11institutetext: INAF - IASF Palermo, Via U. La Malfa 153, I-90146 Palermo,
Italy 22institutetext: Università degli Studi di Palermo, Dipartimento di
Fisica e Chimica, via Archirafi 36, I-90123 Palermo, Italy 33institutetext:
MIT Kavli Institute for Astrophysics and Space Research, Massachusetts
Institute of Technology, Cambridge, MA 02139, USA 44institutetext: Department
of Astronomy and Astrophysics, University of Chicago, 5640 S Ellis Avenue,
Chicago, IL 60637, USA 55institutetext: Université de Toulouse, CNRS, IRAP, 9
Avenue du colonel Roche, BP 44346, 31028 Toulouse Cedex 4, France
66institutetext: Dipartimento di Matematica e Fisica, Università degli Studi
Roma Tre, via della Vasca Navale 84, I-00146 Roma, Italy 77institutetext: ESA
European Space Research and Technology Centre (ESTEC), Keplerlaan 1, 2201 AZ,
Noordwĳk, The Netherlands 88institutetext: Telespazio UK for the European
Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino Bajo del
Castillo, s/n, 28692 Villanueva de la Cañada, Madrid, Spain 99institutetext:
Centre for Astrophysics Research, University of Hertfordshire, College Lane,
Hatfield AL10 9AB, UK

# A systematic study of the ultra-fast outflow responses to luminosity
variations in active galactic nuclei

Yerong Xu<EMAIL_ADDRESS>Ciro Pinto 11 Daniele Rogantini 3344 Didier
Barret 55 Stefano Bianchi 66 Matteo Guainazzi 77 Jacobo Ebrero 88 William
Alston 99 Erin Kara 33 Giancarlo Cusumano 11

(Received XXX; accepted XXX)

###### Abstract

Context. Ultra-fast outflows (UFOs) have been revealed in a large number of
active galactic nuclei (AGN) in the past two decades. Their extreme velocities
and high ionization states make them a promising candidate for AGN feedback on
the evolution of the host galaxy. However, their exact underlying driving
mechanism is not yet fully understood.

Aims. Given that the variability of UFOs may be used to distinguish among
different launching mechanisms, we aim to search for and characterize the
responses of the UFO properties to the variable irradiating luminosity.

Methods. We performed a high-resolution time- and flux-resolved spectroscopy
of archival XMM-Newton observations on six highly-accreting narrow-line
Seyfert 1 (NLS1) galaxies, selected by UFO detection and sufficient exposure
times. The state-of-the-art methods of the blind Gaussian line scan and
photoionization model scan are used to identify UFO solutions. We search for
ionized winds and investigate structure of ionized winds and their responses
to the luminosity variations. The location, density, and kinetic energy of
UFOs are estimated as well.

Results. The powerful photoionization model scan reveals three previously
unreported UFOs in RE J1034+396, PG 1244+026 and I ZW 1 with a detection
significance above $3\sigma$, and two new warm absorbers (WAs) in RE
J1034+396. 5 out of 6 (83%) AGN in our sample hosts multi-phase ionized winds,
where outflows in I ZW 1 are energy-conserved. The relatively low-ionization
entrained UFOs are discovered in 4 (66%) AGN of our sample, supporting the
shocked outflow interpretation for ionized winds in AGN. We notice that 2 out
of 7 (28%) UFOs in our sample seem to respond to the radiation field and 3
(43%) UFOs hint at a radiatively accelerated nature, requiring further
observations. Combined with published works, we do not find any correlations
between UFO responses and AGN properties except for a tentative ($\sim
1.8\sigma$) anti-correlation between the UFO acceleration and the Eddington
ratio, to be confirmed by further observations and an enlarged sample. The
kinetic energy of UFOs, mostly detected in soft X-rays, is found to have a
large uncertainty. We, therefore, cannot conclude whether soft X-ray UFOs have
sufficient energy to drive the AGN feedback, although they are very promising
based on some reasonable assumptions. The primary UFO in I ZW 1 (detected in
the hard X-ray) is the only case in our sample to possess conclusively
sufficient energy to affect the host galaxy.

###### Key Words.:

Black hole physics – X-rays: galaxies – Galaxies: Seyfert

##  1 Introduction

Ultra-fast outflows (UFOs) were first discovered in the X-ray spectra of
active galactic nuclei (AGN) through blueshifted Fe xxv/xxvi absorption lines
around 7 keV (e.g. Chartas et al., 2002, 2003; Pounds et al., 2003; Reeves et
al., 2003). In the past two decades, a number of high column density
($N_{\mathrm{H}}>10^{22}\mathrm{cm}^{-2}$), highly ionized ($\log\xi>3$)
ultra-fast ($v\geq 10000$ km/s or 0.03c) outflows have been found in both
nearby and high-z AGN with a detection rate around 30% (e.g. Tombesi et al.,
2010; Patrick et al., 2012; Gofford et al., 2013; Igo et al., 2020; Chartas et
al., 2021; Matzeu et al., 2023). The ultra-fast velocity suggests an origin
from the innermost regions around the central supermassive black holes
(SMBHs). Such extreme physical properties can result in a large amount of
kinetic power, possibly sufficient to match the theoretical predictions of
effective AGN feedback models (e.g. Di Matteo et al., 2005; Hopkins & Elvis,
2010). UFOs, therefore, are expected to play a crucial role in regulating the
growth of the SMBHs and the bulges of the host galaxies (e.g. Fabian, 2012,
and references therein), offering a promising explanation for the observed
well-known AGN-galaxy relation (e,g. $M_{\mathrm{BH}}\mbox{--}\sigma$,
Kormendy & Ho, 2013, and references therein).

UFOs were not only detected in the hard X-ray band but also resolved in the
soft X-ray band, thanks to the high-resolution grating instruments, i.e., the
Reflection Grating Spectrometer (RGS, Den Herder et al., 2001) onboard XMM-
Newton (Jansen et al., 2001) and the High Energy Transmission Gratings (HETG,
Canizares et al., 2005) onboard Chandra (Weisskopf et al., 2002). The high-
resolution capability can distinguish UFOs from the slow and moderately
ionized outflows (the so-called warm absorbers, WAs) in the soft X-ray band.
Compared with the Fe xxv and xxvi features, which are usually unresolved by
the current CCD detectors and have the potential degeneracy with the X-ray
reprocessing emission (Gallo & Fabian, 2011, 2013; Zoghbi et al., 2015; Parker
et al., 2022), UFOs in soft X-rays can be identified through multiple ion
transitions (e.g., O vii and O viii, Longinotti et al., 2015; Pounds et al.,
2016b; Pinto et al., 2018; Xu et al., 2022), providing more convincing
evidence for the UFO existence. Recently, some atypical UFOs have been
detected in the soft X-rays, as they share a similar velocity range but have a
lower column density ($N_{\mathrm{H}}\leq 10^{22}\,\mathrm{cm}^{-2}$) and a
lower ionization state ($\log\xi\leq 4$) than the highly ionized iron K
absorbers, revealing the multi-phase origin of UFOs (e.g., Reeves et al.,
2016; Serafinelli et al., 2019; Krongold et al., 2021; Xu et al., 2023).

In spite of the large number of UFOs detected in AGN, the exact wind-driven
mechanism has not been well understood so far. The radiatively-driven (e.g.,
Proga et al., 2000; Sim et al., 2010; Hagino et al., 2016) and magnetically-
driven (MHD, e.g., Kato et al., 2004; Fukumura et al., 2010, 2015) mechanisms
were proposed to accelerate winds to relativistic speeds. The former scenario
is naturally expected in high-accretion systems, such as narrow-line Seyfert 1
(NLS1) galaxies, which host the low-mass and highly accreting SMBHs (e.g.,
Komossa, 2008), and quasars, while magnetically-driven UFOs are anticipated in
low-accretion systems. The radiation explanation is supported by the
correlation between UFO velocity and source luminosity noticed in PDS 456
(Matzeu et al., 2017), IRAS 13224-3809 (Pinto et al., 2018), and Mrk 1044 (Xu
et al., 2023). However, the exact behavior of UFOs is complex. For example in
1H 0707-495, an anti-correlation between the UFO velocity and source flux was
observed. It was explained by the slim inner accretion flow at super-Eddington
states, extending the wind launching radii outwards, resulting in a lower
velocity (Xu et al., 2021b), although alternative scenarios invoking MHD might
be possible. Motivated by such complexity, we aim to perform a systematic
study of UFO response to the source variability to better understand their
nature and launching mechanisms.

In this study, we will show the detailed high-resolution spectroscopic
analysis of a sample of UFOs in 6 nearby NLS1 galaxies, observed by XMM-Newton
space telescope, mainly focusing on the RGS data. In Sec. 2 and Sec. 3, we
will list the sample selection criteria and our data reduction processes
respectively. The adopted analysis methods are described in Sec. 4. Our
results are summarized in Sec. 5, where we find previously unreported UFOs in
three AGN, and further study the relationship between the UFO properties and
the source. We discuss our results and compare them with the literature in
Sec. 6. Finally, in Sec. 7 we draw our conclusions and point out prospects.

##  2 Sample Selection

The systems of interest in our study are AGN with UFOs. We thus explored the
archival XMM-Newton dataset, in particular RGS spectra, which possess both
high spectral resolution and sufficient photons due to its large effective
area in the soft X-ray band. Our selection is based on the following
considerations:

  1. (1)

A UFO has to be detected in the system. Since we are also interested in
discovering new UFOs in AGN, the search is not limited to the UFO-reported
AGN, but rather is extended to all Seyfert galaxies and quasars with an XMM-
Newton exposure time of $>50\,$ks, resulting in a sample of 307 targets. The
long exposure time is necessary for RGS to detect and resolve narrow lines
(e.g. see Fig. 11 in Kosec et al., 2018).

  2. (2)

The UFO absorption features in the soft X-ray band might be heavily
contaminated by the transient obscuration event or the persistent torus
obscuration. Thus only AGN with a neutral column density
$\log{N_{\mathrm{H}}/\mathrm{cm}^{-2}}<22$ are selected, leading to the sample
size down to 179.

  3. (3)

To detect the potential UFO response to the source variability, we need enough
counts to perform the time-/flux-resolved spectroscopy. In the initial stage,
we adopted the product of the averaged RGS flux at $15\AA$ and the total
exposure time as a probe for the number of soft X-ray counts, which is easily
accessed through the XMM-Newton Science Archive (XSA). The exact number of
counts is obtained by extracting the RGS spectra (listed in column 6 of
Tab.1). The threshold is set at half the soft counts of PDS 456, which is the
target with the least soft X-ray counts among four previously analyzed
sources, i.e. 50000, to ensure statistics. The resulting sample size becomes
29.

  4. (4)

The detection significance of UFO is a key quantity for the strict constraints
on parameters, which are indispensable for the discovery of UFO response.
Therefore, we selected out sources with a UFO detection of $\Delta\rm
C\mbox{-}stat>30$ for additional 4 degrees of freedom (d.o.f.),
i.e.$>4.6\sigma$, in the stacked spectrum to ensure constraints on UFO
parameters in the flux-/time-resolved spectra. This filter cannot be directly
applied before performing the physical modeling, so we modified the size of
our sample during the analysis and ended up with a number of 6.

Our final sample consists of 10 AGN, including 4 previously studied AGN, all
of which are nearby NLS1 galaxies. Their basic information is shown in Tab. 1,
ordered by the accumulated RGS counts. The black hole mass ($M_{\mathrm{BH}}$)
and the bolometric luminosity ($L_{\mathrm{bol}}$) are obtained from the
literature, while the latter is also estimated in this work (see Sec. 4.3).
The corresponding Eddington ratio is calculated by
$\lambda_{\mathrm{Edd}}\equiv L_{\mathrm{bol}}/L_{\mathrm{Edd}}$, where
$L_{\mathrm{Edd}}\equiv 4\pi
GM_{\mathrm{BH}}m_{\mathrm{p}}c/\sigma_{\mathrm{T}}$ is the Eddington
luminosity. All of them are high-/super-Eddington AGN, expected to launch
outflows (Ohsuga, 2007). The disk inclination angles are obtained based on the
reflection spectroscopy results from the literature and this work, except for
RE J1034+396, which exhibits no discernible reflection features in the
spectra. For this particular case, the value is loosely constrained by the
simulations (Hu et al., 2014).

Table 1: Table of the 6 sources in this sample plus 4 previously studied
sources, including the source name (1), AGN type (2), redshift (3), black hole
mass (4), total on-axis XMM-Newton exposure time without solar flare
correction (5), total counts in the RGS band with solar flare correction (6),
bolometric luminosity (7), Eddington ratio (8) and disk inclination angle (9).
See more details in Sec. 2.

Source | Type | Redshift | $\log(M_{\mathrm{BH}}/M_{\odot})$ | Exposure | RGS Counts | $L_{\mathrm{bol}}$ | $\lambda_{\mathrm{Edd}}$ | $i$
---|---|---|---|---|---|---|---|---
|  | z |  | (ks) | ($10^{5}$) | ($10^{44}\,\mathrm{erg/s}$) | ($\equiv L_{\mathrm{bol}}/L_{\mathrm{Edd}}$) | (deg)
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9)
This work
1H 1934-063 | NLS1 | 0.0102 |  $6.46^{+0.20}_{-0.20}$a,ba,bfootnotemark: $a,b$ | 492 | 4.2 | 1.73m,nm,nfootnotemark: $m,n$ | $0.47\pm 0.22$ |  $42^{+14}_{-2}$nn$n$This work
RE J1034+396 | NLS1 | 0.042 |  $6.40^{+0.2}_{-0.4}$cc$c$Bian & Huang (2010) | 1417 | 3.7 |  $2.7\mbox{--}5.4$n,on,ofootnotemark: $n,o$ | $1.29\pm 0.43$ |  $30^{+28}_{-28}$ww$w$Hu et al. (2014)
PG 1244+026 | NLS1 | 0.048 |  $7.11^{+0.14}_{-0.41}$b,d,eb,d,efootnotemark: $b,d,e$ | 764 | 2.8 |  $14\mbox{--}17$n,pn,pfootnotemark: $n,p$ | $1.04\pm 0.59$ |  $31^{+1}_{-1}$nn$n$This work
PG 1211+143 | NLS1/quasar | 0.0809 |  $8.16^{+0.12}_{-0.15}$ff$f$Peterson et al. (2004) | 876 | 2.3 |  $31\mbox{--}53$n,qn,qfootnotemark: $n,q$ | $0.23\pm 0.08$ |  $30^{+1}_{-1}$nn$n$This work
I ZW 1 | NLS1 | 0.061 |  $7.45^{+0.08}_{-0.12}$gg$g$Vestergaard & Peterson (2006) | 528 | 1.8 |  $22\mbox{--}39$n,rn,rfootnotemark: $n,r$ | $0.88\pm 0.21$ |  $39^{+4}_{-2}$nn$n$This work
IRAS 17020+4544 | NLS1 | 0.0604 |  $6.72^{+0.10}_{-0.10}$b,hb,hfootnotemark: $b,h$ | 209 | 0.8 |  $7.8\mbox{--}9.9$n,sn,sfootnotemark: $n,s$ | $1.33\pm 0.31$ |  $55^{+4}_{-4}$nn$n$This work
Published work
Mrk 1044 | NLS1 | 0.016 |  $6.45^{+0.12}_{-0.13}$ii$i$Du et al. (2015) | 733 | 9.8 |  $1.3\mbox{--}1.6$tt$t$Husemann et al. (2022) | $0.40\pm 0.12$ |  $34^{+1}_{-2}$xx$x$Xu et al. (2023)
1H 0707-495 | NLS1 | 0.0406 |  $6.30^{+0.30}_{-0.30}$jj$j$Done & Jin (2016) | 1385 | 4.1 |  $2\mbox{--}55$uu$u$Xu et al. (2021b) | $9.05\pm 5.43$ |  $43^{+2}_{-2}$yy$y$Parker et al. (2018)
IRAS 13224-3809 | NLS1 | 0.0658 |  $6.54^{+0.41}_{-0.08}$kk$k$Chiang et al. (2015) | 2131 | 3.3 |  $4\mbox{--}13$vv$v$Buisson et al. (2018) | $1.13\pm 0.58$ |  $59^{+1}_{-1}$yy$y$Parker et al. (2018)
PDS 456 | quasar | 0.184 |  $9.3^{+0.4}_{-0.4}$ll$l$Reeves et al. (2009) | 1146 | 1.1 | 1800ll$l$Reeves et al. (2009) | $0.72\pm 0.66$ |  $65^{+2}_{-2}$ll$l$Reeves et al. (2009)

111References: $e$$e$footnotetext: Marconi et al. (2008) $h$$h$footnotetext:
Wang & Lu (2001) $m$$m$footnotetext: Xu et al. (2022) $o$$o$footnotetext:
Czerny et al. (2016) $p$$p$footnotetext: Jin et al. (2013) $q$$q$footnotetext:
Kriss et al. (2018) $r$$r$footnotetext: Porquet et al. (2004)
$s$$s$footnotetext: Gonzalez et al. (2020)

##  3 Data Reduction

The analyzed observations of the sources in our sample are shown in Tab. 2. We
discarded the observations with less than 20 ks exposure time. Specifically
for RE J1034+396, we also excluded several observations prior to 2020 that had
a similar flux level with the extensive campaigns in 2020 and 2021. This was
to avoid potential influence from the long-term continuum variation on flux-
resolved spectroscopy. The data sets were reduced following the standard SAS
threads with the XMM-Newton Science Analysis System (SAS v20.0.0) and
calibration files available by September 2022. In this work, apart from the
RGS data, we also use EPIC-pn (a CCD-based instrument, Strüder et al., 2001)
and Optical Monitor (OM, Mason et al., 2001) data to help constrain the
spectral energy distribution (SED) of the AGN.

Briefly, we reduced the EPIC-pn data using epproc and filtered the time
intervals affected by the background flares, which show the count rates larger
than 0.5 counts/sec in the $10\mbox{--}12$ keV range. The source and
background spectra were extracted from a circular region with a radius of 30
arcsec centered on and offset but near the source respectively. The pile-up
effect was examined by task epatplot. Only one observation of RE J1034+396
(0506440101) and four observations of PG 1211+143 (0112610101, 05020501(2)01,
0745110301) are affected by pile-up. Therefore, an annulus region with an
inner radius of 32 arcsec and an outer radius of 45 arcsec was applied to
extract the source spectrum of RE J1034+396, while an annulus with an inner
radius of 10 arcsec and an outer radius of 30 arcsec was adopted for the PG
1211+143 source spectra. The RGS data were processed by the rgsproc package
with a flare filter of 0.3 counts/sec. The first-order RGS spectra were
extracted from a cross-dispersion region of 1 arcmin width and the background
spectra were extracted from photons beyond 98% of the source point-spread
function as default. We only used the good time intervals (GTI) common to both
RGS 1 and 2 and combined their spectra for the high signal-to-noise (S/N). The
OM data were reduced with omichain and stacked into a time-averaged spectrum
for each source, since they are relatively stable and much less variable than
the X-ray flux, at most 25% variations in our sample. The response files are
retrieved from the ESA webpage222https://www.cosmos.esa.int/web/xmm-newton/om-
response-files.

Figure 1: The EPIC-pn ($0.3\mbox{--}10$ keV) light curve (upper) and the
corresponding hardness ratio (lower) of the observations of 1H 1934-063 (a),
RE J1034+396 (b), PG 1244+026 (c), PG 1211+143 (d), I ZW 1 (e) and IRAS
17020+4544 (f). The individual and flux-/time-resolved spectra of each source
stacked by different approaches (listed in Tab. 2) are marked in different
colors with labels.

To investigate the dependence of UFOs on source variability, we adopted
different stacking approaches for the EPIC-pn and RGS spectra of each object
and generated the time-averaged, time-resolved, and flux-resolved spectra. The
stacking approaches and corresponding labels are listed in Tab. 2. The EPIC-pn
($0.3\mbox{--}10$ keV) light curves and corresponding hardness ratios
($\mathrm{HR}=\mathrm{H}/\mathrm{H+S}$, H: $2\mbox{--}10$ keV; S:
$0.3\mbox{--}2$ keV) are extracted with the epiclccorr task and shown in Fig.
1. For the flux-resolved approach, we equally divided the light curves into
several flux levels (the number shown in Tab. 2), which makes the number of
counts of each level comparable ($>10^{4}$ counts). The GTI files were created
with the tabgitgen package and the flux-resolved spectra were subsequently
extracted and stacked. For each source, except for 1H 1934-063, a time-
averaged spectrum from all observations is also extracted and labeled as
‘avg’, while the averaged spectrum of 1H 1934-063 results from stacking two
new observations in 2021 and refers to as ‘2021’. The EPIC-pn and RGS spectra
were separately stacked with epicspeccombine and rgscombine and grouped to
over-sample the instrumental resolution at least by a factor of 3.

Table 2: Table of the 6 sources analyzed in this work. The second column lists the stacking approach according to the observations. The number in the brackets means the number of the generated spectra after stacking. The individual XMM-Newton observations are shown in the third column. For clarity, the corresponding labels of the stacked and individual spectra are listed in the fourth column, where the time-resolved spectra are referred to as T1…T11 chronologically and the flux-resolved spectra are referred to as F1…F4, from the faintest to brightest state. For each source, except for 1H 1934-063, the time-averaged spectrum from all observations is also generated and referred to as the ‘avg’ spectrum, while for 1H 1934-063, the two new observations (Obs. ID: 08910101(2)01) are stacked and named as ‘2021’.  Sources | Stacking Approach | Obs. ID | Labels
---|---|---|---
1H 1934-063 | individual (1) | 0761870201 | 2015
flux-resolved (2) | 0891010101, 0891010201 | F1, F2
RE J1034+396 | time-averaged (1) | 0506440101, 0561580201, 0675440301 | High
flux-resolved (2) | 0865010101, 0865011001, 0865011101, | F1, F2
0865011201, 0865011301, 0865011401,
0865011501, 0865011601, 0865011701, 0865011801
PG 1244+026 | flux-resolved (4) | 0675320101, 0744440101, 0744440201 | F1, F2, F3, F4
0744440301, 0744440401, 0744440501
PG 1211+143 | time-resolved (11) | 0112610101, 0208020101, 0502050101, 0502050201 | T1, T2, T3, T4
0745110101, 0745110201, 0745110301, 0745110401 | T5, T6, T7, T8
0745110501, 0745110601, 0745110701 | T9, T10, T11
I ZW 1 | individual (1) | 0300470101 | 2005
flux-resolved (2) | 0743050301, 0743050801 | F1, F2
time-averaged (1) | 0851990101, 0851990201 | 2020
IRAS 17020+4544 | flux-resolved (3) | 0206860101, 0206860201, 0721220101, 0721220301 | F1, F2, F3

##  4 Methods

In this section, we introduce our analysis methods, including the spectral
modeling (see Sec. 4.1), Gaussian line scan (see Sec. 4.2), and the
photoionization model scan (see Sec. 4.3) to visualize the UFO absorption
lines in each spectrum, identify the best-fit solution for UFOs and obtain the
UFO properties.

###  4.1 Continuum Modeling

The X-ray data analysis software XSPEC (v12.12.1, Arnaud, 1996) is used for
broadband-band spectral analysis of the EPIC-pn and RGS data. We consider the
RGS spectra between $0.4\mbox{--}1.77$ keV, and the EPIC-pn spectra only
between $1.77\mbox{--}10$ keV (except for RE J1034+396 and PG 1244+026 between
$1.77\mbox{--}8$ keV due to the background domination above 8 keV) in our
analysis, due to the influence of the lower resolution but higher count rate
of EPIC-pn on the detection of atomic features. The instrumental differences
are taken into account by adopting a variable cross-calibration factor
constant. We use the C–stat (Cash, 1979) statistics and estimate the
uncertainties of all parameters at the 90% confidence level (i.e.
$\Delta\mathrm{C}\mbox{--}\mathrm{stat}=2.71$) unless explicitly stated. In
this paper, the luminosities are calculated by the cflux model with the
assumption of $H_{\mathrm{0}}=70$ km/s/Mpc, $\Omega_{\mathrm{\Lambda}}=0.73$
and $\Omega_{\mathrm{M}}=0.27$. We use tbabs in XSPEC to model the Galactic
absorption with Galactic column densities provided by HI4PI Collaboration et
al. (2016), with the exception of 1H 1934-063. For this particular case, we
accounted for the relatively heavy Galactic absorption ($\sim
10^{21}\,\mathrm{cm}^{-2}$) using the high-resolution photoabsorption model
ismabs instead. We adopt the solar abundance calculated by Lodders et al.
(2009) to keep consistent with the subsequently used photoionization model in
Sec. 4.3. The redshift of AGN is taken into account by zashift in XSPEC. In
general, the broadband X-ray continuum of AGN consists of a primary power-law
component from hot Comptonization (the hot corona, Haardt & Maraschi, 1993), a
soft excess, and an X-ray reprocessing of the primary irradiation (Ross &
Fabian, 2005), displayed by fluorescent lines (especially Fe K emission). The
origin of the soft excess is still being debated, either relativistically
blurred high-density reflection or warm Comptonization (e.g., Petrucci et al.,
2018; García et al., 2019; Middei et al., 2020; Petrucci et al., 2020; Xu et
al., 2021a). In this paper, since we are only interested in the atomic
features instead of the origin of the broadband continuum, we adopt the model
diskbb, characterized by the temperature at the inner accretion disk, to
phenomenologically account for the soft excess for the sake of simplicity. The
primary and reprocessing emissions are explained by a flavor of the
relativistic reflection model (RELXILL v1.4.3, García et al., 2014), which
includes a hot Comptonization continuum (relxillCp). This model is
characterized by the temperature $kT_{\mathrm{e}}$ and the emissivity index
$q$ of the hot corona, the spectral slope $\Gamma$, the spin of the black hole
$a_{\star}$, and several disk properties (inner $R_{\mathrm{in}}$ and outer
$R_{\mathrm{out}}$ radius, inclination angle $i$, ionization state $\log\xi$,
and iron abundance $A_{\mathrm{Fe}}$).

Therefore, the general continuum model for most targets in this work is:

constant*tbabs*zashift*cflux*(diskbb+relxillCp),

except for RE J1034+396 and IRAS 17020+4544. Due to the lack of discernible
reflection features in the spectra of RE J1034+396, we adopted the best model
combination from Jin et al. (2021), which assumes the warm Comptonization
explanation for the soft excess and consists of three Comptonization
components for the hot, intermediate, and warm Comptonization emission. In
IRAS 17020+4544, a single reflection component cannot explain the
relativistically broadened Fe K emission. Therefore, in accordance with the
best-fit continuum model from Gonzalez et al. (2020), we included an
additional laor component, which models the disk line affected by strong
gravity, with disk parameters (the inclination angle, inner and outer disk
radius) linked to those of relxillCp, while the line energy, emissivity index,
and normalization are left free. For the remaining targets, our general
continuum model also aligns with the best combination in prior studies on
those sources (e.g. Kara et al., 2014; Lobban et al., 2016; Xu et al., 2022;
Wilkins et al., 2022). The long-term invariants, such as the black hole spin,
disk inclination angle, and iron abundance, were linked together across the
averaged, time- and flux-resolved spectra of the same source during the
analysis. Moreover, we have tested a few different continuum models, such as
changing the flavors of RELXILL and replacing the phenomenological model
diskbb with a warm corona or a high-density relativistic reflection model. We
found that the choice of the continuum model does not affect the following
results on the line modeling and detection of UFOs. Details of continuum
parameters are unrelated to our goal and thus are not shown in this work. Only
inclination angles derived from the reflection model are listed in Tab.1 for
further analysis in Sec. 5.2.

###  4.2 Gaussian Line Scan

The blind Gaussian line scan over the spectra, which have been modeled by the
continuum components, is a straightforward way to visualize the atomic
features on the continua. The method is to fit an additional Gaussian line
upon the continuum model with a logarithmic grid of energy steps over
$0.4\mbox{--}10$ keV and record the statistical improvement
($\Delta\mathrm{C}\mbox{--}\mathrm{stat}$) at each step. The energy centroid
and the line width are fixed at each step, while the normalization is free to
be negative or positive. To identify both the narrow and broad atomic
features, we assumed the line widths at $\sigma_{v}$ of 500, 1500, 4500 km/s,
and the corresponding numbers of the energy steps at 2000, 700, 300,
respectively, to maintain the balance between the computational cost and the
resolving power of instruments. The recorded statistical improvements provide
a rough estimate of the detection significance of individual lines in a single
trial (i.e. in the unit of $\sigma$), in the form of the square root of
$\Delta\mathrm{C}\mbox{--}\mathrm{stat}$ times the sign of the normalization
(Cash, 1979). This analysis approach is performed for every spectrum extracted
from the observations of the sources in our sample. The results are shown in
Figs. 11, 12, 13, 14, 15 and 16, where the centroid and the uncertainty of
prominent UFO absorption features discovered in the following photoionization
modeling are respectively highlighted by the vertical dashed red lines and
shaded regions. The details of the line scan results over each spectrum of
individual sources are presented in Appendix A.

###  4.3 Photoionization Model Scan

To obtain the physical properties of UFOs, we employ the physical
photoionization model, pion, in the SPEX package (Kaastra et al., 1996). This
model self-consistently calculates the transmission and emission spectra of
ionized gas in photoionization equilibrium and only needs to provide the SED
of the radiation field. To implement the pion model in XSPEC, we adopted the
code used in Parker et al. (2019) to construct the tabulated XSPEC version of
pion. In this work, we only make use of the absorption component of pion
(solid angle $\Omega=0$ and covering fraction $C_{\mathrm{F}}=1$), i.e.,
equals to the xabs code in SPEX, and the re-built model is thus named as
xabs_xs. The xabs model is characterized by four main parameters: column
density $N_{\mathrm{H}}$, ionization parameter $\xi$, turbulence velocity
$\sigma_{v}$ and the line-of-sight (LOS) velocity of gas $v_{\mathrm{LOS}}$.

Figure 2: The averaged SED of sources in our sample compared with 1H 0707-495
(Xu et al., 2021b), IRAS 13224-3809 (Jiang et al., 2018), and Mrk 1044 (Xu et
al., 2023).

The intrinsic SEDs of individual sources are derived from the UV, constrained
by OM spectra, to the hard X-ray band (from 1 eV to 10 keV). We adopted the
AGN SED model, AGNSLIM (Kubota & Done, 2018, 2019), sharing the same
temperature between the disk and the seed photon of the warm Comptonization,
only for SED calculations. This model allows us to directly measure the
Eddington ratio, listed in Tab.1. The relativistic reflection component was
included as well and fixed at the best fit derived from the continuum modeling
in Sec. 4.1 without the primary continuum in the model. The Galactic
extinction is also considered by the redden model according to Schlafly &
Finkbeiner (2011). Nonetheless, for RE J1034+396, PG 1244+026, and I ZW 1, the
UV/optical data cannot be well explained by AGNSLIM. In these cases, we
employed the phenomenological model diskbb for the UV/optical spectra.
Specifically, the characterized disk temperatures of these sources are
$30^{+16}_{-15}$, $28^{+17}_{-15}$, and $12^{+10}_{-9}$ eV respectively. We
roughly estimated their Eddington ratios by calculating the bolometric
luminosity ($10^{-3}\mbox{--}10^{3}$ keV) predicted by the model. The
intrinsic time-averaged SEDs of each source are shown in Fig. 2. Due to the
concerns about the potential impact of the loosely constrained UV/optical
measurements on photoionization modeling, we investigated and confirmed that
variations in the disk temperature within the uncertainties do not
significantly affect the ionization balance of the plasma, and the conclusions
of this work.

Ideally, given the SED of the radiation field, we can obtain the best-fit
parameters of xabs_xs by directly fitting the spectra. However, the fits to
the photoionization model are easy to fall in the local minima of the
parameter space due to the fact that the same absorption features (if without
enough statistics) can be comparably explained by different solutions with
different ionization states and speeds. In addition, some weak UFO solutions
might be overlooked if there is no obviously significant single absorption
line but multiple moderately significant absorption features in the spectra.
Therefore, we launch a systematic scan over a multi-dimension grid of the
parameters ($\log\xi,z_{\mathrm{LOS}},\sigma_{v}$) of xabs_xs upon the
continuum model for each spectrum. This method is capable of identifying the
globally best-fit solution and showing the locations of all potential
solutions in the parameter space, which might reveal the multiphase outflows
as long as the other solutions do not degenerate with the primary solution.
The grids consist of the ionization parameter $\log\xi$, ranging from 0 to 5
with a step of $\Delta\log\xi=0.1$, the turbulent velocity $\sigma_{v}$
($\sigma_{v}=500,1500,4500$ km/s) and the LOS velocity $v_{\mathrm{LOS}}$,
from -105000 km/s to 0 with an increment, like Gaussian line scan, depending
on the choice of $\sigma_{v}$ ($c\Delta z_{\mathrm{LOS}}=500,700,1500$ km/s
for $\sigma_{v}=500,1500,4500$ km/s respectively). In the scan, the column
density $N_{\mathrm{H}}$ and the continuum parameters are left free to vary.
The C-stat improvement is recorded at each grid to reveal the detection
significance of the absorber.

Figure 3: Photoionization absorption model search for the time-averaged
spectra of 1H 1934-063 (a), RE J1034+396 (b), PG 1244+026 (c), PG 1211+143
(d), I ZW 1 (e) and IRAS 17020+4544 (f) over the baseline model (continuum or
plus WAs). The color illustrates the statistical improvement after adding an
absorption component with a line width of 1500 km/s (except PG 1211+143 with
$\sigma_{v}=500$ km/s). The purple, green, and yellow contour lines correspond
to 99.73%, 95.4%, and 68.3% confidence level. The solution with the most
significant detection is marked by a red cross and the secondary detection is
marked by a blue diamond, while it may not be the final solution, as another
potential solution can be the most significant detection during the spectral
modeling when the line width $\sigma_{v}$ is free to vary.

The photoionization model scan is performed on every spectrum in our sample.
If the secondary solutions have a significance above $3\sigma$ in a single
trial, i.e. $\Delta$C-stat/d.o.f.$=16.25/4$ (the real significance of several
solutions will be measured by simulations in Sec.5.1), we will iteratively
include an additional absorption component into the model and re-perform the
scan upon the new baseline model until the significance of adding a further
absorption component to the model falls below $3\sigma$. For clarity, we only
present the scan results detecting UFOs across the time-averaged spectrum of
each target in Fig.3, while the results detecting WAs, such as 1H 1934-063 (Xu
et al., 2022), RE J1034+396 (firstly detected), I ZW 1 (Costantini et al.,
2007; Rogantini et al., 2022a), and IRAS 17020+4544 (Sanfrutos et al., 2018)
are not shown. We exhibit results with a line width of 1500 km/s with the
exception of PG 1211+143 ($\sigma_{v}=$500 km/s) due to the consistency among
scan results with different line widths. The velocity on the X-axis is the
relativistically corrected velocity according to the equation:
$v/c=\sqrt{(1+v_{\mathrm{LOS}}/c)/(1-v_{\mathrm{LOS}}/c)}-1$. The grid with
the strongest detection is marked by a red cross but it may not be the final
result, because during the direct spectral modeling, the line width is free to
vary and the best fit may fall in another solution. But the scan plots at
least provide a reference map for the globally best-fit solution of UFOs. The
second UFO solution is marked by a blue diamond (i.e. in PG 1211+143 and I ZW
1). The purple, green, and yellow contour lines represent 3, 2, and 1$\sigma$
uncertainty (i.e. 99.73%, 95.4% and 68.3% confidence level).

##  5 Results

In this section, we present the results of the photoionization modeling
(Section.5.1) and the tentative dependence of UFO detection on viewing angles
(Section.5.2).

###  5.1 Photoionization Modeling

According to the scan results in Fig.3, we directly fit the photoionization
absorption model with a free turbulent velocity to each spectrum in our sample
with the initial values obtained from the scan results. Conservatively, we
also test other peaks in the scan plots in case their significance is larger
than those obtained from the scan with a fixed line width, e.g. the best-fit
UFO in RE J1034+396. The final best-fit parameters of UFOs are listed in
Tab.3, while those of WAs are listed in Tab.6. The single trial significance
is estimated from the $\chi^{2}$ test (similar to the C-statistics for a large
number sample (Cash, 1979)). Only the absorbers with a significance above
$3\sigma$ (i.e. $\Delta\mathrm{C\mbox{--}stat/d.o.f.}>16/4$) are taken into
account, which explains why some previously reported UFOs are not included in
our results, e.g. 4 UFOs in IRAS 17020+4544 but only 1 UFO with
$\Delta\mathrm{C\mbox{--}stat/d.o.f.}>16/4$ (Sanfrutos et al., 2018). Despite
the presence of numerous solutions in the scan plots, multiple UFOs are not
detected in our results, except for PG 1211+143 and I ZW 1. This is because
the solutions partially degenerate and account for the same line features,
making the secondary solutions insufficiently apparent once the primary UFO is
considered. We have also estimated the potential influence of the strong
emission lines in some spectra on the modeling of the absorption component. We
compared the fits before and after including a photoionization emission
component (calculated from pion in SPEX) and found it does not significantly
affect the fits and our conclusions, perhaps due to the narrow line widths of
the emission lines. The descriptions of WAs and UFOs in individual sources are
presented in Appendix.A.

Table 3: Table of the best-fit UFO parameters derived from extracted spectra
of targets in this work. The uncertainties of parameters are estimated at the
90% confidence level ($\Delta\mathrm{C-stat}=2.71$).

Sources | UFO | Luminosity
---|---|---
| $\log\xi$ | $N_{\mathrm{H}}$ | $\sigma_{\mathrm{v}}$ | $v_{\mathrm{LOS}}$ | $\Delta\rm C\mbox{-}stat$ | single trial | $L_{\mathrm{0.4\mbox{--}10\,keV}}$
| $\mathrm{erg\,cm\,s^{-1}}$ | ($10^{21}$ cm-2) | (km/s) | (km/s) |  | significance ($\sigma$) | ($10^{43}$ erg/s)
1H 1934-063 |  |  |  |  |  |  |
2015 | $1.60^{+0.20}_{-0.18}$ | $0.05^{+0.02}_{-0.01}$ | $900^{+700}_{-500}$ | $-24000^{+300}_{-300}$ | 30 | 4.6 | $1.74^{+0.02}_{-0.01}$
2021 | $3.31^{+0.14}_{-0.10}$ | $2.4^{+1.0}_{-0.6}$ | $2200^{+4500}_{-1400}$ | $-37000^{+1500}_{-1200}$ | 32 | 4.7 | $1.73^{+0.02}_{-0.02}$
F1 | $3.32^{+0.28}_{-0.12}$ | $2.3^{+2.2}_{-0.8}$ | $700^{+1400}_{-600}$ | $-35800^{+1200}_{-1500}$ | 20 | 3.5 | $1.44^{+0.02}_{-0.01}$
F2 | $3.32^{+0.18}_{-0.09}$ | $2.1^{+1.8}_{-0.6}$ | $300^{+1300}_{-300}$ | $-38000^{+600}_{-600}$ | 17 | 3.1 | $2.22^{+0.02}_{-0.02}$
RE J1034+396 |  |  |  |  |  |  |
avg | $3.38^{+0.11}_{-0.11}$ | $2.7^{+2.9}_{-1.0}$ | $<100$ | $-63500^{+300}_{-300}$ | 75 | 7.9 | $3.8^{+0.1}_{-0.1}$
F1 | $3.26^{+0.22}_{-0.18}$ | $1.8^{+2.3}_{-1.3}$ | $200^{+400}_{-100}$ | $-63300^{+300}_{-300}$ | 28 | 4.4 | $3.3^{+0.1}_{-0.2}$
F2 | $3.43^{+0.19}_{-0.14}$ | $2.9^{+3.3}_{-2.0}$ | $<100$ | $-63700^{+300}_{-300}$ | 34 | 5.0 | $4.0^{+0.2}_{-0.2}$
high | $3.60^{+0.35}_{-0.13}$ | $9.1^{+6.7}_{-5.3}$ | $<100$ | $-48000^{+1000}_{-1400}$ | 30 | 4.6 | $4.2^{+0.1}_{-0.1}$
PG 1244+026 |  |  |  |  |  |  |
avg | $1.42^{+0.12}_{-0.18}$ | $0.15^{+0.08}_{-0.05}$ | $100^{+100}_{-50}$ | $-13500^{+300}_{-300}$ | 114 | $>8$ | $7.0^{+0.1}_{-0.1}$
F1 | $1.59^{+0.19}_{-0.26}$ | $0.23^{+0.07}_{-0.10}$ | $<100$ | $-13200^{+300}_{-300}$ | 32 | 4.7 | $5.4^{+0.1}_{-0.1}$
F2 | $1.46^{+0.33}_{-0.19}$ | $0.25^{+0.07}_{-0.10}$ | $100^{+100}_{-50}$ | $-13700^{+300}_{-300}$ | 53 | 6.5 | $7.1^{+0.1}_{-0.1}$
F3 | $1.3^{+0.4}_{-0.2}$ | $0.12^{+0.10}_{-0.06}$ | $100^{+200}_{-50}$ | $-13600^{+300}_{-300}$ | 22 | 3.7 | $8.3^{+0.1}_{-0.1}$
F4 | $1.3^{+0.4}_{-0.5}$ | $0.04^{+0.02}_{-0.02}$ | $300^{+1000}_{-200}$ | $-13500^{+600}_{-300}$ | 18 | 3.2 | $10.7^{+0.2}_{-0.2}$
PG 1211+143 |  |  |  |  |  |  |
avg | $1.79^{+0.09}_{-0.09}$ | $0.42^{+0.07}_{-0.06}$ | $<100$ | $-17600^{+300}_{-300}$ | 126 | $>8$ | $19.9^{+0.2}_{-0.2}$
$2.25^{+0.18}_{-0.14}$ | $0.15^{+0.18}_{-0.07}$ | $3200^{+2600}_{-900}$ | $-10800^{+900}_{-1200}$ | 48 | 6.1
T1⋆ | $2.33^{+0.09}_{-0.09}$ | $2.7^{+1.2}_{-0.7}$ | $100^{+100}_{-50}$ | $-20700^{+300}_{-300}$ | 57 | 6.8 | $33^{+12}_{-9}$
$5.0^{+0.2}_{-0.3}$ | $600^{+800}_{-400}$ | $400^{+400}_{-300}$ | $-27300^{+900}_{-300}$ | 24 | 3.9
T3 | $3.03^{+0.19}_{-0.18}$ | $2.6^{+2.0}_{-0.9}$ | $200^{+500}_{-100}$ | $-12800^{+300}_{-300}$ | 69 | 7.6 | $28.3^{+0.6}_{-0.6}$
T4 | $1.63^{+0.32}_{-0.31}$ | $0.6^{+0.5}_{-0.3}$ | $<100$ | $-17800^{+600}_{-600}$ | 22 | 3.7 | $27.0^{+0.6}_{-0.6}$
T5 | $4.5^{+0.4}_{-0.1}$ | $1300^{+600}_{-300}$ | $<100$ | $-51900^{+600}_{-600}$ | 23 | 3.8 | $57^{+11}_{-11}$
T6 | $1.53^{+0.21}_{-0.19}$ | $2.3^{+0.7}_{-0.8}$ | $<100$ | $-17800^{+300}_{-300}$ | 100 | $>8$ | $15.7^{+0.4}_{-0.3}$
T7 | $2.22^{+0.19}_{-0.21}$ | $0.7^{+0.5}_{-0.4}$ | $200^{+100}_{-100}$ | $-17600^{+300}_{-300}$ | 73 | 7.8 | $18.5^{+0.3}_{-0.3}$
T8 | $3.33^{+0.19}_{-0.29}$ | $20^{+30}_{-10}$ | $<100$ | $-41200^{+900}_{-900}$ | 17 | 3.1 | $18.6^{+0.8}_{-0.7}$
T9 | $4.17^{+0.17}_{-0.15}$ | $406^{+180}_{-200}$ | $<100$ | $-76300^{+300}_{-600}$ | 17 | 3.1 | $35^{+6}_{-2}$
T10 | $2.17^{+0.19}_{-0.19}$ | $0.4^{+0.3}_{-0.2}$ | $100^{+100}_{-50}$ | $-10100^{+300}_{-300}$ | 23 | 3.8 | $25^{+3}_{-7}$
T11⋆ | $4.19^{+0.31}_{-0.09}$ | $110^{+260}_{-60}$ | $100^{+500}_{-100}$ | $-72900^{+600}_{-600}$ | 23 | 3.8 | $19^{+1}_{-1}$
$2.47^{+0.42}_{-0.36}$ | $0.7^{+0.4}_{-0.2}$ | $8400^{+1400}_{-1500}$ | $-11000^{+1300}_{-1200}$ | 20 | 3.5
I ZW 1 |  |  |  |  |  |  |
avg⋆ | $4.80^{+0.11}_{-0.12}$ | $1500^{+100}_{-400}$ | $<100$ | $-64200^{+300}_{-300}$ | 56 | 6.7 | $72^{+16}_{-12}$
$2.26^{+0.12}_{-0.17}$ | $0.14^{+0.12}_{-0.09}$ | $2000^{+700}_{-800}$ | $-25800^{+600}_{-600}$ | 48 | 6.1
F1⋆ | $4.54^{+0.32}_{-0.10}$ | $1500^{+1000}_{-900}$ | $<100$ | $-64000^{+300}_{-300}$ | 51 | 6.4 | $71^{+19}_{-21}$
$2.06^{+0.20}_{-0.12}$ | $0.15^{+0.13}_{-0.08}$ | $2500^{+700}_{-900}$ | $-26100^{+600}_{-600}$ | 23 | 3.8
F2⋆ | $4.50^{+0.10}_{-0.08}$ | $1500^{+500}_{-600}$ | $<100$ | $-65400^{+300}_{-300}$ | 19 | 3.3 | $87^{+23}_{-22}$
$2.69^{+0.19}_{-0.27}$ | $0.36^{+0.23}_{-0.21}$ | $1500^{+600}_{-600}$ | $-25800^{+600}_{-600}$ | 29 | 4.5
2020 | $3.76^{+0.21}_{-0.11}$ | $7^{+4}_{-4}$ | $600^{+900}_{-500}$ | $-41300^{+600}_{-600}$ | 18 | 3.2 | $12.6^{+0.3}_{-0.3}$
IRAS 17020+4544 |  |  |  |  |  |  |
avg | $1.9^{+0.1}_{-0.2}$ | $0.30^{+0.07}_{-0.06}$ | $2500^{+500}_{-500}$ | $-23200^{+600}_{-600}$ | 49 | 6.2 | $22.6^{+0.5}_{-0.5}$
F1 | $1.5^{+0.4}_{-0.2}$ | $0.19^{+0.08}_{-0.10}$ | $3000^{+2000}_{-600}$ | $-23100^{+1500}_{-1500}$ | 17 | 3.1 | $20.5^{+0.2}_{-0.8}$
F2 | $1.8^{+0.2}_{-0.2}$ | $0.26^{+0.07}_{-0.05}$ | $1700^{+900}_{-900}$ | $-23100^{+600}_{-600}$ | 19 | 3.3 | $22.6^{+0.6}_{-0.6}$
F3 | $1.9^{+0.2}_{-0.2}$ | $0.33^{+0.12}_{-0.09}$ | $2000^{+800}_{-800}$ | $-23200^{+600}_{-600}$ | 22 | 3.7 | $28.7^{+1.0}_{-0.8}$

⋆ A secondary UFO is detected in this spectrum.

Notably, UFOs in RE J1034+396 and PG 1244+026, and the second UFO in I ZW 1
(low ionization), referred as to ‘I ZW 1-2’, are reported for the first time
in this work. Two WAs in RE J1034+396 are also for the first time detected.
Importantly, these detections are not merely a result of including new and
previously unanalyzed observations of these sources but are primarily
attributed to the effectiveness of our methodology. To estimate the detection
significance of newly discovered UFOs, we performed the Monte Carlo (MC)
simulations. For each case, we simulated 10,000 spectra based on the best-fit
model before including the newly detected UFO component (i.e. continuum+3WAs
for RE J1034+396 and I ZW 1, and continuum model for PG 1244+026). The
photoionization scan described in Sec. 4.3 was performed on each simulated
spectra. For each searched grid $i$, we estimate the significance by comparing
the $\Delta$C-$\mathrm{stat}_{\mathrm{real},i}$ of an additional UFO
absorption for the real spectrum with the
$\Delta$C-$\mathrm{stat}_{\mathrm{MC}}$ of an additional UFO absorption within
the whole searched parameter space for simulated spectra. This step takes into
account the look-elsewhere effect. The ratio between the number of simulations
yielding occurrences of
$\Delta$C-$\mathrm{stat}_{\mathrm{MC}}>\Delta$C-$\mathrm{stat}_{\mathrm{real},i}$
and the total number of MC simulations is the $p$-value of the grid $i$. The
collected significance maps are shown in Fig.4. The significance of UFO in PG
1244+026 is $\sim 3.3\sigma$ (smaller than the single trial significance in
Tab.3) and those in RE J1034+396 and I ZW 1 are $\geq 3.89\sigma$ (limited by
the number of simulations), confirming the presence of newly discovered UFOs.

Figure 4: The Monte Carlo (MC) simulations of photoionization absorption model
search for the time-averaged spectra of RE J1034+396 (top), PG 1244+026
(middle), and I ZW 1 (bottom) over the baseline model (continuum or plus
several absorbers). The color illustrates the detection significance of the
newly discovered UFOs considering the look-elsewhere effect. The upper limit
of the significance is $3.89\sigma$ as the number of simulated spectra is
10000.

###  5.2 Inclination-dependent UFO detection?

By employing the relativistic reflection model for modeling the Fe K emission,
we can constrain the inclination angle of the accretion disk. It is observed
that most UFOs in our sample are detected in AGN with $i>30^{\circ}$. Combined
with the sample of Parker et al. (2018), most of which are Type 1 AGN, we
expand the population size to 26 AGN, including UFO detection and inclination
angles derived from relativistic reflection spectroscopy, shown in Fig.5. UFO
detections are strongly concentrated at $30\mbox{--}60^{\circ}$, suggesting
UFOs are detectable only within specific viewing angles. However, this
phenomenon most likely results from selection effects. At low inclinations,
our LOS intersects directly the innermost region of the accretion disk, where
the plasma may be fully ionized and undetectable, even if a UFO exists (Pinto
et al., 2018). In the edge-on scenario, the nucleus is heavily obscured by the
dusty torus (typically Type 2 AGN, e.g. (Marin et al., 2024)), preventing the
detection of soft X-ray UFOs. In cases that are not Compton-thick with a
column density of $N_{\mathrm{H}}<10^{24}\,\mathrm{cm}^{-2}$, UFOs are
detectable in hard X-rays, while UFOs in Type 2 AGN, which have a similar
detection fraction as that in Type 1 AGN (Tombesi et al., 2010), are not
equally included in the sample, leading to the lack of UFO detection at high
inclinations. Another caveat is the degeneracy between the inclination angle
and other parameters of the reflection model (e.g. Fe abundance
$A_{\mathrm{Fe}}$ and ionization parameter $\log\xi$), which may affect the
values of the inclination angle (Reynolds, 2014). Consequently, due to the
biases mentioned above, the hypothesis of inclination-dependent UFO detection
is tentative, awaiting an enhanced sample size of AGN with detections of both
UFOs and relativistic reflection, as well as model-independent measurements of
inclination angles.

Figure 5: The distribution of disk inclination angle of sources in our sample
plus four studied sources compared with the sample of Parker et al. (2018).
Most UFOs in the sample are detected with a disk inclination angle between
$30\mbox{--}60^{\circ}$.

##  6 Discussion

By performing the state-of-the-art photoionization model scan over archival
XMM-Newton spectra of 7 AGN, we obtain parameters of ionized outflows and find
three previously unreported UFOs in RE J1034+396, PG 1244+026, and I ZW 1-2
and two new WAs in RE J1034+396. In this section, we discuss the multiphased
outflows in our sample (Sec. 6.1), potential correlations between UFO
parameters and X-ray luminosities as well as their relations with intrinsic
AGN properties (Sec. 6.2), the energetics of UFOs (Sec. 6.3), and the
capability of future missions to improve our understanding of UFOs (Sec. 6.4).

###  6.1 Multi-phase outflows

One of the most relevant features of our analysis is the simultaneous
detection of multi-phase outflows. Except for PG 1244+026, all AGN in our
sample host multi-phase outflows (UFOs and WAs). Multi-phase UFOs are observed
in two of them, i.e. PG 1211+143 and I ZW 1. UFOs in PG 1211+143 have already
been found multi-phase in Pounds et al. (2016a); Reeves et al. (2018); Pounds
& Nayakshin (2023), while these papers do not mention some of the UFO
components that we present in this paper (e.g. UFOs in T5, T8, and T9) as they
did not perform the photoionization model scan like what we did. Thanks to
this powerful method, UFOs in I ZW 1 are for the first time discovered to have
multiple phases in this work.

To investigate the structure of ionized winds in these two AGN, we plot the
velocity of outflows versus ionization parameters in Fig.6 and fit them with a
powerlaw function. We include detected WAs into the plot of I ZW 1, while the
WA in PG 1211+143 is detected in only one observation, so it is discarded. The
Spearman’s rank correlation coefficient $\rho_{\mathrm{sp}}$ between $\xi$ and
$v$ are $r=-0.64$ in PG 1211+143 and -0.81 in I ZW 1 with $p$-values of 0.02
and $0.003$ respectively, suggesting strong correlations. Here we perform the
powerlaw fit for following physical-motivated discussions. The fit for PG
1211+143 provides

$v/c=(-0.026\pm 0.013)\xi^{(0.17\pm 0.06)},$ (1)

and the fit for I ZW 1 yields

$v/c=(-0.008\pm 0.002)\xi^{(0.31\pm 0.03)}.$ (2)

A similar correlation was also observed or hinted at other AGN, e.g. NGC 4051
(Pounds & King, 2013), IRAS 13224-3809 (Pinto et al., 2018) and 1H 0707-495
(Xu et al., 2021b), compatible with the scenario that the UFO launched from
the inner and hotter accretion disk requires a larger velocity to escape the
local Keplerian velocity.

Figure 6: The velocity of ionized winds versus ionization parameters in PG
1211+143 (top) and I ZW 1 (bottom). The blue line shows the powerlaw
regression fitted to data with $1\sigma$ uncertainty shaded.

According to the definition of the kinetic energy of outflows
$L_{\mathrm{kin}}\propto v_{w}^{3}/\xi$ (see details in Eq.4 in Sec. 6.3),
$v^{3}/\xi=\mathrm{constant}$ (i.e. $v\propto\xi^{1/3}$) implies an energy-
conserved outflow. Therefore, our result suggests that the kinetic energy of
UFOs in I ZW 1 is conserved during the propagation from the inner accretion
disk to large scales if they originate from a stratified wind. However, in PG
1211+143 and the power index $(0.17\pm 0.06)$ is inconsistent with either
energy-conserved ($v\propto\xi^{1/3}$) or momentum-conserved
($v\propto\xi^{1/2}$) outflows, where the momentum of outflow is expressed by
$\dot{P}_{w}\sim\dot{M}_{\mathrm{out}}v_{w}\propto v_{w}^{2}/\xi$. The
possible reason is that outflows in PG 1211+143 do not originate from a
stratified wind but from random disk instability, indicated by rapidly
variable UFO parameters (Pounds et al., 2016b).

In most AGN (except PG 1244+026) in our sample, we detect UFO and WA
components with similar best-fit ionization parameters (see Tab.3 and Tab.6).
These components may be a signature of entrained UFOs (E-UFOs) as proposed by
Pounds & King (2013) and Serafinelli et al. (2019). These authors suggested a
scenario whereby WAs are produced in the shock where UFOs collide with the
surrounding medium. In this case, the interstellar medium (ISM) is entrained
by UFOs launched from the inner disk, leading to E-UFOs, which keep the low
ionization state of ISM with the ultra-fast velocities from UFOs. Our results
support this interpretation for these UFO/WA ‘pairs’. An intriguing case is RE
J1034+396, where a WA is detected with a very high ionization parameter
($\log\xi\sim 3.6$, Zhou et al., 2024)), in agreement with the UFO detected at
all epochs, although it is still compatible with the shocked outflow mode. We
observe that the ratio of velocities in these UFO/WA component pairs with a
similar ionization parameter is larger than the value predicted by shock
theory ($\sim 4$ Pounds & King, 2013), possibly because the momentum is lost
during the shock.

###  6.2 The evolution of UFO properties across different X-ray luminosities

To further investigate the dependence of the wind properties on the source
luminosity, we plot the best-fitting column density, ionization parameter, and
velocity of UFOs at their $1\sigma$ uncertainties versus the unabsorbed
luminosity between $0.4\mbox{--}10\,$keV in 17 and fit them with a powerlaw
function. Only 4 UFOs are fitted after excluding UFOs with distinct parameters
from others (to avoid tracking different phases) and with only two
measurements (see details in Appendix.B). The fitted power indexes, referred
to as $\Gamma_{\mathrm{N_{H}}}$, $\Gamma_{\mathrm{\log\xi}}$ and
$\Gamma_{\mathrm{velocity}}$, are listed in Tab.3, which also include results
from previous archival studies, where only $\Gamma_{\mathrm{velocity}}$ was
calculated for PDS 456.

Table 4: Table of the fitted power indexes
($\mathrm{parameter}=L_{\mathrm{X}}^{\Gamma}$) of the column density,
ionization parameter, and velocity of the photoionized plasma in our sample
(plus the published results) with their $1\,\sigma$ uncertainties versus the
unabsorbed luminosity between $0.4\mbox{--}10\,$keV.

Names | $\Gamma_{N_{H}}$ | $\Gamma_{\mathrm{log}\xi}$ | $\Gamma_{\mathrm{velocity}}$
---|---|---|---
This work
RE J1034+396 | $4.61\pm 2.90$ | $1.95\pm 1.09$ | $-0.09\pm 0.31$
PG 1244+026 | $-2.45\pm 0.81$ | $-0.85\pm 0.87$ | $0.03\pm 0.05$
PG 1211+143 | $6.87\pm 2.37$ | $3.91\pm 1.94$ | $0.81\pm 0.62$
IRAS 17020+4544 | $1.05\pm 1.10$ | $1.41\pm 2.20$ | $0.017\pm 0.022$
Published work
Mrk 1044aa$a$Malizia et al. (2008) | $1.59\pm 0.98$ | $1.08\pm 0.41$ | $0.39\pm 0.16$
1H 0707-495bb$b$Ponti et al. (2012) | $1.25\pm 0.51$ | $1.83\pm 0.77$ | $-0.15\pm 0.05$
IRAS 13224-3809cc$c$Pinto et al. (2018) | $-0.08\pm 0.04$ | $0.28\pm 0.11$ | $0.05\pm 0.02$
PDS 456dd$d$Kara et al. (2014) |  |  | $0.24\pm 0.03$
333References: $a$$a$footnotetext: Xu et al. (2023) $b$$b$footnotetext: Xu et
al. (2021b)

Due to the limited measurements, fitted parameters are loosely constrained
(see Tab.3 and broad shaded regions in Fig.17), although the variations could
still be seen through individual parameters. In our sample, only 2 UFOs (RE
J1034+396 and PG 1211+143) exhibit positive $\Gamma_{\mathrm{\log\xi}}$ within
uncertainties, while the remaining UFOs (i.e. 1H 1934-063, PG 1244+026, I ZW
1, and IRAS 17020+4544) are consistent with zero, except for I ZW 1-2, which
may have a higher ionization parameter at brighter states.
$\Gamma_{\mathrm{N_{H}}}$ usually follows the same trend as
$\Gamma_{\mathrm{\log\xi}}$ due to the systematic degeneracy that only
outflows with a higher column density can be observable at a higher ionization
state. The negative $\Gamma_{\mathrm{N_{H}}}$ of PG 1244+026 is explained in
Sec. A.3. According to the definition of the ionization parameter: $\xi\equiv
L_{\mathrm{ion}}/n_{\mathrm{H}}R^{2}$, where $L_{\mathrm{ion}}$ is the
ionizing luminosity calculated between $1\mbox{--}1000\,$Ryd (13.6 eV–13.6
keV), $n_{\mathrm{H}}$ is the hydrogen number density, and $R$ is the distance
between the materials and the ionizing source, positive
$\Gamma_{\mathrm{\log\xi}}$ suggest a UFO responding to the ionizing
luminosity. As a result, we prefer to claim that 2 UFOs in our sample seem to
respond to the radiation field (more-ionized-when-brighter) while for the
other 5, we do not yet have found evidence, which may be intrinsic or caused
by limited measurements.

As for velocity, only 1 UFO (PG 1211+143) exhibits a positive
$\Gamma_{\mathrm{velocity}}$ with a large uncertainty due to a multi-phase
nature, and UFOs with only two measurements (1H 1934-063 and I ZW 1) hint
positive $\Gamma_{\mathrm{velocity}}$ but limited by measurements, while the
others are consistent with zero. The positive $\Gamma_{\mathrm{velocity}}$
points towards a radiatively-driven UFO (King & Pounds, 2003), while a zero
value may result from the stacked flux-resolved spectra smearing out the lines
and trends or an intrinsically stable nature of UFOs.

We further tried to explore the potential correlations between the dependence
of UFO properties on luminosity and the intrinsic AGN properties (Tab.1),
combined with published works, for any indications. The properties consists of
the black hole mass $M_{\mathrm{BH}}$, bolometric luminosity
$L_{\mathrm{bol}}$, Eddington ratio $\lambda_{\mathrm{Edd}}$, and inclination
angle $i$. The plots for each combination are depicted in Fig.18 combined with
AGN in published works. However, we did not find any statistically significant
correlations among all pairs of quantities except for a potential correlation
between $\lambda_{\mathrm{Edd}}$ and $\Gamma_{\mathrm{velocity}}$ (see the
bottom plot of panel $c$ of Fig.18). After removing PG 1211+143, which is
obtained from multi-phase UFOs, we find a tentative anti-correlation with a
Pearson correlation coefficient of $r=-0.72$ and a $p$-value of $0.07$,
corresponding to $\sim 1.8\sigma$ significance. That pair is depicted and
fitted in Fig.7 with the $1\sigma$ uncertainty, yielding

$\Gamma_{\mathrm{velocity}}=(-0.69\pm 0.21)\log\lambda_{\mathrm{Edd}}+(0.10\pm
0.04).$ (3)

Figure 7: The power indexes of the UFO velocity $\Gamma_{\mathrm{velocity}}$
as a function of X-ray luminosity versus Eddington ratio
$\lambda_{\mathrm{Edd}}$. The data come from the results listed in Tab.1 and
3. The horizontal dashed line denotes $\Gamma_{\mathrm{velocity}}=0$. The blue
line shows the linear regression fitted to the data in the linear-log scale
with $1\sigma$ uncertainty shaded. PG 1211+143 is excluded from this plot due
to multi-phase UFOs.  Figure 8: The simplified schemes of AGN with high
accretion rates. The SMBH is surrounded by a standard thin disk and a hot
corona. UFOs are launched by the radiation field from the accretion disk. The
inner part of the accretion disk is slim in the high-accretion regime. Three
competitive scenarios are explored to explain a possible
$\Gamma_{\mathrm{velocity}}$ vs $\lambda_{\mathrm{Edd}}$ anti-correlation (see
Sec.6.2).

If the tentative ($<2\sigma$) anticorrelation is real, it indicates that in
high-/super-Eddington regimes, the radiation acceleration on winds may
decrease with increasing Eddington ratios, since the dependence of the
velocity on the source luminosity, $\Gamma_{\mathrm{velocity}}$, represents a
form of ‘radiation acceleration’. In the standard thin disk accretion model
(Shakura & Sunyaev, 1973), an anticipated outcome of the force multiplier is
the increasing acceleration of UFOs as the Eddington ratio rises. We consider
three possibilities for high-Eddington systems with a slim inner disk (e.g.,
Abramowicz et al., 1988; Ohsuga, 2007; Jiang et al., 2019b; Curd & Narayan,
2023) (summarized in Fig.8) to explain the tentative anticorrelation: 1) In
high-Eddington AGN, the spherization radius $R_{\mathrm{sp}}$ (Shakura &
Sunyaev, 1973; Poutanen et al., 2007), where the height and radius of the disk
are comparable $H\sim R$ and winds are assumed to be launched from this point,
is proportional to the Eddington ratio, $R_{\mathrm{sp}}\propto
R_{\mathrm{in}}\lambda_{\mathrm{Edd}}$. The wind launching radius will thus
increase as the Eddington ratio rises, coupled with reduced Keplerian
velocity, thus leading to a slower launching velocity. The same phenomenon was
observed in the population study of UFOs (SUBWAYS, Gianolli et al., 2024). 2)
In the slim disk, frequent interactions between matter and photons would delay
the liberation of the radiation energy or even trap photons (Ohsuga et al.,
2002), resulting in reduced radiation acceleration. 3) The intense radiation
field can result in an over-ionization of plasma in the inner part of the
accretion disk, leading to a decrease in the cross-section $\sigma$ (Rybicki &
Lightman, 1979; Kallman & Palmeri, 2007), $\sigma\propto\log E/E$, where $E$
is the energy available for the ionization of plasma. The launched winds thus
become transparent to photons and experience low radiatively-driven force,
dampening the radiation acceleration.

Nevertheless, we have to caution that the observed trend is not statistically
strong ($\sim 1.8\sigma$) and just based on a sample of only 7 cases, making
it just an indication at the moment. The confirmation of this trend and the
discrimination between three possible mechanisms of deceleration require more
observations and targets, especially AGN across various accretion rates
($\lambda_{Edd}<0.1$ or $\lambda_{Edd}>1$). Furthermore, theoretical
simulations about how the properties of UFOs launched by different mechanisms
evolve with the accretion rates should be done in the future for comparison
with observational results.

###  6.3 Implications for AGN feedback

It is expected that UFOs at small scales can carry out sufficient power to
quench or trigger star formation in their hosts and affect the evolution of
galaxies (e.g. Di Matteo et al., 2005; Hopkins & Elvis, 2010; Maiolino et al.,
2017). According to simulations, the deposition of kinetic energy larger than
0.5% of the Eddington luminosity into the ISM is sufficient to produce
considerable feedback on the host galaxy. The kinetic power of the outflows
can be expressed as:

$L_{\mathrm{kin}}=\frac{1}{2}\dot{M}_{\mathrm{out}}v_{\mathrm{w}}^{2}=2\pi
C_{\mathrm{V}}\Omega R^{2}\rho v_{\mathrm{w}}^{3}$ (4)

where $\dot{M}_{\mathrm{out}}=4\pi C_{\mathrm{V}}\Omega R^{2}\rho
v_{\mathrm{w}}$ is the mass outflow rate; $C_{\mathrm{V}}$ the volume filling
factor; $\Omega$ the solid angle normalized by $4\pi$; $R$ the distance
between the ionizing source and outflows; $\rho$ the outflow mass density;
$v_{\mathrm{w}}$ is the wind velocity. The mass density is defined as
$\rho=n_{\mathrm{H}}m_{\mathrm{p}}\mu$, where $n_{\mathrm{H}}$ is the hydrogen
number density; $m_{\mathrm{p}}$ the proton mass and $\mu=1.2$ the mean atomic
mass assuming solar abundances. The solid angle is assumed at
$\Omega/4\pi=0.3$ in this paper, which is determined by the observational UFO
detection rate (Tombesi et al., 2010) and is consistent with the GR-MHD
simulations of radiatively-driven winds in super-Eddington systems (Takeuchi
et al., 2013).

We estimate the wind location following the method adopted in Tombesi et al.
(2013) and Gofford et al. (2015). The lower limit on the wind location is
constrained by assuming that the UFO velocity is larger than or equal to the
escape velocity, $R_{\mathrm{w}}\geq
R_{\mathrm{esc}}=2GM_{\mathrm{BH}}/v_{\mathrm{w}}^{2}$, while the upper limit
is obtained by hypothesizing that the thickness of UFOs is lower than or equal
to its maximal distance from the source, $\Delta R\leq R_{\mathrm{w}}$,
combined with the definition of ionization parameter $\xi\equiv
L_{\mathrm{ion}}/n_{\mathrm{H}}R^{2}$ and
$N_{\mathrm{H}}=\int^{\infty}_{R_{\mathrm{max}}}{n(r)dr}$, leading to
$R_{\mathrm{w}}\leq L_{\mathrm{ion}}/\xi N_{\mathrm{H}}$. The estimated
distance and the corresponding number density are listed in Tab.4, according
to the definition of the ionization parameter ($\xi\equiv
L_{\mathrm{ion}}/n_{\mathrm{H}}R^{2}$). The UFO properties are taken from the
results of the stacked spectra, so the secondary UFO of PG 1211+143 in the
time-averaged spectrum is also included and denoted as ‘PG 1211+143-2’.

Table 5: Table of the inferred wind parameters in our sample (plus the
published results). See details in the content.

Names $\log R_{w}$ $\log n_{\mathrm{H}}$ $\log\dot{M}_{\mathrm{out}}$ $\log
L_{\mathrm{kin}}$ $[C_{\mathrm{V}}]^{a}$
$L_{\mathrm{kin}}/L_{\mathrm{Edd}}^{b}$ (cm) ($\mathrm{cm}^{-3}$) (g/s)
(erg/s) ($10^{-3}$) % This work 1H 1934-063 $13.8\mbox{--}18.8(17.1)$
$2.6(6^{\star})\mbox{--}12.6$ $21.6(23.3)\mbox{--}26.6$
$40.4(42.1)\mbox{--}45.4$ $9.0\pm 2.4$ $6.8\times
10^{-3}(0.4)\mbox{--}7.6\times 10^{2}$ [$3.5\pm 2.0$] RE J1034+396
$13.3\mbox{--}19.9(17.6)$ $1.6(6^{\star})\mbox{--}14.7$
$21.4(23.6)\mbox{--}27.9$ $40.6(42.8)\mbox{--}47.2$ $7.1\pm 2.6$ $1.2\times
10^{-2}(2.1)\mbox{--}4.7\times 10^{4}$ [$26.0\pm 18.6$] PG 1244+026
$15.3\mbox{--}22.8(18.5)$ $-2.6(6^{\star})\mbox{--}12.4$
$21.5(25.8)\mbox{--}29.0$ $39.4(43.7)\mbox{--}47.0$ $0.7\pm 0.2$ $1.6\times
10^{-4}(3.4)\mbox{--}5.6\times 10^{3}$ [$1.0\pm 0.5$] PG 1211+143
$16.1\mbox{--}22.2(18.4)$ $-1.6(6^{\star})\mbox{--}10.6$
$22.9(26.7)\mbox{--}29.0$ $41.0(44.8)\mbox{--}47.1$ $1.2\pm 0.4$ $5.8\times
10^{-4}(3.6)\mbox{--}7.3\times 10^{2}$ [$0.4\pm 0.2$] PG 1211+143-2
$16.5\mbox{--}22.2(18.2)$ $-2.1(6^{\star})\mbox{--}9.3$
$22.6(26.6)\mbox{--}28.3$ $40.4(44.4)\mbox{--}46.1$ $5.6\pm 2.1$ $1.3\times
10^{-4}(1.3)\mbox{--}6.2\times 10^{1}$ [$0.15\pm 0.09$] I ZW 1
$14.3\mbox{--}16.2(17.2)$ $7.9(6^{\star})\mbox{--}11.8$
$25.2(24.2)\mbox{--}27.1$ $44.4(43.4)\mbox{--}46.3$ $71.2\mbox{--}26.6$
$7.0\times 10^{0}(0.8)\mbox{--}5.7\times 10^{2}$ [$17.8\pm 9.0$] I ZW 1-2
$15.1\mbox{--}22.8(18.5)$ $-2.7(6^{\star})\mbox{--}12.8$
$21.5(25.8)\mbox{--}29.2$ $40.0(44.3)\mbox{--}47.7$ $0.5\pm 0.2$ $2.8\times
10^{-4}(6.0)\mbox{--}1.5\times 10^{4}$ [$3.2\pm 2.0$] IRAS 17020+4544
$14.4\mbox{--}22.8(18.6)$ $-2.4(6^{\star})\mbox{--}14.4$
$21.1(25.3)\mbox{--}29.5$ $39.6(43.7)\mbox{--}47.9$ $0.2\pm 0.1$ $5.4\times
10^{-4}(8.2)\mbox{--}1.3\times 10^{5}$ [$3.6\pm 1.7$] Published work Mrk
1044cc$c$Xu et al. (2023) $13.6\mbox{--}15.4$ $9.0\mbox{--}12.6$ 24.2 43.2 7.0
4.4 1H 0707-495dd$d$Matzeu et al. (2017) $13.4\mbox{--}14.8$
$10.7\mbox{--}13.0$ 24.5 43.4 8.0 13.7 IRAS 13224-3809e,fe,ffootnotemark:
$e,f$ $13.6\mbox{--}14.2$ $10\mbox{--}12$ 24.4 43.4 3.8 PDS 456gg$g$Nardini et
al. (2015) $16.2\mbox{--}16.8$ $6.5\mbox{--}8.9$ 27.1 46.3 15.0 444 The
inferred parameters are calculated by assuming a solid angle of
$\Omega/4\pi=0.3$ (Tombesi et al., 2010; Takeuchi et al., 2013).
$$\star$$$$\star$$footnotetext: The lower limit on the density is assumed
above the typical density of narrow line region (NLR,
$>10^{6}\,\mathrm{cm}^{-3}$). The corresponding results are shown in
parentheses. $a$$a$footnotetext: The filling factor is calculated by assuming
that the outflow rate is comparable to the accretion rate
$\dot{M}_{\mathrm{out}}\sim\dot{M}_{\mathrm{acc}}$ (Kobayashi et al., 2018).
$b$$b$footnotetext: The value in the bracket is estimated by inputting
$C_{\mathrm{V}}$ into Eq.4 based on assumption of
$\dot{M}_{\mathrm{out}}\sim\dot{M}_{\mathrm{acc}}$. References:
$d$$d$footnotetext: Xu et al. (2021b) $e$$e$footnotetext: Parker et al.
(2017b) $f$$f$footnotetext: Pinto et al. (2018)

The value of $C_{\mathrm{V}}$ is difficult to determine because it depends on
the ionization and clumpiness of the gas. At low ionization states, the flow
is likely to be clumpy, where the column density of the wind can be given by
$N_{\mathrm{H}}\sim C_{\mathrm{V}}n(R)\Delta R$ with $C_{\mathrm{V}}<1$
allowing for an inhomogeneous gas, while at high ionization states it can be
considered largely smooth with $C_{\mathrm{V}}\sim 1$ and $R\rightarrow
R_{\mathrm{max}}$. Therefore, following Gofford et al. (2015), we substitute
for $R_{\mathrm{min}}$ and $R_{\mathrm{max}}$, leading to the upper and lower
limits on the mass outflow rate:

$\displaystyle\dot{M}_{\mathrm{out}}^{\mathrm{max}}\sim 1.2\Omega
m_{\mathrm{p}}L_{\mathrm{ion}}/\xi v_{w}$ (5)
$\displaystyle\dot{M}_{\mathrm{out}}^{\mathrm{min}}\sim 2.4\Omega
m_{\mathrm{p}}GM_{\mathrm{BH}}N_{\mathrm{H}}v_{w}$ (6)

where in Eq.5 $n_{\mathrm{H}}R^{2}$ is replaced by $L_{\mathrm{ion}}/\xi$ due
to the definition. The estimated mass outflow rate and kinetic power of UFOs
in our sample (plus the published results) are listed in Tab.4. The ratio
between estimated kinetic power and Eddington luminosity is listed as well.
For comparison, we plot the kinetic energy versus the Eddington luminosity of
UFOs in this (blue) and published (red) works in Fig.9, compared with the
sample in Tombesi et al. (2013) (marked by grey symbols). We note that the
kinetic power of soft X-ray UFOs in our sample has a much larger uncertainty
than those in Tombesi et al. (2013), except for the primary UFO in I ZW 1
(detected in the Fe K region). It is because UFOs detected in soft X-rays
usually have smaller velocities and column densities compared with those of
hard X-ray UFOs (e.g. Serafinelli et al., 2019; Laha et al., 2021). Given such
large uncertainties of individual soft X-ray UFOs, we cannot conclude that
UFOs in our sample have sufficient kinetic energy to affect the host galaxy,
although it is still promising, requiring better constraints on wind
parameters.

Figure 9: The kinetic luminosity of UFOs in this (blue stars, based on the
most conservative assumptions) and published (red crosses) works versus the
Eddington luminosity. The grey circles, triangles, and diamonds correspond to
UFOs, non-UFOs, and WAs in Tombesi et al. (2013), respectively, for
comparison. The transverse lines indicate the ratios between the outflow
kinetic luminosity and Eddington luminosity of 100 percent (solid), 5 percent
(dashed), and 0.5 percent (dotted).

We note that most lower limits on the density of UFOs in Tab.4 are
unreasonably small, resulting from the relatively low column densities.
Theoretically, UFOs are expected to originate from the nuclear region of AGN,
i.e. within the narrow line region (NLR), which has typical densities of
$10^{3}\mbox{--}10^{6}\,\mathrm{cm}^{-3}$ (e.g. Netzer, 1990). Therefore, we
take $n_{\mathrm{H}}=10^{6}\,\mathrm{cm}^{-3}$ as the lower limit and infer
the corresponding wind parameters, shown in the parentheses in Tab.4. Under
this assumption, we can further constrain the lower bounds on the kinetic
energy of UFOs, most of which in this work surpasses the theoretical threshold
($>0.5\%L_{\mathrm{Edd}}$), indicating UFOs have significant impacts on the
evolution of host galaxies.

Alternatively, we try to further constrain the wind parameters by assuming
that the outflow mass rate is comparable to the accretion rate
$\dot{M}_{\mathrm{out}}\sim\dot{M}_{\mathrm{acc}}$, which is reasonable in
high-accretion systems, the filling factor can be estimated through Eq. 23 in
(Kobayashi et al., 2018). The estimated filling factors are between
$10^{-4}\mbox{--}10^{-2}$ listed in Tab.4, averagely larger than those
estimated for WAs, $10^{-2}\mbox{--}10^{-6}$ (Blustin et al., 2005), as UFOs
are expected to be closer to SMBHs and less porous than WAs. The corresponding
kinetic energy of UFOs is listed in the bracket of the last column. Most of
them are above the theoretical criterion except for UFOs in PG 1211+143,
consistent with what was found in Danehkar et al. (2018), although the total
kinetic power of two UFOs reaches the threshold.

Based on the above investigations from two different but both reasonable
assumptions, our results suggest that UFOs detected in soft X-rays also have
sufficient power to affect the surrounding medium and host galaxy,
complementing the conclusion made from only hard X-ray UFOs (Tombesi et al.,
2013). Within our sample, the primary UFO in I ZW 1 is the only case with
conclusively sufficient power to affect the host galaxy, which is consistent
with the estimation from Reeves & Braito (2019) ($15\mbox{--}25\%$).
Additionally, the location of this UFO is tightly constrained, $\log R_{w}\sim
14.3\mbox{--}16.2\,\mathrm{cm}$, indicating its origin within the inner
accretion disk with a high density $>10^{8}\,\mathrm{cm}^{-3}$. Other UFOs are
promisingly powerful enough to build effective AGN feedback while requiring
further stricter constraints, in need of future observatories, e.g. ATHENA
(Nandra et al., 2013), and new methods, e.g. time-dependent photoionization
models (Rogantini et al., 2022b; Luminari et al., 2023) and resolved density-
sensitive lines (Mao et al., 2017).

###  6.4 ATHENA/X-IFU simulations

The future mission, ATHENA (Nandra et al., 2013), with unprecedented spectral
resolution and large effective areas, will resolve the systematic limitations
of the flux-resolved spectroscopy and tightly constrain the nature of UFOs.
The X-ray Integral Field Unit (X-IFU, Barret et al., 2018, 2023) onboard
ATHENA will collect sufficient photons for spectroscopy within a short
timescale with well-resolved absorption lines, thus avoiding the risk of
spectral broadening due to the stacked flux-resolved spectra. This will enable
us to trace the UFO responses to the source variability and provide tight
constraints on their launching mechanisms.

Figure 10: The data/model ratio for the ATHENA/X-IFU spectra of PG 1211+143 at
low (top), middle (middle), and high (bottom) states with an exposure time of
10 ks. The simulation of spectra is based on the best-fit continuum model,
with the UFO ionization state predicted by the fit (see Tab.3) and
normalization adapted to reproduce the luminosity indicated in the legends.
The UFO velocity is assumed to follow the trend of I ZW 1, instead of the
constant trend of PG 1211+143, to simulate the change in UFO velocity. The
vertical dashed green lines present the blueshifted UFO absorption features at
different states.

We utilize the fakeit tool within XSPEC to create simulated ATHENA/X-IFU
spectra of, for example, PG 1211+143 at different luminosities with new
response files (released on
12/07/2023)555http://x-ifu.irap.omp.eu/resources/for-the-community. The aim is
to illustrate the corresponding UFO variations. We hypothesize that the source
brightness linearly increases from its dimmest ($L_{\mathrm{ion}}=1.5\times
10^{44}$erg/s) to its brightest ($L_{\mathrm{ion}}=3.3\times 10^{44}$erg/s)
state within 30 ks, achieved by adjusting only the normalization of diskbb and
relxillCp components. The UFO ionization state is assumed to evolve based on
our fit results found in Tab.3, while the velocity is assumed to increase,
instead of being constant, to simulate the change in UFO velocity. The
observation is divided into three 10-ks segments, which is the typical
variability timescale of UFOs (Parker et al., 2017a; Reeves et al., 2023). In
Fig.10, we depict the corresponding data/model ratios with respect to the
broadband continuum model. The blueshifted UFO features are indicated by
vertical dashed green lines. The significance of UFO detection in each
spectrum is at least larger than 5$\sigma$
($\Delta\mathrm{C-stat/d.o.f.}=53\mbox{--}376/4$), whereas in the simulated
100-ks XMM-Newton spectra, the UFO in the faintest state is undetectable
($\Delta\mathrm{C-stat}=6$). Additionally, the constraints on UFO parameters
by ATHENA/X-IFU with only a 10 ks exposure are a factor of $1\mbox{--}4$
stricter than those by XMM-Newton with a $100$ ks exposure time, (e.g.
$\Delta\log\xi_{XMM}=0.06$ versus $\Delta\log\xi_{\mathrm{X-IFU}}=0.03$)
(Barret et al., 2018).

This simulation demonstrates that ATHENA can achieve about ten times more
effective UFO detection with only one-tenth of the exposure time compared with
XMM-Newton. Its powerful capabilities allow to track the response of the UFO
on the variability time-scale of the ionizing continuum and the dynamical
time-scale of the innermost regions of the accretion disk. Consequently,
ATHENA holds significant promise in advancing our understanding of AGN
outflows and identifying the UFO launching mechanisms.

##  7 Conclusions

In this work, we present a systematic analysis of the available archival XMM-
Newton observations of six highly accreting NLS1 galaxies, selected by UFO
detection and exposure times, through high-resolution time- and flux-resolved
spectroscopy. In summary, the results of our analysis are the following:

  1. -

The powerful method of the photoionization model scan over the high-resolution
RGS spectra reveals three previously unreported UFOs in the archival datasets
of RE J1034+396, PG 1244+026, and I ZW 1. All of them, confirmed through MC
simulations, exhibit a detection significance above $3\sigma$. Additionally,
in RE J1034+396, two previously unknown WAs have been detected.

  2. -

Outflows (WAs and UFOs) in 5 out of 6 (83%) AGN of our sample shows a multi-
phase structure. We discover an energy-conserved outflow in I ZW 1 and a
strong correlation between the velocity and ionization parameter of UFOs in PG
1211+143. 4 (66%) AGN in our sample host UFOs and WAs sharing a similar
ionization parameter, supporting the shocked outflow interpretation for multi-
phase ionized winds in AGN.

  3. -

The UFO detection in our sample combined with the literature (Parker et al.,
2018) exhibits an inclination-dependent behavior, where most UFOs are detected
in AGN with an inclination angle between $30\mbox{--}60^{\circ}$, most likely
due to selection effects.

  4. -

We notice that 2 out of 7 (28%) UFOs in our sample seem to respond to the
ionizing luminosity and 3 (43%) UFOs hint at a radiatively-driven nature,
requiring further observations for confirmation.

  5. -

Combined with published works, we discover no correlations between UFO
responses and AGN intrinsic properties except for a tentative ($\sim
1.8\sigma$) anti-correlation between the radiation acceleration on winds and
Eddington ratio. Further observations and an enlarged sample are required to
confirm this trend.

  6. -

We estimate the location and energetics of UFOs and find the constraints on
soft X-ray UFOs are too loose to conclude that soft X-ray UFOs could exert a
significant feedback impact on the surrounding environment, requiring future
observations and new methods, although they are very promising based on some
reasonable assumptions. The hard X-ray UFO in I ZW 1 is the only case in our
sample with conclusively sufficient power to affect the host galaxy.

##  8 Acknowledgements

We thank the anonymous referee for useful suggestions. This research has made
use of data obtained with the XMM-Newton, an ESA science mission funded by ESA
Member States and the USA (NASA). We thank Peter Kosec for insightful
discussions on the interpretation of our results. Y. X. acknowledges support
from the European Space Agency (ESA) archival research visitor program. C. P.
and S. B. acknowledge support for PRIN MUR 2022 SEAWIND 2022Y2T94C (funded by
NextGenerationEU) and INAF LG 2023 BLOSSOM. D.R. is supported by NASA through
the Smithsonian Astrophysical Observatory (SAO) contract SV3-73016 to MIT for
Support of the Chandra X-Ray Center (CXC) and Science Instruments and the
Margaret Burbidge Prize at University of Chicago. E.K. acknowledges XRISM
Participating Scientist Program for support under NASA grant 80NSSC20K0733.
The research leading to these results has received funding from the European
Union’s Horizon 2020 Programme under the AHEAD2020 project (grant agreement n.
871158).

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##  Appendix A Details of Individual targets and Spectral Analysis

Our sample comprises six AGN. In this appendix, we present an overview of
basic information for each source, alongside details of the Gaussian line scan
results and the photoionization modeling of warm absorbers (listed in Tab.6)
and UFOs (see Tab.3).

Table 6: Table of the best-fit WA parameters in extracted spectra of targets
in this work. The uncertainties of parameters are estimated at the 90%
confidence level ($\Delta\mathrm{C-stat}=2.71$).

Sources | WA
---|---
| $\log\xi$ | $N_{\mathrm{H}}$ | $\sigma_{\mathrm{v}}$ | $v_{\mathrm{LOS}}$ | $\Delta\rm C\mbox{-}stat$ | single trial
| $\mathrm{erg\,cm\,s^{-1}}$ | ($10^{20}$ cm-2) | (km/s) | (km/s) |  | significance ($\sigma$)
1H 1934-063 |  |  |  |  |  |
2015 | $1.88^{+0.04}_{-0.05}$ | $8^{+3}_{-2}$ | $<150$ | $-400^{+200}_{-300}$ | 159 | ¿8
2021 | $1.89^{+0.04}_{-0.04}$ | $8^{+3}_{-2}$ | $100^{+50}_{-50}$ | $-300^{+100}_{-100}$ | 215 | ¿8
F1 | $1.88^{+0.05}_{-0.06}$ | $10^{+5}_{-3}$ | $<100$ | $-250^{+100}_{-200}$ | 99 | ¿8
F2 | $1.88^{+0.05}_{-0.03}$ | $8^{+3}_{-2}$ | $100^{+50}_{-50}$ | $-300^{+100}_{-100}$ | 142 | ¿8
RE J1034+396 |  |  |  |  |  |
avg⋆ | $3.61^{+0.03}_{-0.03}$ | $27^{+3}_{-3}$ | $300^{+100}_{-50}$ | $-1100^{+100}_{-100}$ | 514 | ¿8
$0.0^{+0.2}_{-0.2}$ | $1.1^{+0.4}_{-0.5}$ | $7200^{+1600}_{-2200}$ | $-19800^{+1500}_{-2700}$ | 109 | ¿8
$1.89^{+0.11}_{-0.20}$ | $0.65^{+0.19}_{-0.09}$ | $300^{+100}_{-100}$ | $-350^{+100}_{-100}$ | 100 | ¿8
F1⋆ | $3.64^{+0.11}_{-0.20}$ | $32^{+10}_{-9}$ | $100^{+200}_{-50}$ | $-1400^{+200}_{-200}$ | 149 | ¿8
$-0.9^{+0.7}_{-0.8}$ | $2.4^{+0.7}_{-1.1}$ | $10000^{\bullet}$ | $-30900^{+5100}_{-1800}$ | 36 | 5.1
$1.97^{+0.18}_{-0.21}$ | $1.6^{+1.0}_{-0.5}$ | $150^{+100}_{-100}$ | $-300^{+200}_{-200}$ | 53 | 6.5
F2⋆ | $3.59^{+0.07}_{-0.07}$ | $27^{+6}_{-4}$ | $300^{+100}_{-100}$ | $-1000^{+200}_{-200}$ | 180 | ¿8
$-0.2^{+0.1}_{-0.1}$ | $1.1^{+0.4}_{-0.3}$ | $2000^{+900}_{-1000}$ | $-21300^{+3000}_{-600}$ | 67 | 7.4
$1.78^{+0.17}_{-0.27}$ | $0.6^{+0.3}_{-0.2}$ | $300^{+400}_{-100}$ | $-600^{+200}_{-300}$ | 23 | 3.8
high⋆ | $3.46^{+0.09}_{-0.09}$ | $27^{+4}_{-4}$ | $550^{+300}_{-200}$ | $-700^{+200}_{-200}$ | 100 | ¿8
$0.0^{+0.3}_{-0.4}$ | $1.2^{+0.8}_{-1.0}$ | $10000^{\bullet}$ | $-21000^{+2400}_{-3900}$ | 20 | 3.5
PG 1211+143 |  |  |  |  |  |
T7 | $2.40^{+0.18}_{-0.19}$ | $18^{+11}_{-9}$ | $<100$ | $-3000^{+900}_{-600}$ | 22 | 3.7
I ZW 1 |  |  |  |  |  |
avg⋆ | $-0.40^{+0.10}_{-0.09}$ | $5.0^{+0.7}_{-0.7}$ | $200^{+50}_{-50}$ | $-1800^{+100}_{-100}$ | 384 | ¿8
$2.70^{+0.12}_{-0.11}$ | $6^{+6}_{-3}$ | $<100$ | $-2400^{+300}_{-300}$ | 41 | 5.6
2005 | $-0.34^{+0.21}_{-0.31}$ | $7^{+2}_{-2}$ | $150^{+100}_{-100}$ | $-1900^{+200}_{-300}$ | 76 | 8.0
F1⋆ | $-0.27^{+0.09}_{-0.09}$ | $3.5^{+0.8}_{-0.7}$ | $500^{+200}_{-300}$ | $-1800^{+200}_{-200}$ | 111 | ¿8
$2.44^{+0.30}_{-0.18}$ | $5^{+7}_{-2}$ | $100^{+200}_{-50}$ | $-1800^{+300}_{-300}$ | 28 | 4.4
F2⋆ | $-0.14^{+0.19}_{-0.09}$ | $4.8^{+1.0}_{-0.9}$ | $100^{+100}_{-50}$ | $-2000^{+200}_{-200}$ | 91 | ¿8
$2.78^{+0.10}_{-0.18}$ | $30^{+30}_{-20}$ | $<100$ | $-2400^{+900}_{-600}$ | 19 | 3.3
2020 | $-1.00^{+0.09}_{-0.19}$ | $14^{+3}_{-3}$ | $200^{+100}_{-100}$ | $-1700^{+200}_{-200}$ | 172 | ¿8
IRAS 17020+4544 |  |  |  |  |  |
avg⋆ | $-0.3^{+0.1}_{-0.1}$ | $4.7^{+0.6}_{-0.7}$ | $750^{+700}_{-200}$ | $50^{+200}_{-300}$ | 638 | ¿8
$1.9^{+0.1}_{-0.1}$ | $23^{+4}_{-4}$ | $<100$ | $300^{+200}_{-100}$ | 160 | ¿8
$-2.8^{+0.2}_{-0.1}$ | $6^{+1}_{-1}$ | $700^{+200}_{-200}$ | $-3900^{+300}_{-300}$ | 164 | ¿8
F1⋆ | $-1.0^{+0.2}_{-0.2}$ | $3.9^{+1.0}_{-0.6}$ | $1000^{+800}_{-100}$ | $-6000^{+600}_{-600}$ | 248 | ¿8
$2.0^{+0.1}_{-0.1}$ | $16^{+4}_{-6}$ | $<100$ | $250^{+300}_{-300}$ | 72 | 7.8
$-2.5^{+0.2}_{-0.2}$ | $9^{+1}_{-1}$ | $750^{+200}_{-200}$ | $-3900^{+300}_{-300}$ | 68 | 7.5
F2⋆ | $-0.2^{+0.3}_{-0.1}$ | $5.0^{+2.1}_{-1.4}$ | $600^{+100}_{-100}$ | $100^{+200}_{-200}$ | 222 | ¿8
$1.8^{+0.1}_{-0.1}$ | $21^{+4}_{-4}$ | $100^{+50}_{-50}$ | $200^{+300}_{-200}$ | 104 | ¿8
$-2.7^{+0.3}_{-0.2}$ | $5^{+2}_{-2}$ | $1000^{+700}_{-200}$ | $-4200^{+600}_{-600}$ | 44 | 5.8
F3⋆ | $0.0^{+0.2}_{-0.3}$ | $4.7^{+1.0}_{-0.9}$ | $500^{+300}_{-300}$ | $0^{+300}_{-300}$ | 205 | ¿8
$1.9^{+0.1}_{-0.1}$ | $29^{+10}_{-6}$ | $<100$ | $350^{+200}_{-200}$ | 92 | ¿8
$-2.7^{+0.2}_{-0.3}$ | $8^{+2}_{-2}$ | $700^{+300}_{-200}$ | $-3900^{+300}_{-300}$ | 81 | ¿8

⋆ Multiple WAs are detected in this spectrum.

∙ The parameter is fixed.

###  A.1 1H 1934-063

1H 1934-063 is a nearby ($z=0.0102$) radio-quiet NLS1 galaxy, presenting
variable X-ray fluxes (Ponti et al. 2012). The spin of the central SMBH was
estimated at $a_{\star}<0.56$ (Xu et al. 2022) or $a_{\star}>0.4$ (Jiang et
al. 2019a) depending on whether a high-density relativistic reflection model
was adopted. In the 2015 observation of 1H 1934-063, a $\sim 20$s time lag was
detected between the disk reprocessing component and the primary continuum,
indicating a compact corona with a height of $9\pm 4\,R_{\mathrm{g}}$
($R_{\mathrm{g}}\equiv GM_{\mathrm{BH}}/c^{2}$) in the lamppost geometry. In
the RGS spectrum, distinct signatures of a WA and a moderately ionized UFO
have been identified as well (Xu et al. 2022). Moreover, the tentative
evidence for the reprocessing of the coronal photons onto the base of winds
has also been observed. Furthermore, two XMM-Newton observations were
conducted on 1H 1934-063 in 2021 and the data analysis is presented here.

The results of the Gaussian line scan in the RGS band are shown in Fig.11,
highlighting the consistent presence of the WA features, such as N vii, O
viii, Fe xviii, Fe xvii, and Ne ix across all spectra. The prominent UFO
absorption features transition from O vii and O viii to Fe complex lines, Fe
xxi-xxiii between 2015 and 2021. In contrast, the properties of the WA remain
constant for six years (see Tab.6).

UFOs detected in the 2021 observations exhibit distinct properties from that
in 2015 (Xu et al. 2022) with higher ionization states, larger column
densities, and faster speeds (see Tab.3). However, the observations of these
two epochs share similar X-ray luminosity (see panel a of Fig.1), indicating
that the difference is unrelated to the radiation field. The origin of the UFO
change remains mysterious, perhaps resulting from different phases of UFOs or
unknown prior variable accretion rates. In the flux-resolved spectra from
consecutive 2021 observations, most UFO properties remain stable within their
uncertainties, except for a slightly higher velocity at the brighter state.

Figure 11: The single trial significance obtained from the Gaussian line scan
with different line widths (500, 1500, 4500 km/s) over the rest-frame spectra
of 1H 1934-063 in the RGS band. The vertical dashed blue lines represent the
rest-frame energies of the known ion transitions as a reference, while the red
lines and the shaded region respectively correspond to the centroid and
$1\sigma$ uncertainties of the prominent UFO absorption lines detected in the
following photoionization modeling. The gray region marks the $3\sigma$
significance.

###  A.2 RE J1034+396

RE J1034+396 is a nearby ($z=0.042$) NLS1 galaxy, firstly exhibiting
significant X-ray quasi-periodic oscillation (QPO) within an AGN with the
period of $2.7\times 10^{-4}$ Hz (e.g., Gierliński et al. 2008; Alston et al.
2014b; Jin et al. 2020). It has an extraordinarily steep soft X-ray in the
spectrum (Puchnarewicz et al. 1995). The mass of the central SMBH was
estimated within $10^{6}\mbox{--}10^{7}\,M_{\odot}$ (summarized by Czerny et
al. 2016), with the most probable mass range of $(1\mbox{--}4)\times
10^{6}\,M_{\odot}$ (e.g., Gierliński et al. 2008; Middleton et al. 2009;
Chaudhury et al. 2018). Over a span of more than a decade, XMM-Newton has
observed this source multiple times. A large observation campaign of this
source was executed in 2020 and 2021 with a total amount of 855 ks exposure
time. In this work, we focus on the data from the 2020-2021 campaign, as well
as three archival observations capturing RE J1034+396 at bright states.

We present the outcomes of the Gaussian line scan over the continuum model in
Fig.12. The results for the first time unveil a series of strong absorption
lines at their rest-frame energies, including Ne ix, Fe xx, O vii, and O viii.
The spectra require two distinct WAs, each existing at different ionization
states ($\log\xi\sim 3.6$ and $\log\xi\sim 1.9$). However, the cooler WA is
superfluous for the ‘high’ spectrum (see Tab.6). A broad trough is evident on
the blue side of the O vii line. We initially speculated its association with
blueshifted O vii. However, our photoionization model scan suggests a neutral
absorber ($\log\xi\sim 0$) with an ultra-fast velocity. In the F1 and ‘high’
spectra, the line width of this component is too broad to be constrained and
thus fixed at 10000 km/s. This particular neutral ionization state precludes
its classification as a UFO. Consequently, we name it a ‘warm absorber’, while
its origin remains subject to future investigation.

UFOs are degenerated to explain similar Fe complex absorption lines between
$1\mbox{--}1.2$ keV (Fig.12), indicating the same origin. The degenerated
region can be observed in the panel b of Fig.3 and the top panel of Fig.4,
where the best-fit UFO solutions for F1 and F2 spectra manifest at the high-
speed end of the degenerate solutions while the ‘high’ spectrum solution is
notably confined to a lower-speed domain. The statistical difference between
these two distinct solutions (see Tab.3) within the ‘high’ spectrum is
$\Delta\mathrm{C}\mbox{--}\mathrm{stat}=16$ and it becomes even larger for
UFOs in flux-resolved spectra, disfavoring the explanation of stochastic
variability. Therefore, statistics differentiate these UFOs, resulting in
correlations of the ionization parameter and column density with X-ray
luminosity while the velocity does not exhibit the same behavior, of which
origin is still unknown.

Figure 12: Similiar to Fig. 11, but the scan is performed on the spectra of RE
J1034+396.

###  A.3 PG 1244+026

PG 1244+026, identified as a highly variable NLS1 galaxy (Jin et al. 2013),
exhibits notable features in the spectrum, including a strong soft excess and
a highly ionized Fe K emission line (Crummy et al. 2006). Within this source,
a soft lag at high frequencies and hard lags at low frequencies were
independently discovered by Alston et al. (2014a) and Kara et al. (2014). It
suggests the relativistic reflection off the inner accretion disk and the
propagation of the accretion fluctuations. Over the span of 2011 to 2014, XMM-
Newton conducted six observations of PG 1244+026, with five of these
observations occurring consecutively in 2014. Despite the observations, the
literature lacks any reports of UFOs in PG 1244+026.

The findings from the Gaussian line scan are presented in Fig.13. Within the
time-averaged spectrum, a series of absorption lines appear as well as the N
vii, O vii and $\sim 0.9$ keV emission lines. The identified UFO features
encompass blueshifted O vii and O viii, featuring a stable velocity of
$v_{\mathrm{LOS}}\sim-13500$ km/s across all flux- and time-resolved spectra
(time-resolved results are not shown). No warm absorber is detected in this
system.

The UFO has stable velocity and ionization parameter within their
uncertainties while simultaneously exhibiting an anticorrelation between the
column density and X-ray luminosity (see Tab.3). However, we noticed that one
observation (2011) occurred three years before the others (2014). Through the
trial of the time-resolved spectroscopy, we found that the UFO properties in
that observation resemble those found in the others, ruling out the
explanation of different UFO phases. After removing the 2011 observation,
time-resolved results lead to a decreasing trend of the column density at only
$1\sigma$ from a constant. Therefore, the observed decreasing trend may result
from long time-gap accretion variations, while the possibility of an intrinsic
anticorrelation cannot be ruled out. Moreover, given its relatively low
velocity $v_{\mathrm{LOS}}\sim-13500$ km/s, the UFO may originate from a
distant place from the SMBH, leading to a less responsive UFO to the source
variation, which awaits future investigation.

Figure 13: Similiar to Fig. 11, but the scan is performed on the spectra of PG
1244+026.

###  A.4 PG 1211+143

PG 1211+143 is a well-studied and luminous NLS1/quasar at a redshift of
$z=0.0809$, showing a typical X-ray luminosity of $\sim
10^{44}\,\mathrm{erg/s}$ and a bright optical flux with a strong ‘Big Blue
Bump’. This source is well-known for its spectral complexity and the presence
of highly variable and multi-phase UFOs (e.g., Pounds et al. 2003; Pounds &
Reeves 2007, 2009; Pounds 2014; Pounds et al. 2016b, a; Reeves et al. 2018).
The velocity range of these UFOs spans from -18000 km/s to -81000 km/s (Pounds
et al. 2016b; Danehkar et al. 2018), revealing absorption lines across both
soft and hard X-ray bands. Moreover, a corresponding UV counterpart to the
UFO, outflowing at a comparable velocity, was documented by Kriss et al.
(2018). In addition, a soft time lag of $\sim 500$s at $\sim 10^{-4}$ Hz (de
Marco et al. 2011) and a hard lag up to $\sim 3$ks at $\sim 10^{-5}$ Hz
(Lobban et al. 2018) were reported in this source. The total XMM-Newton
exposure on this source culminates at $\sim 900$ ks, with a majority of
observations conducted consecutively at varying flux levels. As a result, a
time-resolved spectroscopic analysis is undertaken to investigate both
temporal and flux variability.

The Gaussian line scan results are shown in Fig.14, where the UFO features are
marked by vertical red lines. The predominant UFO features are blueshifted O
viii and Fe UTA lines in the soft X-ray regime, along with S xvi, Ar xviii,
and Fe xxv/xxvi features in the hard X-ray band. The UFOs identified within
our analysis are multi-phase and highly variable, in accordance with prior
investigations (e.g., Reeves et al. 2018; Pounds et al. 2016b). According to
our criterion for the outflow detection significance, we only find one fast
warm absorber in the ‘T7’ spectrum (see Tab.6).

Consistent with the literature (e.g. Pounds et al. 2016a; Reeves et al. 2018),
we found that UFOs are highly variable and multi-phase. The LOS velocity
ranges from $-10000$ to $-76000$ km/s and the ionization parameter $\log\xi$
spans between 1.5 and 5. The predominant UFO features are blueshifted Fe UTA
lines in the soft X-ray regime, along with S xvi, Ar xviii, and Fe xxv/xxvi
features in the hard X-ray band. We do not find any UFOs with a significance
$\Delta\mathrm{C}\mbox{--}\mathrm{stat/d.o.f.}>16/4$ in the T2 spectrum,
whereas a secondary UFO attains noteworthy significance in the T1 and T11
spectrum. The most robust UFO detection falls in the faintest T6 spectrum
($\Delta\mathrm{C}\mbox{--}\mathrm{stat/d.o.f.}=100/4$), attributed to the
passage of an absorbing cloud (Reeves et al. 2018). Among UFOs in our results,
the solution featuring $v_{\mathrm{LOS}}\sim-18000$ km/s emerges as the most
recurrent, while others manifest a notably stochastic behavior. Given the
consecutive observations of 2014, such complexity cannot be attributed to the
long time-gap accretion variations and was explained by some intrinsic disk
instability (Pounds et al. 2016a).

Figure 14: Similiar to Fig. 11, but the scan is performed on the spectra of PG
1211+143.

###  A.5 I ZW 1

I ZW 1 is a nearby ($z\sim 0.06$) NLS1 galaxy with a bright ($\sim
10^{44}\,\mathrm{erg/s}$, Gallo et al. 2004) and variable X-ray luminosity
(Wilkins et al. 2017). Its X-ray spectrum reveals the presence of a strong Fe
K emission and a weak soft excess (Gallo et al. 2007). Wilkins et al. (2017)
unveiled a time lag of $\sim 160$s between the reflection-dominated energy and
continuum-dominated band within $3\mbox{--}12\times 10^{-4}$ Hz. Notably, the
signatures of the light bending and X-ray echoes around the event horizon were
observed through the delayed and redshifted flare emission observed in a
luminous event in 2020 (Wilkins et al. 2021). Furthermore, the soft X-ray
spectrum of I ZW 1 reveals the presence of two WAs, exhibiting a long-term
variable nature (Costantini et al. 2007; Silva et al. 2018). It was attributed
to the presence of either a two-phase WA originating from a shared clump or
absorbing gas existing in a non-equilibrium state. The exploration of the hard
X-ray spectrum unveils the existence of a highly ionized ($\log\xi\sim 4.9$)
and high-speed ($v\sim-0.25c$) UFO during the 2005 and 2015 observations
(Reeves & Braito 2019). A subsequent observation in 2020, analyzed by
Rogantini et al. (2022a), discovered a UFO, characterized by a similar
velocity yet manifesting a lower ionization state ($\log\xi\sim 3.8$).

We present the results of the Gaussian line scan in Fig.15, where discernible
absorption lines such as O viii and Fe xviii are clearly identified at their
rest-frame positions. A prominent trough appears around 0.53 keV across all
spectra, which is associated with low-ionized oxygen. The UFO features are
marked by the red vertical dashed lines in both soft (O viii and Fe xxi-xxiii)
and hard (Fe xxv-xxvi) X-rays. Consistent with findings by (Silva et al.
2018), our analyses have detected two distinct slow absorbers, characterized
by neutral ($\log\xi\sim-0.4$) and high ($\log\xi\sim 2.7$) ionization states
(see Tab.6). However, the high-ionization WA is not statistically necessary
for the 2005 spectrum, according to our detection threshold. The limited
photon counts of the 2005 spectrum cannot provide robust secondary absorber
detection. While similar residuals around 0.7 keV are observed in the 2020
spectrum, they have already been explained by the warm absorber featuring a
lower ionization parameter ($\log\xi\sim-1$), identified as Fe v-vi lines. The
requirement for this lower ionization state is attributed to a distinct
absorption feature solely within the 2020 spectrum, located around 0.63 keV.
The absence of this feature within the 2015 spectra prevents the neutral warm
absorber from entering the cooler regime, thus compelling the consideration of
an alternative UFO to account for the unexplained 0.7 keV feature.

We found a highly-ionized ($\log\xi>4.5$) and fast-moving UFO in 2015
observations through blueshifted Fe xxv-xxvi absorption lines, consistent with
previous works (Reeves & Braito 2019). This UFO in flux-resolved spectra
remains stable. The UFO detected within the 2020 spectrum exhibits a
comparable ionization parameter ($\log\xi\sim 3.8$) to the one found in
Rogantini et al. (2022a), accounting for residuals $\sim 1.2$ keV (Wilkins et
al. 2022). In 2015 observations, our scan uncovers a previously unreported
secondary UFO in soft X-rays (I ZW 1-2), particularly evident for the
absorption feature around 0.7 keV (Fig.15). The column density and velocity of
this UFO are stable in 2015 observations, while the ionization parameter seems
to increase with the X-ray luminosity.

Figure 15: Similiar to Fig. 11, but the scan is performed on the spectra of I
ZW 1.

###  A.6 IRAS 17020+4544

IRAS 17020+4544 emerges as a nearby ($z=0.0604$) radio-loud NLS1 galaxy, known
to be characterized by a WA (Leighly et al. 1997) and a compact radio emission
(Snellen et al. 2004). The archival multi-wavelength campaign for IRAS
17020+4544 has revealed the presence of multi-phase UFOs ($v\sim
24000\mbox{--}27000$ km/s) in the X-ray spectra (Longinotti et al. 2015;
Sanfrutos et al. 2018), a galaxy-scale molecular outflow (Longinotti et al.
2018) in addition to a sub-relativistic jet on parsec scales in the radio band
(Giroletti et al. 2017). Moreover, a UV counterpart of the X-ray UFO outflow
has been detected through Ly$\alpha$ absorption, showing a velocity similar to
its X-ray counterpart. Collectively, these discoveries suggest that AGN-driven
hot gas gives rise to large-scale shocks into the interstellar medium.

The outcomes of the line scan are depicted in Fig.16, exhibiting strong
absorption and emission lines within the spectra. The prominent absorption
features are located around 0.53, 0.75, and 0.88,keV. As reported in Sanfrutos
et al. (2018), our investigation identifies the presence of three distinct
warm absorbers (WAs) in the spectra, each marked by substantial statistical
significance (see Tab.6). WA1 and WA3 emerge as absorbers characterized by low
ionization states, mainly explaining the absorption feature at 0.53 keV. On
the other hand, WA2 is moderately ionized and models the feature around 0.75
and 0.88 keV.

We found a moderately ionized ($\log\xi\sim 1.9$) UFO with a LOS velocity of
$v_{\mathrm{LOS}}\sim-23100$ km/s in the soft X-ray band. It accounts for the
residual around 0.71 keV (Fig.16). This UFO is consistent with the findings of
Sanfrutos et al. (2018), while the remaining three UFOs in their work
disappear in our analyses due to their tiny significance
($\Delta$C-stat/d.o.f.$<10/4$). The properties of such UFO are remarkably
stable across flux-resolved spectra.

Figure 16: Similiar to Fig. 11, but the scan is performed on the spectra of
IRAS 17020+4544.

##  Appendix B UFO properties versus unabsorbed X-ray luminosity

The best-fitting column density, ionization parameter, and velocity of UFOs in
our sample versus the unabsorbed luminosity between $0.4\mbox{--}10\,$keV are
shown in Fig.17, where a powerlaw function is applied to fit using the
scipy.odr.ODR package in Python, as depicted by the dashed lines. Given the
variable and multi-phase nature of UFOs, discerning whether UFOs exhibiting
distinct properties are manifestations of the same plasma is challenging.
Consequently, to ensure that we are tracing the same absorber at different
fluxes rather than comparing different UFOs in different epochs, in our
fitting, we exclude UFOs that significantly differ from others and have long
intervals from the rest within the same system, i.e. excluding UFOs in the
‘2015’ spectrum of 1H 1934-063 and in the ‘2020’ spectrum of I ZW 1 from the
fits. In addition, UFOs with only two measurements are not included in our
fits due to zero degrees of freedom, resulting in only 4 UFOs (in RE
J1034+396, PG 1244+026, PG 1211+143, and IRAS 17020+4544) remaining in the
fits. The second UFOs observed in T1 and T11 spectra of PG 1211+143 are marked
by the same label as others and all UFOs in PG 1211+143 are fitted together
because UFOs in this AGN have too many phases to identify which UFOs share the
same origin.

Figure 17: The column density, ionization parameter, and velocity of UFOs in
our sample versus the unabsorbed luminosity between $0.4\mbox{--}10\,$keV. The
fits with a power function are performed and depicted by dashed lines with
$1\sigma$ uncertainty shaded.

##  Appendix C The slope of the UFO properties versus $M_{\mathrm{BH}}$ and
$L_{\mathrm{ion}}$

The slopes of the UFO properties including the column density
$\Gamma_{N_{H}}$, ionization state $\Gamma_{\mathrm{\log\xi}}$ and velocity
$\Gamma_{v}$ are collected to compare with the intrinsic AGN properties,
consisting of the black hole mass $M_{\mathrm{BH}}$, bolometric luminosity
$L_{\mathrm{bol}}$, Eddington ratio $\lambda_{\mathrm{Edd}}$, and inclination
angle. The results are depicted in Fig.18. Our examination, facilitated by
calculating the Pearson correlation coefficient, failed to reveal any
significant correlations between the pairs of
$\Gamma_{N_{H}}$/$\Gamma_{\mathrm{\log\xi}}$ and AGN properties by calculating
the Pearson correlation coefficients. Only an anticorrelation is obviously
observed between $\Gamma_{v}$ and $\lambda_{\mathrm{Edd}}$, discussed in Sec.
6.2.

Figure 18: The evolution slopes of the UFO column density $\Gamma_{N_{H}}$
(top), ionization state $\Gamma_{\mathrm{\log\xi}}$ (middle) and velocity
$\Gamma_{v}$ (bottom) versus the black hole mass $M_{\mathrm{BH}}$ (a),
bolometric luminosity $L_{\mathrm{bol}}$ (b), Eddington ratio
$\lambda_{\mathrm{Edd}}$ (c), and inclination angle (d). The data come from
the results listed in Tables 2 and 3. The horizontal dashed lines denote the
zero value of the slope.