaction between radio jets and the ISM [
22
]. In contrast,
using a large sample of optically-selected Type 2 AGNs, Woo et al. [
23
] reported that while the
kinematics of ionized gas traced by [O III]
λ
5007Å emission line strongly correlates with AGN
radiation, ionized gas outflows are not connected to the radio activity. A similar conclusion
was given for Type 1 AGNs [
24
]. It is worth mentioning that both Woo et al. [
23
] and Rakshit
and Woo [
24
] also observed that the width of [O III]
λ
5007Å profiles ([O III] velocity dispersion)
increases with radio luminosity, however, they noticed such a trend fades after correcting for
the effect of host-galaxy gravitational component (see Section 4.2).
Since the radio luminous sources are predominantly associated with AGNs with higher
X-ray luminosity, it is important to control X-ray luminosity when we explore the correlation
between ionized gas kinematics and radio emission. Despite the great insight provided by
previous works using large samples, those studies suffer from the lack of such controlling. A
recent study by Harrison et al. [
25
] provided a sample of X-ray detected radio AGNs with
ionized outflow signature. When compared to non-radio-luminous sources, they found that
a higher fraction of radio-luminous AGNs have high velocity line widths. However, due
to lack of enough targets, they were unable to test their results while X-ray luminosity is
controlled. Hence, in this work our primary interest is to explore the dependency of the
kinematic properties of ionized gas outflows on both X-ray luminosity and radio luminosity,
while we control luminosities during our investigations to understand which mechanism is
Journal Not Specified 2022,1, 0 3 of 23
Figure 1.
Absolute extinction-corrected r-band magnitude as a function of redshift. Grey dots and purple
circles show our parent sample and final sample; the sources identified as AGN in some other works are
also shown (Section 2.3). The dashed curve shows the SDSS Petrosian r-band magnitude corresponding
of rpetro = 17.77.
more responsible for driving highest-velocity ionized outflows using a sample of nearby AGNs.
In Section 2we describe our sample construction. In Section 3we present our data analyses.
In Section 4we discuss the relation of ionized gas outflows with X-ray, radio and accreting
properties of our sample and in Section 5we draw our conclusions. A cosmology with
H0
= 71
km s−1Mpc−1,Ωm= 0.27 and ΩΛ= 0.73 is used throughout the paper.
2. Sample Construction
Our initial sources are selected from the Sloan Digital Sky Survey (SDSS) which is a
large-area multiband spectral imaging and spectroscopic redshift survey and covers 14,555
square degrees of the sky. We use the data from the Data Release 15 (DR15 [
26
]) as the third
data release of the fourth phase of the SDSS (SDSS-IV) and that includes all the sky coverage
of prior releases. By applying the Structured Query Language (SQL), we collect emission-line
objects that satisfy the following:
• Being spectroscopically classified as “GALAXY” or “QSO” by the SDSS DR15.
•
Having a secure redshift of 0.01
<z<
0.4 (ZWARNING = 0, indicating a confident
spectroscopic classification). Galaxies at
z<
0.01 are usually very extended, resulting in
a lack of a reliable optical position. On the other hand, at higher redshifts of
z>
0.4 the
quality of the SDSS spectrum is usually low.
• Having a median signal-to-noise ratio (S/N) ≥10.
•
Having four emission lines, H
α
, H
β
, [O III]
λ
5007 and [N II]
λ
6584, whose intensities are at
least 2 times larger than their corresponding measured errors.
Using the above criteria we obtain 322,006 emission-line galaxies and hereafter we define them
as our parent sample. The grey points in Figure 1represent the absolute extinction-corrected
r-band magnitudes of our parent sample as a function of redshift. The r-band magnitude is
corrected using the dust map of Schlafly and Finkbeiner [
27
] and extinction law of Fitzpatrick
[28].
2.1. Cross-correlation: SDSS-FIRST
Since the area of the Faint Images of the Radio Sky at Twenty-centimeters (FIRST; [
29
])
survey has been chosen to coincide with that of SDSS, nearly one third of its sources have
Journal Not Specified 2022,1, 0 4 of 23
optical counterparts in the SDSS. Therefore, we utilize the FIRST survey to find our radio
sources. The survey uses the NRAO Very Large Array (VLA) to observe 9,000 square degrees
in the north Galactic cap and a smaller strip along the celestial equator at 1365 and 1435 MHz.
To select galaxies with detected radio core emission (or small-scale jet), we cross-correlate our
parent sample with all FIRST sources. It is important to reduce the number of coincidental
false matches during the cross-correlation process. Therefore, we test three different matching
radii and estimate the number of random false matches in each case. At first, we search for
the best matched (nearest-neighbour) radio sources within 2
00
angular separation from the
optical core and we find 17,918 matches. We next offset the positions (RA and DEC) of the
SDSS sources by 1
◦
and re-matched them with the FIRST catalogue. We find on average 28
random matches, corresponding to
∼
0.2% contamination from coincidental matches (
>
99.8%
efficiency). We then repeat this algorithm for matching radius 3
00
and find that the selection
efficiency is
∼
99.6% (with on average 68 random matches among 18,372 matches). The fraction
of false matches increases to
∼
1% (efficiency
∼
99%) when we cross-correlate SDSS galaxies
with the FIRST sources within 5
00
angular separation. Considering the fact that none of the false
matches is included in our final sample when we use the matching radius of either 2
00
or 3
00
, we
finally adopt a match criterion of 3
00
for cross-correlating our parent sample with the FIRST
sources to have a more complete sample. We classify these matched sources into resolved and
unresolved radio galaxies based on the definition from Banfield et al. [
30
] as a resolved source
satisfies the criterion:
Speak/Sint <1.0 −(0.1/log(Speak)), (1)
where
Speak
and
Sint
are the peak flux density and integrated flux density measured in
mJy at 1.4 GHz, respectively. We next exclude sources with the radio flux (integrated flux
for resolved and peak flux for unresolved sources; see also Zhu et al. [
31
]) below the FIRST
detection limit (5
σ
flux limit is 1 mJy). Therefore, we consider the surviving 18,153 SDSS-FIRST
detected galaxies as the ‘radio sample’ for the following investigations.
2.2. Cross-correlation: SDSS-FIRST-X-ray Surveys
We identify X-ray counterparts of our radio sample within 5
00
from the optical core using
three catalogs from the sensitive, wide and flexible X-ray surveys as follows. I) The 3XMM-DR8
[
32
] which is the third-generation catalogue of serendipitous X-ray sources from the XMM-
Newton
observatory and contains 531,454 unique X-ray sources drawn from a total of 10,242
XMM-
Newton
EPIC observations. A number of 522 of our galaxies in the radio sample have
X-ray counterparts in this catalogue. II) The 1SWXRT catalogue of the serendipitous sources
detected in the 7 years (2005-2011) of
Swi f t
-XRT observations with exposure time longer than
500 s [
33
] including a total of
∼
36,000 distinct X-ray sources. We find that 227 sources of our
radio sample are included in this catalogue. III) The full z
<
0.4 spectroscopic
Chandra
/SDSS
catalogue [34] including 617 sources from the Chandra Source catalogue matched to the SDSS
DR7 spectroscopic catalogue. A cross-matching procedure of our radio sample with this cata-
logue returns 117 sources. There are 106 radio galaxies which are common between at least two
X-ray catalogs. In this case, we choose the survey with the highest X-ray photon count. We also
estimate the false-match rates in cross correlating of radio sample with X-ray catalogs similar
as in Section 2.1 for matching radii 5
00
. Except two random matches from
Swi f t
catalog, we
find no false-match cases. Since these two sources do not impact on our results we keep them.
As such, we obtain X-ray data for 760 individual sources from our radio sample. Afterward,
we call these SDSS-FIRST-X-ray detected galaxies as the ‘full sample’.
Journal Not Specified 2022,1, 0 5 of 23
Figure 2.
The BPT diagram with our final sample (denoted by purple circles). The solid curve is the
classification curve from Kauffmann et al. [
36
] and the dotted line shows the division of Seyferts and
LINERs (Low Ionization Nuclear Emission-Line Regions) from Schawinski et al. [
37
]. The contours show
our parent sample.
2.3. Exclusion of Star-forming Galaxies
It is important to avoid selecting pure star-forming galaxies whose X-ray emission is
dominated by star formation. Here, we explain our efforts to discriminate between star-forming
galaxies and AGNs among our full sample. Given that a pure star-forming galaxy should have
an extreme star-formation rate (SFR
&
1900 M
yr
−1
) in order to produce an X-ray luminosity
L
X∼
10
42
erg s
−1
[
25
], we select sources with hard X-ray luminosity of L
2−10 keV >
10
42
erg s
−1
,
where X-ray emission is AGN-dominated. For this step, we estimate X-ray luminosity using
the observed fluxes from X-ray catalogues with the assumption of photon index
Γ
= 1.7 for all
sources (see Section 2.2). The selection of other values for photon index does not impact on our
final sample significantly. This process reduces our full sample into 348 sources. We next plot
these remaining targets on the BPT diagram [
35
] in Figure 2. A small fraction of our sources (70
targets) reside in the star-forming region defined by Kauffmann et al. [
36
]. It is very possible
that radio-quiet AGNs (whose radio emission is produced by a variety of possible mechanisms
such as star formation (see Panessa et al. [
38
] for a review) overlap star-forming region based
on emission-line diagnostic. Therefore, we check the reliable classification for each source in
the literatures when it is available. We summarize this procedure as follows:
- We find that 28 targets are identified as quasar in the SDSS DR14 quasar catalogue
(DR14Q [39]).
- We find 16 targets labeled as radio AGN by either Best and Heckman [
40
] or Li et al. [
41
]
who provided radio AGN catalogues in total including ∼19,000 sources.
- Finally, 18 targets are identified as AGNs in these studies: Anderson et al. [
42
]; Sun and
Shen [43]; Véron-Cetty and V´ron [44]; Monroe et al. [45].
Overall, a very high fraction (i.e., 62/70) of the sources which reside in the BPT star-
forming region are classified as AGNs in previous studies. Therefore, we keep all the 70 targets
and identify 348 AGNs in total detected in optical, radio and X-ray as our ‘final sample’ (see
Figure 1for the redshift distribution of absolute extinction-corrected r-band magnitude for our
final sample).
摘要：

Citation:Title.JournalNotSpecied2022,1,0.https://doi.org/Received:Accepted:Published:Publisher'sNote:MDPIstaysneutralwithregardtojurisdictionalclaimsinpublishedmapsandinstitutionalafl-iations.Copyright:©2022bytheauthors.LicenseeMDPI,Basel,Switzerland.Thisarticleisanopenaccessarticledistributedunde...

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