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# Centaurus A: Exploring the Nature of the Hard X-Ray/Soft Gamma-Ray Emission with INTEGRAL

James Rodi, E. Jourdain, M. Molina, J. P. Roques

► To cite this version:

James Rodi, E. Jourdain, M. Molina, J. P. Roques. Centaurus A: Exploring the Nature of the Hard X-Ray/Soft Gamma-Ray Emission with INTEGRAL. The Astrophysical Journal, 2023, 957, 10.3847/1538-4357/acfc23. insu-04473137

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# Centaurus A: Exploring the Nature of the Hard X-Ray/Soft Gamma-Ray Emission with INTEGRAL

James Rodi<fnref n="1" />, E. Jourdain<fnref n="2" />,<fnref n="3" />, M. Molina<fnref n="4" />, and J. P. Roques<fnref n="2" />,<fnref n="3" />

Received 2023 June 6; revised 2023 September 19; accepted 2023 September 19; published 2023 October 27

## Abstract

The question of the origin of the hard X-ray/soft gamma-ray emission in Centaurus A (Cen A) persists despite decades of observations. Results from X-ray instruments suggest a jet origin since the implied electron temperature ($kT_e$) would cause runaway pair production in the corona. In contrast, instruments sensitive to soft gamma rays report electron temperatures indicating that a coronal origin may be possible. In this context, we analyzed archival INTEGRAL/IBIS-ISGRI and SPI data and observations from a 2022 Cen A monitoring program. Our analysis did not find any spectral variability. Thus we combined all observations for long-term average spectra, which were fit with a NuSTAR observation to study the 3.5 keV–2.2 MeV spectrum. Spectral fits using a CompTT model found $kT_e \sim 550$ keV, near runaway pair production. The spectrum was also well described by a log-parabola to model synchrotron self-Compton emission from the jet. Additionally, a spectral fit with the 12 yr catalog Fermi/LAT spectrum using a log-parabola can explain the data up to $\sim 3$ GeV. Above $\sim 3$ GeV, a power-law excess is present, which has been previously reported in LAT/H.E.S.S. analysis. However, including a coronal spectral component can also describe the data well. In this scenario, the hard X-rays/soft gamma rays are due the corona and the MeV to GeV emission is due to the jet.

Unified Astronomy Thesaurus concepts: Active galactic nuclei (16); Gamma-rays (637)

## 1. Introduction

As one of the brightest radio-loud active galactic nuclei (AGNs) in the hard X-ray sky, Centaurus A (Cen A, $z=0.001826$) has been observed by numerous missions since its first detection in 1969 (Bowyer et al. 1970). Results have shown that the spectral shape does not vary with flux (Jourdain et al. 1993; Rothschild et al. 2006, 2011; Beckmann et al. 2011; Burke et al. 2014). Consequently, one would expect reported spectral parameters for Cen A to be similar across time and instruments. Yet that has not been the case as there has been a lack of consistency in the values, which has made interpreting the origin of the hard X-ray/soft gamma-ray emission difficult.

The presence of spectral curvature and where it occurs have implications for the emission process. Often, the hard X-ray continuum in AGNs is interpreted as thermal inverse Comptonization of UV seed photons from the accretion disk (Haardt & Maraschi 1993; Merloni & Fabian 2003). The spectra typically have emission up to a few hundred keV (Molina et al. 2013), and the spectral cutoff energy is related to the temperature of electrons in the corona. In the corona, photon-photon collisions can create electron-positron pairs when the sum of the photon energies is above $\sim 1$ MeV (Svensson 1984; Stern et al. 1995; Fabian et al. 2015). Thus if the electron temperature is too high, the production of electron-positron pairs can become a runaway process that reduces the temperature of the corona. Additional pairs form and gain energy from the corona, which lowers the amount of energy per particle (Fabian et al. 2015, 2017).

The maximum temperature is related to the geometry of the source, which is typically given by the compactness parameter, $l$, which is the ratio of the source luminosity to its size (Guilbert et al. 1983). The limits on electron temperature range from $\sim 500$ keV in the case of very low compactness to $\sim 70$ keV in the case of very high compactness (Fabian et al. 2017). For Cen A, $l \sim 10$ (Fabian et al. 2017), suggesting a maximum temperature of the corona of a few hundred keV.

Such disagreements over the curvature in Cen A can be seen when comparing results from the past $\sim 30$ years with the main disagreement over the location of spectral curvature. Multiple analyses have found spectra well fit with a power-law model with similar spectral indices. GRANAT/SIGMA observations in 1990–1991 found a power-law spectrum with a slope of $1.9 \pm 0.3$ (35–200 keV) with only a weak indication of a spectral break (Jourdain et al. 1993). Later observations from RXTE and INTEGRAL in the 3–240 keV energy range found a power-law spectrum with a slope of $1.83 \pm 0.01$ and no clear indication of a spectral break (Rothschild et al. 2006). Also, analysis by Rothschild et al. (2011) using approximately 12 years of RXTE data supported earlier findings with a slope of $1.822 \pm 0.004$ and no evidence of curvature, constraining the cutoff to $> 2$ MeV. More recently, XMM-Newton and NuSTAR observations found an index of $1.81$ with no need for a cutoff $< 1$ MeV (Fürst et al. 2016). These high-energy spectral cutoff energies are consistent with the hard X-rays as part of the inverse Compton hump of the spectral energy distribution (SED), which Chiaberge et al. (2001) interpreted as synchrotron self-Compton (SSC) emission. However, they do find the data are consistent with a thermal Comptonization model with an electron temperature of $\sim 100–300$ keV. All of these proposed spectral turnovers in the above results are well outside the energy ranges of the considered spectra and thus are not able to constrain the spectral break.

<figure><img src="image_2.png" /></figure>

Original content from this work may be used under the terms of the [Creative Commons Attribution 4.0 licence](https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

<footnote n="1">¹INAF—Istituto di Astrofisica e Planetologia Spaziali, via Fosso del Cavaliere 100; I-00133 Roma, Italy</footnote>

<footnote n="2">²Université de Toulouse, UPS-OMP, IRAP, Toulouse, France</footnote>

<footnote n="3">³CNRS, IRAP, 9 Av. Colonel Roche, BP 44346, F-31028 Toulouse cedex 4, France</footnote>

<footnote n="4">⁴Istituto di Astrofisica Spaziale e Fisica Cosmica di Milano, Milan, Italy</footnote>
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CrossMark

# Centaurus A: Exploring the Nature of the Hard X-Ray/Soft Gamma-Ray Emission with INTEGRAL

James Rodi<fnref n="1" />, E. Jourdain<fnref n="2" />,<fnref n="3" />, M. Molina<fnref n="4" />, and J. P. Roques<fnref n="2" />,<fnref n="3" />

Received 2023 June 6; revised 2023 September 19; accepted 2023 September 19; published 2023 October 27

## Abstract

The question of the origin of the hard X-ray/soft gamma-ray emission in Centaurus A (Cen A) persists despite decades of observations. Results from X-ray instruments suggest a jet origin since the implied electron temperature ($kT_e$) would cause runaway pair production in the corona. In contrast, instruments sensitive to soft gamma rays report electron temperatures indicating that a coronal origin may be possible. In this context, we analyzed archival INTEGRAL/IBIS-ISGRI and SPI data and observations from a 2022 Cen A monitoring program. Our analysis did not find any spectral variability. Thus we combined all observations for long-term average spectra, which were fit with a NuSTAR observation to study the 3.5 keV–2.2 MeV spectrum. Spectral fits using a CompTT model found $kT_e \sim 550$ keV, near runaway pair production. The spectrum was also well described by a log-parabola to model synchrotron self-Compton emission from the jet. Additionally, a spectral fit with the 12 yr catalog Fermi/LAT spectrum using a log-parabola can explain the data up to $\sim 3$ GeV. Above $\sim 3$ GeV, a power-law excess is present, which has been previously reported in LAT/H.E.S.S. analysis. However, including a coronal spectral component can also describe the data well. In this scenario, the hard X-rays/soft gamma rays are due the corona and the MeV to GeV emission is due to the jet.

Unified Astronomy Thesaurus concepts: Active galactic nuclei (16); Gamma-rays (637)

## 1. Introduction

As one of the brightest radio-loud active galactic nuclei (AGNs) in the hard X-ray sky, Centaurus A (Cen A, $z=0.001826$) has been observed by numerous missions since its first detection in 1969 (Bowyer et al. 1970). Results have shown that the spectral shape does not vary with flux (Jourdain et al. 1993; Rothschild et al. 2006, 2011; Beckmann et al. 2011; Burke et al. 2014). Consequently, one would expect reported spectral parameters for Cen A to be similar across time and instruments. Yet that has not been the case as there has been a lack of consistency in the values, which has made interpreting the origin of the hard X-ray/soft gamma-ray emission difficult.

The presence of spectral curvature and where it occurs have implications for the emission process. Often, the hard X-ray continuum in AGNs is interpreted as thermal inverse Comptonization of UV seed photons from the accretion disk (Haardt & Maraschi 1993; Merloni & Fabian 2003). The spectra typically have emission up to a few hundred keV (Molina et al. 2013), and the spectral cutoff energy is related to the temperature of electrons in the corona. In the corona, photon-photon collisions can create electron-positron pairs when the sum of the photon energies is above $\sim 1$ MeV (Svensson 1984; Stern et al. 1995; Fabian et al. 2015). Thus if the electron temperature is too high, the production of electron-positron pairs can become a runaway process that reduces the temperature of the corona. Additional pairs form and gain energy from the corona, which lowers the amount of energy per particle (Fabian et al. 2015, 2017).

The maximum temperature is related to the geometry of the source, which is typically given by the compactness parameter, $l$, which is the ratio of the source luminosity to its size (Guilbert et al. 1983). The limits on electron temperature range from $\sim 500$ keV in the case of very low compactness to $\sim 70$ keV in the case of very high compactness (Fabian et al. 2017). For Cen A, $l \sim 10$ (Fabian et al. 2017), suggesting a maximum temperature of the corona of a few hundred keV.

Such disagreements over the curvature in Cen A can be seen when comparing results from the past $\sim 30$ years with the main disagreement over the location of spectral curvature. Multiple analyses have found spectra well fit with a power-law model with similar spectral indices. GRANAT/SIGMA observations in 1990–1991 found a power-law spectrum with a slope of $1.9 \pm 0.3$ (35–200 keV) with only a weak indication of a spectral break (Jourdain et al. 1993). Later observations from RXTE and INTEGRAL in the 3–240 keV energy range found a power-law spectrum with a slope of $1.83 \pm 0.01$ and no clear indication of a spectral break (Rothschild et al. 2006). Also, analysis by Rothschild et al. (2011) using approximately 12 years of RXTE data supported earlier findings with a slope of $1.822 \pm 0.004$ and no evidence of curvature, constraining the cutoff to $> 2$ MeV. More recently, XMM-Newton and NuSTAR observations found an index of $1.81$ with no need for a cutoff $< 1$ MeV (Fürst et al. 2016). These high-energy spectral cutoff energies are consistent with the hard X-rays as part of the inverse Compton hump of the spectral energy distribution (SED), which Chiaberge et al. (2001) interpreted as synchrotron self-Compton (SSC) emission. However, they do find the data are consistent with a thermal Comptonization model with an electron temperature of $\sim 100–300$ keV. All of these proposed spectral turnovers in the above results are well outside the energy ranges of the considered spectra and thus are not able to constrain the spectral break.

<figure><img src="image_4.png" /></figure>

Original content from this work may be used under the terms of the [Creative Commons Attribution 4.0 licence](https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

<footnote n="1">¹INAF—Istituto di Astrofisica e Planetologia Spaziali, via Fosso del Cavaliere 100; I-00133 Roma, Italy</footnote>

<footnote n="2">²Université de Toulouse, UPS-OMP, IRAP, Toulouse, France</footnote>

<footnote n="3">³CNRS, IRAP, 9 Av. Colonel Roche, BP 44346, F-31028 Toulouse cedex 4, France</footnote>

<footnote n="4">⁴Istituto di Astrofisica Spaziale e Fisica Cosmica di Milano, Milan, Italy</footnote>
Unfortunately, observations at soft gamma-ray energies have not fared any better at determining where the spectral break is. Joint spectral fits from the OSSE and COMPTEL instruments (50 keV–30 MeV) found a spectral break at ~150 keV, a low-energy power-law slope of 1.74, and a high-energy power-law slope of 2.0 (Steinle et al. 1998). INTEGRAL observations covering 3–1000 keV analyzed by Beckmann et al. (2011) can be fit with a cutoff power-law with a photon index of ~1.7 and $E_c \sim 400$ keV and by excluding cutoff energies below 300 keV and above 700 keV at $3\sigma$, so this is significantly different from the spectral cutoff above 1–2 MeV predicted from lower-energy instruments. Analysis of INTEGRAL/SPI with Chandra in the 2–500 keV energy range also found spectral curvature. Their analysis, which included a reflection component, found a cutoff energy above 700 keV with a confidence of >95% (Burke et al. 2014).

Skibo et al. (1994) proposed an interesting alternative where the emission is the result of beamed photons Compton-scattered into our line of sight. Using OSSE data in the 50–1000 keV range, they found a photon index of $1.68 \pm 0.03$ and an angle of ~61° between the jet and our line of sight, assuming the material scattering the beamed emission is nonrelativistic.

In this work, we report on additional INTEGRAL observations of Cen A spanning nearly 20 years, which allow us to explore the long-term temporal variability and study the soft gamma-ray spectrum to investigate the possible high-energy cutoff, which provides key information on the emission process at these energies.

## 2. Instruments and Observations

### 2.1. INTEGRAL

The INTEGRAL satellite was launched in 2002 October from Baikonur, Kazakhstan, with an eccentric orbit (Jensen et al. 2003) that has a period of ~2.5–3 days. We analyzed data from both the Spectrometer on board INTEGRAL (SPI, Vedrenne et al. 2003) and IBIS/ISGRI (Imager on board INTEGRAL/INTEGRAL Soft Gamma-Ray Imager; Ubertini et al. 2003). SPI spans the 20 keV–8 MeV energy range with an energy resolution of 2–8 keV (Roques et al. 2003), and ISGRI covers energies from 15 to 1000 keV.

The SPI data were analyzed using the SPI Data Analysis Interface (SPIDAI)<fnref n="5" /> to generate light curves and spectra, which consist of 39 channels over the 20 keV–2.2 MeV range. The data above 400 keV were corrected for pulse shape discriminator efficiency following the method outlined in Roques & Jourdain (2019). The ISGRI data were analyzed with the Offline Scientific Analysis 11.2 (OSA 11.2)<fnref n="6" /> to produce light curves and spectra, which span the 30–630 keV range in 43 channels with a 1% systematic error included.

The observations used in this work span from revolution 48 to 2590 (MJD 52,705–59,948 or 2003 March 7 to 2023 January 4) when the source was within 10° of the INTEGRAL pointing direction and incorporate archival data and data from our current observing campaign during INTEGRAL’s AO-19 observation cycle. Each observation or science window lasts ~1800–3600 s. Observations contaminated by solar activity and Earth’s radiation belt have been removed. Thus the total exposure times are 5.3 Ms for SPI and 4.6 Ms for ISGRI.

### 2.2. NuSTAR

NuSTAR data (from both focal plane detectors, FPMA and FPMB) were reduced using `nustardas_04May21_v2.1.1` and `CALDB` version 20220118. In this work, we reduced observation 60001081002, taken on 2013 August 6, with a cleaned exposure of ~51.3 ks. Spectral extraction and the subsequent production of response and ancillary files were performed using the `nuproducts` task with an extraction radius of ~136" to maximize the signal-to-noise ratio. Background spectra were extracted from circular regions of 70" radius in source-free areas of the detectors.

## 3. Results

### 3.1. Temporal Variability

To study the temporal behavior of Cen A, we constructed the SPI and ISGRI light curves on an INTEGRAL revolution timescale (~2.5–3 days). Figure 1 shows the temporal variability in the 20–40, 40–60, 60–100, and 100–200 keV energy bands. The SPI data are shown as black diamonds, and the ISGRI data are shown as red triangles. The time of the NuSTAR observation is denoted by a vertical green line. The SPI and ISGRI instruments show similar temporal evolutions with significantly higher fluxes above the mean between MJD 54,500 and 55,000, which are present in the data up to the 100–200 keV range. The source is significantly detected up to the 200–400 keV band in SPI at $11.3\sigma$ and in the 200–450 keV band in ISGRI at $10.0\sigma$ during the mission.

### 3.2. Spectral Variability

Numerous authors have reported that Cen A’s spectral shape does not change with flux (Jourdain et al. 1993; Rothschild et al. 2006, 2011; Beckmann et al. 2011; Burke et al. 2014). However, recent results from Swift/BAT reported spectral softening when the flux increased after 2013 (Rani et al. 2022). Therefore, we searched for spectral variability in the INTEGRAL data by fitting the SPI 25–70 keV and ISGRI 34–68 keV spectra independently to a power-law model. To reduce uncertainties in the fit parameters, we grouped observations close in time to generate average spectra. Table 1 lists the revolution groupings. Isolated revolutions were excluded from the comparison.

Figure 2 shows the photon index versus 50 keV flux for each grouping in SPI (top) and ISGRI (bottom). The best-fit photon index values from all the groups were fit to a constant value. The best-fit average values are $\Gamma = 1.73 \pm 0.04$ for SPI and $\Gamma = 1.83 \pm 0.02$ for ISGRI, compared to $1.75 \pm 0.04$ and $1.80 \pm 0.01$ for the long-term average spectra of SPI and ISGRI, respectively. The errors are at the $1\sigma$ level (as are subsequent errors). The reduced $\chi^2/\nu = 0.509/13$ for SPI and 1.08/13 for ISGRI. Therefore, the photon indices are consistent with a constant value, with the best-fit indices for both instruments presenting a marginal agreement.

We note that the last observing period (rev. 2581–2590) showed relatively soft spectra with photon indices of roughly 2.1 (SPI) and 2.0 (ISGRI), though the errors are large. During this period, the source was at its lowest flux level observed by INTEGRAL, which does not confirm the behavior reported by Rani et al. (2022).

<footnote n="5">⁵ Publicly available interface developed at IRAP to analyze SPI data. Available by contacting: spidai@irap.omp.eu. See description in Burke et al. (2014).</footnote>

<footnote n="6">⁶ https://www.isdc.unige.ch/integral/analysis#Software</footnote>
Unfortunately, observations at soft gamma-ray energies have not fared any better at determining where the spectral break is. Joint spectral fits from the OSSE and COMPTEL instruments (50 keV–30 MeV) found a spectral break at ~150 keV, a low-energy power-law slope of 1.74, and a high-energy power-law slope of 2.0 (Steinle et al. 1998). INTEGRAL observations covering 3–1000 keV analyzed by Beckmann et al. (2011) can be fit with a cutoff power-law with a photon index of ~1.7 and $E_c \sim 400$ keV and by excluding cutoff energies below 300 keV and above 700 keV at $3\sigma$, so this is significantly different from the spectral cutoff above 1–2 MeV predicted from lower-energy instruments. Analysis of INTEGRAL/SPI with Chandra in the 2–500 keV energy range also found spectral curvature. Their analysis, which included a reflection component, found a cutoff energy above 700 keV with a confidence of >95% (Burke et al. 2014).

Skibo et al. (1994) proposed an interesting alternative where the emission is the result of beamed photons Compton-scattered into our line of sight. Using OSSE data in the 50–1000 keV range, they found a photon index of $1.68 \pm 0.03$ and an angle of ~61° between the jet and our line of sight, assuming the material scattering the beamed emission is nonrelativistic.

In this work, we report on additional INTEGRAL observations of Cen A spanning nearly 20 years, which allow us to explore the long-term temporal variability and study the soft gamma-ray spectrum to investigate the possible high-energy cutoff, which provides key information on the emission process at these energies.

# 2. Instruments and Observations

## 2.1. INTEGRAL

The INTEGRAL satellite was launched in 2002 October from Baikonur, Kazakhstan, with an eccentric orbit (Jensen et al. 2003) that has a period of ~2.5–3 days. We analyzed data from both the Spectrometer on board INTEGRAL (SPI, Vedrenne et al. 2003) and IBIS/ISGRI (Imager on board INTEGRAL/INTEGRAL Soft Gamma-Ray Imager; Ubertini et al. 2003). SPI spans the 20 keV–8 MeV energy range with an energy resolution of 2–8 keV (Roques et al. 2003), and ISGRI covers energies from 15 to 1000 keV.

The SPI data were analyzed using the SPI Data Analysis Interface (SPIDAI)<fnref n="5" /> to generate light curves and spectra, which consist of 39 channels over the 20 keV–2.2 MeV range. The data above 400 keV were corrected for pulse shape discriminator efficiency following the method outlined in Roques & Jourdain (2019). The ISGRI data were analyzed with the Offline Scientific Analysis 11.2 (OSA 11.2)<fnref n="6" /> to produce light curves and spectra, which span the 30–630 keV range in 43 channels with a 1% systematic error included.

The observations used in this work span from revolution 48 to 2590 (MJD 52,705–59,948 or 2003 March 7 to 2023 January 4) when the source was within 10° of the INTEGRAL pointing direction and incorporate archival data and data from our current observing campaign during INTEGRAL’s AO-19 observation cycle. Each observation or science window lasts ~1800–3600 s. Observations contaminated by solar activity and Earth’s radiation belt have been removed. Thus the total exposure times are 5.3 Ms for SPI and 4.6 Ms for ISGRI.

## 2.2. NuSTAR

NuSTAR data (from both focal plane detectors, FPMA and FPMB) were reduced using `nustardas_04May21_v2.1.1` and `CALDB` version 20220118. In this work, we reduced observation 60001081002, taken on 2013 August 6, with a cleaned exposure of ~51.3 ks. Spectral extraction and the subsequent production of response and ancillary files were performed using the `nuproducts` task with an extraction radius of ~136" to maximize the signal-to-noise ratio. Background spectra were extracted from circular regions of 70" radius in source-free areas of the detectors.

# 3. Results

## 3.1. Temporal Variability

To study the temporal behavior of Cen A, we constructed the SPI and ISGRI light curves on an INTEGRAL revolution timescale (~2.5–3 days). Figure 1 shows the temporal variability in the 20–40, 40–60, 60–100, and 100–200 keV energy bands. The SPI data are shown as black diamonds, and the ISGRI data are shown as red triangles. The time of the NuSTAR observation is denoted by a vertical green line. The SPI and ISGRI instruments show similar temporal evolutions with significantly higher fluxes above the mean between MJD 54,500 and 55,000, which are present in the data up to the 100–200 keV range. The source is significantly detected up to the 200–400 keV band in SPI at $11.3\sigma$ and in the 200–450 keV band in ISGRI at $10.0\sigma$ during the mission.

## 3.2. Spectral Variability

Numerous authors have reported that Cen A’s spectral shape does not change with flux (Jourdain et al. 1993; Rothschild et al. 2006, 2011; Beckmann et al. 2011; Burke et al. 2014). However, recent results from Swift/BAT reported spectral softening when the flux increased after 2013 (Rani et al. 2022). Therefore, we searched for spectral variability in the INTEGRAL data by fitting the SPI 25–70 keV and ISGRI 34–68 keV spectra independently to a power-law model. To reduce uncertainties in the fit parameters, we grouped observations close in time to generate average spectra. Table 1 lists the revolution groupings. Isolated revolutions were excluded from the comparison.

Figure 2 shows the photon index versus 50 keV flux for each grouping in SPI (top) and ISGRI (bottom). The best-fit photon index values from all the groups were fit to a constant value. The best-fit average values are $\Gamma = 1.73 \pm 0.04$ for SPI and $\Gamma = 1.83 \pm 0.02$ for ISGRI, compared to $1.75 \pm 0.04$ and $1.80 \pm 0.01$ for the long-term average spectra of SPI and ISGRI, respectively. The errors are at the $1\sigma$ level (as are subsequent errors). The reduced $\chi^2/\nu = 0.509/13$ for SPI and 1.08/13 for ISGRI. Therefore, the photon indices are consistent with a constant value, with the best-fit indices for both instruments presenting a marginal agreement.

We note that the last observing period (rev. 2581–2590) showed relatively soft spectra with photon indices of roughly 2.1 (SPI) and 2.0 (ISGRI), though the errors are large. During this period, the source was at its lowest flux level observed by INTEGRAL, which does not confirm the behavior reported by Rani et al. (2022).

<footnote n="5">⁵ Publicly available interface developed at IRAP to analyze SPI data. Available by contacting: spidai@irap.omp.eu. See description in Burke et al. (2014).</footnote>

<footnote n="6">⁶ https://www.isdc.unige.ch/integral/analysis#Software</footnote>
<figure><img src="image_3.png" /><figcaption>**Figure 1.** Cen A SPI (black diamonds) and ISGRI (red triangles) long-term light curves on an INTEGRAL revolution timescale. The date of the NuSTAR observation is shown with a vertical green line. The solid black line denotes a flux of 0 mCrab. The dashed black line denotes the mean flux.</figcaption></figure>

<table><caption>**Table 1**
Spectral Groupings</caption><thead><tr><th colspan="2">INTEGRAL Revolutions</th></tr></thead><tbody><tr><td>48–49</td><td>1309–1311</td></tr><tr><td>149–163</td><td>1370–1386</td></tr><tr><td>514–523</td><td>1437–1439</td></tr><tr><td>574–588</td><td>2313–2315</td></tr><tr><td>648–651</td><td>2457–2470</td></tr><tr><td>702–705</td><td>2517–2539</td></tr><tr><td>764–768</td><td>2581–2590</td></tr></tbody></table>

### 3.3. Average Spectrum

#### 3.3.1. Phenomenological Models

Since no significant spectral variability was found, the groupings were combined for long-term average spectra to study the high-energy spectrum of Cen A. Also, we included NuSTAR observations, which extend to lower energies, that can test the presence of an Fe line and reflection. As shown in previous works (Burke et al. 2014), a reflection component in

the Cen A spectrum can result in larger high-energy cutoff energy.

The NuSTAR data were fit first with an absorbed power-law model (phabs*phabs*(zpowerlw+zgauss)) with absorption components for both the galactic absorption (fixed to $2.36 \times 10^{20} \text{ cm}^{-2}$; HI4PI Collaboration et al. 2016) and an intrinsic absorption. The best parameters from this fit are $\Gamma = 1.798 \pm 0.002$ with $n_H = (8.73 \pm 0.07) \times 10^{22} \text{ cm}^{-2}$. The Fe line energy is $6.36 \pm 0.01$ keV with a width of $0.08 \pm 0.2$ keV and reduced $\chi^2 = 2581.36/2533 = 1.02$. The calculated equivalent width from XSPEC is ~32 eV. The best-fit continuum parameters are listed in Table 2. In subsequent fits, the Fe line energy and width were fixed to these values.

To investigate the presence of a spectral cutoff, we next fit the NuSTAR spectra to a zcutoffpl model. The model better describes the data with a reduced $\chi^2 = 2469.56/2534 = 0.97$ with $\Delta\chi^2 = 111.8$. The intrinsic absorption was $(8.0 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$. The fit parameters are given in Table 2.

Next we applied the zpowerlw model to the SPI and ISGRI data independently. The best-fit photon indices are in perfect
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Cen A SPI (black diamonds) and ISGRI (red triangles) long-term light curves on an INTEGRAL revolution timescale. The date of the NuSTAR observation is shown with a vertical green line. The solid black line denotes a flux of 0 mCrab. The dashed black line denotes the mean flux.</figcaption></figure>

<table><caption>**Table 1**
Spectral Groupings</caption><thead><tr><th colspan="2">INTEGRAL Revolutions</th></tr></thead><tbody><tr><td>48–49</td><td>1309–1311</td></tr><tr><td>149–163</td><td>1370–1386</td></tr><tr><td>514–523</td><td>1437–1439</td></tr><tr><td>574–588</td><td>2313–2315</td></tr><tr><td>648–651</td><td>2457–2470</td></tr><tr><td>702–705</td><td>2517–2539</td></tr><tr><td>764–768</td><td>2581–2590</td></tr></tbody></table>

### 3.3. Average Spectrum

#### 3.3.1. Phenomenological Models

Since no significant spectral variability was found, the groupings were combined for long-term average spectra to study the high-energy spectrum of Cen A. Also, we included NuSTAR observations, which extend to lower energies, that can test the presence of an Fe line and reflection. As shown in previous works (Burke et al. 2014), a reflection component in

the Cen A spectrum can result in larger high-energy cutoff energy.

The NuSTAR data were fit first with an absorbed power-law model (phabs*phabs*(zpowerlw+zgauss)) with absorption components for both the galactic absorption (fixed to $2.36 \times 10^{20} \text{ cm}^{-2}$; HI4PI Collaboration et al. 2016) and an intrinsic absorption. The best parameters from this fit are $\Gamma = 1.798 \pm 0.002$ with $n_H = (8.73 \pm 0.07) \times 10^{22} \text{ cm}^{-2}$. The Fe line energy is $6.36 \pm 0.01$ keV with a width of $0.08 \pm 0.2$ keV and reduced $\chi^2 = 2581.36/2533 = 1.02$. The calculated equivalent width from XSPEC is ~32 eV. The best-fit continuum parameters are listed in Table 2. In subsequent fits, the Fe line energy and width were fixed to these values.

To investigate the presence of a spectral cutoff, we next fit the NuSTAR spectra to a zcutoffpl model. The model better describes the data with a reduced $\chi^2 = 2469.56/2534 = 0.97$ with $\Delta\chi^2 = 111.8$. The intrinsic absorption was $(8.0 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$. The fit parameters are given in Table 2.

Next we applied the zpowerlw model to the SPI and ISGRI data independently. The best-fit photon indices are in perfect
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Plot of photon index vs. 50 keV flux for spectral groups for SPI (top) and ISGRI (bottom). The best-fit photon index for each instrument is shown as a red dashed line.</figcaption></figure>

agreement between the two instruments for the power-law model. However, neither spectrum was well described by the model, which overpredicted the fluxes above ~150 keV. The resulting $\chi^2/\nu$ values were 63.18/34 for SPI and 64.20/43 for ISGRI.

Due to the implied presence of curvature in the spectra, we next fit the data with a cutoff power-law model (z cutoff $\nu$). The $\chi^2/\nu$ values improved to 31.15/33 and 38.66/42 for SPI

and ISGRI, respectively. The best-fit parameters in Table 2 are in agreement between the two instruments. Thus we performed a joint fit with the two instruments. A cross-instrument normalization was added to the model with the SPI normalization fixed. The model was still an acceptable fit to the data with $\chi^2/\nu$ of 77.81/79. The cross-instrument normalization was $0.873 \pm 0.008$.

Subsequently, we performed a joint fit between the NuSTAR, SPI, and ISGRI data covering 3.5–2200 keV. A power-law fit to the data is statistically acceptable with a reduced $\chi^2 = 2795.87/2610 = 1.07$, but it is unsurprisingly a worse fit due to the high-energy cutoffs seen in the three instruments. As expected, including a high-energy cutoff improves the quality of the fit (reduced $\chi^2 = 2625.40/2609 = 1.01$), but with a relatively high cutoff energy of ~650 keV. The cross-normalization values for the NuSTAR spectra were $1.81 \pm 0.02$ for FPMA and $1.80 \pm 0.02$ for FPMB. Subsequent spectral fits result in similar cross-normalization values. These values are large compared to the long-term average SPI spectrum because the NuSTAR observation occurs while Cen A was in a high-flux state.

To investigate the presence of a reflection component, which can result in artificially high cutoff energies (Burke et al. 2014), we used the pexrav continuum model. The best-fit reflection fraction was $2 \times 10^{-7} \pm 1 \times 10^{-2}$. We also tested the presence of reflection with relativistic smearing using a xion* (pexrav+zgauss) model. We assumed a geometry with a central hot sphere and a cold outer disk. The model describes the data well (reduced $\chi^2 = 2503.97/2527 = 0.991$), but most of the fit parameters are unconstrained, including the reflection fraction ($0.0 \pm 0.2$). Thus we consider that no significant reflection is required by the data. Consequently, the reflection fraction was fixed to 0. The spectrum was refit, and the best-fit parameters (Table 2 and subsequent fit parameters; $\chi^2/\nu = 2594.66/2608 = 0.99$) are the same as those of the z cutoff $\nu$ model.

### 3.3.2. Physically Motivated Models

To better understand the emission mechanism(s) in this energy range, we fit the data using more physically motivated models. We fit the data to a CompTT model. As pointed out in Fürst et al. (2016), the seed photon temperature is unknown, thus they fit their data to a range of seed photon temperatures with extremes of 0.05 and 0.5 keV. Therefore, we fit our data to minimum and maximum values to explore the range of electron temperatures. Both fits find comparable values of $kT_e \sim 520$ keV and $\tau \sim 0.03$. The data prefer the lower $kT_0$ (0.05 keV) with $\Delta\chi^2 = 21.64$, though both models acceptably

<table><caption>**Table 2**
Average Spectral Parameters</caption><thead><tr><th rowspan="2">Instrument</th><th colspan="3">zpower1w</th><th colspan="4">z cutoff $\nu$</th></tr><tr><th>n<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>χ<sup>2</sup>/ν</th><th>n<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>E<sub>cut</sub><br>(keV)</th><th>χ<sup>2</sup>/ν</th></tr></thead><tbody><tr><td>NuSTAR<sup>a</sup></td><td>8.73 ± 0.07</td><td>1.798 ± 0.002</td><td>1.02</td><td>8.0 ± 0.1</td><td>1.725 ± 0.007</td><td>246 ± 24</td><td>0.97</td></tr><tr><td>SPI</td><td>...</td><td>1.86 ± 0.02</td><td>1.86</td><td>...</td><td>1.62 ± 0.05</td><td>381 ± 85</td><td>0.94</td></tr><tr><td>ISGRI</td><td>...</td><td>1.851 ± 0.007</td><td>1.49</td><td>...</td><td>1.72 ± 0.03</td><td>517 ± 112</td><td>0.92</td></tr><tr><td>SPI/ISGRI</td><td>...</td><td>1.859 ± 0.007</td><td>1.51</td><td>...</td><td>1.72 ± 0.02</td><td>543 ± 94</td><td>0.98</td></tr><tr><td>NuSTAR/SPI/ISGRI<sup>a</sup></td><td>8.94 ± 0.07</td><td>1.807 ± 0.002</td><td>1.071</td><td>8.37 ± 0.08</td><td>1.767 ± 0.004</td><td>638 ± 54</td><td>1.00</td></tr></tbody></table>

**Note.**

<footnote><sup>a</sup> zgauss model included in fit with fixed parameters to model Fe line (see Section 3.3.1).</footnote>
<figure><img src="image_6.png" /><figcaption>**Figure 2.** Plot of photon index vs. 50 keV flux for spectral groups for SPI (top) and ISGRI (bottom). The best-fit photon index for each instrument is shown as a red dashed line.</figcaption></figure>

agreement between the two instruments for the power-law model. However, neither spectrum was well described by the model, which overpredicted the fluxes above ~150 keV. The resulting $\chi^2/\nu$ values were 63.18/34 for SPI and 64.20/43 for ISGRI.

Due to the implied presence of curvature in the spectra, we next fit the data with a cutoff power-law model (z cutoff $p$1). The $\chi^2/\nu$ values improved to 31.15/33 and 38.66/42 for SPI

and ISGRI, respectively. The best-fit parameters in Table 2 are in agreement between the two instruments. Thus we performed a joint fit with the two instruments. A cross-instrument normalization was added to the model with the SPI normalization fixed. The model was still an acceptable fit to the data with $\chi^2/\nu$ of 77.81/79. The cross-instrument normalization was $0.873 \pm 0.008$.

Subsequently, we performed a joint fit between the NuSTAR, SPI, and ISGRI data covering 3.5–2200 keV. A power-law fit to the data is statistically acceptable with a reduced $\chi^2 = 2795.87/2610 = 1.07$, but it is unsurprisingly a worse fit due to the high-energy cutoffs seen in the three instruments. As expected, including a high-energy cutoff improves the quality of the fit (reduced $\chi^2 = 2625.40/2609 = 1.01$), but with a relatively high cutoff energy of ~650 keV. The cross-normalization values for the NuSTAR spectra were $1.81 \pm 0.02$ for FPMA and $1.80 \pm 0.02$ for FPMB. Subsequent spectral fits result in similar cross-normalization values. These values are large compared to the long-term average SPI spectrum because the NuSTAR observation occurs while Cen A was in a high-flux state.

To investigate the presence of a reflection component, which can result in artificially high cutoff energies (Burke et al. 2014), we used the pexrav continuum model. The best-fit reflection fraction was $2 \times 10^{-7} \pm 1 \times 10^{-2}$. We also tested the presence of reflection with relativistic smearing using a xion* (pexrav+zgauss) model. We assumed a geometry with a central hot sphere and a cold outer disk. The model describes the data well (reduced $\chi^2 = 2503.97/2527 = 0.991$), but most of the fit parameters are unconstrained, including the reflection fraction ($0.0 \pm 0.2$). Thus we consider that no significant reflection is required by the data. Consequently, the reflection fraction was fixed to 0. The spectrum was refit, and the best-fit parameters (Table 2 and subsequent fit parameters; $\chi^2/\nu = 2594.66/2608 = 0.99$) are the same as those of the z cutoff $p$1 model.

### 3.3.2. Physically Motivated Models

To better understand the emission mechanism(s) in this energy range, we fit the data using more physically motivated models. We fit the data to a CompTT model. As pointed out in Fürst et al. (2016), the seed photon temperature is unknown, thus they fit their data to a range of seed photon temperatures with extremes of 0.05 and 0.5 keV. Therefore, we fit our data to minimum and maximum values to explore the range of electron temperatures. Both fits find comparable values of $kT_e \sim 520$ keV and $\tau \sim 0.03$. The data prefer the lower $kT_0$ (0.05 keV) with $\Delta\chi^2 = 21.64$, though both models acceptably

<table><caption>**Table 2**
Average Spectral Parameters</caption><thead><tr><th rowspan="2">Instrument</th><th colspan="3">zpower1w</th><th colspan="4">z cutoff $p$1</th></tr><tr><th>n<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>χ<sup>2</sup>/ν</th><th>n<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>E<sub>cut</sub><br>(keV)</th><th>χ<sup>2</sup>/ν</th></tr></thead><tbody><tr><td>NuSTAR<sup>a</sup></td><td>8.73 ± 0.07</td><td>1.798 ± 0.002</td><td>1.02</td><td>8.0 ± 0.1</td><td>1.725 ± 0.007</td><td>246 ± 24</td><td>0.97</td></tr><tr><td>SPI</td><td>...</td><td>1.86 ± 0.02</td><td>1.86</td><td>...</td><td>1.62 ± 0.05</td><td>381 ± 85</td><td>0.94</td></tr><tr><td>ISGRI</td><td>...</td><td>1.851 ± 0.007</td><td>1.49</td><td>...</td><td>1.72 ± 0.03</td><td>517 ± 112</td><td>0.92</td></tr><tr><td>SPI/ISGRI</td><td>...</td><td>1.859 ± 0.007</td><td>1.51</td><td>...</td><td>1.72 ± 0.02</td><td>543 ± 94</td><td>0.98</td></tr><tr><td>NuSTAR/SPI/ISGRI<sup>a</sup></td><td>8.94 ± 0.07</td><td>1.807 ± 0.002</td><td>1.071</td><td>8.37 ± 0.08</td><td>1.767 ± 0.004</td><td>638 ± 54</td><td>1.00</td></tr></tbody></table>

**Note.**

<footnote><sup>a</sup> zgauss model included in fit with fixed parameters to model Fe line (see Section 3.3.1).</footnote>
<table><caption>**Table 3**
Joint NuSTAR/SPI/ISGRI Fit Spectral Parameters</caption><thead><tr><th colspan="5">CompTT</th><th colspan="4">Log-parabola</th></tr><tr><th>N<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>kT<sub>0</sub><br>(keV)</th><th>kT<sub>e</sub><br>(keV)</th><th>τ</th><th>χ<sup>2</sup>/ν</th><th>N<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>b</th><th>χ<sup>2</sup>/ν</th></tr></thead><tbody><tr><td>8.38 ± 0.08</td><td>0.05 (fixed)</td><td>535 ± 53</td><td>0.029 ± 0.006</td><td>1.01</td><td>7.8 ± 0.1</td><td>1.830 ± 0.003</td><td>0.069 ± 0.005</td><td>0.98</td></tr><tr><td>8.66 ± 0.08</td><td>0.5 (fixed)</td><td>525 ± 53</td><td>0.029 ± 0.006</td><td>0.99</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><td>8.5 ± 0.2</td><td>0.4 ± 0.1</td><td>556 ± 62</td><td>0.026 ± 0.006</td><td>0.99</td><td>...</td><td>...</td><td>...</td><td>...</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Figure 3.** Cen A long-term average spectra from INTEGRAL SPI (green squares) and ISGRI (blue stars) with NuSTAR/FPMA (black diamonds) and FPMB (red triangles). The best-fit CompTT model with $kT_e = 0.5$ keV (cyan dotted–dashed line) and the log-parabola model (black dashed line) are overplotted.</figcaption></figure>

describe the data. We also tried a fit with $kT_0$ free, finding a best-fit seed photon temperature of $0.4 \pm 0.1$ keV and a reduced $\chi^2 = 2588.54/2607 = 0.99$, $\Delta\chi^2 = 5.34$ for one additional free parameter compared to the fit with $kT_0 = 0.05$ keV. The best-fit parameters for each fit are listed in Table 3. We note that implied electron temperatures above 500 keV disfavor a thermal origin (Fabian et al. 2017).

As discussed above, the hard X-ray/soft gamma-ray emission is potentially due to SSC jet emission. Thus, we fit the spectra to a log-parabola model, which can model the inverse Comptonization found in Fermi blazars (see Esposito et al. 2015 and references within). The $\alpha$ value in the log-parabola is the slope observed at the pivot energy ($F(E) = N(E/E_{\text{pivot}})^{-\alpha-\beta \log(E/E_{\text{pivot}})}$). Thus, we fixed $E_{\text{pivot}}$ to 50 keV to compare this slope with previously reported power-law results. This model also provides a good fit to the data (reduced $\chi^2 = 2553.05/2608 = 0.98$) with $\Delta\chi^2 = 41.45$ for the same number of free parameters as the pexrav model and $\Delta\chi^2 = 35.49$ for one less free parameter than the CompTT model with $kT_0$ free. Figure 3 shows the NuSTAR spectrum in black diamonds (FPMA) and red triangles (FPMB), the SPI spectrum in green squares, and the ISGRI spectrum in blue stars with the CompTT with $kT_e = 0.5$ keV (cyan dotted–dashed line) and log-parabola (black dashed line) models. Therefore, we find that statistically both thermal Comptonization and SSC emission can acceptably describe the joint NuSTAR/

INTEGRAL spectrum. Below, we discuss the implications of the parameters to potentially differentiate the two origins.

# 4. Discussion

## 4.1. Implications of Model Parameters

### 4.1.1. Iron Line and Reflection

An Fe K$\alpha$ line is suggestive of the presence of photons from an X-ray source reflecting off a surrounding medium (George & Fabian 1991). The width of the line profile provides an indication of the distance between the source and the reflecting medium (Evans et al. 2004). The width of $\le 8$ eV found in this work is similar to that in Fürst et al. (2016), indicating that the reflecting medium is far from the central black hole.

Additionally, the column density and the equivalent width of the line are related to the geometry and elemental abundances of the material. The calculated equivalent width from XSPEC is $\sim 32$ eV. This value combined with the fit column densities ($\sim 7-9 \times 10^{22} \text{ cm}^{-2}$) is compatible with a face-on torus interpretation with no significant Compton hump expected (Matt et al. 2003), which is consistent with the reflection value from our pexrav fit. Such an interpretation is in agreement with results from MYtorus and BNtorus fits in Fürst et al. (2016) and infrared observations from Ramos Almeida et al. (2009). Absence of reflection has also been reported in other
<table><caption>**Table 3**
Joint NuSTAR/SPI/ISGRI Fit Spectral Parameters</caption><thead><tr><th colspan="5">CompTT</th><th colspan="4">Log-parabola</th></tr><tr><th>N<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>kT<sub>0</sub><br>(keV)</th><th>kT<sub>e</sub><br>(keV)</th><th>τ</th><th>χ<sup>2</sup>/ν</th><th>N<sub>H</sub><br>(×10<sup>22</sup> cm<sup>-2</sup>)</th><th>Γ</th><th>b</th><th>χ<sup>2</sup>/ν</th></tr></thead><tbody><tr><td>8.38 ± 0.08</td><td>0.05 (fixed)</td><td>535 ± 53</td><td>0.029 ± 0.006</td><td>1.01</td><td>7.8 ± 0.1</td><td>1.830 ± 0.003</td><td>0.069 ± 0.005</td><td>0.98</td></tr><tr><td>8.66 ± 0.08</td><td>0.5 (fixed)</td><td>525 ± 53</td><td>0.029 ± 0.006</td><td>0.99</td><td>...</td><td>...</td><td>...</td><td>...</td></tr><tr><td>8.5 ± 0.2</td><td>0.4 ± 0.1</td><td>556 ± 62</td><td>0.026 ± 0.006</td><td>0.99</td><td>...</td><td>...</td><td>...</td><td>...</td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>**Figure 3.** Cen A long-term average spectra from INTEGRAL SPI (green squares) and ISGRI (blue stars) with NuSTAR/FPMA (black diamonds) and FPMB (red triangles). The best-fit CompTT model with $kT_e = 0.5$ keV (cyan dotted–dashed line) and the log-parabola model (black dashed line) are overplotted.</figcaption></figure>

describe the data. We also tried a fit with $kT_0$ free, finding a best-fit seed photon temperature of $0.4 \pm 0.1$ keV and a reduced $\chi^2 = 2588.54/2607 = 0.99$, $\Delta\chi^2 = 5.34$ for one additional free parameter compared to the fit with $kT_0 = 0.05$ keV. The best-fit parameters for each fit are listed in Table 3. We note that implied electron temperatures above 500 keV disfavor a thermal origin (Fabian et al. 2017).

As discussed above, the hard X-ray/soft gamma-ray emission is potentially due to SSC jet emission. Thus, we fit the spectra to a log-parabola model, which can model the inverse Comptonization found in Fermi blazars (see Esposito et al. 2015 and references within). The $\alpha$ value in the log-parabola is the slope observed at the pivot energy ($F(E) = N(E/E_{\text{pivot}})^{-\alpha-\beta \log(E/E_{\text{pivot}})}$). Thus, we fixed $E_{\text{pivot}}$ to 50 keV to compare this slope with previously reported power-law results. This model also provides a good fit to the data (reduced $\chi^2 = 2553.05/2608 = 0.98$) with $\Delta\chi^2 = 41.45$ for the same number of free parameters as the pexrav model and $\Delta\chi^2 = 35.49$ for one less free parameter than the CompTT model with $kT_0$ free. Figure 3 shows the NuSTAR spectrum in black diamonds (FPMA) and red triangles (FPMB), the SPI spectrum in green squares, and the ISGRI spectrum in blue stars with the CompTT with $kT_e = 0.5$ keV (cyan dotted–dashed line) and log-parabola (black dashed line) models. Therefore, we find that statistically both thermal Comptonization and SSC emission can acceptably describe the joint NuSTAR/

INTEGRAL spectrum. Below, we discuss the implications of the parameters to potentially differentiate the two origins.

# 4. Discussion

## 4.1. Implications of Model Parameters

### 4.1.1. Iron Line and Reflection

An Fe K$\alpha$ line is suggestive of the presence of photons from an X-ray source reflecting off a surrounding medium (George & Fabian 1991). The width of the line profile provides an indication of the distance between the source and the reflecting medium (Evans et al. 2004). The width of $\le 8$ eV found in this work is similar to that in Fürst et al. (2016), indicating that the reflecting medium is far from the central black hole.

Additionally, the column density and the equivalent width of the line are related to the geometry and elemental abundances of the material. The calculated equivalent width from XSPEC is $\sim 32$ eV. This value combined with the fit column densities ($\sim 7-9 \times 10^{22} \text{ cm}^{-2}$) is compatible with a face-on torus interpretation with no significant Compton hump expected (Matt et al. 2003), which is consistent with the reflection value from our pexrav fit. Such an interpretation is in agreement with results from MYtorus and BNtorus fits in Fürst et al. (2016) and infrared observations from Ramos Almeida et al. (2009). Absence of reflection has also been reported in other
radio-loud AGNs (Sambruna et al. 1999, 2009; Eracleous et al. 2000; Reeves & Turner 2000; Grandi et al. 2001; Ballantyne et al. 2002, 2014; Ogle et al. 2005; Ballantyne 2007; Evans et al. 2010; Walton et al. 2013; Madsen et al. 2015). There are other potential explanations for the lack of a Compton hump: a truncated inner disk from a retrograde spin (Garofalo 2009), an ionized accretion disk (Ballantyne et al. 2002), an outflowing corona (Beloborodov 1999; Malzac et al. 2001), relativistic jet dilution (Reeves & Turner 2000), changing geometry of the inner disk (Eracleous et al. 2000), or obscuration of central accretion flow by the jet (Sambruna et al. 2009). All of these models are consistent with the result in Cen A.

### 4.1.2. Continuum

When including data up to the soft gamma rays, we find spectral curvature is present in Cen A. Even the cutoff power-law fit to the NuSTAR spectrum is preferred over the power-law fit. This contrasts with spectral fits based on hard X-ray instruments that reported no spectral cutoff until the MeV region (Rothschild et al. 2011; Fürst et al. 2016). The cutoff energy value varies across the instruments (~250–520 keV) in this work. This behavior is similar to what has been reported in other works using soft gamma-ray data, since the parameter is sensitive the energy domain of the instruments.

Our joint NuSTAR/SPI/ISGRI fit has a best-fit cutoff energy of roughly 650 keV or an electron temperature of ~520–550 keV. This implies a corona near the runaway pair-production zone of the compactness–temperature diagram for a normal corona size of 3–10 $r_g$ (Fabian et al. 2015, 2017). These results together with the lack of significant reflection suggest that the continuum in the hard X-ray region is due to SSC emission. However, we are not able to exclude coronal emission as the dominant emission process in the hard X-ray/soft gamma-ray band. For example, the quasar 3C 273 showed similar Fe line and reflection characteristics, and analysis of the hard X-ray/soft gamma-ray spectral continuum showed it to be a combination of coronal plus jet emission (Grandi & Palumbo 2004; Madsen et al. 2015).

## 4.2. Joint Fit with Fermi/LAT

Following Madsen et al. (2015), we included Fermi/LAT data using the 12 yr Data Release 3 catalog fluxes in eight channels over the 50 MeV–1 TeV energy range (Abdollahi et al. 2022). Joint LAT/HESS analysis found a spectral break at ~3 GeV (H.E.S.S. Collaboration et al. 2018). Thus, we included a power-law model to fit the data above 3 GeV for a continuum model of zpowerlw in fits to the LAT data.

### 4.2.1. Jet-only Scenario

Initially, we tested a model where the keV to GeV emission is due to the jet (log-parabola + zpowerlw) with the LAT cross-normalization parameter ($C_{LAT}$) free and fixed to 1. The parameters for this fit are $n_H = (8.1 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$, $\alpha = 1.83 \pm 0.009$ ($E_{\text{pivot}} = 50$ keV), $\beta = 0.115 \pm 0.008$, and $\Gamma_{\text{HE}} = 2.17 \pm 0.02$ with reduced $\chi^2 = 2490.84/2613 = 0.99$ and $C_{LAT} = 0.38 \pm 0.09$. When the cross-normalization is fixed to 1, the parameters are $N_H = (8.3 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$, $\alpha = 1.826 \pm 0.007$ ($E_{\text{pivot}} = 50$ keV), $\beta = 0.156 \pm 0.003$, and $\Gamma_{\text{HE}} = 2.250 \pm 0.005$ with reduced $\chi^2 = 2611.81/2614 = 1.00$. We can describe the data with both $C_{LAT}$ values, but the free value implies a LAT flux significantly higher than the flux

($\sim 2.6 \times$) reported by the LAT team (Abdollahi et al. 2022). Thus we fixed $C_{LAT}$ to 1 in subsequent fits.

### 4.2.2. Jet and Corona Scenario

Also, we tested a model where the coronal emission dominates the hard X-ray/soft gamma-ray emission and the jet component dominates in the MeV to GeV range, similar to the scenario presented for 3C 273 in Grandi & Palumbo (2004) and Madsen et al. (2015). We used a (CompTT + log-parabola + zpowerlw) continuum model. However, some parameters are poorly constrained due to the lack of data in the MeV range and the GeV power-law component.

We found $n_H = (8.40 \pm 0.09) \times 10^{22} \text{ cm}^{-2}$, $kT_e = 481 \pm 121$ keV, $\tau = 0.03 \pm 0.01$, $\alpha = 2.6 \pm 0.1$ at $E_{\text{pivot}} = 1 \times 10^5$ keV, $\beta = 0.3 \pm 0.3$, and $\Gamma_{\text{HE}} = 2.1 \pm 0.2$ with reduced $\chi^2 = 2611.60/2612 = 1.00$. We report only the results with $kT_0$ fixed to 0.5 keV because the fit to $kT_0 = 0.05$ keV results in similar poorly constrained values. We obtain $kT_e$ near the runaway limit, but with a large error.

The fit well describes the data, but the high-energy power-law overpredicts the observed high-energy flux seen by LAT and H.E.S.S. Thus, we fixed the photon index value found in the jet-only scenario (2.25) and refit the spectra. The new model results in comparable parameters without much change in constraints and in goodness of fit when including expabs in the zpowerlw to limit its low-energy contribution. $\chi^2 = 2623.95/2613 = 1.00$. The low-energy cutoff energy was fixed to $10^5$ keV.

Figure 4 shows the NuSTAR spectrum in black diamonds (FPMA) and red triangles (FPMB), the SPI spectrum in green squares, the ISGRI spectrum in blue stars, and the LAT spectrum in magenta crosses with both the log-parabola + zpowerlw model (left) and the CompTT+log-parabola + zpowerlw model (right; where the hard X-rays are due to the corona and the MeV to GeV flux is from the jet). The differences between the models can be seen in the MeV region, where the jet-only scenario smoothly connects from hard X-rays to high-energy gamma rays. In contrast, the other scenario predicts a drop in flux above a few MeV. Thus, using the long-term average spectra from INTEGRAL/SPI, ISGRI, and LAT, we are not able to differentiate between the possibilities without observations in the medium MeV region.

Note that Rani et al. (2022) proposed a scenario where the peak energy of the jet overlaps with the corona component at ~500 keV, thus hiding the corona component. However, we were not able to disentangle the presence of the two components with our data.

### 4.2.3. Comparison with Previous Works

In their work on Cen A, Rani et al. (2022) also showed that the 230 GHz flux correlates with the hard X-ray flux with no time lag. (Israel et al. 2008 found similar results.) In addition, they found the 230 GHz flux is higher than what is predicted for an advection-dominated accretion flow (ADAF), and the radio spectrum is inconsistent with the slope predicted for an ADAF. Thus the authors conclude a jet component is enough to explain the hard X-ray emission. Our work supports that conclusion including X-ray to GeV data.

The source 3C 273 provides an interesting comparison since it was the first AGN where both corona and jet components have been reported (Grandi & Palumbo 2004). However, the
radio-loud AGNs (Sambruna et al. 1999, 2009; Eracleous et al. 2000; Reeves & Turner 2000; Grandi et al. 2001; Ballantyne et al. 2002, 2014; Ogle et al. 2005; Ballantyne 2007; Evans et al. 2010; Walton et al. 2013; Madsen et al. 2015). There are other potential explanations for the lack of a Compton hump: a truncated inner disk from a retrograde spin (Garofalo 2009), an ionized accretion disk (Ballantyne et al. 2002), an outflowing corona (Beloborodov 1999; Malzac et al. 2001), relativistic jet dilution (Reeves & Turner 2000), changing geometry of the inner disk (Eracleous et al. 2000), or obscuration of central accretion flow by the jet (Sambruna et al. 2009). All of these models are consistent with the result in Cen A.

### 4.1.2. Continuum

When including data up to the soft gamma rays, we find spectral curvature is present in Cen A. Even the cutoff power-law fit to the NuSTAR spectrum is preferred over the power-law fit. This contrasts with spectral fits based on hard X-ray instruments that reported no spectral cutoff until the MeV region (Rothschild et al. 2011; Fürst et al. 2016). The cutoff energy value varies across the instruments (~250–520 keV) in this work. This behavior is similar to what has been reported in other works using soft gamma-ray data, since the parameter is sensitive the energy domain of the instruments.

Our joint NuSTAR/SPI/ISGRI fit has a best-fit cutoff energy of roughly 650 keV or an electron temperature of ~520–550 keV. This implies a corona near the runaway pair-production zone of the compactness–temperature diagram for a normal corona size of 3–10 $r_g$ (Fabian et al. 2015, 2017). These results together with the lack of significant reflection suggest that the continuum in the hard X-ray region is due to SSC emission. However, we are not able to exclude coronal emission as the dominant emission process in the hard X-ray/soft gamma-ray band. For example, the quasar 3C 273 showed similar Fe line and reflection characteristics, and analysis of the hard X-ray/soft gamma-ray spectral continuum showed it to be a combination of coronal plus jet emission (Grandi & Palumbo 2004; Madsen et al. 2015).

## 4.2. Joint Fit with Fermi/LAT

Following Madsen et al. (2015), we included Fermi/LAT data using the 12 yr Data Release 3 catalog fluxes in eight channels over the 50 MeV–1 TeV energy range (Abdollahi et al. 2022). Joint LAT/HESS analysis found a spectral break at ~3 GeV (H.E.S.S. Collaboration et al. 2018). Thus, we included a power-law model to fit the data above 3 GeV for a continuum model of zpowerlw in fits to the LAT data.

### 4.2.1. Jet-only Scenario

Initially, we tested a model where the keV to GeV emission is due to the jet (log-parabola + zpowerlw) with the LAT cross-normalization parameter ($C_{LAT}$) free and fixed to 1. The parameters for this fit are $n_H = (8.1 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$, $\alpha = 1.83 \pm 0.009$ ($E_{\text{pivot}} = 50$ keV), $\beta = 0.115 \pm 0.008$, and $\Gamma_{\text{HE}} = 2.17 \pm 0.02$ with reduced $\chi^2 = 2490.84/2613 = 0.99$ and $C_{LAT} = 0.38 \pm 0.09$. When the cross-normalization is fixed to 1, the parameters are $N_H = (8.3 \pm 0.1) \times 10^{22} \text{ cm}^{-2}$, $\alpha = 1.826 \pm 0.007$ ($E_{\text{pivot}} = 50$ keV), $\beta = 0.156 \pm 0.003$, and $\Gamma_{\text{HE}} = 2.250 \pm 0.005$ with reduced $\chi^2 = 2611.81/2614 = 1.00$. We can describe the data with both $C_{LAT}$ values, but the free value implies a LAT flux significantly higher than the flux

($\sim 2.6 \times$) reported by the LAT team (Abdollahi et al. 2022). Thus we fixed $C_{LAT}$ to 1 in subsequent fits.

### 4.2.2. Jet and Corona Scenario

Also, we tested a model where the coronal emission dominates the hard X-ray/soft gamma-ray emission and the jet component dominates in the MeV to GeV range, similar to the scenario presented for 3C 273 in Grandi & Palumbo (2004) and Madsen et al. (2015). We used a (CompTT + log-parabola + zpowerlw) continuum model. However, some parameters are poorly constrained due to the lack of data in the MeV range and the GeV power-law component.

We found $n_H = (8.40 \pm 0.09) \times 10^{22} \text{ cm}^{-2}$, $kT_e = 481 \pm 121$ keV, $\tau = 0.03 \pm 0.01$, $\alpha = 2.6 \pm 0.1$ at $E_{\text{pivot}} = 1 \times 10^5$ keV, $\beta = 0.3 \pm 0.3$, and $\Gamma_{\text{HE}} = 2.1 \pm 0.2$ with reduced $\chi^2 = 2611.60/2612 = 1.00$. We report only the results with $kT_0$ fixed to 0.5 keV because the fit to $kT_0 = 0.05$ keV results in similar poorly constrained values. We obtain $kT_e$ near the runaway limit, but with a large error.

The fit well describes the data, but the high-energy power-law overpredicts the observed high-energy flux seen by LAT and H.E.S.S. Thus, we fixed the photon index value found in the jet-only scenario (2.25) and refit the spectra. The new model results in comparable parameters without much change in constraints and in goodness of fit when including expabs in the zpowerlw to limit its low-energy contribution. $\chi^2 = 2623.95/2613 = 1.00$. The low-energy cutoff energy was fixed to $10^5$ keV.

Figure 4 shows the NuSTAR spectrum in black diamonds (FPMA) and red triangles (FPMB), the SPI spectrum in green squares, the ISGRI spectrum in blue stars, and the LAT spectrum in magenta crosses with both the log-parabola + zpowerlw model (left) and the CompTT+log-parabola + zpowerlw model (right; where the hard X-rays are due to the corona and the MeV to GeV flux is from the jet). The differences between the models can be seen in the MeV region, where the jet-only scenario smoothly connects from hard X-rays to high-energy gamma rays. In contrast, the other scenario predicts a drop in flux above a few MeV. Thus, using the long-term average spectra from INTEGRAL/SPI, ISGRI, and LAT, we are not able to differentiate between the possibilities without observations in the medium MeV region.

Note that Rani et al. (2022) proposed a scenario where the peak energy of the jet overlaps with the corona component at ~500 keV, thus hiding the corona component. However, we were not able to disentangle the presence of the two components with our data.

### 4.2.3. Comparison with Previous Works

In their work on Cen A, Rani et al. (2022) also showed that the 230 GHz flux correlates with the hard X-ray flux with no time lag. (Israel et al. 2008 found similar results.) In addition, they found the 230 GHz flux is higher than what is predicted for an advection-dominated accretion flow (ADAF), and the radio spectrum is inconsistent with the slope predicted for an ADAF. Thus the authors conclude a jet component is enough to explain the hard X-ray emission. Our work supports that conclusion including X-ray to GeV data.

The source 3C 273 provides an interesting comparison since it was the first AGN where both corona and jet components have been reported (Grandi & Palumbo 2004). However, the
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Cen A long-term average spectra from INTEGRAL SPI (green squares), ISGRI (blue stars) with NuSTAR/FPMA (black diamonds) and FPMB (red triangles) and LAT (magenta crosses). The left panel shows the `log-parabola+zpowerlw` model (black dashed line) with the individual continuum components shown as red dotted lines. The right panel shows the `CompTT+log-parabola+zpowerlw` model (black dashed line) with individual continuum components as red dotted lines.</figcaption></figure>

Cen A jet component peaks at ~50 MeV compared to roughly 2 MeV for 3C 273. Additionally, for Cen A, the SED peak is dominated by the corona emission (around 500 keV) while the jet component dominates the SED peak in 3C 273 (Madsen et al. 2015). Therefore, it seems probable that even if a corona exists and contributes to the hard X-ray emission in Cen A, it would be hard to observe and distinguish from the jet emission.

## 5. Conclusion

In this work, we analyzed INTEGRAL/ISGRI and SPI observations of Cen A covering roughly 20 years. We first searched for spectral variability on a timescale of months, and did not find any significant deviations from a power law with a constant value. Building from this result, we constructed a long-term average spectrum up to 2.2 MeV. We included an observation from NuSTAR, which provides coverage down to 3.5 keV, to study the X-ray to soft gamma-ray spectrum.

Analysis of this spectrum found a narrow Fe line (<8 eV) and no significant reflection component, which is consistent with previous results (apart from the report of marginal reflection by Burke et al. 2014). The joint NuSTAR/ISGRI/ SPI spectral fit has a cutoff energy of ~650 keV or an electron temperature of ~520–550 keV, depending on the seed temperature. The physical interpretation of the hard X-ray/soft gamma-ray emission with these values is ambiguous, as the $kT_e$ values are near the runaway pair-production region for the corona. Another possible scenario is synchrotron self-Compton emission from the jet, which can also well describe the spectrum using a `log-parabola` model.

To complete our overview of the source, the LAT spectrum in the 50 MeV–100 GeV range was included in the spectral fit. A fit to a `log-parabola` model for the jet emission explains the spectrum from NuSTAR to LAT below ~3 GeV. However, the joint spectrum can also be adequately described by the

inclusion of a `CompTT` component to investigate the presence of coronal emission.

The results with this component are degenerate, however, but the best-fit parameters indicate two general scenarios: one where the X-ray emission is completely due to the corona and the jet emission dominates at MeV/GeV energies, and the other where the jet flux can explain the spectrum from X-rays to the GeV region. Our work favors the jet interpretation because one component can explain the whole emission from keV to LAT and due to the high electron temperature implied by the corona scenario. This interpretation is consistent with the polarization results by IXPE, which did not detect significant X-ray polarization (Ehlert et al. 2022). In their scenario, the X-rays can be explained by SSC emission with electrons accelerated in magnetic fields that are highly disorganized around the innermost jet.

To definitively exclude/constrain the presence of a corona component, several possibilities can be explored. As discussed above, the high-energy gamma-ray spectrum has two components, which limits the constraints on the curvature of the jet spectrum from LAT observations that can be extrapolated to lower energies. A detailed analysis of the Cen A long-term spectrum in high-energy gamma rays (potentially including H.E.S.S. data) may help to better constrain the hard X-ray/soft gamma-ray emission.

Another constraint can come from a significant Cen A detection at energies between SPI and LAT to differentiate between the jet-only model and the corona + jet scenario because the predicted fluxes are significantly different in the MeV range (Figure 4). Future observations by COSI may provide clarification, but the energy range is expected to extend up to only 5 MeV (Tomsick et al. 2019). Thus observations from a proposed mission such a AMEGO-X will be the best
<figure><img src="image_8.png" /><figcaption>**Figure 4.** Cen A long-term average spectra from INTEGRAL SPI (green squares), ISGRI (blue stars) with NuSTAR/FPMA (black diamonds) and FPMB (red triangles) and LAT (magenta crosses). The left panel shows the `log-parabola+zpowerlw` model (black dashed line) with the individual continuum components shown as red dotted lines. The right panel shows the `CompTT+log-parabola+zpowerlw` model (black dashed line) with individual continuum components as red dotted lines.</figcaption></figure>

Cen A jet component peaks at ~50 MeV compared to roughly 2 MeV for 3C 273. Additionally, for Cen A, the SED peak is dominated by the corona emission (around 500 keV) while the jet component dominates the SED peak in 3C 273 (Madsen et al. 2015). Therefore, it seems probable that even if a corona exists and contributes to the hard X-ray emission in Cen A, it would be hard to observe and distinguish from the jet emission.

## 5. Conclusion

In this work, we analyzed INTEGRAL/ISGRI and SPI observations of Cen A covering roughly 20 years. We first searched for spectral variability on a timescale of months, and did not find any significant deviations from a power law with a constant value. Building from this result, we constructed a long-term average spectrum up to 2.2 MeV. We included an observation from NuSTAR, which provides coverage down to 3.5 keV, to study the X-ray to soft gamma-ray spectrum.

Analysis of this spectrum found a narrow Fe line (<8 eV) and no significant reflection component, which is consistent with previous results (apart from the report of marginal reflection by Burke et al. 2014). The joint NuSTAR/ISGRI/SPI spectral fit has a cutoff energy of ~650 keV or an electron temperature of ~520–550 keV, depending on the seed temperature. The physical interpretation of the hard X-ray/soft gamma-ray emission with these values is ambiguous, as the $kT_e$ values are near the runaway pair-production region for the corona. Another possible scenario is synchrotron self-Compton emission from the jet, which can also well describe the spectrum using a `log-parabola` model.

To complete our overview of the source, the LAT spectrum in the 50 MeV–100 GeV range was included in the spectral fit. A fit to a `log-parabola` model for the jet emission explains the spectrum from NuSTAR to LAT below ~3 GeV. However, the joint spectrum can also be adequately described by the

inclusion of a `CompTT` component to investigate the presence of coronal emission.

The results with this component are degenerate, however, but the best-fit parameters indicate two general scenarios: one where the X-ray emission is completely due to the corona and the jet emission dominates at MeV/GeV energies, and the other where the jet flux can explain the spectrum from X-rays to the GeV region. Our work favors the jet interpretation because one component can explain the whole emission from keV to LAT and due to the high electron temperature implied by the corona scenario. This interpretation is consistent with the polarization results by IXPE, which did not detect significant X-ray polarization (Ehlert et al. 2022). In their scenario, the X-rays can be explained by SSC emission with electrons accelerated in magnetic fields that are highly disorganized around the innermost jet.

To definitively exclude/constrain the presence of a corona component, several possibilities can be explored. As discussed above, the high-energy gamma-ray spectrum has two components, which limits the constraints on the curvature of the jet spectrum from LAT observations that can be extrapolated to lower energies. A detailed analysis of the Cen A long-term spectrum in high-energy gamma rays (potentially including H.E.S.S. data) may help to better constrain the hard X-ray/soft gamma-ray emission.

Another constraint can come from a significant Cen A detection at energies between SPI and LAT to differentiate between the jet-only model and the corona + jet scenario because the predicted fluxes are significantly different in the MeV range (Figure 4). Future observations by COSI may provide clarification, but the energy range is expected to extend up to only 5 MeV (Tomsick et al. 2019). Thus observations from a proposed mission such as AMEGO-X will be the best
tool for studying the full MeV energy range (Caputo et al. 2022).

## Acknowledgments

The research leading to these results has received funding from the European Union's Horizon 2020 Programme under the AHEAD2020 project (grant agreement No. 871158). J.R. acknowledges financial support under the INTEGRAL ASI/ INAF No. 2019-35.HH.0 and from an INAF 2022 mini-grant. M.M. acknowledges financial support from ASI under contract No. 2019-35-HH.0. The INTEGRAL SPI project has been completed under the responsibility and leadership of CNES. We are grateful to ASI, CEA, CNES, DLR, ESA, INTA, NASA, and OSTC for support. We thank the referee for the comments and input.

## ORCID iDs

James Rodi https://orcid.org/0000-0003-2126-5908

E. Jourdain https://orcid.org/0000-0001-9932-3288

M. Molina https://orcid.org/0000-0003-0681-9984

J. P. Roques https://orcid.org/0000-0002-6529-4121

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tool for studying the full MeV energy range (Caputo et al. 2022).

## Acknowledgments

The research leading to these results has received funding from the European Union's Horizon 2020 Programme under the AHEAD2020 project (grant agreement No. 871158). J.R. acknowledges financial support under the INTEGRAL ASI/ INAF No. 2019-35.HH.0 and from an INAF 2022 mini-grant. M.M. acknowledges financial support from ASI under contract No. 2019-35-HH.0. The INTEGRAL SPI project has been completed under the responsibility and leadership of CNES. We are grateful to ASI, CEA, CNES, DLR, ESA, INTA, NASA, and OSTC for support. We thank the referee for the comments and input.

## ORCID iDs

James Rodi https://orcid.org/0000-0003-2126-5908

E. Jourdain https://orcid.org/0000-0001-9932-3288

M. Molina https://orcid.org/0000-0003-0681-9984

J. P. Roques https://orcid.org/0000-0002-6529-4121

## References

Abdollahi, S., Acero, F., Baldini, L., et al. 2022, ApJS, 260, 53

Ballantyne, D. R. 2007, MPLA, 22, 2397

Ballantyne, D. R., Bollenbacher, J. M., Brenneman, L. W., et al. 2014, ApJ, 794, 62

Ballantyne, D. R., Ross, R. R., & Fabian, A. C. 2002, MNRAS, 332, L45

Beckmann, V., Jean, P., Lubinski, P., Soldi, S., & Terrier, R. 2011, A&A, 531, A70

Beloborodov, A. M. 1999, ApJL, 510, L123

Bowyer, C. S., Lampton, M., Mack, J., & de Mendonca, F. 1970, ApJL, 161, L1

Burke, M. J., Jourdain, E., Roques, J. P., & Evans, D. A. 2014, ApJ, 787, 50

Caputo, R., Ajello, M., Kierans, C. A., et al. 2022, JATIS, 8, 044003

Chiaberge, M., Capetti, A., & Celotti, A. 2001, MNRAS, 324, L33

Ehlert, S. R., Ferrazzoli, R., Marinucci, A., et al. 2022, ApJ, 935, 116

Eracleous, M., Sambruna, R., & Mushotzky, R. F. 2000, ApJ, 537, 654

Esposito, V., Walter, R., Jean, P., et al. 2015, A&A, 576, A122

Evans, D. A., Kraft, R. P., Worrall, D. M., et al. 2004, ApJ, 612, 786

Evans, D. A., Reeves, J. N., Hardcastle, M. J., et al. 2010, ApJ, 710, 859

Fabian, A. C., Lohfink, A., Belmont, R., et al. 2017, MNRAS, 467, 2566

Fabian, A. C., Lohfink, A., Kara, E., et al. 2015, MNRAS, 451, 4375

Fürst, F., Müller, C., Madsen, K. K., et al. 2016, ApJ, 819, 150

Garofalo, D. 2009, ApJ, 699, 400

George, I. M., & Fabian, A. C. 1991, MNRAS, 249, 352

Grandi, P., Maraschi, L., Urry, C. M., et al. 2001, ApJ, 556, 35

Grandi, P., & Palumbo, G. G. C. 2004, Sci, 306, 998

Guilbert, P. W., Fabian, A. C., & Rees, M. J. 1983, MNRAS, 205, 593

Haardt, F., & Maraschi, L. 1993, ApJ, 413, 507

H.E.S.S. Collaboration, Abdalla, H., Abramowski, A., et al. 2018, A&A, 619, A71

HI4PI Collaboration, Ben Bekhti, N., Flöer, L., et al. 2016, A&A, 594, A116

Israel, F. P., Raban, D., Booth, R. S., et al. 2008, A&A, 483, 741

Jensen, P. L., Clausen, K., Cassi, C., et al. 2003, A&A, 411, L7

Jourdain, E., Bassani, L., Roques, J. P., et al. 1993, ApJ, 412, 586

Madsen, K. K., Harrison, F. A., Markwardt, C. B., et al. 2015, ApJS, 220, 8

Malzac, J., Beloborodov, A. M., & Poutanen, J. 2001, MNRAS, 326, 417

Matt, G., Guainazzi, M., & Maiolino, R. 2003, MNRAS, 342, 422

Merloni, A., & Fabian, A. C. 2003, MNRAS, 342, 951

Molina, M., Bassani, L., Malizia, A., et al. 2013, MNRAS, 433, 1687

Ogle, P. M., Davis, S. W., Antonucci, R. R. J., et al. 2005, ApJ, 618, 139

Ramos Almeida, C., Levenson, N. A., Rodríguez Espinosa, J. M., et al. 2009, ApJ, 702, 1127

Rani, B., Mundo, S. A., Mushotzky, R., et al. 2022, ApJ, 932, 104

Reeves, J. N., & Turner, M. J. L. 2000, MNRAS, 316, 234

Roques, J.-P., & Jourdain, E. 2019, ApJ, 870, 92

Roques, J. P., Schanne, S., von Kienlin, A., et al. 2003, A&A, 411, L91

Rothschild, R. E., Markowitz, A., Rivers, E., et al. 2011, ApJ, 733, 23

Rothschild, R. E., Wilms, J., Tomsick, J., et al. 2006, ApJ, 641, 801

Sambruna, R. M., Eracleous, M., & Mushotzky, R. F. 1999, ApJ, 526, 60

Sambruna, R. M., Reeves, J. N., Braito, V., et al. 2009, ApJ, 700, 1473

Skibo, J. B., Dermer, C. D., & Kinzer, R. L. 1994, ApJL, 426, L23

Steinle, H., Bennett, K., Bloemen, H., et al. 1998, A&A, 330, 97

Stern, B. E., Poutanen, J., Svensson, R., et al. 1995, ApJL, 449, L13

Svensson, R. 1984, MNRAS, 209, 175

Tomsick, J., Zoglauer, A., Sleator, C., et al. 2019, BAAS, arXiv:1908.04334

Ubertini, P., Lebrun, F., Di Cocco, G., et al. 2003, A&A, 411, L131

Vedrenne, G., Roques, J.-P., Schönfelder, V., et al. 2003, A&A, 411, L63

Walton, D. J., Nardini, E., Fabian, A. C., et al. 2013, MNRAS, 428, 2901