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

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 (

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]

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

) with bulge mass [

] and

stellar velocity dispersion of the host-galaxy [

]. 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 [

] 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 [

] or sweep up gas reservoirs from the host-galaxy [

] and reduce SF activity

[

]. However, some studies found evidence of positive feedback in which AGN-driven

outﬂows trigger local SF through the compression of ISM [

] and/or providing physical

conditions for SF occurring within outﬂows [

]. Most recently, Bessiere and Almeida [

] 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 .

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 [

–

]. However the results are not unanimous. Mullaney et al. [

] ana-

lyzed the [O III]

5007Å proﬁle for a large sample of nearby AGNs and found that AGNs with

1.4 GHz >

W Hz

−1

are much more likely to exhibit extremely broad [O III]

5007Å lines

compared to weak radio AGNs. They concluded that in comparison with [O III]

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 [

]. In contrast,

using a large sample of optically-selected Type 2 AGNs, Woo et al. [

] reported that while the

kinematics of ionized gas traced by [O III]

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 [

]. It is worth mentioning that both Woo et al. [

] and Rakshit

and Woo [

] also observed that the width of [O III]

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. [

] 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

= 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 [

]) 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

0.01 are usually very extended, resulting in

a lack of a reliable optical position. On the other hand, at higher redshifts of

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

, H

, [O III]

5007 and [N II]

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 [

] 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; [

])

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

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

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

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

or 3

, we

ﬁnally adopt a match criterion of 3

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. [

] 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. [

]) below the FIRST

detection limit (5

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

from the optical core using

three catalogs from the sensitive, wide and ﬂexible X-ray surveys as follows. I) The 3XMM-DR8

[

] 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 [

] 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

. 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. [

] and the dotted line shows the division of Seyferts and

LINERs (Low Ionization Nuclear Emission-Line Regions) from Schawinski et al. [

]. 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



−1

) in order to produce an X-ray luminosity

X∼

erg s

−1

[

], we select sources with hard X-ray luminosity of L

2−10 keV >

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

= 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 [

] in Figure 2. A small fraction of our sources (70

targets) reside in the star-forming region deﬁned by Kauffmann et al. [

]. 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. [

] 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 [

] or Li et al. [

]

who provided radio AGN catalogues in total including ∼19,000 sources.

- Finally, 18 targets are identiﬁed as AGNs in these studies: Anderson et al. [

]; 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).

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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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