# MAXI and NuSTAR observations of the faint X-ray transient MAXI J1848–015 in
the GLIMPSE-C01 Cluster

Sean N. Pike Cahill Center for Astronomy and Astrophysics, California
Institute of Technology, Pasadena, CA 91125, USA  Hitoshi Negoro Department of
Physics, Nihon University, 1-8 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8308,
Japan  John A. Tomsick Space Sciences Laboratory, 7 Gauss Way, University of
California, Berkeley, CA 94720-7450, USA  Matteo Bachetti INAF–Osservatorio
Astronomico di Cagliari, via della Scienza 5, I-09047 Selargius (CA), Italy
McKinley Brumback Cahill Center for Astronomy and Astrophysics, California
Institute of Technology, Pasadena, CA 91125, USA  Riley M. T. Connors Cahill
Center for Astronomy and Astrophysics, California Institute of Technology,
Pasadena, CA 91125, USA  Javier A. García Cahill Center for Astronomy and
Astrophysics, California Institute of Technology, Pasadena, CA 91125, USA
Brian Grefenstette Cahill Center for Astronomy and Astrophysics, California
Institute of Technology, Pasadena, CA 91125, USA  Jeremy Hare NASA Goddard
Space Flight Center, Greenbelt, MD 20771, USA  Fiona A. Harrison  Cahill
Center for Astronomy and Astrophysics, California Institute of Technology,
Pasadena, CA 91125, USA  Amruta Jaodand Cahill Center for Astronomy and
Astrophysics, California Institute of Technology, Pasadena, CA 91125, USA  R.
M. Ludlam Cahill Center for Astronomy and Astrophysics, California Institute
of Technology, Pasadena, CA 91125, USA  Guglielmo Mastroserio Cahill Center
for Astronomy and Astrophysics, California Institute of Technology, Pasadena,
CA 91125, USA  Tatehiro Mihara RIKEN, Hirosawa, Wako, Saitama, 351-0198, Japan
Megumi Shidatsu Department of Physics, Ehime University, 2-5, Bunkyocho,
Matsuyama, Ehime 790-8577, Japan  Mutsumi Sugizaki National Astronomical
Observatories, Chinese Academy of Sciences, 20A Datun Road, Beijing 100012,
People’s Republic of China  Ryohei Takagi  Department of Physics, Nihon
University, 1-8 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8308, Japan

###### Abstract

We present the results of MAXI monitoring and two NuSTAR observations of the
recently discovered faint X-ray transient MAXI J1848–015. Analysis of the MAXI
light-curve shows that the source underwent a rapid flux increase beginning on
2020 December 20, followed by a rapid decrease in flux after only $\sim 5$
days. NuSTAR observations reveal that the source transitioned from a bright
soft state with unabsorbed, bolometric ($0.1$–$100$ keV) flux $F=6.9\pm
0.1\times 10^{-10}\,\mathrm{erg\,cm^{-2}\,s^{-1}}$, to a low hard state with
flux $F=2.85\pm 0.04\times 10^{-10}\,\mathrm{erg\,cm^{-2}\,s^{-1}}$. Given a
distance of $3.3$ kpc, inferred via association of the source with the
GLIMPSE-C01 cluster, these fluxes correspond to an Eddington fraction of order
$10^{-3}$ for an accreting neutron star of mass $M=1.4M_{\odot}$, or even
lower for a more massive accretor. However, the source spectra exhibit strong
relativistic reflection features, indicating the presence of an accretion disk
which extends close to the accretor, for which we measure a high spin,
$a=0.967\pm 0.013$. In addition to a change in flux and spectral shape, we
find evidence for other changes between the soft and hard states, including
moderate disk truncation with the inner disk radius increasing from
$R_{\mathrm{in}}\approx 3\,R_{\mathrm{g}}$ to $R_{\mathrm{in}}\approx
8\,R_{\mathrm{g}}$, narrow Fe emission whose centroid decreases from $6.8\pm
0.1$ keV to $6.3\pm 0.1$ keV, and an increase in low-frequency
($10^{-3}$–$10^{-1}$ Hz) variability. Due to the high spin we conclude that
the source is likely to be a black hole rather than a neutron star, and we
discuss physical interpretations of the low apparent luminosity as well as the
narrow Fe emission.

neutron stars — X-ray binaries — black holes — stellar clusters

††software: Astropy (Astropy Collaboration et al., 2013, 2018), Corner
(Foreman-Mackey, 2016), DS9 (Joye & Mandel, 2003), Matplotlib (Hunter, 2007),
Scipy (Virtanen et al., 2020), Stingray (Huppenkothen et al., 2019), relxill
(Dauser et al., 2014; García et al., 2014), XSpec (Arnaud, 1996)††thanks: NASA
Einstein Fellow

##  1 Introduction

###  1.1 X-ray binaries in outburst

Compact objects, such as neutron stars (NS) and black holes (BH), orbiting
main sequence stars often undergo cycles of outburst and quiescence due to
modulation in the rate at which matter from the companion star accretes onto
the compact object. Matter falls from the surface of the companion into the
orbit of the compact object via Roche-lobe overflow or stellar winds (also
known as Bondi-Hoyle accretion). According to the Disk Instability Model
(Lasota, 2001), this material eventually reaches a critical density at which
angular momentum can be transported efficiently outward, resulting in the
formation of an accretion disk (Shakura & Sunyaev, 1973). This disk may reach
all the way down to the surface or inner-most stable circular orbit (ISCO) of
the compact object. As the gravitational potential energy of the accreting
material is converted into heat, the innermost regions of the disk can reach
temperatures of order $10^{7}$ K, emitting photons with energy exceeding
thousands of electron volts, hence these systems are referred to as X-ray
binaries. This cycle of transient disk accretion leads to a variety of
observable phenomena. The X-ray spectra of accreting NSs and BHs vary between
a low-luminosity hard state and a brighter soft state, with intermediate
states in between. During the hard state, emission is dominated by a power-
law-shaped component which originates from a region of hot plasma near the
central accretor known as the corona, while the soft state spectrum is
dominated by thermal emission from the inner regions of the disk.

Additional spectral features result from the disk geometry in an X-ray binary.
Iron in the disk may be irradiated by coronal emission and fluoresce, giving
rise to emission lines around $6.4$ keV. Line emission originating from the
inner regions of the disk may be blurred by Doppler shifts due to the rapid
orbital motion of the disk material and by the strong gravitational potential
near the central compact object. Furthermore, soft photons from the corona may
undergo Compton upscattering resulting in a “Compton hump” in the spectrum at
high energies. These “reflection” features encode information regarding the
inner disk radius, $R_{\mathrm{in}}$, and the spin parameter, $a$, of the
central accretor. Spectral models such as relxill (Dauser et al., 2014; García
et al., 2014), which self-consistently model relativistic disk reflection, are
therefore important tools for probing the properties of X-ray binaries, and
can help us to differentiate between NS and BH accretors.

###  1.2 MAXI J1848–015

Each year, the Monitor of All-sky X-ray Image, or MAXI (Matsuoka et al.,
2009), discovers dozens of X-ray sources. Among these sources are accreting
black holes, neutron stars, and white dwarfs. Follow-up with other X-ray
observatories can help to elucidate the nature of these sources and lays the
groundwork for their future study.

One such source, MAXI J1848–015, was discovered with the MAXI/GSC on December
20, 2020 (Takagi et al., 2020). The MAXI/GSC nova alert system (Negoro et al.,
2016) triggered on the source at 05:04 (all times are given in UT), and the
source flux was found to be increasing. The average X-ray flux on eight scan
transits from 00:25 to 11:16 on December 20 was $63\pm 10$ mCrab in the 4–10
keV band. The MAXI $90\%$ confidence region had a radius of about $0.3$ deg
and was consistent with the previously detected ASCA source AX J1848.8-0129
(Sugizaki et al., 2001). Since the source had an angular separation of $26$
deg from the Sun at the time of detection, neither the Neil Gehrels Swift
Observatory X-ray Telescope (Swift/XRT, Gehrels et al., 2004; Burrows et al.,
2005) nor the Neutron Interior Composition Explorer Mission (NICER, Gendreau &
Arzoumanian, 2017) could observe the source.

However, the Nuclear Spectroscopic Telescope Array, or NuSTAR (Harrison et
al., 2013), was able to perform follow-up observations of the source despite
its angular proximity to the Sun. NuSTAR performed tiling observations to
search the MAXI error region, and the source was detected during the first
pointing. The source exhibited a soft spectrum, and although the source
position was further refined to a region with radius $\sim 90^{\prime\prime}$,
it could still not be distinguished from AX J1848.8-0129 with certainty (Pike
et al., 2020). Soon after the NuSTAR ToO observations, on December 23, the
2–10 keV source flux rapidly decreased in a day from about 40 mCrab to less
than 15 mCrab (Negoro et al., 2020). About a week later, the source was again
observed by NuSTAR, this time exhibiting a much harder spectrum (Mihara et
al., 2021).

By the end of February 2021, MAXI J1848–015 was far enough from the Sun that
it could be observed by other instruments. Thereafter, the source was
localized by both Swift/XRT and the Chandra X-ray Observatory (Chandra,
Weisskopf et al., 2000) to $90\%$ confidence regions of $\pm
2.3^{\prime\prime}$ (Kennea et al., 2021) and $\pm 0.8^{\prime\prime}$
(Chakrabarty et al., 2021), respectively, while radio observations further
refined the source position to $\alpha\mathrm{(J2000)=18h\,48m\,49.824s\pm
0.003s}$,
$\delta\mathrm{(J2000)=-01^{\circ}\,29^{\prime}\,49.99^{\prime\prime}\pm
0.05^{\prime\prime}}$ (Tremou et al., 2021).111The authors do not specify
whether the uncertainties represent $1\sigma$ or $90\%$ confidence regions.
Interestingly, the radio position is coincident with a relatively bright NIR
counterpart (Hare et al., 2021). Around the same time, NICER observations of
the source were performed and Miller et al. (2021) reported a number of
emission lines in the Fe K band and a flux of about $1$ mCrab.

Importantly, the precise localization of the source confirmed that MAXI
J1848–015 is not consistent with the previously reported position of AX
J1848.8-0129, and that it is spatially coincident with, and likely resides in,
the core of the Galactic cluster GLIMPSE-C01 (GC01 hereafter). This cluster
was originally discovered by Kobulnicky et al. (2005), who suggested that the
cluster was an old globular cluster passing through the Galactic disk at a
distance of $3.1-5.2$ kpc. Several subsequent studies have alternatively
suggested that GC01 is a young or intermediate age massive cluster candidate
with an age between $0.3-2.5$ Gyr (Davies et al. 2011; Davidge et al. 2016).
More recently, Hare et al. (2018) reported on Hubble Space Telescope
observations of GC01, which they used to estimate a cluster distance of $\sim
3.3$ kpc and a cluster age of $>2$ Gyr by studying the absolute magnitudes of
red clump stars in the cluster. Unfortunately, the cluster’s large source
density, strong differential reddening across the cluster (ranging between
$A_{V}=14-22$), and unknown metallicity make it difficult to more precisely
constrain the cluster’s age (Hare et al., 2018).

In this paper, we present the results of MAXI monitoring of MAXI J1848–015 as
well as spectral and timing analysis of the two NuSTAR observations performed
following the detection of the source by MAXI. In Section 2, we describe the
MAXI observations in detail, including the shape and duration of the outburst.
In Section 3, we discuss the NuSTAR observations of the source, beginning with
a description of the observations and data reduction and continuing onto an
investigation of the source spectra of as well as the results of reflection
modeling applied to these spectra in Section 3.1. Next, we present an analysis
of the timing properties of the NuSTAR light-curves in Section 3.2. Finally,
in Section 4, we discuss what our results mean in regards to the questions of
whether the source is a neutron star or a black hole accretor and how its
particularly low luminosity can be understood in the context of disk
accretion.

##  2 MAXI Observations

###  2.1 Observations and data reduction

MAXI has been monitoring about 85% of sky every 92 minutes with the Gas Slit
Cameras, GSCs, in the 2–20 keV band since August 2009 (Mihara et al., 2011;
Sugizaki et al., 2011). The GSCs have two wide fields of view of
$1.5^{\circ}\times 160^{\circ}$ to the horizontal and zenith directions, and
typically observe a source for 40–100 seconds every 92 minutes as the
International Space Station (ISS) orbits Earth.

In December 2020, the GSC_1, GSC_2, GSC_4, GSC_5, and GSC_7 cameras and the
degraded GSC_3 and GSC_6 cameras were operating. The source was detected by
all these detectors, but in these analyses we only used those obtained with
the well-calibrated GSC_4 and GSC_5 cameras with a high voltage of 1650 V and
GSC_2 and GSC_7 cameras with 1550 V.

We employed a point-spread function (PSF) fit method to obtain MAXI/GSC light-
curves with the best signal-to-noise ratios (Morii et al., 2010). The count
rate in each light-curve bin was obtained by fitting an image with the PSFs of
the GSCs taking into account the presence of nearby sources such as the high-
mass X-ray binary AX J1846.4-0258 (1.60 degree separation) and the Super-giant
Fast X-ray Transient IGR J18483$-$0311 (1.68 degree separation). On the other
hand, the nearby transient sources in quiescent states, including Swift
J185003.2$-$005627 (0.64 deg), GS 1843$-$02 (0.93 deg), and Swift
J1845.7$-$0037 (1.11 deg), were ignored. AX J1848.8$-$0129 (0.012 deg $\simeq$
0.74 arcmin) was also excluded. We note that AX J1848.8$-$0129 is originally
named as AX J184848$-$0129 (Sugizaki et al., 2001), and its position has about
1 arcmin uncertainty. We first produced 1-scan, 6-hr, and 1-day bin light-
curves in the 2–4 keV and 4–10 keV bands, respectively. The 6-hr and 1-day bin
data were obtained by fitting 4-scan and 16-scan image data, respectively. We
then subtracted constant background components, mainly originating from the
galactic ridge X-ray emission, as the average count rates from MJD 58000 (2017
September 4) to 58599 (2019 April 26) were consistent with zero. Finally, we
obtained 2–10 keV curves by summing the background subtracted 2–4 keV and 4–10
keV curves.

As shown later, every $\sim 92$ days (the ISS precession period), when the
source was at the right side of the GSC_2 and GSC_5, the source was obscured
by the Space-X Crew-1 spacecraft attached on the Harmony module of the ISS for
several days. We did not use data during the periods shown in the current
calibration database (CALDB) and we also excluded data from 1 day before and
after this period due to some ambiguity regarding the shape of the spacecraft
shadow.

###  2.2 Long-term light-curve

Figure 1: 2–4 keV and 4–10 keV light-curves (upper and middle panels) and
their ratios (lower) of MAXI J1848–015 obtained with MAXI/GSC. Average fluxes
in 1 scan (grey), 6 hours (black), and 1 day (red) are shown (1 scan data are
omitted in the lower panel). The average 2–4 keV and 4–10 keV count rates for
Crab are 1.065 and 1.172 ct cm-2 s-1, respectively. The blue and green lines
are the start and end time of the first and second NuSTAR observations,
respectively. Figure 2: Long-term 2–10 keV light-curve of MAXI J1848–015 from
MAXI. Unused data during interference with the Space-X Crew-1 spacecraft are
also shown in grey. A logarithmically rebinned curve and the best fitting
curves are also shown in the inset panel. The data during a dip shown in grey
are not used in the fits (see Section 2.2). Observed fluxes for the two NuSTAR
and Swift observations are indicated with the red filled circle, rectangle,
and triangle, respectively, between the dashed lines showing the observation
periods. The orange line shown in the inset represents a linear fit to the
initial rapid decay, while the blue and green lines represent exponential and
power law fits, respectively, to the observed second decay.

Figure 1 shows the MAXI/GSC 2–4 keV and 4–10 keV light-curves and their ratio
for MAXI J1848–015 obtained by the PSF-fit method. In the seven scan transits
from 18:37 on December 18 to 01:12 on December 19 (MJD 59201.7763 –
59202.0501), the source was not visible on GSC images (Takagi et al., 2020).
No count excess is recognized in each scan curve. The PSF-fit method provides
two-sided 1$\sigma$ errors based on the likelihood method (Morii et al.,
2010). Fitting eight one-scan data points during the period with a constant
model gives the average count rate of -0.094$\pm$0.0128 ct cm-2 s-1. Using the
size of this error, we estimate a 1$\sigma$ upper limit of 0.0128 ct cm-2 s-1,
$\sim 5.7$ mCrab222We adopt the 2–10 keV count rate and the flux for Crab as
2.237 ct cm-2 s-1 and $2.4\times 10^{-8}$ erg cm-2 s-1, respectively.. This is
consistent with a value 12 mCrab of a typical 3$\sigma$ detection limit of 1
day of $\sim 16$ scans (Negoro et al., 2016). After the scan transit at 01:12
until 22:52 on December 19 (MJD 59202.05-59202.95), the GSC did not fully
observe the source region due to Sun avoidance. During the three scan transits
from 11:59 to 15:05, however, some count excess was recognized at the edge of
the detectors, which suggests the outburst started between 02:22 and 11:59.

The light-curves and hardness ratios in Fig. 1 show that the 4–10 keV flux
reached the peak in almost one day on December 20 (MJD 59203) followed by
gradual spectral softening. On December 23, the 2–10 keV flux rapidly
decreased to below the detection limit in one day (Negoro et al., 2020) from
$0.117\pm 0.016$ ct cm-2 s-1 at MJD 59205.89 (the center time of the 6-hr bin)
to $-0.003\pm 0.009$ ct cm-2 s-1 at 59206.86 (we note that background
subtraction may result in nonphysical negative count rates). However, we note
that the light-curve obtained during the first NuSTAR observation performed on
December 23 indicates a flux increase during the 4 hour observation (see §3).
This suggests that the rapid decrease observed by MAXI on December 23 is not
simply due to the occultation by the companion. This flux drop continued until
around December 26.0 (MJD 59209.0), and the 4–10 keV flux increased again,
possibly prior to an increase in the 2–4 keV flux.

We plot long-term variations in the flux of MAXI J1848–015 in Figure 2. The
data when the source is hidden by the Space-X Crew-1 spacecraft are not used
and shown in grey. GIS images for the duration show extended enhancement
around the source region. The origin of the enhancement is unknown, but it is
difficult to consider that it is intrinsic to the source because of the
periodicity closely connected with the interference and the extended image
even though there is still some ambiguity in the shadow shape of the
spacecraft.

We also show the 2–10 keV light-curve with a logarithmic time axis from the
time December 22 04:48 (MJD59205.2 $\equiv T$) in the inset panel in Fig. 2.
We fit the decay with three different models: a linear decay, an exponential
decay, and a power law decay. The linear fit to the putative rapid decay
starting at $t_{0}(\equiv t-T)=$ 0.69 d (=MJD 59205.89) is shown by the orange
solid line. After $t_{0}=3.92$ d the flux exhibited an exponential (blue
curve) or a power law (green) decay. Fitting the data for $t_{0}\geq 3.92$ d
with an exponential function gives a time constant of $28.0\pm 9.4$ d (shown
by the blue solid line and its extrapolation by the dotted line). Fitting the
flux decrease from $t_{0}\geq 0.69$ d to a power law function, we obtained a
power law index of $-0.97\pm 0.08$, shown by the green solid and dotted line,
however we note that the result of the power law fit depends strongly on the
choice of $T$.

##  3 NuSTAR Observations

Table 1: Log of NuSTAR observations presented in this paper.  Observatory | Observation ID | Start time (UTC) | Stop time (UTC) | Exposure (s)
---|---|---|---|---
NuSTAR | 90601340002 (NuObs 1) | 2020-12-23 02:53:36 | 2020-12-23 07:06:26 | 9805
NuSTAR | 90601341002 (NuObs 2) | 2020-12-31 09:08:34 | 2021-01-01 03:40:01 | 36395

Figure 3: Background-subtracted 3-78 keV NuSTAR light-curve for each of the
two observations, NuObs 1 (left) and NuObs 2 (right). The light-curves have
been split into different CHU combinations. Time is measured in seconds since
the observation start times listed in Table 1.

NuSTAR, launched in June 2012, is the first high-energy focusing X-ray
telescope (Harrison et al., 2013). It is composed of two focal planes, FPMA
and FPMB, each paired with a set of focusing optics with a focal length of 10
m. The focal planes are each made up of 4 pixelated Cadmium Zinc Telluride
(CZT) detectors, bonded to a set of custom readout electronics. NuSTAR has a
resulting bandpass of 3–78 keV, making it a uniquely powerful tool for
studying hard X-ray emission.

MAXI J1848–015 was first observed by NuSTAR on 2020 December 23. This
observation was taken with the goal of localizing the source, and was
therefore broken down into 5 pointings, forming a mosaic which tiled the error
region reported by MAXI. The source was detected by NuSTAR in the first of
these pointings (OBSID 90601340002, PI Fiona Harrison), which had an exposure
time of 9.8 ks. NuSTAR followed up on MAXI J1848–015 about a week later on
2020 December 31 (OBSID 90601341002, PI Fiona Harrison), after the source had
dimmed. This observation had an exposure time of 36 ks. Hereafter we refer to
these observations as NuObs 1 and NuObs 2, respectively. Table 1 lists the
NuSTAR observations as well as their start and stop times and their total
exposure times.

During both NuSTAR observations, MAXI J1848–015 was in close angular proximity
to the Sun. This limits the aspect reconstruction as the primary Camera Head
Unit (CHU) that NuSTAR uses to project counts onto the sky is blinded by the
Sun. Instead, the ground software must make use of CHUs 1, 2, and 3 which are
attached to the spacecraft bus. As a result, Mode 1 scientific data was
unavailable. Instead, we analyzed Mode 6 scientific data, with which the
source image cannot be perfectly reconstructed. This produces a source image
with multiple centroids, each corresponding roughly to a different combination
of CHUs. We reprocessed the unfiltered event files using NuSTARDAS v2.0.0 and
CALDB v20200826. Next, we split the cleaned Mode 6 event files into event
files corresponding to different combinations of CHUs 1, 2, and 3 using
nusplitsc in the strict splitting mode. Figure 3 shows the background-
subtracted light-curve for each NuSTAR observation, split into different CHU
combinations.

Figure 4: Summed Mode 6 data (all CHU combinations) from NuObs 1. The color
bar is shown in units of counts. The source landed on the gap between
detectors, and due to poor image reconstruction, multiple peaks in the count
distribution are apparent. The green circle, which has a radius of
$1^{\prime}$, represents the ASCA error region for source AX J184848–0129 as
reported by Sugizaki et al. (2001).

For the purpose of extracting spectra, we used DS9 (Joye & Mandel, 2003) to
select circular source and background regions for each CHU combination. For
NuObs 1, we chose source regions with radii equal to $60^{\prime\prime}$ and
background regions with radii equal to $90^{\prime\prime}$. The centers of the
source regions were determined using the automated centroid detection
algorithm provided by DS9. During this observation, the source fell on the gap
between detectors. Therefore, the source centroid fell on a different detector
for different CHU combinations (see Figure 4). We chose background regions
which fell on the same detectors as the source centroid for each CHU
combination. This was not a concern when choosing source and background
regions for NuObs 2 because the source did not fall near the chip gap. Due to
the lower count rate and better pointing during this observation, we chose
source regions with radii of $45^{\prime\prime}$ in order to reduce the
contribution of background counts, and we again chose background regions with
radii of $90^{\prime\prime}$.

Using nuproducts we extracted scientific products for each of these CHU
combinations, essentially treating each as a separate observation. We then
used the routine addarf to sum the resulting Ancillary Response Files, and the
routine addspec to sum the resulting source spectra, background spectra, and
Response Matrix Files. The final result for each observation was a single
source spectrum, background spectrum, RMF, and ARF for each focal plane
module. We used the spectral fitting package Xspec (v12.11.1 Arnaud, 1996) to
analyze the spectra. In order to determine best fit models, we used the $W$
fit statistic (Wachter et al., 1979), and the full NuSTAR band, 3–78 keV, was
used for spectral fitting. Spectra were binned using the optimal binning
procedure described by Kaastra & Bleeker (2016). Spectra shown in figures have
been further rebinned for clarity such that each bin has a significance of at
least $5\sigma$, with the exception of the highest-energy bins, each of which
has a significance between $3\sigma$ and $4\sigma$. All errors quoted
represent $90\%$ confidence intervals, and upper/lower limits represent $99\%$
confidence intervals, unless otherwise stated.

We made significant use of the Python modules Scipy (Virtanen et al., 2020),
Astropy (Astropy Collaboration et al., 2013, 2018), Matplotlib (Hunter, 2007),
Corner (Foreman-Mackey, 2016), and Stingray (Huppenkothen et al., 2019). We
used Astropy to easily read and write NuSTAR event and light curve files, we
used Scipy to perform various calculations and curve fitting, and we used
Stingray to calculate and analyze power density spectra. We used Matplotlib
and Corner to produce plots of spectra, light-curves, power density spectra,
and parameter distributions.

###  3.1 Spectral variability

Figure 5: Soft state (blue) and hard state (orange) spectra with best fit models and model components shown with solid and dashed lines, respectively. FPMA spectra are shown with x’s while FPMB spectra are shown with filled circles. The soft state spectrum is described well by a Comptonized disk blackbody, while the hard state spectrum does not require a disk component. Instead, the hard state spectrum is described well by a power law with a high energy cutoff. Both models are improved by the addition of relativistic disk reflection as well as a narrow Fe line component. The lower two panels show the residuals resulting from the model fits in units of $\chi=\mathrm{(data-model)/error}$.  Figure 6: Broad Fe emission profiles in the soft state (top) and hard state (bottom) spectra. These residuals were produced by fitting the spectra to a simplified continuum model while ignoring data points in the range $5-10$ keV. Significant changes to the shape of the profile can be seen between the two states with the peak growing stronger and shifting to lower energies during the hard state.  Table 2: Spectral parameters determined by performing a joint fit of the soft and hard state spectra in Xspec.  Model component | Parameter | Soft State (NuObs 1) | Hard State (NuObs 2)
---|---|---|---
tbabs |  $N_{\rm H}$ ($10^{22}\,\mathrm{cm}^{-2}$) | $4.2^{+0.2}_{-0.1}$ | $6.1\pm 0.2$
gauss |  $\mu$ (keV) | $6.8\pm 0.1$ | $6.3\pm 0.1$
$K$ ($10^{-5}\mathrm{Photon\,cm^{-2}\,s^{-1}}$) | $17.7\pm 0.4$ | $6.26^{+0.05}_{-0.07}$
Equivalent Width (eV) | $42\pm 3$ | $42\pm 1$
diskbb |  $kT_{\mathrm{in}}$ (keV) | $1.38^{+0.02}_{-0.03}$ |  $\cdots$
$(R_{\mathrm{km}}/D_{10})^{2}\cos{i}$ | $6.4^{+0.2}_{-0.3}$ |  $\cdots$
nthcomp/cutoffpl | $\Gamma$ | $2.42\pm 0.04$ | $1.58^{+0.01}_{-0.02}$
$E_{\mathrm{cut}}$ (keV) |  $\cdots$ | $28.9\pm 0.4$
Norm ($10^{-3}$) | $9.6\pm 0.4$ | $21.3^{+0.7}_{-0.8}$
relxillNS/relxilllp |  $h$ ($R_{\mathrm{g}}$) |  $\cdots$ | $5.7\pm 0.2$
$a$ | $0.967\pm 0.013$
Inclination (deg) | $26.4\pm 0.5$
$R_{\mathrm{in}}$ ($R_{\mathrm{g}}$) | $2.9\pm 0.2$ | $7.90^{+0.15}_{-0.16}$
$\log(\xi/\mathrm{erg\,cm\,s^{-1}})$ | $2.58\pm 0.06$ | $2.77^{+0.04}_{-0.02}$
$A_{\mathrm{Fe}}$ (Solar) | $0.77^{+0.02}_{-0.01}$
$\log(N)$ ($\mathrm{cm^{-3}}$) | $<15.3$ |  $\cdots$
$f_{\mathrm{refl}}$aaWe determined the reflection fraction by first fitting with the direct emission components included in the relxill models (i.e. with a positive value of $f_{\mathrm{refl}}$), then we determined the normalizations of the direct components by freezing the reflection fractions and separating the direct and reflected components (with a negative value of $f_{\mathrm{refl}}$). | $0.61\pm 0.01$ | $0.83^{+0.02}_{-0.03}$
$F_{\mathrm{bol}}(10^{-10}\,\mathrm{erg\,cm^{-2}\,s^{-1}})$bbUnabsorbed bolometric ($0.1-100\,\mathrm{keV}$) flux. | $6.9\pm 0.1$ | $2.85\pm 0.04$
$L_{\mathrm{bol}}(10^{35}\,\mathrm{erg\,s^{-1}})$ccBolometric ($0.1-100\,\mathrm{keV}$) luminosity assuming a distance of $3.3\,\mathrm{kpc}$. | $9.1\pm 0.1$ | $3.73\pm 0.05$
$W/\mathrm{d.o.f.}$ | 834/695

NuSTAR revealed a stark spectral change between the first and second
observations. The spectra are shown in Figure 5 along with their best-fit
models. We found that the spectrum during NuObs 1 was significantly softer
than that observed during NuObs 2. We therefore refer to the former as the
“soft state” and the latter as the “hard state”. The spectra are described
remarkably well by models which are frequently used to model the soft and hard
states of accreting black holes and neutron stars: the continuum emission
during the soft state is described well by an absorbed disk blackbody (diskbb)
and a power law with index $\Gamma$, while the continuum emission during the
hard state is described well by an absorbed power law with a high-energy
cutoff, $E_{\mathrm{cut}}$, which we modeled using cutoffpl. We modeled
absorption using the tbabs model. We used cross-sections provided by Verner et
al. (1996) and abundances provided by Wilms et al. (2000).

Each of the spectra exhibits broad emission lines around 6.4 keV corresponding
to Fe K$\alpha$. Figure 6 shows the Fe line profiles which result from fitting
the continuum emission while ignoring data bins between 5 and 8 keV. The
broad, asymmetrical structure of the Fe line profiles led us to add
relativistic disk reflection to the continuum models described above. We added
a reflected component using relxilllp (Dauser et al., 2014; García et al.,
2014) in order to self-consistently model emission originating from a hot
corona with a lamppost geometry which irradiates and is reprocessed by a thin
disk. We tied the power law index and high energy cutoff333Because the soft
state does not require a high-energy cutoff, we fixed the cutoff energy at
1000 keV, far beyond the upper edge of the NuSTAR bandpass. of each power law
component to those of relxilllp. We found that this model was able to describe
the the spectrum well, achieving a fit statistic of
$W/\mathrm{d.o.f.}=449/323$ and $W/\mathrm{d.o.f.}=420/373$ (and a reduced
Chi-squared test statistic of $\chi^{2}_{\nu}=0.98$ and $\chi^{2}_{\nu}=1.01$)
for the soft and hard states, respectively. However, the Fe line emission
could not be fully accounted for, and residuals indicated the presence of a
narrow line component. We therefore added a Gaussian component near 6.4 keV,
and we froze its width at $\sigma=10^{-5}$ keV, much narrower than the
instrumental energy resolution. We allowed the strength and the centroid of
the line to vary while fitting, and we found that the addition of this narrow
line improved the fit by $\Delta W=-17.5$ and $\Delta W=-10.6$ for the soft
and hard states, respectively, while decreasing the number of degrees of
freedom by 2. We also found that the addition of this component led to better
constraints on other parameters, such as the spin and the inclination, while
still remaining consistent with their previous estimates.

In order to determine the statistical significance of the narrow components,
we simulated 5000 spectra each for the soft and hard states, originating from
the reflection models without narrow components. We then added a narrow
component, again leaving the centroid energy and line strength free and fixing
the width at $\sigma=10^{-5}$ keV. By calculating the resulting improvement in
the fit statistic for each simulation, we arrived at a false positive rate for
the addition of a narrow component. We found that for the soft state, only one
of these simulations was improved by more than $\Delta W=-17.5$, and for the
hard state, 23 out of the 5000 simulations were improved by more than $\Delta
W=-10.6$. In other words, we estimate a statistical significance of
$3.7\sigma$ and $2.8\sigma$ for the addition of a narrow Fe component in the
soft and hard state observations, respectively.

Finally, prompted by the clear presence of a hot thermal component, when
modeling the soft state spectrum we replaced relxilllp with the sum of nthcomp
(Zdziarski et al., 1996; Życki et al., 1999), which models Comptonization of
seed photons originating from a blackbody, and relxillNS (García et al.,
2022), which models reflection of a blackbody spectrum rather than a power
law. We tied the disk blackbody temperature to that of the seed photon
temperature for both nthcomp and relxillNS, and we fixed the electron
temperature of nthcomp, $kT_{e}$, at $1000$ keV. We found that the fit was not
affected by the type of seed blackbody specified for nthcomp, so for
consistency we used a disk blackbody seed spectrum. We found that this model
improved the fit ($\Delta W=-10$, $\Delta\mathrm{d.o.f.}=1$) when compared to
the relxilllp model. We also tried modeling the hard state spectrum using a
combination of a Comptonized disk blackbody with a reflected Fe line (diskbb
$+$ nthcomp $+$ rellinelp). We found that this model struggled to describe the
hard state spectrum ($W/\mathrm{d.o.f.}=472/372$), particularly at high photon
energies ($>20$ keV). It resulted in a photon index of $\Gamma=1.8$ and an
electron temperature of $kT_{e}=9.1$ keV.

Having arrived at a suitable model for the spectra during both the soft
(diskbb $+$ nthcomp $+$ relxillNS $+$ gaussian) and hard (cutoffpl $+$
relxilllp $+$ gaussian) states, we performed a Markov Chain Monte Carlo
analysis in Xspec in order to explore the parameter space in detail. We used
the Goodman-Weare algorithm (Goodman & Weare, 2010) with a chain length of
$10^{6}$ and a burn-in length of $10^{5}$. We initialized all walkers in a
Gaussian distribution about the best fit parameters, with $\sigma$ defined by
the covariance matrix resulting from least-squares fitting. All spectral
parameters are therefore given as the median values of the final posterior
distributions, and the errors represent the bounds between which $90\%$ of the
samples lie.444See Hogg & Foreman-Mackey (2018) for a discussion of best
practices when interpreting the results of MCMC analyses. We found that both
models recovered a high spin, $a>0.7$, and an inner disk inclination angle
around $25$ deg. However there was significant degeneracy such that each model
had valid solutions with different values for spin, disk inclination, inner
disk radius, and other key parameters (see Appendix A for details regarding
the individual fits). In order to break this degeneracy, we performed a joint
fit wherein the inner disk inclination, the spin parameter, and the iron
abundance were tied between the two spectral states.

Table 2 lists the median parameters for the joint fit resulting from the MCMC
analysis described above, as well as the $W$-statistic of the best fit. Figure
5 shows the spectra as well as the best fit models and residuals for both the
soft and the hard states. By performing a joint fit, we successfully narrowed
the parameter space, resulting in a consistent solution across both the soft
and hard states with a spin of $a=0.967\pm 0.013$ and an inclination of
$i=26.4\pm 0.5$ deg.

The Fe K$\alpha$ emission line profile (Figure 6) shows clear evolution of the
region responsible for this emission, with the peak shifting towards lower
energies by about $0.5$ keV and the overall profile becoming more pronounced
as the source evolved from the soft to the hard state. Interestingly, we found
that the centroid of the narrow Fe line during the hard state was less than
$6.4$ keV at the $95\%$ confidence level. In other words, we detect a redshift
in the narrow component at a significance of about $2\sigma$. We also fit the
data while freezing the centroid at $6.4$ keV given that this is still
consistent with our measurement of $\mu=6.3\pm 0.1$ keV, but this resulted in
a somewhat degraded fit ($\Delta W=3$; $\Delta\mathrm{d.o.f.}=1$), and it led
to significantly looser constraints on parameters such as spin, inclination,
and lamppost height.

The evolution of the accretion disk is further reflected in the best-fit
relativistic reflection models, which suggest a significant increase in the
inner radius of the accretion disk. This could constitute evidence for disk
truncation in the hard state. In order to determine whether the choice of
spectral model affects the apparent evolution of the inner disk radius, we
performed a joint fit wherein the disk reflection features of both the soft
and hard state spectra were modeled using relxilllp (rather than using
relxillNS/relxilllp for the soft/hard states, respectively). For this fit, we
tied the spin parameter, the inner disk inclination, and the Fe abundance
between the soft and the hard states. This resulted in a slightly larger value
for the inner disk radius in both states – $R_{\mathrm{in}}=3.4\pm
0.2\,R_{\mathrm{g}}$ (where $R_{\mathrm{g}}=GM/c^{2}$) for the soft state and
$R_{\mathrm{in}}=8.6^{+0.5}_{-1.1}\,R_{\mathrm{g}}$ for the hard state – but
the radii remained significantly different, indicating that the evolution of
the inner disk radius which we observe is independent of the choice of
relxillNS or relxilllp.

The narrow Fe line components may be interpreted as distant disk reflection.
Therefore we investigated whether non-relativistic reflection modeling could
describe this component. We chose to use another member of the relxill suite,
xillver (García & Kallman, 2010; García et al., 2013) for this component. In
this model, the relxill and xillver components can be interpreted as
reflection from the inner and outer regions of the disk, respectively. In the
soft state, distant reflection, using either xillver or xillverNS to model
reflection of the power law component or the blackbody component,
respectively, is not able to fit the data as well as a simple Gaussian and
results in a change in the fit statistic of $\Delta W=10$.

For the hard state, replacing the Gaussian emission line with the distant
reflection model did not change the fit statistic appreciably, but we found
that the resulting parameters show significant degeneracies, such as between
the disk inclination, the power law photon index, and the lamppost height. We
tied the photon index, $\Gamma$, and the cutoff energy, $E_{\mathrm{cut}}$, of
the distantly reflected power law to those of the power law reflected from the
inner disk, and we tied the iron abundance of the inner and outer disk but we
allowed the ionization of the two components to vary independently. Given that
we measured a centroid of $\mu=6.3\pm 0.1\,\mathrm{keV}$, slightly lower than
the rest frame energy of the neutral Fe K$\alpha$ line, when modeling the
narrow emission component using a Gaussian component, we also allowed the
redshift of the outer disk component represented by xillver to vary.

We found that this model was not sensitive to the inclination of the outer
disk. When allowed to vary independently of the inner disk inclination the
model preferred a high outer disk inclination of
$i_{\mathrm{out}}=79^{+6}_{-11}$ deg ($\Delta i\equiv
i_{\mathrm{out}}-i_{\mathrm{in}}=57\pm 10$ deg), but tying the inner and outer
inclinations did not affect the fit statistic and resulted in an inclination
which was closer to that resulting from the joint fits, $i=22^{+4}_{-5}$ deg.
In addition to a slightly smaller inclination angle, adding the xillver
component while tying the inner and outer disk inclinations also resulted in
an increased inner disk radius
($R_{\mathrm{in}}=14^{+6}_{-5}\,R_{\mathrm{g}}$).

We also found that allowing the redshift of the xillver component to vary
improved the fit by $\Delta W=-4$ compared to the same model with the redshift
frozen at a value of zero. We measure a redshift of $z<3.4\times 10^{-2}$ at
the $99\%$ confidence level, corresponding to an upper limit on the line-of-
sight velocity of the emitting region of $v<10000\,\mathrm{km\,s^{-1}}$,
assuming a rest frame energy of $6.4$ keV. We found that performing the same
calculations using the posterior distribution of Gaussian centroids resulting
from the joint fit produces upper and lower limits differing from these by
less than $10\%$. The fit is slightly degraded by fixing the redshift to zero,
but the main effect on the parameters is a decrease in the inner disk
inclination by a few degrees. We note that the source is unlikely to
experience a strong redshift due to the motion of the binary system, and it
certainly does not experience cosmological redshift, but rather any observed
strong redshift is more likely to be caused by motion of the emitting region
itself. In Section 4.3, we discuss one scenario – that of ionized outflows –
which could result in red- and blue-shifting of narrow emission.

###  3.2 Timing analysis

Figure 7: Averaged cospectrum calculated for the hard state NuSTAR observation, NuObs 2, using only CHU12 data. The cospectrum has been rebinned for clarity. The best-fit power law is shown in red. We did not find evidence for QPOs or pulsations.  Table 3: Timing properties of the source during each NuSTAR observation.  Observation | rms ($10^{-3}$–$10^{-1}$ Hz) | rms ($0.1$–$10$ Hz) | $\gamma$
---|---|---|---
NuObs 1 | $<8\%$ | $<15\%$ |  $\cdots$
NuObs 2 | $12\pm 2\%$ | $<14\%$ | $-2.1\pm 0.1$

We investigated the source variability by producing cospectra (Bachetti et
al., 2015) for each of the NuSTAR observations. We first corrected the photon
times of arrival for the motion of NuSTAR using barycorr. We specified the
Chandra source position reported by (Chakrabarty et al., 2021), and we used
the JPL planetary ephemeris DE-430. In order to minimize the impact of the
motion of the source on the detectors on our timing analysis, we analyzed each
of the CHU combinations separately. We split the event files into segments of
length $1024$ s, then binned the events with a time resolution of $2048^{-1}$
s in order to probe variability between $10^{-3}$ Hz and $10^{3}$ Hz555Recent
improvements to the calibration of NuSTAR have greatly improved its timing
capabilities, allowing for precision down to the $\sim 65\,\mathrm{\mu s}$
level (Bachetti et al., 2021). This range of frequencies allowed us to
investigate both the low-frequency noise, and to search for any hint of
pulsations potentially arising from a neutron star source. For each segment,
we calculated the cospectrum between FPMA and FPMB. We found that for both
observations, only CHU combination CHU12 contained continuous good time
intervals of length greater than 1024 s, and therefore this was the only CHU
combination for which we calculated cospectra. For each observation we then
averaged all of the cospectra. Finally, we applied deadtime and background
corrections by multiplying the averaged fractional rms normalized power by
$(1-\tau(\overline{S+B}))^{-2}(\overline{S+B}/\overline{S})^{2}$, where
$\tau=25\,\mathrm{ms}$ is the deadtime per event, $S$ and $B$ are the source
and background rates, respectively, calculated from the event list, and bars
indicate the geometric mean of the FPMA and FPMB count rates.

Table 3 shows the timing properties of the source during both observations.
Because the source landed on the gap between detectors during NuObs 1, which
is sure to exacerbate any systematic variability due to motion of the source
on the focal plane, we do not present the cospectrum here. The quality of the
data was not sufficient to perform modeling of the cospectrum, but we did not
observe a clear flattening in the low frequency noise of the source. We were
able to place an upper limit on the low-frequency noise of $\mathrm{rms}<8\%$
by integrating the measured power in the range $10^{-3}-10^{-1}$ Hz. In order
to estimate the continuum rms variability, we produced an averaged cospectrum
with segment length $64$ s (due to the shorter segment length, we were able to
utilize the data from all CHU combinations except for CHU2) and sampled the
resulting error distributions for the power in the range $0.1-10$ Hz. We
produced $10^{5}$ sample cospectra in this range, and calculated the total rms
for each. The result was an upper limit, defined as the 99th percentile of
this sample, of $\mathrm{rms}<15\%$.

The source did not fall on the chip gap during NuObs 2, and we therefore
present the averaged, logarithmically rebinned cospectrum in Figure 7.
Although there is clear red noise, similar to the previous observation we do
not observe a low frequency turnover. We fitted the low-frequency ($<0.1$ Hz)
noise to a power law and found an index of $\gamma=-2.1\pm 0.1$. This is
consistent with the tail of a zero-centered Lorentzian, which is often used to
describe the low-frequency noise in accreting black holes and neutron stars
(Belloni et al., 2002). We integrated the low-frequency noise and obtained
$\mathrm{rms}=12\pm 2\%$, and we obtained an upper limit on the power
integrated between $0.1-10$ Hz of $\mathrm{rms}<14\%$ using the same method as
described for the previous observation (in this case only CHU13 was excluded).

Noting a potential feature in the cospectrum at $\sim 2\times 10^{-2}$ Hz, we
performed a search for quasiperiodic oscillations (QPO) by stepping
logarithmically from $10^{-3}$ Hz to $1024$ Hz and fitting the unbinned hard
state cospectrum to the power law described above plus a Lorentzian centered
at each frequency step. For each frequency, we recorded the change in the
$\chi^{2}$ fit statistic compared to the power law alone. Using this method,
we did not find any significant QPO candidates. To determine whether the
potential feature could be due to coherent pulsations, we also folded the
events for each observation, summing all CHU combinations, at 10000 pulse
frequencies between $2\times 10^{-2}$ Hz and $3\times 10^{-2}$ Hz and
calculating the $Z^{2}_{1}$ statistic (Buccheri et al., 1983) for each
candidate frequency. For the soft state observation, NuObs 1, we found a peak
in the $Z^{2}_{1}$ distribution at $\sim 44$ s with a significance of
$2.1\,\sigma$, and for the hard state observation, NuObs 2, the highest peak
was at $\sim 42$ s and had a significance of only $0.7\,\sigma$. We further
searched for pulsations in each observation by producing cospectra for the
frequency range $0.008$–$2048$ Hz, again using the sum of all CHU
combinations. We did not observe any significant peaks during either
observation.

##  4 Discussion

###  4.1 The nature of the accretor

While there is no “smoking gun” evidence for one particular type of compact
object (for example, the detection of pulsations would prove the presence of a
neutron star), the evidence we have presented thus far favors the case of a
black hole X-ray binary.

The soft state spectrum is described well by a Comptonized multi-temperature
disk blackbody with relativistic reflection features, which may represent
returning radiation (c.f. Connors et al., 2020, 2021; Lazar et al., 2021), and
the hard state spectrum is described by a reflected power law alone. Joint
modeling using relxilllp and relxillNS indicates that the accreting object has
a high spin, $a\approx 0.97$. Given the relation $a=cJ/GM^{2}$, where $J$ is
the angular momentum of the spinning compact object, and $M$ is its mass, and
assuming a moment of inertia $I=\frac{2}{5}MR^{2}$ for a neutron star, we may
estimate the maximum spin that a neutron star can attain. Assuming a canonical
neutron star with $M=1.4M_{\odot}$ and $R=10$ km, we arrive at a spin of
$a\approx 0.4\frac{\nu_{\mathrm{spin}}}{\mathrm{kHz}}$, meaning that even the
most rapidly rotating neutron stars will not achieve spin parameters
approaching that which we have measured. We consider this a compelling piece
of evidence which favors the classification of MAXI J1848–015 as an accreting
black hole – explaining the broad Fe line in the case of an accreting neutron
star would prove difficult.

Additionally, using archival Chandra observations of the GC01 cluster, Hare et
al. (2021) were able to place an upper limit of $\sim 3.3\times
10^{30}\,\mathrm{erg\,s^{-1}}$ on the quiescent luminosity in the 0.5–10 keV
band. Whereas accreting neutron stars tend to have quiescent luminosities
around $10^{33}\,\mathrm{erg\,s^{-1}}$ (Tsygankov et al., 2017), the
luminosity of MAXI J1848–015 prior to outburst is more in line with those
measured for black holes, perhaps due to the presence of an event horizon
rather than a boundary layer (Garcia et al., 2001).

The initial outburst observed by MAXI was very short-lived compared to many
black hole X-ray binaries, which tend to show exponential decays with
e-folding times of tens of days (McClintock & Remillard, 2006), however
similarly rapid outbursts are not unheard of (c.f. Maitra & Bailyn, 2006). Of
course, the count rate in the limited energy band does not always reflect the
mass accretion rate, especially in cases where the source spectrum changes
significantly. It is, however, interesting to note that some objects, e.g.
gamma-ray bursts, exhibit power law decays similar to the flux decrease
observed for MAXI J1848–015 by NuSTAR, MAXI, and Swift (Miller et al., 2021).

###  4.2 Disk accretion at low apparent luminosity

MAXI J1848–015 reached an unabsorbed bolometric luminosity of $\sim
10^{36}\,\mathrm{erg\,s^{-1}}$ during the soft state, and dropped to a
luminosity of $\sim 4\times 10^{35}\,\mathrm{erg\,s^{-1}}$ in the hard state.
The general shape of the spectrum observed during each of these states is
consistent with accretion onto a neutron star or a black hole, and despite the
low luminosities, observations of broad emission features around $6.4$ keV
indicate the presence of an optically thick accretion disk which extends close
to the central accretor and reaches a high temperature of $\sim 1.4$ keV.
Models of accretion onto black holes predict the formation of an advection-
dominated accretion flow, or ADAF, at mass accretion rates below a few percent
of the Eddington limit, resulting in truncation of the disk at large radii
(Esin et al., 1997). Indeed, observations have demonstrated that X-ray
binaries tend to undergo state transitions at $\sim 2\%$ of the Eddington
limit (Maccarone, 2003; Vahdat Motlagh et al., 2019). Given the inconsistency
we observe between the low source luminosity and evidence for a small disk
radius, we consider two effects which could suppress the observed luminosity:
disk inclination and obscuration.

Reflection features – the broad Fe line profile and excess “Compton hump”
above $10$ keV – allowed us to constrain the inclination of the inner regions
of the disk as well as the inner disk radius. Reflection modeling of the soft
state spectrum resulted in an inner disk radius of $R_{\mathrm{in}}=2.9\pm
0.2R_{\mathrm{g}}$. Even for a neutron star accretor with mass
$M=1.4M_{\odot}$, this implies an inner disk radius of about 6 km, whereas the
flux of the disk blackbody implies an effective inner disk radius of
$R_{\mathrm{in}}\sqrt{\cos i}=0.8\,\mathrm{km}$, assuming a distance to the
source of $3.3$ kpc. Several effects, including gravitational redshift,
Compton scattering of disk photons (Kubota & Makishima, 2004), spectral
hardening (Shimura & Takahara, 1995), and boundary condition corrections
(Kubota et al., 1998), will increase or decrease the actual value of the inner
disk radius compared to the apparent radius, but in total these effects are
unlikely to introduce a factor of more than order unity.

Thus we are left with a contradiction between inner disk radius measurements
which could presumably be resolved by assuming a high inclination, $i$, of the
inner disk, resulting in a smaller projected disk flux from the point of view
of an observer. While reflection modeling appears to rule this out, preferring
an inclination between 20 and 30 degrees, it has been shown that the
inclination inferred from reflection modeling can conflict drastically from
the actual inclination of a system, possibly due to obscuration of the blue
wing of the broad Fe line (Connors et al., 2019).

High inclination of the inner disk alone may not be able to explain the low
flux of MAXI J1848–015. We therefore also consider obscuration of the inner
regions of the disk by the outer disk. In this scenario, the outer regions of
the disk intercept the line of sight between the observer and the inner disk.
If the outer regions of the disk have a clumpy structure, this will result in
an effective partial coverer, and may be consistent with the change in column
density we have measured between the soft and hard states. Alternatively, we
may be observing emission from the inner disk which has been scattered off the
outer regions of the disk on the side opposite the observer.

A combination of these two effects has been proposed for the high mass X-ray
binary, V4641 Sgr (Koljonen & Tomsick, 2020), which has similarly been shown
to exhibit evidence for a disk extending close to the central black hole
despite a low Eddington ratio (Miller et al., 2002). In fact, the hard state
of MAXI J1848–015 shares a number of similar characteristics with V4641 Sgr.
Both exhibit power law spectra with indices between 1 and 2 and relatively low
cutoff energies ($<30$ keV). Additionally, both systems undergo short
outbursts with durations of tens of days or less (Wijnands & van der Klis,
2000; Revnivtsev et al., 2002), and on shorter timescales they both exhibit
relatively featureless power spectra with red noise components described by a
power law of slope $\sim-2$ (Maitra & Bailyn, 2006). However, the amplitude of
variability in the 0.1–10 Hz range that we have observed, while poorly
constrained, is somewhat lower than that of V4641 Sgr (Maitra & Bailyn, 2006).
In both of these systems, reprocessing of emission from the central regions of
the accretor could help to explain this behavior by “smearing out” variability
on short timescales.

Given the low luminosity as well as the very short outburst duration, we also
suggest the possibility that the source may reside in a compact binary. A
smaller-than-usual disk could lead to short outbursts, and depending upon the
orbital period, the mass accretion rate may be low (Deloye & Bildsten, 2003).
It is interesting to note that black hole binaries undergoing mass transfer in
globular clusters are likely to harbor both low-mass donors and relatively
low-mass black holes (Kremer et al., 2018). Because we are unable to detect
the orbital period, and due to the fact that a compact binary would imply a
small companion, which is contradicted by the potential NIR counterpart of the
system, we consider this case speculative. However, given the rarity of known
black holes in compact binaries, it is an interesting possibility nonetheless
and one which warrants further observations of the source.

###  4.3 Evolving narrow line emission

We found that the narrow Fe lines observed in the soft and hard state spectra
have different centroid energies, evolving from $\sim 6.8$ keV in the soft
state to $\sim 6.3$ keV in the hard state. This change likely corresponds to a
change in the ionization of the emitting region, perhaps originating from the
outer regions of the accretion disk, with neutral or lowly-ionized Fe I–XVII
responsible for the line in the hard state and highly ionized Fe XXV–XXVI
responsible for the line in the soft state (García et al., 2013). Indeed, the
significantly higher thermal X-ray flux in the Fe K$\alpha$ complex energy
range during the soft state would lead to a higher ionization.

Rather than an evolution of the emitting region, it is also possible that
narrow emission from neutral Fe was actually present during both states, but
that it did not increase drastically in flux during the soft state and was
therefore not detectable above the thermal-dominated continuum, which was
significantly higher in flux around $6.4$ keV as compared with the hard state.
Indeed, when MAXI J1848–015 was observed by NICER during a second, less
pronounced increase in flux, Miller et al. (2021) not only reported that the
spectrum was described well by a blackbody with temperature $kT=1.0$ keV,
indicating that the source had again entered the soft state, but the authors
also reported both the detection of a prominent, narrow emission line at $6.7$
keV with flux $K=1.5\times 10^{-5}\,\mathrm{photon\,cm^{-2}\,s^{-1}}$, as well
as a tentative detection of a weaker line at $6.4$ keV.

In order to test whether the lower-energy line could have been present but
undetected during the NuSTAR observation of the soft state, we added a second
Gaussian component to the soft state in our joint spectral model. We froze the
centroid at $\mu=6.4$ keV and the width at $\sigma=10^{-5}$ keV. We allowed
the flux of this component to vary, then we calculated the $99\%$ confidence
upper limit as defined by a change in fit statistic of $\Delta W=6.63$. The
resulting upper limit was $K<7.7\times
10^{-5}\,\mathrm{photon\,cm^{-2}\,s^{-1}}$. In other words, we cannot rule out
the possibility that neutral Fe emission was present in the soft state at a
similar flux level to that observed in the hard state.

One alternative scenario to that of differing ionization is an ionized
outflow. Given that we do not observe clear absorption features which might
indicate disk winds, such an outflow may instead take the form of a jet
launched during the short outburst observed by MAXI. In this case, the narrow
emission lines may originate from fast-moving, ionized blobs of plasma on
opposite sides of the accretor along the jet axis. One would then expect to
see a pair of components, one of which represents the blue-shifted jet
component moving towards the observer, and the second of which originates from
the red-shifted jet component moving away from the observer. Due to
relativistic beaming, the blue-shifted component would have a higher observed
flux than that of the red-shifted component. Additionally, depending on the
orientation of the system one may expect a delay between the appearance of the
blue component and that of the red component due to the difference in light-
travel time from each of the emitting blobs. Migliari et al. (2002) observed a
pair of Fe lines during Chandra observations of SS 433, which they were able
to spatially associate with extended jet emission. They determined that the Fe
line emitting regions were located at a distance of $>10^{17}$ cm from the
central accretor. For a source with low or moderate inclination, this would
result in a light-travel time between the two lobes of $30$–$40$ days.

Indeed, we have shown that the $6.8$ keV line had a higher flux than, and was
observed prior to, the $6.3$ keV line. If the two lines originated from
regions with similar ionization states, and the difference in energy is solely
due to blue- and red-shifting, then we may calculate the velocity of the
narrow line emitting regions:

$\frac{E_{\mathrm{obs}}}{E_{\mathrm{rest}}}=\frac{1}{\gamma\left(1-\beta\cos{\theta}\right)}$
(1)

where $E_{\mathrm{obs}}$ is the energy of the line in the frame of the
observer, $E_{\mathrm{rest}}$ is the energy of the line in the rest frame of
the emitting region, $\beta$ is the ratio of the velocity of the emitting
region to the speed of light, $\gamma$ is the Lorentz factor, and $\theta$ is
the angle at which the emitter is moving with respect to the line of sight. If
we assume that the velocities of the red and blue components are equal in
magnitude, the result is $\beta\cos{\theta}\approx 0.038$. Given that we have
measured a moderate inclination via spectral analysis, we arrive at a
deprojected velocity of $\beta\approx 0.043$ and a rest frame energy of
$E_{\mathrm{rest}}\approx 6.55$ keV, which corresponds to Fe XXII–XXIII.

Assuming a delay of about a week in the appearance of the red-shifted line, we
arrive at a distance of $\sim 10^{16}$ cm between the central accretor and the
narrow line emitting regions. This distance is difficult to square with a
velocity of $0.04c$ in the case that the putative jets were launched during
the initial outburst of MAXI J1848–015, but as we have shown, the $6.3$ keV
line may have gone undetected early in the outburst. While the evidence we
have presented may be consistent with emission from an outflow, we are unable
to meaningfully distinguish this case with the simpler case of different
ionization states. The jet model may be probed by future observations of the
source by observatories, such as Chandra, with high spatial resolution and
high spectral resolution in the Fe K$\alpha$ complex.

##  5 Summary and Conclusions

We have presented MAXI and NuSTAR observations of the low-luminosity transient
MAXI J1848–015, residing in the GC01 cluster. The source was observed twice by
NuSTAR, which was uniquely able to perform observations of the source in
outburst due to low angular separation from the Sun. Spectral and timing
analyses of the two NuSTAR observations demonstrated a clear change in states
from a high soft state to a low hard state. We presented the following
results:

  * •

MAXI observed a short period of brightening with duration $\sim 5$ days, which
then underwent a power law decay for several tens of days.

  * •

In the bright state the source reached a luminosity of only $\sim
10^{36}\,\mathrm{erg\,cm^{-2}\,s^{-1}}$, corresponding to an Eddington
fraction $<0.5\%$.

  * •

NuSTAR spectra revealed relativistic disk reflection features. Analysis of
these features showed:

    * –

Reflection of thermal emission in the soft state, representing evidence for
returning radiation.

    * –

An accretor with nearly maximal spin.

    * –

An increase in the inner radius of the accretion disk, providing evidence for
moderate disk truncation in the low hard state.

    * –

Narrow Fe emission components which may differ in energy due to differences in
ionization or due to Doppler shifts in an outflow.

  * •

Timing analysis of NuSTAR data revealed clear red noise in the hard state. We
did not find evidence for features such as QPOs or pulsations, and the
continuum noise in both states was too low for us to constrain.

Due to the high spin measurement as well as other features such as an
anomalously low quiescent luminosity and spectral shapes that resemble those
of black hole X-ray binaries, we favor the conclusion that the source is an
accreting black hole.

However, the low luminosity of the source is difficult to explain at the same
time as evidence for a hot disk which extends very close to the central
accretor. We therefore discussed scenarios such as high disk inclination or
scattering of emission from the outer disk in order to explain this apparent
inconsistency. Further observations of the source during future outbursts –
particularly those observations which can provide measurements of the binary
inclination – will help to elucidate the nature of this intriguing X-ray
binary.

This work was partially supported under NASA contract No. NNG08FD60C and made
use of data from the NuSTAR mission, a project led by the California Institute
of Technology, managed by the Jet Propulsion Laboratory, and funded by the
National Aeronautics and Space Administration. We thank the NuSTAR Operations,
Software, and Calibration teams for support with the execution and analysis of
these observations. This research has made use of the NuSTAR Data Analysis
Software (NuSTARDAS), jointly developed by the ASI Science Data Center (ASDC,
Italy) and the California Institute of Technology (USA). R.M.L. acknowledges
the support of NASA through Hubble Fellowship Program grant HST-HF2-51440.001.
J.H. acknowledges support from an appointment to the NASA Postdoctoral Program
at the Goddard Space Flight Center, administered by the Universities Space
Research Association under contract with NASA. A.J. would like to acknowledge
support from Chandra X-ray Observatory Center’s grant GO0-21067X. This work
also made use of MAXI data provided by RIKEN, JAXA and the MAXI team. Part of
this work was financially supported by Grants-in-Aid for Scientific Research
21K03620 (H.N.), 17H06362 (H.N.), and 19K14762 (M.S.) from the Ministry of
Education, Culture, Sports, Science and Technology (MEXT) of Japan. Finally,
we would like to thank the anonymous reviewer whose comments and suggestions
significantly improved the quality of this work.

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##  Appendix A Breaking the Spectral fit degeneracy

Fitting the spectra with their respective best fit models (described in
Section 3.1) individually, rather than performing a joint fit, resulted in
significant degeneracies between a number of parameters. In Figure A.1 we show
the resulting distributions for those parameters which demonstrate this
degeneracy. In particular, although the spin is consistent with values above
$a=0.7$, it is not particularly well-constrained.

In the soft state, the spin and the inclination show a clear dependence on one
another, as do the spin and the inner radius. The latter degeneracy is due to
the proximity of the inner radius with the inner-most stable circular orbit,
the physical value of which depends directly on the spin of the central
accretor. The strength of reflection, parametrized by the reflection fraction,
$f_{\mathrm{refl}}$, also shows a clear correlation with a number of
parameters, including the absorption column density, the spin, the
inclination, and the inner disk radius. In the hard state, on the other hand,
the spin appears to be controlled mainly by the iron abundance,
$A_{\mathrm{Fe}}$, the absorption column density, the height of the lamppost,
and the inner disk radius, and it shows less dependence on the inclination of
the inner disk. In the soft state, the iron abundance consistently tended
towards the lower limit of the model,
$A_{\mathrm{Fe}}=0.5\,A_{\mathrm{Fe,\odot}}$, so we froze the parameter at
this value.

Figure A.1: Distributions of selected parameters resulting from MCMC analysis
of each spectrum individually, without joint fitting. The dashed lines shown
in the one-dimensional histograms represent, from left to right, the $5\%$,
$50\%$, and $95\%$ quantiles, while the contours shown in the two-dimensional
histograms represent confidence regions of increasing sigma. Top: soft state
parameters. Bottom: hard state parameters.

We also show the parameter distributions for the joint fits in Figure A.2 in
order to demonstrate the superior constraints we were able to achieve via this
method. Importantly, the spin and the inner disk inclination were constrained
very well compared to the individual fits. A few distinct correlations remain,
with the spin depending on the inner disk radius of the soft state and the
lamppost height during the hard state, and the inclination being controlled by
the ionization of the disk in the hard state. Both values also show a
noticeable dependence on the absorption column density. Notably, using this
joint fitting method, we obtained a well-constrained distribution for the iron
abundance, which we were not able to achieve via the individual fits.

Figure A.2: Distributions of selected parameters resulting from MCMC analysis
of the NuSTAR spectra with joint fitting where the parameters $a$, $i$, and
$A_{\mathrm{Fe}}$ were tied between the soft and hard states. The dashed lines
shown in the one-dimensional histograms represent, from left to right, the
$5\%$, $50\%$, and $95\%$ quantiles, while the contours shown in the two-
dimensional histograms represent confidence regions of increasing sigma.