# Detection of a Highly Ionized Outflow in the Quasi-periodically Erupting
Source GSN 069

P. Kosec MIT Kavli Institute for Astrophysics and Space Research,
Massachusetts Institute of Technology, Cambridge, MA 02139  Center for
Astrophysics — Harvard & Smithsonian, Cambridge, MA, USA  E. Kara MIT Kavli
Institute for Astrophysics and Space Research, Massachusetts Institute of
Technology, Cambridge, MA 02139  L. Brenneman Center for Astrophysics —
Harvard & Smithsonian, Cambridge, MA, USA  J. Chakraborty MIT Kavli Institute
for Astrophysics and Space Research, Massachusetts Institute of Technology,
Cambridge, MA 02139  M. Giustini Centro de Astrobiología (CAB), CSIC-INTA,
Camino Bajo del Castillo s/n, 28692 Villanueva de la Cañada, Madrid, Spain  G.
Miniutti Centro de Astrobiología (CAB), CSIC-INTA, Camino Bajo del Castillo
s/n, 28692 Villanueva de la Cañada, Madrid, Spain  C. Pinto INAF - IASF
Palermo, Via U. La Malfa 153, I-90146 Palermo, Italy  D. Rogantini Department
of Astronomy and Astrophysics, The University of Chicago, Chicago, IL 60637
R. Arcodia MIT Kavli Institute for Astrophysics and Space Research,
Massachusetts Institute of Technology, Cambridge, MA 02139  M. Middleton
School of Physics & Astronomy, University of Southampton, Southampton,
Southampton SO17 1BJ, UK  A. Sacchi Center for Astrophysics — Harvard &
Smithsonian, Cambridge, MA, USA

###### Abstract

Quasi-periodic eruptions (QPEs) are high-amplitude, soft X-ray bursts
recurring every few hours, associated with supermassive black holes. Many
interpretations for QPEs were proposed since their recent discovery in 2019,
including extreme mass ratio inspirals and accretion disk instabilities. But,
as of today, their nature still remains debated. We perform the first high-
resolution X-ray spectral study of a QPE source using the RGS gratings onboard
XMM-Newton, leveraging nearly 2 Ms of exposure on GSN 069, the first
discovered source of this class. We resolve several absorption and emission
lines including a strong line pair near the N VII rest-frame energy,
resembling the P-Cygni profile. We apply photoionization spectral models and
identify the absorption lines as an outflow blueshifted by $1700-2900$ km/s,
with a column density of about $10^{22}$ cm-2 and an ionization parameter
$\log(\xi$/erg cm s${}^{-1})$ of $3.9-4.6$. The emission lines are instead
redshifted by up to 2900 km/s, and likely originate from the same outflow that
imprints the absorption features, and covers the full $4\pi$ sky from the
point of view of GSN 069. The column density and ionization are comparable to
the outflows detected in some tidal disruption events, but this outflow is
significantly faster and has a strong emission component. The outflow is more
highly ionized when the system is in the phase during which QPEs are present,
and from the limits we derive on its location, we conclude that the outflow is
connected to the recent complex, transient activity of GSN 069 which began
around 2010.

Accretion (14), Supermassive black holes (1663), X-ray transient sources(1852)

††facilities: XMM-Newton††software: SPEX (Kaastra et al., 1996), Veusz

##  1 Introduction

Quasi-periodic eruptions (hereafter QPEs) are recently discovered high-
amplitude transient phenomena, first detected in GSN 069 (Miniutti et al.,
2019), which appear to occur in some low-mass supermassive black holes
($10^{5}-10^{7}$ M⊙). They involve a sudden spike in the X-ray flux of the
source, mostly in the soft X-ray band ($<2$ keV) with a blackbody spectral
shape ($kT\sim 100$ eV), a duration of $1-30$ ks (Miniutti et al., 2023b), and
a repeating timescale from hours to tens of days, depending on the source. As
of February 2024, 5 sources were known to exhibit QPEs in addition to GSN 069
(Sun et al., 2013; Giustini et al., 2020; Arcodia et al., 2021, 2024), and
further systems are good candidates or likely related to the QPE phenomenon
(Chakraborty et al., 2021; Quintin et al., 2023; Evans et al., 2023; Guolo et
al., 2024). These sources show that QPEs are primarily an X-ray band
phenomenon, and their host systems exhibit little, if any nuclear
(supermassive black hole related) activity in other energy bands.
Additionally, QPEs have been observed to be a transient phenomenon, appearing
and disappearing for years at a time (GSN 069, Miniutti et al., 2023a), as
well as showing a long-term flux fading trend (eRO-QPE1, Chakraborty et al.,
2024; Pasham et al., 2024a).

In the last few years, many models have been proposed to explain QPEs. The
phenomenon may be related to tidal disruption events and/or extreme mass ratio
inspirals (Suková et al., 2021; Xian et al., 2021; King, 2022; Metzger et al.,
2022; Krolik & Linial, 2022; Franchini et al., 2023; Lu & Quataert, 2023;
Linial & Metzger, 2023; Tagawa & Haiman, 2023; Zhou et al., 2024a, b).
Alternative models propose that it is connected to accretion disk
instabilities or disk tearing (Raj & Nixon, 2021; Pan et al., 2022, 2023;
Śniegowska et al., 2023; Kaur et al., 2023). However, all of these models
struggle to explain all the complex behaviour of QPE systems, and so the
nature of QPEs remains to be determined. Crucially, more observational work is
required to reveal further physics and the emission mechanism of these
intriguing systems.

All previous X-ray spectral QPE studies exclusively focused on data from the
moderate spectral resolution X-ray instruments such as the CCDs onboard XMM-
Newton and Chandra, which offer the highest effective area, and result in the
best count rates. However, the very soft (kT$\sim 50-100$ eV) blackbody-like
spectral energy distribution (SED) of QPE sources both during their quiescence
as well as QPEs makes them also ideal targets for X-ray gratings such as the
Reflection Grating Spectrometers (RGS) onboard XMM-Newton, which operate in
this soft X-ray band ($0.35-2$ keV). RGS gratings offer a lower collecting
area compared with the CCD instruments, and hence worse statistics, but much
better spectral resolution. Therefore, with grating spectra, we may resolve
individual spectral lines in these systems, revealing further the physics of
the QPE phenomenon. As an example, high-spectral resolution X-ray grating
spectra of two tidal disruption events (Miller et al., 2015; Kosec et al.,
2023), which have X-ray spectral shapes similar to those of QPE sources,
revealed complex absorption line spectra imprinted by ionized outflows.

By the end of 2023, individual QPE sources have been the targets of intensive
observational campaigns - e.g., XMM-Newton has already observed GSN 069 for
almost 2 Ms. Here we present the first in-depth high-spectral resolution study
of a QPE system, making use of this extensive archive of RGS spectra on GSN
069. In Section 2, we describe our data reduction and stacking procedures. In
Section 3, we present our spectral modelling approach of the RGS dataset and
the main results of this study. In the following Section 4, we analyze the
simultaneous XMM-Newton European Photon Imaging Camera (EPIC) datasets.
Finally, in Section 5 we discuss our findings and their implications and list
the conclusions in Section 6.

##  2 Data reduction and stacking

We analyze all XMM-Newton (Jansen et al., 2001) observations of GSN 069
performed by the end of July 2023. These data were downloaded from the XMM-
Newton Science Archive and reduced using sas v20, caldb as of February 2023.
We primarily work with data from the RGS (den Herder et al., 2001), but also
reduce data from the EPIC pn and MOS instruments (Strüder et al., 2001; Turner
et al., 2001).

RGS data were filtered using standard methods with the rgsproc routine, while
centering the extraction region position on the location of GSN 069. Any
background flares were filtered with a threshold of 0.25 counts/s. We
primarily work with observational background spectra, but also tested the
robustness of our results using blank field backgrounds. Data from the two RGS
instruments (RGS 1 and 2) were not stacked, instead we always analyze them
simultaneously using an extra cross-calibration constant parameter. The value
of this constant was always within 10% of unity, indicating good agreement
between RGS 1 and RGS 2. We binned the RGS spectra by a factor of 3 to achieve
mild oversampling of the instrumental spectral resolution. This was achieved
with the ‘bin’ command in the spex fitting package (Kaastra et al., 1996).
Wavelength range in which the RGS spectra are used varies from dataset to
dataset. We use as broad wavelength band as possible, and only cut off any
range which has no source signal. This often happens on the lower end of the
RGS wavelength coverage (given the spectral softness of GSN 069). The upper
end of the wavelength range is 36 Å, on the edge of the fully calibrated RGS
band. Additionally, we also removed the 31 to 33.5 Å region in all RGS 1
datasets as there is a large spike in background flux at these wavelengths,
greatly exceeding the source flux in all datasets. In this region we only use
RGS 2 data.

EPIC-pn and EPIC-MOS data were processed alongside the reduced RGS datasets
using the epproc and emproc routines, and filtered such that only events of
PATTERN$\leq$4 were accepted for pn data, and only events of PATTERN$\leq$12
were accepted for MOS data. The data were screened for background flares using
a threshold of 0.4 ct/s in the $10-12$ keV pn lightcurve. The source region
for both instruments was a circle with a radius of 35 arcsec centered on the
position of GSN 069. The background region was a polygon on the same CCD as
the source, maximizing the region area while being at least 125 arcsec away
from the source. Background-subtracted EPIC-pn lightcurves were then produced
using the epiclccorr routine. The data were grouped using the specgroup
procedure to at least 25 counts per bin and at the same time to oversample the
instrumental resolution by at most a factor of 3. The EPIC-pn data are used
between 0.3 and 4.0 keV, and the EPIC-MOS data are used between 0.5 keV and
4.0 keV.

###  2.1 Stacking

Individual RGS spectra of GSN 069 have poor data quality due to the faintness
of the source. They have at most $\sim 2000$ net source counts (RGS 1+2), but
typically show only hundreds of net counts. Therefore, we make use of data
stacking. Initially, we stacked the RGS 1 and RGS 2 spectra from all
observations together into just two spectral files (RGS 1 stack and RGS 2
stack). We note that we never analyze RGS 1 and 2 data stacked into a single
spectral file (such stacking is only done for plotting purposes). Instead, we
always stack individual RGS exposures into one RGS 1 and one RGS 2 spectrum,
which are analyzed simultaneously using a cross-calibration constant. This
stacking procedure yielded two spectra totalling 12544 and 13451 net counts
for RGS 1 and 2, respectively. This is a very high data quality achieved using
a combined net exposure of about 1.6 Ms. These stacked spectra are analyzed in
section 3.1.

Since there are over 25000 net RGS counts in total, we were able to do a data
split. To track the time and state evolution of GSN 069, we split the dataset
into 3 groups: 1. QPE state (time during QPEs), 2. Quiescent state with QPEs
(time between individual QPEs during QPE active observations), 3. Quiescent
state without QPEs (observations when the source is not showing any QPE
activity). For clarity, we show these 3 states using EPIC-pn lightcurves of
two example XMM-Newton observations in Fig. 1.

Figure 1: EPIC-pn lightcurves from two example XMM-Newton observations,
showing how we denote the 3 states of GSN 069 in this work: Quiescence without
QPEs, Quiescence with QPEs and the QPE state.

To perform this split, we identified all observations in which QPEs were
observed, primarily using EPIC-pn lightcurves, which were double-checked with
RGS lightcurves. We identified the intervals of QPE activity during each
observation (with a typical duration of $1-3$ ks) and saved them in good-time
interval (GTI) files. Then, for these XMM-Newton observations containing QPEs,
we extracted the RGS QPE, and Quiescence spectra using these GTI files.
Finally, we combined all data from the individual observations into these 3
state stacks. The same kind of splitting procedure was applied to the EPIC pn
and MOS datasets, using the same GTI files.

We note that there are a number of observations performed between 30 November
2022 and 15 January 2023 with durations shorter than the typical time interval
between two consecutive QPEs. 11 out of 19 of these observations contain QPEs.
Here we assume that GSN 069 was constantly in the QPE active state during the
period of time between Nov 2022 and Jan 2023, despite the remaining 8 XMM-
Newton observations not directly showing evidence for QPEs. We include these 8
observations in the Quiescent state with QPEs dataset stack.

The details of the stacked RGS datasets are given in Table 1. Further details
of all individual XMM-Newton observations are listed in Table 4 in Appendix A.
The quiescence state spectra (with or without QPEs) both still have very good
data quality (around 10000 net RGS counts each), while the QPE spectrum has
poorer quality with about 5000 net RGS counts due to the lower net exposure
time.

Table 1: Details of the RGS spectra in the 3 stacked datasets.  State name | RGS1 | RGS2
---|---|---
| net exposure | net counts | net exposure | net counts
| ks |  | ks |
Quiescence without QPEs | 448.7 | 4955 | 452.9 | 5222
Quiescence with QPEs | 1042.5 | 5191 | 1054.3 | 5834
QPE | 108.5 | 2503 | 109.1 | 2401

##  3 RGS dataset Spectral modelling and results

All spectra are fitted in the spex (version 3.07.03) spectral fitting package
(Kaastra et al., 1996). To analyze GSN 069 spectra using this package, we
converted the reduced spectra from ogip format into spex format using the
trafo routine. We quote all uncertainties at $1\sigma$ significance level, and
use Cash statistic (Cash, 1979) for spectral fitting. We adopt a redshift of
$z=0.018$ for GSN 069 (Miniutti et al., 2019).

###  3.1 Stacked RGS Grating Spectrum of GSN 069

As the first step of this analysis, we consider the stacked RGS spectrum of
GSN 069 including all of the XMM-Newton observations of this source. This is
the highest signal-to-noise RGS spectrum, but necessarily it will also contain
the most observation-to-observation variability as it contains all the states
of GSN 069 - the QPEs, as well as the quiescence. To investigate the
statistical significance of any tentative spectral lines in the stacked RGS
spectrum, we perform a Gaussian line scan.

First, the spectrum is fitted with a baseline continuum model. We chose a disk
blackbody (dbb in spex) as the baseline emission model. We note here that the
definition of the dbb temperature differs from the definition of temperature
in the popular diskbb model in xspec, resulting in roughly a factor of 2
difference between the two values when fitted to the same spectrum111Further
info on the dbb model can be found at https://spex-xray.github.io/spex-
help/models/dbb.html. We model the Galactic (nearly neutral) gas absorption
using the hot model, where the gas temperature is set to $10^{-3}$ eV and its
column density is fixed to $2.3\times 10^{20}$ cm-2 (HI4PI Collaboration et
al., 2016). Additionally, we use the reds model to take into account the
redshift of GSN 069.

On top of this baseline continuum, we fit a Gaussian line which can have
either positive or negative normalization (either emission or absorption line
allowed), and has a fixed wavelength and width. The width is calculated from a
pre-defined line velocity width, and the wavelength is varied according to a
wavelength grid. We search the spectrum using two representative line widths -
100 km/s (a narrow line) and 1000 km/s (a moderately broadened line). We use a
wavelength grid spanning the full energy range of the RGS spectrum (18.5 Å to
36 Å), spaced by 0.01 Å. For each wavelength in the grid, we fit the emission
model with the additional Gaussian line and recover the $\Delta$C-stat fit
improvement over the baseline continuum.

While this $\Delta$C-stat value cannot be precisely converted into statistical
significance of a potential line using a single Gaussian scan (without
performing Monte Carlo simulations) as we did not account for the look-
elsewhere effect, $\Delta$C-stat is still a good indicator of whether a
feature is real. For comparison, we highlight recent work on ultraluminous
X-ray sources (ULXs) and AGN, where much computational effort was spent to
quantify how different spectral fit improvements $\Delta$C-stat (upon adding
an outflow component to the baseline continuum model) translate to detection
significance. Even though there is no universal rule for this relationship,
typically, a $\Delta$C-stat fit improvement of $19-22$ translates to a
significance of about $3\sigma$ (Pinto et al., 2020; Kosec et al., 2018a,
2020b). Conversely, a $\Delta$C-stat fit improvement of about 30 usually
translates to a significance of $4\sigma$ (Kosec et al., 2018b; Pinto et al.,
2021). We further note that these ULX spectra, acquired also with XMM-Newton
RGS, typically have between 5000 and 30000 net counts (RGS 1 + 2 combined),
which is very similar to our GSN 069 RGS datasets in this work. At least
around 5000 net counts in the combined RGS spectrum are necessary to begin
detecting line features at $3-4\sigma$ level (Kosec et al., 2018a, 2021).

Figure 2: Top panel: RGS grating spectrum of GSN 069, obtained by combining
all available XMM-Newton observations. Most of the wavelength range contains
RGS 1+2 data, stacked and overbinned for visual purposes only, except the
range between 30.5 and 32.9 Å (in GSN 069 rest-frame) which only contains RGS
2 data. The best-fitting continuum model is shown in red and the observational
background is in blue. Bottom panel: Gaussian line scan of the same spectrum.
The Y axis defines the $\Delta$C-stat fit improvement upon adding a line to
the continuum-only model (multiplied by the sign of the spectral line
normalization), with a line width of either 100 km/s (black) or 1000 km/s
(red). Green dashed lines indicate the rest-frame wavelengths of transitions
which can plausibly explain the strongest residuals.

The results of the Gaussian line scan for the stacked RGS spectrum are shown
in Fig. 2. The spectrum reveals two strong spectral lines exceeding
$\Delta$C-stat of 50 at around 25 Å, as well as a large number of weaker (but
still likely real) features with $\Delta$C-stat between 15 and 30. In this
figure we also list potential rest-frame line identifications of these
features taken from the spectral fits of Miller et al. (2015) and Kosec et al.
(2023), who studied the RGS spectra of tidal disruption events with similar
spectral shapes as that of GSN 069. The strongest two features seen in GSN 069
are both close to the rest-frame wavelength of N VII, and appear to form a
P-Cygni shaped profile around this transition. Given the $\Delta$C-stat fit
improvements of more than 50 for both the absorption and emission components,
its statistical detection significance is thus far more than $4\sigma$. Most
of the other residuals appear to cluster close to the rest-frame transitions
of Ar XIII, XIV and S XIII, XIV. All of these transitions produced prominent
absorption lines in the spectra of TDEs ASASSN-14li (Miller et al., 2015) and
ASASSN-20qc (Kosec et al., 2023), but the Ar and S transitions are not usually
strong in AGN warm absorber spectra as those outflows are typically less
ionized (e.g. Fig. 9 of Kaastra et al., 2011). We further note that all
absorption residuals appear to the blue of the rest-frame wavelengths (with a
visually consistent blueshift), while the emission residuals are to the red of
the rest-frame wavelengths, supporting a possible P-Cygni shape origin. Based
on these spectral residuals and their positions, we conclude that GSN 069
likely exhibits an ionized outflow, observed both in absorption and emission.

To begin understanding the kinematic properties of this outflow, we use
Gaussian lines to fit the two strongest residuals located near N VII (rest-
frame wavelength of 24.77 Å). The best-fitting absorption component wavelength
is $24.48_{-0.03}^{+0.05}$ Å, indicating a blueshift of $3500_{-600}^{+400}$
km/s if associated with N VII. Conversely, the best-fitting emission component
wavelength is $25.00_{-0.08}^{+0.04}$ Å, resulting in a redshift of
$2800_{-1000}^{+500}$ km/s.

###  3.2 State-Resolved Photoionization Analysis

The presence of a large number of residuals in the RGS spectrum of GSN 069
motivates us to apply more complex photoionization spectral models which can
describe multiple spectral features at once, and allow us to determine the
physical properties of the absorbing or emitting plasma. To describe these
features we primarily use the pion photoionization spectral model (Mehdipour
et al., 2016). pion calculates transmission through a slab of plasma
illuminated by the continuum currently loaded in spex. This comes at a
significant computational cost, but ensures the most accurate calculation of
the plasma ionization balance. pion can produce both absorption and re-
emission from the illuminated plasma slab.

For this analysis, we also move away from a single stacked RGS spectrum and
instead separately study the 3 RGS spectra of GSN 069 during its 3 different
system states - Quiescence without QPEs, Quiescence with QPEs, and QPE state.
The first two of these states offer sufficient quality RGS spectra for data
analysis, which will inform us of any long-term trends in the evolution of the
ionized outflow. The QPE dataset produces the lowest-quality RGS spectrum (due
to the low exposure), but also the highest flux, which could be causing a bias
in the overall RGS stack. Comparing the QPE and Quiescence with QPEs state
spectra should allow us to probe how the plasma responds to the QPEs on the
short timescales of ks and tens of ks.

Table 2: Spectral fits of the ionized absorption and emission using the pion
photoionization model, without coupling any parameters between the absorption
and emission components.

State | Absorption component | Emission component
---|---|---
| $N_{\rm{H}}$ | $\log\xi$ | Velocity | Outflow | $\Delta$ | $N_{\rm{H}}$ | $\log\xi$ | Velocity | Outflow | $\Delta$
|  |  | width | velocity | C-stat |  |  | width | velocity | C-stat
|  $10^{22}$ cm-2 | erg cm s-1 | km/s | km/s |  |  $10^{22}$ cm-2 | erg cm s-1 | km/s | km/s |
Quiescent | $1.1_{-0.2}^{+0.3}$ | $3.86_{-0.12}^{+0.11}$ | $1100\pm 200$ | $-2900\pm 300$ | 53.33 | $0.34_{-0.10}^{+0.11}$ | $3.0\pm 0.2$ | $2700_{-1000}^{+800}$ | $100_{-900}^{+1000}$ | 23.76
without QPEs
Quiescent | $1.7\pm 0.4$ | $4.57\pm 0.13$ | $490_{-80}^{+90}$ | $-2340\pm 120$ | 77.31 | $1.3\pm 0.4$ | $3.95_{-0.22}^{+0.20}$ | $1500_{-400}^{+500}$ | $2700_{-300}^{+400}$ | 46.37
with QPEs
QPE | $1.0_{-0.4}^{+0.7}$ | $4.6\pm 0.2$ | $400_{-200}^{+400}$ | $-1700_{-400}^{+300}$ | 20.12 | $0.02_{-0.02}^{+0.09}$ | 3.95* | 1500* | 2700* | 0.04

Note. — ∗Parameter value is fixed to the best-fitting value from the spectral
fit of Quiescence with QPEs.

####  3.2.1 Quiescent states with and without QPEs

The spectrum of Quiescence without QPEs is the highest signal-to-noise dataset
since GSN 069 generally shows higher time-averaged X-ray flux (by about a
factor of two) in that state compared with Quiescence with QPEs (Miniutti et
al., 2023b). Nevertheless, the two quiescence state spectra show comparable
spectral fitting results. The baseline continuum is described using a dbb
component with a best-fitting temperature of $0.122\pm 0.002$ keV for
Quiescence without QPEs and $0.109\pm 0.002$ keV for Quiescence with QPEs.
This is absorbed by Galactic, nearly neutral hot absorption, same as was done
in the Gaussian line scan and we also use the reds model to take into account
the redshift of GSN 069. Additionally, we tested for the presence of neutral
absorption in the host galaxy of GSN 069 by adding an extra hot component
redshifted by $z=0.018$, but did not detect any significant column density.

We then apply two pion components to describe the ionized absorption and
emission separately, with the expectation (based on the Gaussian scan results,
Fig. 2) that the absorption will be blueshifted, while the emission will be
redshifted. Here, the absorber is assumed to be fully covering the X-ray
emission region from our point of view (pion parameter fcov equal to 1) and
the emitter is assumed to cover the full $4\pi$ solid angle from the point of
view of GSN 069 (pion parameter $\Omega$ equal to 1). As a first step, we fit
the absorption and emission components completely independently (without
coupling any spectral parameters). Therefore, this fit does not assume any
physical connection between the absorption and emission lines. We fit for the
column density, ionization parameter $\log(\xi$/erg cm s${}^{-1})$, systematic
(outflow) velocity and the velocity width of both components. We also recover
the fit improvement $\Delta$C-stat upon adding the ionized absorber over the
baseline (dbb) continuum, and the fit improvement upon adding the ionized
emitter to the baseline containing continuum and ionized absorption. The
results of this spectral fit for both the quiescent states are listed in Table
2, and shown in Fig. 3.

Figure 3: RGS spectrum of GSN 069 during Quiescence without QPEs (top panel)
and Quiescence with QPEs (bottom panel). Most of the wavelength range (shown
in GSN 069 rest-frame) contains RGS 1+2 data, stacked and overbinned for
visual purposes only, except the range between 30.5 and 32.9 Å which only
contains RGS 2 data. The best-fitting continuum-only model is shown in green,
while the outflow model is in red, and contains both ionized absorption and
emission (the decoupled spectral model). The most prominent spectral features
are identified with red labels. The background spectrum is in blue.

In the Quiescence without QPEs, we find that the absorber is moving at a
velocity of $2900\pm 300$ km/s, while the emitter appears roughly stationary
at $100^{+1000}_{-900}$ km/s (but with significant uncertainties). Both
components are relatively highly ionized at $\log(\xi$/erg cm s${}^{-1})$$\sim
3.86_{-0.12}^{+0.11}$ and $3.0\pm 0.2$ for the absorption and emission,
respectively, and show comparable column densities of $10^{21-22}$ cm-2.
Importantly, the addition of the absorber to the baseline continuum fit is
highly statistically significant as it improves the statistic by
$\Delta$C-stat$=53$. The emitter improves the spectral fit by somewhat less,
$\Delta$C-stat$\sim 23$. This is still significant at about $3\sigma$ (Pinto
et al., 2020; Kosec et al., 2020b).

In the Quiescence with QPEs, the addition of ionized absorption and emission
is highly significant over the baseline continuum with a fit improvement of
$\Delta$C-stat $\sim 77$ and $\Delta$C-stat $\sim 46$, respectively. Both
components show a column density of about $10^{22}$ cm-2 and high ionization
parameters $\log(\xi$/erg cm s${}^{-1})$ of $4.57\pm 0.13$ (absorber) and
$3.95^{+0.20}_{-0.22}$ (emitter). The absorber is blueshifted by $2340\pm 120$
km/s, while the emitter is redshifted by $2700^{+400}_{-300}$ km/s.

The strongest spectral feature of both the absorber and the emitter is the N
VII transition, where our signal-to-noise is highest, but other notable
transitions that are present include O VII, Ar XIII, S XIV, S XIII and C VI.
We note that while during the Quiescence without QPEs the absorption appears
to be stronger than the emission, the opposite is true for the Quiescence with
QPEs where the ionized emission dominates, particularly in the N VII
transition.

The best-fitting $0.3-2.0$ keV X-ray flux is $(6.7\pm 0.2)\times 10^{-13}$ erg
s-1 cm-2 for Quiescence without QPEs and $(3.55\pm 0.11)\times 10^{-13}$ erg
s-1 cm-2 for Quiescence with QPEs.

The relative similarity of the column density and the ionization parameter of
the absorber and the emitter motivates us to couple these components. We
couple both the column density and the ionization parameter $\log(\xi$/erg cm
s${}^{-1})$ and instead introduce a new variable parameter, $\Omega$, the
solid angle of the ionized emitter as seen from the ionizing source.
Physically, this combination would represent a 3D outflow launched from GSN
069 in a range of directions (but not necessarily covering $4\pi$ of the sky
of GSN 069). The outflow is seen directly along the line of sight to GSN 069
in absorption, as well as through re-emission from the outflow regions which
are out of our line of sight towards GSN 069. The remaining parameters of this
more constrained spectral model, the velocity width and outflow velocity, are
left decoupled.

We caution, however, that this is not a fully accurate ‘P-Cygni’ 3D model. In
our first-order model, the kinematics of the emitting gas are given
phenomenologically with the velocity width (derived from line widths) rather
than using the ratio of the ionized absorption and emission velocities based
on the geometric projection of the 3D outflow properties. More complex
spectral models such as wine (Luminari et al., 2018) or xrade (Matzeu et al.,
2022) would likely provide a more physical 3D kinematic description of the
outflow. The application of more advanced wind spectral models is beyond the
scope of this first discovery paper.

The results of this second spectral fit are shown in Table 3. The coupled
absorption-emission fit is slightly worse than the previous decoupled one (as
it has fewer free parameters), and the addition of the coupled emission
improves the absorption-only fit of the Quiescence without QPEs by
$\Delta$C-stat$\sim 17$, and of the Quiescence with QPEs by
$\Delta$C-stat$\sim 38$. Importantly, we find a solid angle $\Omega/4\pi$ of
$0.9\pm 0.3$ for Quiescence without QPEs and $1.1_{-0.3}^{+0.4}$ for
Quiescence with QPEs. In other words, with such a best-fitting solid angle,
the emitter is consistent with covering the whole $4\pi$ sky from the point of
view of GSN 069. We also note that the outflow velocity of the emitter in the
Quiescence without QPEs shifts to $2900_{-800}^{+900}$ km/s (which may explain
the observed difference in the fit quality) and is now consistent with the
redshift of the emitter during Quiescence with QPEs. This likely occurs due to
the limited signal-to-noise in the emission component. It is also possible
that the C-stat function has multiple local minima, one for a roughly
stationary emitter (which works better in the decoupled case), and one for a
significantly redshifted emitter, preferred in the coupled case where
$\log(\xi$/erg cm s${}^{-1})$ of the emitter is somewhat higher.

Table 3: Spectral fits of the ionized absorption and emission using the pion
photoionization model, while coupling the column density and ionization
parameter between the absorption and emission models.

State | Absorption component | Emission component
---|---|---
| $N_{\rm{H}}$ | $\log\xi$ | Velocity | Outflow | Solid | Velocity | Outflow | $\Delta$
|  |  | width | velocity | angle | width | velocity | C-stat
|  $10^{22}$ cm-2 | erg cm s-1 | km/s | km/s | $\Omega/4\pi$ | km/s | km/s |
Quiescent | $0.9\pm 0.2$ | $4.13_{-0.10}^{+0.09}$ | $600_{-200}^{+400}$ | $-2700^{+800}_{-300}$ | $0.9\pm 0.3$ | $2200_{-500}^{+600}$ | $2900_{-800}^{+900}$ | 16.99
without QPEs
Quiescent | $1.4_{-0.3}^{+0.4}$ | $4.51\pm 0.12$ | $470_{-70}^{+90}$ | $-2340\pm 120$ | $1.1_{-0.3}^{+0.4}$ | $1100\pm 400$ | $2800\pm 300$ | 38.17
with QPEs
QPE | $1.0_{-0.4}^{+0.8}$ | $4.6\pm 0.2$ | $400_{-200}^{+400}$ | $-1700_{-400}^{+300}$ | $0.06_{-0.06}^{+0.22}$ | 1100* | 2800* | 0.05

Note. — ∗Parameter value is fixed to the best-fitting value from the spectral
fit of Quiescence with QPEs.

As a further step, we consider that the outflow has non-Solar elemental
abundances. Recent work by Miller et al. (2023) on the TDE ASASSN-14li
indicated a very high nitrogen over-abundance (N$~{}>100$ over Solar ratios)
compared with other elements. This could also be the case in GSN 069. In fact,
the UV spectra of GSN 069 (from the Hubble Space Telescope) show over-
abundance of nitrogen (Sheng et al., 2021).

We free the N abundance in the pion model for both the ionized absorber and
the emitter, linking this parameter between the two components, and re-fit.
For Quiescence without QPEs, the best-fitting N abundance is $11_{-5}^{+9}$
for the decoupled fit and $11_{-5}^{+8}$ for the coupled fit. The introduction
of N abundance as a free parameter further improves the spectral fit by
$\Delta$C-stat$\sim 17$ for the decoupled fit and by $\Delta$C-stat$\sim 24$
for the coupled fit. For the Quiescence with QPEs, we obtain an N abundance of
$40_{-18}^{+43}$ for the decoupled spectral fit and an N abundance of
$50_{-20}^{+40}$ for the coupled fit. Freeing the N abundance improves the fit
by $\Delta$C-stat$\sim 40$ (for the decoupled fit) or by $\Delta$C-stat$\sim
32$ (for the coupled fit). Therefore, it appears that N is likely strongly
overabundant in comparison with other metals in GSN 069. As we have limited
data quality, we only perform this procedure for N, which shows the strongest
spectral feature (N VII transition). Caution is still required when
interpreting this result considering we have a limited number of plasma line
detections to make this measurement, but it is statistically significant and
in line with the UV spectroscopic results by Sheng et al. (2021).

As a final step, we perform a combined fit of both quiescence states to
determine the most likely N over-abundance value. We use the coupled
absorption-emission model and simultaneously fit the two RGS datasets while
keeping all of the physical parameters decoupled except the N abundance. This
results in a best-fitting N abundance of $24_{-10}^{+17}$. Fitting for the N
abundance slightly shifts the other best-fitting ionized absorber and emitter
parameters, but for nearly all parameters these shifts are within $1-2\sigma$
uncertainties of the original values.

####  3.2.2 QPE state

The QPE RGS spectrum has the highest count rate, but also the briefest total
exposure, and thus the lowest total count statistics. During the QPEs, GSN 069
is known to harden, a spectral shape which can be reproduced by the quiescent
state dbb component plus an extra soft blackbody with a temperature of about
100 eV. We therefore add this blackbody to the baseline continuum from the
Quiescence with QPEs, and fit for its temperature and normalization. To reduce
the fitting degeneracy, we fix the temperature of the dbb component to the
best-fitting value from the Quiescence with QPEs.

We then follow the same procedure as for the other two states. The results are
shown in Tables 2 and 3, and in Fig. 4. We find evidence for blueshifted
absorption even in this lower quality spectrum. Including the absorber
improves the fit by $\Delta$C-stat$\sim 20$, so it is detected with a
significance of about $3\sigma$. However, the detection likelihood is boosted
by the fact that the absorber properties during the QPE state are consistent
with those during Quiescence with QPEs. We do detect a potential shift in the
outflow velocity from $2340\pm 120$ km/s during that state compared with
$1700^{+300}_{-400}$ km/s during the QPE state. With the harder SED during the
QPE state, the N VII transition is no longer the strongest spectral feature.
Instead, we observe absorption from O VIII, and from the Fe transitions in the
Fe unresolved transition array (UTA).

Figure 4: Same as Fig. 3, but showing the QPE spectral state.

Surprisingly, we do not detect any ionized emission in the QPE state. The
addition of an emission pion component does not significantly improve the
spectral fit. We calculate the upper limit on the emitter column density or
its solid angle by assuming the same ionization parameter, velocity width and
outflow velocity as during the Quiescence with QPEs. We obtain a column
density of less than $0.11\times 10^{22}$ cm-2 and a solid angle $\Omega/4\pi$
of less than $0.28$.

We also tested for non-Solar N abundance during the QPE state, but due to the
lower data quality, we were not able to obtain any meaningful constraints
using this dataset. The best-fitting $0.3-2.0$ keV X-ray flux for this state
is $(1.13\pm 0.07)\times 10^{-12}$ erg s-1 cm-2.

###  3.3 Further data quality checks

For the RGS spectra of each of the 3 states, we also consider other
interpretations for the observed spectral features. First we consider that
some of these features could originate from absorption in the hot phase of the
Galactic interstellar medium (ISM). To test this possibility, we add an extra
hot absorption component in our baseline continuum (disk blackbody) fits. To
model hot ISM, we fix the temperature of this component (at rest with z=0) to
0.1 keV. Then the spectral fit is re-run, and we determine the fit improvement
$\Delta$C-stat as well as the best-fitting hot ISM column density. We found
that the addition of this component is not statistically significant in any of
the 3 state spectra, with fit improvements of at most $\Delta$C-stat$\sim 1$.
The best-fitting column density was less than $10^{20}$ cm-2 in all cases. Hot
ISM can therefore not explain the observed absorption features.

Additionally, as the GSN 069 X-ray flux is very low, the source spectrum is on
the same level or below the RGS background flux level for a significant
fraction of the wavelength range. This is especially important for the
spectrum of Quiescence with QPEs, which is background-dominated throughout all
of the wavelength range. In general, RGS background is relatively stable and
so the background subtraction should be accurate. Nevertheless, we perform an
additional check of our spectra with alternative background spectra. For this
check, instead of instrumental background accumulated during the actual
observations (from the edges of the RGS CCD chips), we use blank field RGS
backgrounds. In this case the background subtraction is significantly worse
than the instrumental background subtraction. Across the wavelength range, we
observe broad continuum residuals correlated with background flux, and the
agreement between RGS 1 and RGS 2 data is no longer within 10% as it is with
instrumental background. Nevertheless, the same spectral features are still
present in background-subtracted source spectra. We find that the addition of
an ionized absorber improves the Quiescent state without QPEs baseline (dbb)
continuum fit by $\Delta$C-stat$=30$, and the Quiescent state with QPEs
baseline fit by $\Delta$C-stat$=82.13$. As the source flux is significantly
higher during the QPE state, we did not perform this check for the QPE
spectrum.

Thirdly, we consider that we may not have matched the observed spectral
residuals with the correct elemental transitions. To verify our
identification, we perform a systematic, automated grid search of the RGS
spectra for plasma in absorption over a broad range of possible ionization
parameters, outflow velocities and velocity widths. This search is described
in further detail in Appendix B, and shows that we have indeed found the
global best fit for the ionized absorber physical properties in the GSN 069
RGS data.

Finally, we test alternative ionizing mechanisms for the observed features.
With the application of the pion model, we explicitly assumed that the plasma
is photoionized, which may not necessarily be the case. Instead, the plasma
may be collisionally ionized, for example by shocks, as was recently found for
one of the ionization zones of the outflow in the AGN NGC 4051 (Ogorzalek et
al., 2022). We test this scenario with collisional ionization spectral models.
We use the hot model to describe the absorption features and the cie model
(Kaastra et al., 1996) to describe the emission. We found that cie at Solar
abundances cannot reproduce the observed emission as the strongest observed
emission line is N VII. A high abundance of N compared with O (N/O$\sim
40-70$), and a high temperature ($\sim 0.3$ keV) is required to observe a
strong N VII line without observing a strong N VI line and not detecting
strong O VIII or O VII emission lines. However, even then the collisional
spectral models are not preferred over the photoionization models presented
above. The photoionization models are preferred in both quiescent state
spectral fits by at least $\Delta$C-stat$\sim 15$. Finally, we test an
alternative where the emission lines are produced by photoionization
(described with pion), but the absorption lines are from collisionally ionized
plasma. However, this solution is not statistically preferred in any of the
spectral fits (in any of the 3 GSN 069 states) over pure photoionization.

##  4 Residuals in XMM-Newton EPIC spectra

Miniutti et al. (2023b) previously showed that XMM-Newton EPIC spectra of GSN
069 in quiescence also contain a strong absorption residual, which can be
reproduced with ionized absorption. This EPIC residual is located at $0.6-0.8$
keV, where our RGS datasets have little signal during both quiescent states
(the spectra lose all source counts above $\sim 0.65$ keV, Fig. 3). Hence, the
strong lines that we observe in the RGS are different spectral features than
this $0.6-0.8$ keV residual seen in EPIC data. For comparison, the N VII lines
we resolve in the RGS data are located at $\sim 0.5$ keV, and most of the
remaining notable residuals are at even lower energies (Fig. 2). By applying
the xstar photoionization model, Miniutti et al. (2023b) were able to fit the
EPIC residuals with a warm absorber with an ionization parameter
$\log(\xi$/erg cm s${}^{-1})$ of about 0.5 and a column density of
$(5-7)\times 10^{21}$ cm-2. However, this interpretation is only tentative
given the limited spectral resolution of EPIC pn and MOS detectors of about
100 eV, resulting in a resolving power of $R<10$ in this energy range.

Now, the RGS data on GSN 069 can help identify the nature of these EPIC
residuals. Any ionized plasma, for example a warm absorber fitted to the EPIC
data, will also produce spectral features across the RGS energy band.
Conversely, the ionized emission and absorption models we fitted to the RGS
data will also produce spectral features across the EPIC energy band. Thus, by
combining these two datasets, we will obtain a better understanding of the
ionized plasma in the vicinity of GSN 069. We begin addressing this question
here, but stress that we perform only a preliminary analysis of the EPIC
dataset on GSN 069. A rigorous combined RGS-EPIC analysis is not
straightforward for very soft X-ray sources such as GSN 069 (as discussed in
Kosec et al., 2023) and is beyond the scope of this discovery paper.

###  4.1 Quiescent states with and without QPEs

As described in Section 2, alongside the state-resolved RGS data reduction, we
also perform EPIC (pn and MOS) data reduction, and hence obtain simultaneous
EPIC spectra. To begin describing these data, we first fit them with a base
continuum model. The spectra are analyzed in the energy range between 0.3 keV
and 4.0 keV (EPIC-pn) and 0.5 keV to 4.0 keV (EPIC-MOS), and are shown in the
top panels of Fig. 5 (Quiescence with and without QPEs) and Fig. 6 (QPE
state). Above $1.0-1.5$ keV, the source is comparable or weaker than the
background, but we do observe a hard tail inconsistent with a Wien tail of a
blackbody or a disk blackbody. The presence and the nature of this hard
component is speculative in GSN 069, but appears to be statistically
significant in these stacked data. We will not focus on the physical
interpretation of this new continuum component, but it must be included in our
fitting to correctly model the absorption residuals. Above 4 keV, we observe
no significant source signal, and so ignore all higher energy counts.

The continuum model is similar to the one we used for the RGS data, but with
an additional powerlaw component describing this hard tail. The powerlaw has a
typical slope in the range between 2.5 and 3.0 (depending on the exact
spectral fit and GSN 069 state), softer than a standard AGN corona emission.
To make this new continuum SED more physical, we add a lower exponential
cutoff to prevent the powerlaw luminosity from diverging at low energies (and
crashing the photoionization SED calculation), and set the cutoff parameter to
be equal to the disk blackbody temperature (assuming that the accretion disk
provides seed photons for this powerlaw emission). For this operation we use
the etau model in spex. Therefore, the baseline continuum model is hot
$\times$ reds $\times$ (dbb+pow $\times$ etau) for both quiescent states, and
hot $\times$ reds $\times$ (dbb+bb+pow $\times$ etau) for the QPE state.

The results of these continuum spectral fits are shown in the top two panels
of Fig. 5 (Quiescence with and without QPEs) and Fig 6 (QPE state). In both
quiescent states, we observe a highly significant absorption residual at
$0.6-0.8$ keV, in agreement with the results of Miniutti et al. (2023b). The
strength of this residual is clear from the high C-stat fit statistics of both
Quiescence without QPEs (C-stat=773 for 83 D.o.F.) and Quiescence with QPEs
(C-stat=604 for 105 D.o.F.) spectral fits. On the other hand, a dominant
$0.6-0.8$ keV residual is not present in the QPE state spectrum, and instead
we observe (a weaker) absorption residual at $0.9-1.0$ keV.

Figure 5: XMM-Newton EPIC spectrum of GSN 069 during Quiescence without QPEs
(left) and Quiescence with QPEs (right). Top panels: EPIC-pn data (MOS 1 and 2
not shown for clarity) fitted with a base continuum model (green) and with the
RGS outflow model (red). Background is shown in cyan. The broad UFO models
appear very similar to the RGS outflow models (red) in this log-log plot and
so are not shown for clarity. Lower three panels: residuals (pn in black, MOS
1 and 2 in blue) to the continuum, RGS outflow, and broad UFO model spectral
fits, respectively. Values of the C-stat fitting statistic are listed for each
fit on the bottom right. The number of degrees of freedom is given for the
continuum fit on the top right. The RGS outflow and Broad UFO models both have
4 less D.o.F. compared with the base continuum.  Figure 6: XMM-Newton EPIC
spectrum of GSN 069 in the QPE state. Top panel: EPIC-pn data (MOS 1 and 2 not
shown for clarity) fitted with a base continuum model (green) and with the RGS
outflow model (red). Background is shown in cyan. Lower two panels: residuals
(pn in black, MOS 1 and 2 in blue) to the continuum and RGS outflow model
spectral fits, respectively. Values of the C-stat fitting statistic are listed
for each fit on the bottom right. The number of degrees of freedom is given
for each fit on the top right.

We begin the photoionization analysis by reproducing the warm absorber
spectral fit from Miniutti et al. (2023b) for both quiescent states, using a
pion component at rest (no outflow velocity). The best-fitting column density
is around $3\times 10^{21}$ cm-2, comparable with their result, however we
obtain an ionization parameter $\log(\xi$/erg cm s${}^{-1})$ of about -0.75.
This discrepancy could be due to either differences between the pion and xstar
codes (Mehdipour et al., 2016), or due to a different SED adopted between our
work and Miniutti et al. (2023b). In any case, such a warm absorber describes
our EPIC residuals reasonably well, reducing the C-stat of the Quiescent state
without QPEs spectral fit to only 132 (for 81 D.o.F) and the C-stat of the
Quiescent state with QPEs fit to 222 (for 103 D.o.F.).

However, this ionized absorption model produces strong narrow lines throughout
the $0.3-1$ keV energy band, unresolved in EPIC data but resolved by the RGS.
These lines are not present in the RGS data from the same GSN 069 states, and
so warm absorption cannot be the explanation of the EPIC residuals. Using the
RGS datasets, we place an upper limit of just $3\times 10^{20}$ cm-2 for a
warm absorber at rest with $\log(\xi$/erg cm s${}^{-1})$ equal to the best-
fitting value from the EPIC analysis. This is a factor of 10 lower than what
is required by the EPIC data.

The first alternative explanation for these EPIC residuals is that they are
produced by the same ionized plasma which imprints the RGS spectral features.
To investigate this possibility, we used the same pion models applied to RGS
data to fit the EPIC spectra. This does not result in fit statistic
improvement under the assumption of Solar abundances. However, the RGS data
show intriguing evidence that the outflow abundances are non-Solar, with a
strong N over-abundance. As a second step, we apply pion models modified to
include the best-fitting N abundance of 24 (fixed) from the combined quiescent
state RGS analysis. Given the limited spectral resolution of EPIC, we simplify
the original pion photoionization models. We freeze all pion outflow
velocities and velocity widths to the best-fitting values from the RGS
analysis (coupled emission-absorption analysis with tied N abundance), and
only fit for pion column densities and ionization parameters, in addition to
the underlying continuum properties.

These models work much better with the EPIC data, and produce reasonable
spectral fits, shown in the third row panels in Fig. 5. The statistic improves
to C-stat=92 (79 D.o.F.) for Quiescence without QPEs, and to C-stat=152 (101
D.o.F.) for Quiescence with QPEs. Effectively, all of the systematic residuals
are removed from the EPIC spectra. However, we note a discrepancy between the
best-fitting outflow parameters from these fits and the RGS dataset analysis.
The best-fitting column density for the ionized absorber (in both GSN 069
states) is $(3-4)\times 10^{21}$ cm-2, and its ionization parameter
$\log(\xi$/erg cm s${}^{-1})$ is only $2.5-2.8$. This is much lower than found
in the RGS analysis (Table 2). The best-fitting parameters of the ionized
emitter roughly match those from the RGS analysis for the Quiescence with QPEs
with a column density of $2.1_{-0.6}^{+0.9}\times 10^{22}$ cm-2 and
$\log(\xi$/erg cm s${}^{-1})$ of $4.82_{-0.09}^{+0.07}$, but no emitter is
found in the EPIC spectrum of Quiescence without QPEs. Given the discrepancy
in the ionization parameter of the absorber, we did not attempt a coupled
analysis as with the RGS dataset.

This is a considerable discrepancy, but we note that some differences are
expected due to the mismatch between the spectral resolution of the two
instruments, due to the different energy bands adopted, as well as due to any
residual calibration differences. Additionally, the ionizing SEDs are not the
same in the RGS and EPIC analyses, especially in the harder band where we
included a hard tail for the EPIC continuum model. At this stage, it is not
clear if the observed difference can be reconciled only with the reasons
mentioned above. A possible alternative explanation is that the RGS outflow is
multi-phase, and the limited signal-to-noise RGS data reveal just one phase as
they are only sensitive below 0.65 keV, while another phase is more clearly
imprinted on the higher-energy EPIC data, which is more sensitive above 0.6
keV (thanks to the resolving power improving with increasing energy). A
detailed simultaneous RGS-EPIC analysis to investigate this hypothesis is
beyond the scope of this discovery paper and will be performed elsewhere.

A second possibility is that the outflow seen in the RGS data is not the
origin of the EPIC residuals, which are instead imprinted by a highly
blueshifted, high-velocity width ultra-fast outflow (UFO). Such a broad UFO
can produce a single dominant, highly broadened absorption feature and thus
reproduce the observed residual in both quiescence spectra. This
interpretation was proposed by Kara et al. (2018) and Pasham et al. (2024b) to
fit similar broad absorption residuals observed between 0.5 and 1 keV in two
TDEs. To test this hypothesis, we apply a UFO model to both quiescent state
EPIC spectra, again using an extra pion photoionization component. The
spectral fit quality is strongly improved for both states, down to C-stat=87
(79 D.o.F.) for Quiescence without QPEs and C-stat=229 (101 D.o.F.) for
Quiescence with QPEs. Therefore, the spectral fit quality is comparable
between the two interpretations for Quiescence without QPEs, while the first
interpretation (RGS outflow) is somewhat better than the UFO hypothesis for
Quiescence with QPEs. The best-fitting UFO properties are similar for both GSN
069 states. We obtain a column density in the range of $(4-10)\times 10^{21}$
cm-2, an ionization parameter $\log(\xi$/erg cm s${}^{-1})$ of $2.6-2.9$, a
velocity width of $(0.13-0.17)$c (full width half-maximum), and a blueshift of
$(0.23-0.30)$c. These parameters are comparable to the results of UFO modeling
in TDEs (Kara et al., 2018; Pasham et al., 2024b).

Importantly, these UFO absorbers produce very broad absorption features, and
thus imprint only weak features in the RGS spectra which have lower count
rates and statistics. To assess if the UFO models are allowed by the RGS
spectra, we added the best-fitting UFO absorbers to the previous continuum +
ionized outflow spectral fits (of the RGS data) for both quiescent states.
Doing this does not significantly modify these spectral fits apart from
needing continuum normalization adjustment. After re-fitting these
normalizations, the differences in fit quality are very small, in both cases
lower than $\Delta$C-stat$\sim 6$. Therefore, the RGS data do not disagree
with the UFO hypothesis.

###  4.2 QPE State

While we had difficulties reproducing the EPIC spectra of the quiescent states
with the RGS outflow models, this is not the case for the QPE state EPIC
spectrum. Instead of a strong $0.6-0.8$ keV residual, the QPE state spectrum
shows a weaker feature at $0.9-1.0$ keV. An ionized absorber model with
kinematics (velocity width and outflow velocity) fixed to those from the RGS
spectral analysis, and an N overabundance of $N=24$ is a good fit to the EPIC
data, improving the fit to C-stat=133 for 97 D.o.F. The fit improvement is
clearly seen in the residual plots comparing this fit with the baseline
continuum one (lower two panels in Fig. 6). The fit results in a best-fitting
column density of $1.6^{+0.4}_{-0.3}\times 10^{22}$ cm-2 and a $\log(\xi$/erg
cm s${}^{-1})$ of $5.03\pm 0.10$. Both of these values are comparable within
$2\sigma$ with the results for this component from the simultaneous RGS
analysis.

To see if a broad UFO could still be present in this spectrum, we added a pion
component with the best-fitting ‘broad UFO’ properties from Quiescence with
QPEs. This significantly worsens the fit by $\Delta$C-stat of about 100, and
introduces an emission spectral residual around $0.7-0.8$ keV. In principle,
the UFO could be over-ionized by the QPE flux and increase in $\log(\xi$/erg
cm s${}^{-1})$. To test this, we free the UFO component ionization in the
spectral fit. We are unable to constrain the component ionization parameter as
its value hits the upper bound of the pion model, but we obtain a lower limit
of $\log(\xi$/erg cm s${}^{-1})$ $=6.2$ for the UFO component ionization.
Hence, the ionization would have to increase by a factor of more than 1000 to
agree with the EPIC QPE dataset, assuming its column density and kinematics do
not vary over the course of individual QPEs. At such high ionization,
practically all of the absorption signatures of this component are gone. We
thus conclude that the EPIC QPE spectrum of GSN 069 can be entirely explained
by the outflow detected in the RGS dataset and no UFO component is required in
this state.

##  5 Discussion

We perform the first high-spectral resolution X-ray study of a quasi-
periodically erupting source by leveraging the extensive archive of XMM-Newton
observations on GSN 069. In the stacked RGS spectrum (totalling almost 2 Ms of
raw exposure time), we resolve an array of emission and absorption lines. The
statistical detection significance of the strongest individual line,
identified as N VII, by far exceeds $4\sigma$. Next we perform a dataset split
based on the GSN 069 flux state and apply photoionization spectral models. We
confirm that an outflow is significantly detected both in absorption and
emission in Quiescence without QPEs (when no QPE activity is observed) and
Quiescence with QPEs (in-between individual QPEs), and detected only in
absorption at around $3\sigma$ significance in the QPE state (during the
QPEs). After establishing that the observed spectral residuals cannot be due
to Poisson noise, we performed a number of checks to make sure we interpret
their nature correctly. These features cannot be consistently explained by an
ionized absorber with a different ionization state, outflow velocity, or
velocity width (Appendix B). The features are observed even if we use blank
field backgrounds instead of observational background files. Finally, they
cannot originate from hot ISM in our Galaxy.

To sum up, we detect an ionized outflow in GSN 069, seen both in absorption
and emission. The column density of the outflow is about $10^{22}$ cm-2, with
an ionization parameter $\log(\xi$/erg cm s${}^{-1})$ of $3.9-4.6$ and a
projected velocity of $1700-2900$ km/s. The observed absorption and emission
components can be linked together, and interpreted as a single outflow moving
away from GSN 069 with a velocity of about 2500 km/s, consistent with covering
the full $4\pi$ sky from the point of view of the ionizing source.

This is the first confirmed detection and detailed characterization of an
ionized outflow in a QPE system. Such phenomena may be present in other
sources of this class, but it is very challenging to detect them. By
exploiting nearly 2 Ms of XMM-Newton observations, we pushed the RGS
instrument to the limit and detected an ionized outflow in this relatively
faint X-ray source. Megasecond-duration observational campaigns (with high-
resolution X-ray instruments), or next-generation X-ray instruments will be
necessary to detect outflow signatures in the fainter QPE sources (such as RX
J1301.9+2747, Giustini et al., 2020) at a similar level as we did here in GSN
069.

Future instruments offering high-spectral resolution in the soft X-rays as
well as improved effective area, such as NewAthena (Nandra et al., 2013),
Light Element Mapper (Kraft et al., 2022) or Arcus (Smith, 2020), are going to
be crucial in revealing further properties of ionized outflows in GSN 069 and
other QPE systems. To judge the performance of one of these instruments for
the case of GSN 069, we performed a 60 ks NewAthena observation simulation of
the Quiescent state with QPEs (the faintest state of GSN 069, for a
conservative simulation). We simulated the best-fitting decoupled absorption-
emission outflow model and used the newest NewAthena responses (from March
2024), assuming the goal 3 eV spectral resolution of the XIFU instrument. The
result is shown in Fig. 7. Even the brief 60 ks observation is sufficient to
detect the outflow at a very high significance, with a fit improvement of
$\Delta$C-stat$~{}>1500$ over the baseline continuum. Thus, with NewAthena it
will be possible to detect the outflow and characterize it in a single
pointing, and track its evolution with time.

Figure 7: Simulation of a 60 ks NewAthena observation of GSN 069 in Quiescence
without QPEs. We used the decoupled absorption-emission spectral model, the
same as shown in Fig. 3 (bottom panel).

In the last part of this analysis, we explored the spectral residuals in the
simultaneous EPIC datasets of GSN 069, previously found in the $0.6-0.8$ keV
energy range by Miniutti et al. (2023b). We confirm these residuals are
present during both quiescent states, and find that they can be reproduced by
an outflow of the same kinematic properties as the one detected in the RGS
data, but likely with a much lower ionization parameter. This would indicate a
multi-phase nature of the outflow, one phase producing spectral features more
strongly in the RGS data, while the other dominating in the EPIC band.
Alternatively, the residuals could be due to a highly broadened UFO with a
projected velocity of about 0.2-0.3c, kinematically unrelated to the outflow
seen in the RGS. On the other hand, curiously, the QPE state EPIC spectra do
not need any extra ionized absorption to reproduce the observed residuals. The
outflow seen in RGS completely reproduces these features.

At this stage, both solutions for the EPIC residuals are plausible and further
analysis of the combined RGS and EPIC dataset is needed. In this initial
analysis, we ignored any long-term variability of GSN 069 since 2010 by
stacking the data simply by spectral state. However, any variability in the
Wien tail of the blackbody, or variability in the ionization and column
density of the ionized outflow could bias the interpretation of the EPIC
residual, which is very broad but located where EPIC has very limited spectral
resolving power. In any case, both hypotheses indicate a likely complex
ionization, and possibly also kinematic structure of outflowing plasma in the
vicinity of GSN 069.

###  5.1 Comparison between the states of GSN 069 and with TDE ionized
outflows

By splitting the RGS dataset, we are able to track the evolution of the plasma
properties during the different spectral states of GSN 069. The plasma column
density appears to be consistently around $1\times 10^{22}$ cm-2 in both
quiescent states, comparable with the outflow detected in the TDE ASASSN-14li
(Miller et al., 2015). The column density of the absorber during the QPE state
is fully consistent with that during the Quiescence with QPEs. However, no
emission component is detected in the QPE state, with an upper limit many
times below the best-fitting column density or solid angle from the analysis
of Quiescence with QPEs.

The ionization parameter of the outflow is quite high at around $\log(\xi$/erg
cm s${}^{-1})$$\sim 4$, again very similar to the outflow detected in
ASASSN-14li. However, the outflow of GSN 069 is much faster, as the observed
velocity of the blueshifted absorber in ASASSN-14li was only about 300 km/s
(Miller et al., 2015). ASASSN-20qc, another TDE with an X-ray detected outflow
(Kosec et al., 2023), shows an outflow with a lower ionization of
$\log(\xi$/erg cm s${}^{-1})$$\sim 3$ (plus a less ionized second component).
The velocity of the outflow in ASASSN-20qc is higher than in ASASSN-14li at
900 km/s, but even this is still much slower than what we observe in GSN 069.

Importantly, neither of these TDE outflows show as strong line emission
components as GSN 069. Miller et al. (2015) noted potential evidence for a
weaker ionized emission component in ASASSN-14li, while no such emission was
detected in ASASSN-20qc.

Intriguingly, the ionization parameter $\log(\xi$/erg cm s${}^{-1})$ of the
outflow is higher in the Quiescence with QPEs and in QPE state than during
Quiescence without QPEs. Using the coupled spectral analysis results, we
observe an increase in ionization parameter of $\Delta$$\log(\xi$/erg cm
s${}^{-1})$$\sim 0.4$. Assuming this increase is purely due to a change in
ionizing luminosity, this would correspond to an increase in luminosity by a
factor of 2.5. Miniutti et al. (2023b) showed that the power emitted in the
QPE is only a very small fraction (up to 15%) of the total bolometric
luminosity of GSN 069 (most of the power emitted by the disk blackbody
component is in the extreme UV), making it unlikely to cause this
$\log(\xi$/erg cm s${}^{-1})$ increase alone. However, we also note that
during the QPEs, the SED of GSN 069 significantly hardens compared with both
quiescent states. The QPE variability amplitude is much higher around 1 keV
compared with the amplitude around 0.3 keV. These SED shape variations are
likely the main contributing factor to the higher ionization state of the
outflowing plasma.

Curiously, we do not detect any ionized line emission during the QPE state,
and place deep upper limits on its presence. The redshifted ionized emitter as
seen during the Quiescence with QPEs is rejected by the QPE state data,
assuming that it sees the same SED as we observe during the QPEs. This non-
detection may have a number of explanations. The ionized emission could weaken
or disappear if the emitting plasma is over-ionized. However, it is not clear
why only the emitting plasma would over-ionize without the same happening to
the absorbing plasma (which has a reasonably well constrained ionization
parameter, Tables 2 and 3).

Instead it is possible that the outflow is located so far away from GSN 069,
that the light travel time from the black hole to the outflow is much longer
than the time delay between consecutive QPEs. In this case, any variability in
the illumination of the emission component (by the QPEs) would be washed out
due to the time travel delays, and the SED that this emitter observes would be
the weighted time average of the QPE and Quiescence with QPEs SEDs. This is
not the case for the ionized absorption, which sees the immediate increase in
the illuminating X-ray flux during the QPE as the absorber is located directly
along our line of sight towards the ionizing source. In such a case, the
contrast of the emission lines against the source continuum would be much
lower than during the Quiescence with QPEs because the QPE continuum is much
stronger than the weighted average of the QPE and Quiescence with QPEs
continua. At the same time, this would likely weaken the upper limit we
obtained on the presence of ionized emission (where we assumed that the
emitter observes the QPE SED).

An alternative explanation is that the ionized emission is located relatively
close to the black hole, but responds with a delay due to light travel time of
more than $1-2$ ks (the duration of the QPE). In that case, the response of
the emitter to the QPE would be extracted in the spectrum of Quiescence with
QPEs, rather than directly in the QPE spectrum (which only contains the QPE
itself). This hypothesis could be tested by splitting the Quiescence with QPEs
spectrum into two halves by time elapsed since the previous QPE.
Unfortunately, we do not have the data quality to achieve this with the
current XMM-Newton dataset. Further observations, specifically of the QPE
active state, are required.

We do not make any conclusions on the measurement of plasma velocity widths.
Since our spectra are composed from large stacks of many individual
observations, any evolution in the outflow velocity (over the timescale of
several years) would imprint on these stacks by broadening the spectral lines.
For the same reason, it is difficult to draw strong conclusions about the
best-fitting outflow velocity and its evolution with GSN 069 state. We
consider the outflow velocity generally consistent across the different
states.

Finally, we also tested for non-Solar abundances in the outflow by fitting for
the abundance of N, which in our dataset has the highest signal-to-noise
elemental line (N VII). N appears strongly over-abundant with an abundance
(with respect to other metals) of $10-50$, in line with the UV spectroscopy of
GSN 069 (Sheng et al., 2021). N overabundance may indicate CNO processing of
the outflowing material, which could originate from an evolved star. Similar
conclusions were recently reached for the outflow in the TDE ASASSN-14li based
on high-resolution X-ray spectra (Miller et al., 2023), as well as UV spectra
(Cenko et al., 2016; Kochanek, 2016). Alternatively, the N over-abundance
could originate from a stripped star (Mockler et al., 2024). Based on the
long-term evolution of GSN 069, it is thought that a partial or a total tidal
disruption of a star, which occurred around 2010 (Miniutti et al., 2023b)
began the transient activity in this enigmatic source. It is thus plausible
that it was a disruption of an evolved or a stripped star that gave rise to
the recent activity seen in GSN 069.

###  5.2 Outflow location and energetics

As this is the first detection of an outflow in a QPE source, we establish
constraints on its location and energetics. We note that below we only
calculate these quantities for the outflow confirmed via the RGS spectra, not
the potential UFO seen in the EPIC data. We assume that the mass of the black
hole in GSN 069 is $10^{6}$ M⊙ (Miniutti et al., 2023b).

First, we put an upper limit on the distance of the outflow from the ionizing
source. This is given by the ionizing balance of plasma, from the definition
of the ionization parameter $\xi=L_{\rm{ion}}/(nR^{2})$ (where $L_{\rm{ion}}$
is the 13.6 eV–13.6 keV ionizing luminosity, $n$ the outflow number density,
and $R$ is the distance from the ionizing source) and the definition of the
column density $N_{\rm{H}}=n\Delta R$ (where $\Delta R$ is the thickness of
the outflow layer):

$R=\frac{L_{\rm{ion}}}{N_{\rm{H}}\xi}\frac{\Delta R}{R}$ (1)

By assuming the maximum thickness of the absorbing layer ($\Delta R/R=1$), we
obtain the maximum distance of the outflow from the ionizing source. We take
the best-fitting values from the coupled absorption-emission spectral
analysis. The maximum distance derived from Quiescence without QPEs is
$9\times 10^{16}$ cm ($6\times 10^{5}$ $R_{\rm{G}}$ for a $10^{6}$ M⊙ black
hole, 0.03 pc), while the Quiescence with QPEs provides a tighter upper limit
of $2\times 10^{16}$ cm ($1\times 10^{5}$ $R_{\rm{G}}$, 0.006 pc). Clearly,
even the tighter of these two limits is not very constraining (for
illustration, the inferred blackbody emitting radius of the QPEs themselves is
about $10^{5}$ times smaller, Miniutti et al., 2023b), but the result shows
that we cannot be observing a galaxy-scale outflow.

By taking the projected absorber outflow velocity, $\sim$2600 km/s, and
assuming that it is comparable to the escape velocity at these radii, we can
obtain a very rough estimate for the outflow location. This value can be
derived as follows:

$R=\frac{2GM}{v^{2}}=2\frac{c^{2}}{v^{2}}R_{\rm G}$ (2)

which is about $3\times 10^{4}$ $R_{\rm{G}}$, several times lower than its
maximum distance from the ionizing source from the ionizing balance. However,
we note that due to the projection of the outflow velocity into our line of
sight, the true distance of the outflow from the black hole may be lower than
this value. At the same time, its distance could also be higher if the outflow
velocity is hyperbolic.

For the ionized emission to respond to QPEs (without washing out the QPE
signal), the light travel time from GSN 069 to the ionized outflow must be
shorter than the typical recurrence time between the QPEs. The time between
consecutive QPEs (when in the QPE active state) is about 30 ks (Miniutti et
al., 2023b), corresponding to a distance of about $6\times 10^{3}$
$R_{\rm{G}}$. From the observed outflow velocity alone, it seems unlikely that
the outflow (in emission) could respond to the QPEs coherently.

Additionally, further constraints on the plasma location can be placed by
considering the response of the outflow in absorption to the QPEs. The
absorbing plasma sees the same SED that we observe, with no time delays as is
the case for the emitting plasma. If it has sufficient number density, it
should react to the increase in the ionizing flux during the QPE and adjust
its ionization parameter (Krolik & Kriss, 1995). This is not observed in our
study, as the ionization parameter does not appear to vary between the QPE and
the Quiescence with QPEs. We stress that given the current data quality of the
QPE state spectrum, this is not a strong constraint, but it will become a
crucial probe of the outflow properties and location with higher quality X-ray
observations, especially those with future X-ray observatories such as
NewAthena (Nandra et al., 2013), Light Element Mapper (Kraft et al., 2022) or
Arcus (Smith, 2020). With higher-quality data, these sources will be perfect
for the application of time-dependent photoionization models such as tpho
(Rogantini et al., 2022) considering the large and fast variation of X-ray
flux during the QPEs, and its effect on ionized plasma.

If the absorber does not respond during the QPE, its density must be so low
that the ionization and recombination time of observed spectral line
transitions is longer than the QPE itself. Taking the strongest observed N VII
transition, we used the ascdump feature of the pion model to determine the
recombination time of N VII as a function of number density. For simplicity,
taking the recombination time to be at least 2000 s (roughly the duration of a
QPE), we obtain an upper limit on the outflow density of $10^{7}$ cm-3.
Applying this limit to the ionizing balance equation, we obtain a lower limit
for the distance of the outflow from the black hole of $5\times 10^{15}$ cm
(0.002 pc, $3\times 10^{4}$ $R_{\rm{G}}$), fully consistent with the estimate
we made using the outflow velocity argument, and with the upper limit from
ionization balance.

Another relevant consideration is the flight time of the ionized outflow, and
how it could relate to GSN 069 and its recent transient history. Assuming the
outflow originates very close to the black hole, at the average projected
velocity of 2600 km/s, it will reach the distance of $6\times 10^{3}$
$R_{\rm{G}}$ in about $3\times 10^{6}$ s (40 days), the distance of $3\times
10^{4}$ $R_{\rm{G}}$ in 200 days and the distance of $1\times 10^{5}$
$R_{\rm{G}}$ in 700 days. Even if the outflow does not decelerate over time
(which is likely), its flight time to the current location is shorter than the
time elapsed since the likely TDE event occurred in this source back in 2010.
Hence it is unlikely that the outflow could originate from previous possible
AGN activity of GSN 069 (before 2010) and be a remnant of that activity. The
outflow is thus solidly associated with the recent nuclear transient behavior
of GSN 069.

Finally, we calculate the mass outflow rate and the kinetic power of the
outflow, assuming that it is continuously being launched by GSN 069. In these
calculations, we follow the steps of Kosec et al. (2020a) in their Section
5.3. The mass outflow rate can be estimated via two approaches. The first one
uses the ionizing balance of the outflow, and $M_{\rm{out}}$ can be obtained
as follows:

$\dot{M}_{\rm{out}}=4\pi\mu
m_{\rm{p}}v\frac{L_{\rm{ion}}}{\xi}C_{\rm{V}}\frac{\Omega}{4\pi}$ (3)

where $\mu$ is the mean atomic mass (assumed 1.2 for Solar abundances),
$m_{\rm{p}}$ is the proton mass and $C_{\rm{V}}$ is the volume filling factor
(unknown). This results in a mass outflow rate of $0.03-0.08$
$M_{\odot}~{}$/year (for Quiescence with and without QPEs, respectively). We
note that there are two caveats to this calculation. First, we did not factor
in the (unknown) value of $C_{\rm{V}}$, which will decrease the estimate.
Secondly, the true value of the outflow velocity is higher than its line-of-
sight projection (which we used here), which will increase the estimate. These
caveats apply to the following calculations as well. The second approach makes
the assumption that the observed projected outflow velocity is equal to the
escape velocity.

$\dot{M}_{\rm{out}}=8\pi\mu
m_{\rm{p}}GM\frac{N_{\textrm{H}}}{v}\frac{1}{\delta
R}C_{\rm{V}}\frac{\Omega}{4\pi}$ (4)

where $G$ is the gravitational constant, $M$ is the mass of the black hole and
$\delta R=\Delta R/R$ is the relative thickness of the outflow layer. Taking
the most extreme case of $\Delta R/R=1$ again, we find a lower limit on the
mass outflow rate (neglecting the $C_{\rm{V}}$ factor again) of $(3-7)\times
10^{-3}$ $M_{\odot}~{}$/year. If the outflow persisted continuously until 2023
since the transient in GSN 069 began in July of 2010 (for 13 years) and its
volume filling factor is high, the total ejected mass should be at least 0.04
$M_{\odot}$, but more realistically around $0.3-1.0$ $M_{\odot}$.

Therefore, if the transient in GSN 069 began by a tidal disruption of a $\sim
M_{\odot}$ star, a significant fraction of its mass could have been ejected
via this wind over the past 13 years. However, we stress we did not account
for the volume filling factor of the plasma, which is unknown and could be
much lower than 1, thus reducing the total mass in the outflow.

Finally, the kinetic power of the outflow is simply:

$\dot{E}_{\rm{kin}}=\frac{1}{2}\dot{M}_{\rm{out}}v^{2}$ (5)

We then obtain $\dot{E}_{\rm{kin}}\sim 7\times 10^{39}-2\times 10^{41}$ erg/s,
about $6\times 10^{-5}-1\times 10^{-3}$ of the Eddington luminosity for a
$10^{6}$ $M_{\odot}$ black hole. Therefore, even if this outflow persisted for
a long amount of time, it is unlikely that it could significantly influence
the host galaxy of GSN 069 (Di Matteo et al., 2005).

##  6 Conclusions

We performed the first in-depth analysis of high-resolution X-ray spectra of a
quasiperiodically erupting source, leveraging the nearly 2 Ms archive of XMM-
Newton observations on GSN 069. We analyze the RGS grating spectra, first by
stacking all the individual observations in a single dataset, and secondly in
3 dataset stacks based on the current states of GSN 069: Quiescence without
QPEs, Quiescence with QPEs or QPE state. Our findings can be summarized as
follows:

  * •

The stacked RGS spectrum reveals an array of absorption and emission lines.
The strongest feature, with a statistical significance far exceeding
$4\sigma$, is located near the rest-frame transition of N VII. If associated
with N VII, we observe a blueshifted absorption component at a velocity of
$3500_{-600}^{+400}$ km/s, and a redshifted emission component with a velocity
of $2800_{-1000}^{+500}$ km/s, very reminiscent of the P-Cygni line shape.

  * •

Ionized absorption is present in all states of GSN 069, with a projected
outflow velocity of $1700-2900$ km/s. The best-fitting column density is
$(0.9-1.7)\times 10^{22}$ cm-2, consistent with being stable across all 3
states. The outflow is highly ionized, with an ionization parameter
$\log(\xi$/erg cm s${}^{-1})$ of $3.9-4.1$ during Quiescence without QPEs, and
$\log(\xi$/erg cm s${}^{-1})$ of $4.5-4.6$ during Quiescence with QPEs and QPE
states.

  * •

Ionized emission has a redshift of up to 2900 km/s, depending on the GSN 069
state. It is strongly detected in both quiescent states, with a column density
and ionization parameter similar to the best-fitting values of the ionized
absorption. This emission component can be interpreted as the same plasma seen
in absorption, only located out of our line of sight. In that case, the
outflow is consistent with covering the full $4\pi$ sky from the point of view
of GSN 069.

  * •

No ionized line emission is observed during the QPEs, and we place deep upper
limits on its presence, several $\sigma$ below the best-fitting values during
the Quiescence with QPEs. This non-detection may be explained if the outflow
is located sufficiently far from the ionizing source that the light-travel
time significantly delays, or washes out any ionization response to the QPEs
in the ionized emission.

  * •

We find strong evidence that nitrogen is highly over-abundant in the outflow
compared with other metals. The best-fitting N abundance is $24^{+17}_{-10}$,
consistent with a previous abundance study of GSN 069 using UV spectra (Sheng
et al., 2021).

  * •

We place limits on the outflow location and energetics. It must be located at
most 0.03 pc from the black hole ($10^{5}$ $R_{\rm{G}}$ assuming a $10^{6}$ M⊙
black hole), with a travel time from the ionizing source of $\leq 2$ years,
and so cannot be a remnant outflow launched by previous black hole activity.
It is hence directly related to the recent transient phenomena occurring in
GSN 069 since 2010.

  * •

Assuming the outflow is continuously launched, its mass outflow rate is
$3\times 10^{-3}-8\times 10^{-2}$ $M_{\odot}~{}$/year, with a total ejected
mass of up to 1 $M_{\odot}$ since 2010 (when the GSN 069 transient activity
apparently began). Its kinetic power is $7\times 10^{39}-2\times 10^{41}$
erg/s, and so the outflow does not have enough power to provide sufficient
feedback to affect the evolution of the host galaxy of GSN 069.

Support for this work was provided by the National Aeronautics and Space
Administration through the Smithsonian Astrophysical Observatory (SAO)
contract SV3-73016 to MIT for Support of the Chandra X-Ray Center and Science
Instruments. Support for this work was provided by NASA through the NASA
Hubble Fellowship grant HST-HF2-51534.001-A awarded by the Space Telescope
Science Institute, which is operated by the Association of Universities for
Research in Astronomy, Incorporated, under NASA contract NAS5-26555. CP
acknowledges support by INAF Large Grant BLOSSOM and PRIN MUR 2022 SEAWIND
(funded by NextGenerationEU). GM thanks grant n. PID2020-115325GB-C31 funded
by MCIN/AEI/10.13039/50110001103 for support. MG is supported by the “Programa
de Atracción de Talento” of the Comunidad de Madrid, grant numbers
2018-T1/TIC-11733 and 2022-5A/TIC-24235.

##  Appendix A Detailed information about XMM-Newton observations

In Table 4 we list the details of XMM-Newton observations used in this work.
All of these observations were combined to create the full RGS stack, as well
as the state-resolved stacked spectra.

Table 4: Details of the individual XMM-Newton observations. We note that the
duration is given before any flare filtering.

Observation ID | Start Date | Duration | QPE detection
---|---|---|---
|  | ks |
0657820101 | 2010-12-02 | 14913 | no
0740960101 | 2014-12-05 | 95100 | no
0823680101 | 2018-12-24 | 63300 | yes
0831790701 | 2019-01-16 | 141400 | yes
0851180401 | 2019-05-31 | 135400 | yes
0864330101 | 2020-01-10 | 141000 | yes
0864330201 | 2020-05-28 | 133100 | no
0864330301 | 2020-06-03 | 133200 | yes
0864330401 | 2020-06-13 | 136100 | no
0884970101 | 2021-06-30 | 53000 | no
0884970201 | 2021-12-03 | 55300 | no
0913990201 | 2022-07-07 | 59180 | yes
0914790101 | 2022-11-30 | 19800 | no*
0914790401 | 2022-12-02 | 15000 | yes
0914790201 | 2022-12-04 | 21900 | yes
0914790301 | 2022-12-08 | 17990 | yes
0914790501 | 2022-12-11 | 15000 | no*
0914790601 | 2022-12-13 | 15000 | no*
0914791101 | 2022-12-14 | 18000 | yes
0914790701 | 2022-12-16 | 14800 | yes
0914790801 | 2022-12-18 | 13000 | no*
0914790901 | 2022-12-20 | 16460 | yes
0914791001 | 2022-12-22 | 20900 | yes
0914791201 | 2022-12-26 | 15000 | yes
0914791301 | 2022-12-30 | 18000 | no*
0914791401 | 2023-01-05 | 16000 | no*
0914791501 | 2023-01-08 | 13900 | yes
0914791601 | 2023-01-10 | 13500 | no*
0914791701 | 2023-01-12 | 29700 | yes
0914791801 | 2023-01-14 | 13900 | no*
0914791901 | 2023-01-15 | 13000 | yes
0914792701 | 2023-05-29 | 69400 | yes
0914792901 | 2023-06-09 | 119700 | yes
0914793101 | 2023-07-09 | 108200 | yes

Note. — ∗No QPEs were detected in these short exposure observations (briefer
than the typical time interval between two QPEs), but we assumed that GSN 069
was constantly in the QPE active state between Nov 2022 and Jan 2023.

##  Appendix B Systematic search for ionized absorption in GSN 069

To verify that we identified the observed spectral residuals with correct
elemental transitions, and accurately measured the plasma physical properties,
we perform a systematic automated search for ionized absorbers in the 3 state-
resolved RGS spectra. In this search we test that there are no ionized
absorber solutions which work with the RGS data better than our
interpretation, i.e. we establish whether our solutions are indeed the global
best fits for these spectra using the pion photoionization model. To test this
hypothesis, we fit (in an automated fashion) the different GSN 069 state RGS
spectra with ionized absorbers of various physical properties, spanning a
broad range of outflow velocities, ionization parameters and velocity widths.
We note that we only search for ionized plasma in absorption, as performing
such a search for plasma in emission is prohibitively computationally
expensive using the pion model in spex.

We closely follow the systematic spectral search method adopted in Section 3.2
of Kosec et al. (2020b), except here we apply the pion ionized absorption
model instead of xabs applied in that work. We search all 3 GSN 069 state
spectra: Quiescence without QPEs, Quiescence with QPEs and QPE state, and test
ionized absorber properties as follows. Outflow velocities from +15000 km/s
(infalling) to -100000 km/s (ultra-fast outflow), ionization parameters
$\log(\xi$/erg cm s${}^{-1})$ from 2.0 to 6.0 (mildly ionized to very highly
ionized) as well as 3 different velocity widths: 250 km/s, 1000 km/s, 2500
km/s. Column density is a fitted parameter at each step of this grid and so it
is not a grid parameter.

For each grid step, we fit the model containing the baseline continuum (dbb
for Quiescence with or without QPEs and dbb+bb for the QPE state) plus the
ionized absorber of the current grid step parameters and recover the
$\Delta$C-stat fit improvement in comparison with the baseline continuum fit.
Performing the search over the full grid, we should obtain a $\Delta$C-stat
parameter space which shows a global maximum for certain ionized absorber
parameters, which are the most preferred solution for this dataset. The
results of this search are shown for Quiescence without QPEs in Fig. 8, for
Quiescence with QPEs in Fig. 9 and for the QPE state in Fig. 10.

Figure 8: Systematic search for ionized plasma in absorption of the Quiescent
state without QPEs RGS spectrum. The top panel shows searches with a velocity
width of 250 km/s, middle panel with a velocity width of 1000 km/s and the
bottom panel with a velocity width of 2500 km/s. The X-axis of all panels is
the outflow velocity, ranging from +15000 km/s (redshifted inflow) to -100000
km/s (high-velocity blueshifted outflow). The Y-axis is the ionization
parameter of the pion component. The colour shows the fit improvement of
adding an absorber of certain parameters to the baseline continuum, according
to the colour scale on the right.  Figure 9: Same as Fig. 8, but showing a
systematic search of the Quiescent state with QPEs RGS spectrum.  Figure 10:
Same as Fig. 8, but showing a systematic search of the QPE state RGS spectrum.

We find that a highly ionized absorber, with $\log(\xi$/erg cm s${}^{-1})$ of
$4-5$, an outflow velocity of about 2500 km/s, and a velocity width of
$250-1000$ km/s is the most preferred solution in all 3 states of GSN 069,
resulting in the highest values of $\Delta$C-stat. We also see secondary peaks
in these systematic searches, indicating possible alternative solutions to the
primary interpretation of the ionized absorber. For Quiescence without QPEs,
this is at an outflow velocity of about 95000 km/s, with $\log(\xi$/erg cm
s${}^{-1})$ of 5 and a velocity width of 1000 km/s. For the Quiescence with
QPEs, this is at an outflow velocity of 20000 km/s, with a $\log(\xi$/erg cm
s${}^{-1})$ of 5 and a velocity width of $1000-2500$ km/s. Finally, for the
QPE state, there is a secondary solution with an inflow velocity of 13000
km/s, a $\log(\xi$/erg cm s${}^{-1})$ of 5.5 and a velocity width of 250 km/s.
However, we stress that all these secondary solutions are weaker (with lower
$\Delta$C-stat) in all 3 GSN 069 states than the preferred primary 2500 km/s
solution. Importantly, none of the secondary solutions repeat among the
different spectral states, while the primary solution remains consistently
similar (and preferred) across all of the GSN 069 states. Therefore, we
conclude that the best solution to the RGS dataset is a highly ionized outflow
in absorption with a velocity of about 2500 km/s.

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