Free Access
Issue
A&A
Volume 574, February 2015
Article Number A117
Number of page(s) 5
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/201425442
Published online 04 February 2015

© ESO, 2015

1. Introduction

Active galactic nuclei (AGN) are among the brightest extragalactic sources at X-ray energies. According to the unification model (Antonucci 1993; Urry & Padovani 1995), the orientation of AGN with respect to the line of sight, different accretion rates, and the presence of a powerful jet lead to different spectral appearances. Jet-dominated sources at the smallest jet inclination angles are classified as blazars. Sources that are oriented at larger angles to the line of sight are typically less dominated by beamed jet emission. The origin of the X-ray emission of radio-loud AGN is still an open question (e.g., Fukazawa et al. 2015). It can arise from Comptonization of seed photons from the accretion disk in the hot corona, synchrotron or inverse Compton emission, or a combination of these. The most prominent emission line in AGN X-ray spectra is the Fe Kα line at ~6.4 keV (e.g., Nandra 2006; Shu et al. 2010; Ricci et al. 2014). This line is typically explained by fluorescence of neutral or mildly ionized iron produced by the primary, hard X-ray photons that irradiate the accretion disk or the molecular torus. Measurements of iron line emission therefore probe the inner regions of AGN. The detection of an iron line is a clear indication of reprocessed radiation from matter in the vicinity of the primary X-ray source. Iron lines are common features in spectra of radio-quiet and radio-loud sources at larger jet angles to the line of sight (Bianchi et al. 2004). In contrast, typical blazar X-ray spectra are featureless continua, clearly dominated by the beamed jet emission that outshines any putative underlying emission components (e.g., Rivers et al. 2013; Grandi et al. 2006).

Müller et al. (2014, hereafter Mue14) discussed the multiwavelength properties of PMN J1603–4904, which is associated with a bright γ-ray source with a remarkably hard spectrum (2FGL J1603.8–4904; Nolan et al. 2012). These properties are difficult to reconcile with its original classification as a BL Lac type blazar (Nolan et al. 2012; Ackermann et al. 2013): High-resolution TANAMI (Ojha et al. 2010) radio observations using very long baseline interferometry (VLBI) revealed a symmetric structure on milliarcsecond (mas) scales with the brightest, most compact component at the center. The broadband spectral energy distribution (SED) showed an excess in the infrared, which could be modeled with a blackbody spectrum with T ~ 1600 K, consistent with the emission of circumnuclear dust heated by the disk photons. Such thermally reprocessed radiation is not expected in typical blazar SEDs. Optical measurements constrained the redshift to z ≲ 4.24 (Shaw et al. 2013). Based on the results presented by Mue14, however, no conclusive classification of PMN J1603–4904 could be made. While Swift/XRT observations showed a faint X-ray counterpart, low photon statistics did not allow us to sufficiently constrain its X-ray spectrum.

In this article, we report on the first XMM-Newton and Suzaku observations of PMN J1603–4904 conducted within the scope of the TANAMI multiwavelength program (Sect. 2). In Sect. 3 we present the X-ray spectral characteristics and discuss its implications in Sect. 4.

2. Observations and data reduction

In 2013 September, we performed quasi-simultaneous X-ray observations of PMN J1603–4904 with XMM-Newton (Jansen et al. 2001, obs-id 0724700101, performed 2013-09-17) and Suzaku (Koyama et al. 2007, obs-id 708035010, performed 2013-09-13) to constrain the X-ray spectrum better than previous observations with Swift/XRT (Burrows et al. 2005, Mue14). The XMM-Newton data processing, analysis, and extraction of the spectrum were performed using the standard tasks of the XMM System Analysis Software (SAS 13.5.0). We detected a single unresolved X-ray source at the radio position of PMN J1603–4904. We worked only with data from EPIC-PN (Strüder et al. 2001, exposure time 39.0 ks) and EPIC-MOS 1 (Turner et al. 2001, exposure time 33.4 ks) cameras because the usable exposure of EPIC-MOS 2 was only 4.7 ks. The PN spectrum was extracted using a circle with 35′′ radius centered on the coordinates of the radio source. For the background spectrum a circular source-free region of 50′′ radius was chosen. For the MOS 1 data extraction, background and source regions with radii of 100′′ were used. We chose larger extraction radii for the background to minimize the measurement uncertainty. We used the HEASOFT v6.15 package to analyze the Suzaku data. Extraction and background regions of 94′′ were used for all XIS detectors, which after filtering had an exposure time of 48.5 ks. The spectral analysis was performed using the Interactive Spectral Interpretation System (ISIS, version 1.6.2-27, Houck & Denicola 2000). An independent analysis of the XMM-Newton and Suzaku data revealed no significant flux variability during the observed period. To improve the statistics and ensure the validity of the χ2-statistics, all 1–10 keV spectra were rebinned to a signal-to-noise ratio of at least 5 and were modeled simultaneously considering the background. Throughout this paper we use the standard cosmological model with Ωm = 0.3, Λ = 0.7, H0 = 70 km s-1 Mpc-1 (Beringer et al. 2012). All uncertainties quoted in the following are given at the 90% confidence level.

3. Results

3.1. X-ray continuum

The quasi-simultaneous data from XMM/PN, MOS 1, and Suzaku/XIS were simultaneously modeled with an absorbed power-law component, a Gaussian emission line, and cross-calibration constants to account for the relative flux calibrations of the instruments. We used the tbnew model (Wilms et al. 2012) to account for neutral Galactic absorption (the Galactic Hi value was fixed to NH = 6.32 × 1021 cm-2; Kalberla et al. 2005), the cross sections of Verner et al. (1996), and abundances of Wilms et al. (2000). Further residuals revealed source intrinsic absorption, which we modeled with an additional, redshifted absorption component (tbnew_z, see below). We detected a strong emission line that we modeled with a Gaussian component at 5.44 ± 0.05 keV with an equivalent width of EW = 200 ± 90 eV (Fig. 1a). Using the centroid energy of the Gaussian emission line with respect to the neutral Fe Kα line rest frame energy, we constrained the redshift of the system to z = 0.18 ± 0.01 (see Sect. 3.2 for details). We found a photon index of with an intrinsic absorption of . The best-fit model parameters can be found in Table 1. Adding a Gaussian line to describe the emission line improves the fit from χ2 = 198.1 (165 degrees of freedom [d.o.f.]) to χ2 = 183.3 (162 d.o.f.). To test for the significance of the line feature at 5.44 keV, we performed a Monte Carlo simulation based on the null-hypothesis that the intrinsic model for the measured counts is an absorbed power-law lacking a line. This hypothesis is rejected with a p-value of p< 1.1 × 10-4. Figure 1 shows the spectra of all single datasets with the best-fit model and the combined datasets regridded to a joint energy grid.

thumbnail Fig. 1

Simultaneous fit to the XMM-Newton and Suzaku data (see Table 1). The data are best fit by an absorbed power-law component with an emission line at ~ 5.44 ± 0.05 keV. a) Count spectrum for all detectors fitted with an absorbed power law and a Gaussian emission line (models shown in gray). Ratio of data to model for a fit of an absorbed power law b) and including a Gaussian emission line c). d) Unfolded, combined spectrum of all data sets with the best-fit model (red). The shaded region highlights the position of the emission line.

3.2. Iron emission line

As a result of its high fluorescent yield, the Fe Kα transition produces the most prominent line feature in the 2–10 keV energy range. Such lines are seen in the X-ray spectra of most Seyfert and radio galaxies (de La Calle Pérez et al. 2010). In most sources where redshifts are known (e.g., Markowitz et al. 2007; Shu et al. 2010; Ricci et al. 2014), the line energy and equivalent width are consistent with an origin by fluorescence with a rest-frame energy of ~6.4 keV in a neutral to mildly ionized medium that is irradiated by hard X-rays. Even in sources showing relativistically broadened Fe Kα lines from the innermost regions of the accretion disk, narrow-line components consistent with a rest-frame energy of 6.4 keV are typically seen (Risaliti et al. 2013; Marinucci et al. 2014a,b). We therefore considered it most probable that the emission line seen in PMN J1603–4904 at 5.44 ± 0.05 keV is also emitted intrinsically at 6.4 keV1, such that the corresponding redshift of the source can be constrained to z = 0.18 ± 0.01.

When this redshift is adopted, the luminosity distance is 872 ± 54 Mpc. In the rest-frame, the intrinsic X-ray luminosity, neglecting Galactic and source intrinsic absorption, is L2–10 keV = (4.03 ± 0.20) × 1043 erg s-1 and the γ-ray luminosity is L1–100 GeV = (8.1 ± 1.1) × 1045 erg s-1 (for S1–100 GeV = (1.44 ± 0.07) × 10-10 erg s-1 cm-2, Nolan et al. 2012). At 8.4 GHz, we derive a rest-frame luminosity density of L8.4 GHz = (7.3 ± 1.5) × 1032 ergs-1 Hz-1 (based on the flux from Mue14). The comparison of ATCA observations at arcsec resolution and VLBI observations with milliarcsecond resolution shows that ~80% of the radio emission is emitted on scales of ~15 mas (Mue14), i.e., ~46 pc at z = 0.18. The remaining ~20% are emitted on larger scales that are constrained to 1′′ (Mue14), that is, ~3 kpc at z = 0.18.

Table 1

Best-fit parameters using an absorbed power-law model with a Gaussian emission line.

Table 2

Typical high-energy spectral parameters for different source classes compared with results for PMN J1603–4904.

4. Discussion

The X-ray properties derived from the XMM-Newton and Suzaku spectra allow us to further constrain the classification of this unusual γ-ray source. Here we compare the X-ray spectrum of PMN J1603–4904 with the typical spectra of different radio-loud AGN (see Table 2).

Compared with other source types, blazars are the most luminous AGN at the X-ray energies (e.g., Chang 2010; Rivers et al. 2013). With an X-ray luminosity of L2–10 keV ~ 4 × 1043 erg s-1, PMN J1603–4904 is only comparable with the fainter blazars of the BL Lac type. Its γ-ray luminosity of Lγ ~ 8 × 1045 erg s-1 is similar to low or intermediate peaked2 BL Lac objects and flat-spectrum radio quasars (Ackermann et al. 2011). Since blazar X-ray spectra are dominated by beamed jet emission, they are generally featureless3 and can in most cases be modeled with a simple or broken power law (Chang 2010; Ushio et al. 2010; Rivers et al. 2013). The strong iron line in the X-ray spectrum of PMN J1603–4904 therefore suggests a different nature from a blazar. The intrinsic X-ray absorption (NH ~ 2 × 1022 cm-2) is furthermore unusually high compared with other blazars (Kubo et al. 1998; Chang 2010; Rivers et al. 2013). We therefore conclude that its original classification as a BL Lac (Nolan et al. 2012; Shaw et al. 2013) is very unlikely.

The multiwavelength properties of PMN J1603–4904 opened the door to an alternative classification as a jet source seen at a larger inclination angle, that is, a radio galaxy (Mue14). Overall, the X-ray properties of PMN J1603–4904 are similar to those of radio galaxies (Table 2). In about 50% of all broad-line radio galaxies, Fe Kα lines with equivalent widths of typically a few 100 eV are detected (e.g., Sambruna et al. 1999). PMN J1603–4904 has a similar equivalent width of EW = 200 ± 90 eV. We caution, however, that only few non-blazar sources are detected at γ-ray energies (Abdo et al. 2010; Nolan et al. 2012; Katsuta et al. 2013). The γ-ray luminosities of these “misaligned” jets show a broad range from Lγ ~ 10411046 erg s-1, with FR I galaxies being typically less γ-ray luminous than FR II sources. The γ-ray luminosity of PMN J1603–4904 is only comparable with the most powerful misaligned sources (Abdo et al. 2010).

Among the sources seen at a large inclination angle, compact steep spectrum (CSS) and gigahertz peaked spectrum (GPS) sources can be interpreted as the younger versions of evolved radio galaxies, often showing compact symmetric object (CSO) radio morphologies at parsec scales (Readhead et al. 1996a,b; O’Dea 1998). Owing to its milliarcsecond-scale properties, we discussed the possible classification of PMN J1603–4904 as a CSO in Mue14. The 2–10 keV spectra of GPS and CSO sources can generally be well modeled by absorbed power laws (e.g., Vink et al. 2006; Guainazzi et al. 2006; Siemiginowska et al. 2008; Tengstrand et al. 2009; Kunert-Bajraszewska et al. 2014). Fe Kα emission is only detected in a few sources (e.g., Guainazzi et al. 2006; Siemiginowska 2009; Tengstrand et al. 2009). The X-ray properties of PMN J1603–4904 are a good match to the findings in these sample studies of GPS and CSS sources. These sources generally have a radio luminosity density of L ≳ 10321036 erg s-1 Hz-1 at 5 GHz (O’Dea & Baum 1997, for combined complete samples). Thus PMN J1603–4904 is compatible with the less powerful GPS and CSS sources. Its linear size is similar to the canonical size limit for CSOs (<1 kpc) or medium-sized symmetric objects (<15 kpc; Fanti et al. 1995; Readhead 1995; Readhead et al. 1996b). Gamma-ray emission was predicted from theoretical modeling of GPS sources (e.g., Stawarz et al. 2008; Ostorero et al. 2010; Kino et al. 2013; Migliori et al. 2014), and first source candidates have been discussed, for instance, 4C +55.17 (McConville et al. 2011) with similar broadband properties as PMN J1603–4904. If it is confirmed as a γ-ray loud young radio galaxy, then PMN J1603–4904 would be a well-suited object in which to investigate the origin of high-energy emission.

5. Conclusions

We have presented new X-ray observations of PMN J1603–4904, which further challenge its previous classification as a blazar and strongly suggest that this jet system is seen at a larger inclination angle to the line of sight. Its X-ray spectrum can be modeled by an absorbed power law and a Gaussian emission line at 5.44 ± 0.05 keV and is best explained as emission from a non-blazar source. These X-ray properties are consistent with a young or evolved radio galaxy. We interpret the significantly detected spectral line as a neutral Fe Kα line with rest-frame energy of 6.4 keV. This identification results in the first redshift measurement for this source of z = 0.18 ± 0.01, that is, a luminosity distance of 872 ± 54 Mpc.

PMN J1603–4904 is associated with a hard-spectrum γ-ray source (Nolan et al. 2012)4. If it is indeed seen at a larger inclination angle where the observed emission is less intensified by Doppler boosting than in blazars, it adds to the class of so-called misaligned sources that are rarely detected at γ-ray energies (Abdo et al. 2010), with a remarkably high γ-ray luminosity.

Further multiwavelength observations are required to confirm PMN J1603–4904 as a γ-ray loud young radio galaxy: VLBI monitoring will allow us to check for proper motion in opposite directions with respect to the core. Low radio frequency observations could help to determine a putative peak at 1 GHz, thus increasing confidence in its identification as a GPS source, and to constrain the extended radio emission.


1

In the very unlikely event that the line is instead due to emission from a strongly ionized plasma, the Lyα resonance at 6.966 keV would yield a redshift of z = 0.28 ± 0.01 for hydrogen-like iron.

2

The synchrotron peak frequency derived from the parametrization of the broadband spectral energy distribution is νsync ≃ 2.2 × 1012 Hz (Mue14), which would be more in line with a low-peaked object (defined by  Hz; Fossati et al. 1998; Donato et al. 2001).

3

As a rare exception, Grandi & Palumbo (2004) discussed the detection of a narrow Fe Kα line in the flat-spectrum radio quasar 3C 273. In this case, the thermal (unbeamed) and the beamed jet emission was distinguished thanks to the source variability, suggesting the presence of an underlying Seyfert-like component (Soldi et al. 2008).

4

Note that a slight possibility of a false association of the γ-ray source with PMN J1603–4904 still remains, although in this case an even more exotic explanation for the γ-ray origin would be required.

Acknowledgments

We thank the referee for the helpful comments, and R. Schulz and P.G. Edwards for the useful discussions that improved the manuscript. C.M. acknowledges the support of the Bundesministerium für Wirtschaft und Technologie (BMWi) through Deutsches Zentrum für Luft- und Raumfahrt (DLR) grant 50 OR 1404 and of the Studienstiftung des Deutschen Volkes. This research was funded in part by the National Aeronautics and Space Administration (NASA) through Fermi Guest Investigator grants NNH09ZDA001N, NNH10ZDA001N, and NNH12ZDA001N, by BMWi through DLR grant 50 OR 1311, by Deutsche Forschungsgemeinschaft grant WI1860/10-1, and by an appointment to the NASA Postdoctoral Program at the Goddard Space Flight Center, administered by Oak Ridge Associated Universities through a contract with NASA. We thank J. E. Davis for the development of the slxfig module that has been used to prepare the figure in this work. This research has made use of ISIS functions provided by ECAP/Dr. Karl Remeis-Observatory (Bamberg, Germany) and MIT (http://www.sternwarte.uni-erlangen.de/isis/).

References

  1. Abdo, A. A., Ackermann, M., Ajello, M., et al. 2010, ApJ, 720, 912 [NASA ADS] [CrossRef] [Google Scholar]
  2. Ackermann, M., Ajello, M., Allafort, A., et al. 2011, ApJ, 743, 171 [NASA ADS] [CrossRef] [Google Scholar]
  3. Ackermann, M., Ajello, M., Allafort, A., et al. 2013, ApJS, 209, 34 [NASA ADS] [CrossRef] [Google Scholar]
  4. Antonucci, R. 1993, ARA&A, 31, 473 [Google Scholar]
  5. Beringer, J., Arguin, J.-F., Barnett, R. M., et al. 2012, Phys. Rev. D, 86, 010001 [Google Scholar]
  6. Bianchi, S., Matt, G., Balestra, I., Guainazzi, M., & Perola, G. C. 2004, A&A, 422, 65 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Burrows, D. N., Hill, J. E., Nousek, J. A., et al. 2005, Space Sci. Rev., 120, 165 [NASA ADS] [CrossRef] [Google Scholar]
  8. Chang, C.-S. 2010, Ph.D. Thesis, Max-Planck-Institut für Radioastronomie, Bonn, Germany [Google Scholar]
  9. de La Cal le Pérez, I., Longinotti, A. L., Guainazzi, M., et al. 2010, A&A, 524, A50 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Donato, D., Ghisellini, G., Tagliaferri, G., & Fossati, G. 2001, A&A, 375, 739 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Eracleous, M., Sambruna, R., & Mushotzky, R. F. 2000, ApJ, 537, 654 [NASA ADS] [CrossRef] [Google Scholar]
  12. Evans, D. A., Worrall, D. M., Hardcastle, M. J., Kraft, R. P., & Birkinshaw, M. 2006, ApJ, 642, 96 [NASA ADS] [CrossRef] [Google Scholar]
  13. Fanti, C., Fanti, R., Dallacasa, D., et al. 1995, A&A, 302, 317 [NASA ADS] [Google Scholar]
  14. Fossati, G., Maraschi, L., Celotti, A., Comastri, A., & Ghisellini, G. 1998, MNRAS, 299, 433 [NASA ADS] [CrossRef] [Google Scholar]
  15. Fukazawa, Y., Finke, J., Stawarz, L., et al. 2015, ApJ, 798, 74 [NASA ADS] [CrossRef] [Google Scholar]
  16. Grandi, P., & Palumbo, G. G. C. 2004, Science, 306, 998 [NASA ADS] [CrossRef] [Google Scholar]
  17. Grandi, P., Malaguti, G., & Fiocchi, M. 2006, ApJ, 642, 113 [NASA ADS] [CrossRef] [Google Scholar]
  18. Guainazzi, M., Siemiginowska, A., Stanghellini, C., et al. 2006, A&A, 446, 87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Hardcastle, M. J., Evans, D. A., & Croston, J. H. 2006, MNRAS, 370, 1893 [NASA ADS] [CrossRef] [Google Scholar]
  20. Houck, J. C., & Denicola, L. A. 2000, in Astronomical Data Analysis Software and Systems IX, eds. N. Manset, C. Veillet, & D. Crabtree, ASP Conf. Ser., 216, 591 [Google Scholar]
  21. Jansen, F., Lumb, D., Altieri, B., et al. 2001, A&A, 365, L1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. Kalberla, P. M. W., Burton, W. B., Hartmann, D., et al. 2005, A&A, 440, 775 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Katsuta, J., Tanaka, Y. T., Stawarz, Ł., et al. 2013, A&A, 550, A66 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Kino, M., Ito, H., Kawakatu, N., & Orienti, M. 2013, ApJ, 764, 134 [NASA ADS] [CrossRef] [Google Scholar]
  25. Koyama, K., Tsunemi, H., Dotani, T., et al. 2007, PASJ, 59, 23 [Google Scholar]
  26. Kubo, H., Takahashi, T., Madejski, G., et al. 1998, ApJ, 504, 693 [NASA ADS] [CrossRef] [Google Scholar]
  27. Kunert-Bajraszewska, M., Labiano, A., Siemignowska, A., & Guainazzi, M. 2014, MNRAS, 437, 3063 [NASA ADS] [CrossRef] [Google Scholar]
  28. Marinucci, A., Matt, G., Kara, E., et al. 2014a, MNRAS, 440, 2347 [NASA ADS] [CrossRef] [Google Scholar]
  29. Marinucci, A., Matt, G., Miniutti, G., et al. 2014b, ApJ, 787, 83 [NASA ADS] [CrossRef] [Google Scholar]
  30. Markowitz, A., Takahashi, T., Watanabe, S., et al. 2007, ApJ, 665, 209 [NASA ADS] [CrossRef] [Google Scholar]
  31. McConville, W., Ostorero, L., Moderski, R., et al. 2011, ApJ, 738, 148 [NASA ADS] [CrossRef] [Google Scholar]
  32. Migliori, G., Siemiginowska, A., Kelly, B. C., et al. 2014, ApJ, 780, 165 [NASA ADS] [CrossRef] [Google Scholar]
  33. Müller, C., Kadler, M., Ojha, R., et al. 2014, A&A, 562, A4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Nandra, K. 2006, MNRAS, 368, L62 [NASA ADS] [CrossRef] [Google Scholar]
  35. Nolan, P. L., Abdo, A. A., Ackermann, M., et al. 2012, ApJS, 199, 31 [NASA ADS] [CrossRef] [Google Scholar]
  36. O’Dea, C. P. 1998, PASP, 110, 493 [NASA ADS] [CrossRef] [Google Scholar]
  37. O’Dea, C. P., & Baum, S. A. 1997, AJ, 113, 148 [NASA ADS] [CrossRef] [Google Scholar]
  38. Ojha, R., Kadler, M., Böck, M., et al. 2010, A&A, 519, A45 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Ostorero, L., Moderski, R., Stawarz, Ł., et al. 2010, ApJ, 715, 1071 [NASA ADS] [CrossRef] [Google Scholar]
  40. Readhead, A. C. S. 1995, PNAS, 92, 11447 [Google Scholar]
  41. Readhead, A. C. S., Taylor, G. B., Pearson, T. J., & Wilkinson, P. N. 1996a, ApJ, 460, 634 [NASA ADS] [CrossRef] [Google Scholar]
  42. Readhead, A. C. S., Taylor, G. B., Xu, W., et al. 1996b, ApJ, 460, 612 [NASA ADS] [CrossRef] [Google Scholar]
  43. Ricci, C., Ueda, Y., Ichikawa, K., et al. 2014, A&A, 567, A142 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  44. Risaliti, G., Harrison, F. A., Madsen, K. K., et al. 2013, Nature 494, 449 [NASA ADS] [CrossRef] [Google Scholar]
  45. Rivers, E., Markowitz, A., & Rothschild, R. 2013, ApJ, 772, 114 [NASA ADS] [CrossRef] [Google Scholar]
  46. Sambruna, R. M., Eracleous, M., & Mushotzky, R. F. 1999, ApJ, 526, 60 [NASA ADS] [CrossRef] [Google Scholar]
  47. Shaw, M. S., Romani, R. W., Cotter, G., et al. 2013, ApJ, 764, 135 [NASA ADS] [CrossRef] [Google Scholar]
  48. Shu, X. W., Yaqoob, T., & Wang, J. X. 2010, ApJS, 187, 581 [NASA ADS] [CrossRef] [Google Scholar]
  49. Siemiginowska, A. 2009, Astron. Nachr., 330, 264 [NASA ADS] [CrossRef] [Google Scholar]
  50. Siemiginowska, A., LaMassa, S., Aldcroft, T. L., Bechtold, J., & Elvis, M. 2008, ApJ, 684, 811 [NASA ADS] [CrossRef] [Google Scholar]
  51. Soldi, S., Türler, M., Paltani, S., et al. 2008, A&A, 486, 411 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  52. Stawarz, L., Ostorero, L., Begelman, M. C., et al. 2008, ApJ, 680, 911 [NASA ADS] [CrossRef] [Google Scholar]
  53. Strüder, L., Briel, U., Dennerl, K., et al. 2001, A&A, 365, L18 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Tengstrand, O., Guainazzi, M., Siemiginowska, A., et al. 2009, A&A, 501, 89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Turner, M. J. L., Abbey, A., Arnaud, M., et al. 2001, A&A, 365, L27 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  56. Urry, C. M., & Padovani, P. 1995, PASP, 107, 803 [NASA ADS] [CrossRef] [Google Scholar]
  57. Ushio, M., Stawarz, Ł., Takahashi, T., et al. 2010, ApJ, 724, 1509 [NASA ADS] [CrossRef] [Google Scholar]
  58. Verner, D. A., Ferland, G. J., Korista, K. T., & Yakovlev, D. G. 1996, ApJ, 465, 487 [NASA ADS] [CrossRef] [Google Scholar]
  59. Vink, J., Snellen, I., Mack, K.-H., & Schilizzi, R. 2006, MNRAS, 367, 928 [NASA ADS] [CrossRef] [Google Scholar]
  60. Wilms, J., Allen, A., & McCray, R. 2000, ApJ, 542, 914 [NASA ADS] [CrossRef] [Google Scholar]
  61. Wilms, J., Juett, A. M., Schulz, N. S., & Nowak, M. A. 2012, available at http://pulsar.sternwarte.uni-erlangen.de/wilms/research/tbabs/ [Google Scholar]

All Tables

Table 1

Best-fit parameters using an absorbed power-law model with a Gaussian emission line.

Table 2

Typical high-energy spectral parameters for different source classes compared with results for PMN J1603–4904.

All Figures

thumbnail Fig. 1

Simultaneous fit to the XMM-Newton and Suzaku data (see Table 1). The data are best fit by an absorbed power-law component with an emission line at ~ 5.44 ± 0.05 keV. a) Count spectrum for all detectors fitted with an absorbed power law and a Gaussian emission line (models shown in gray). Ratio of data to model for a fit of an absorbed power law b) and including a Gaussian emission line c). d) Unfolded, combined spectrum of all data sets with the best-fit model (red). The shaded region highlights the position of the emission line.

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.