Characterizing continuum variability in the radio-loud narrow-line Seyfert 1 galaxy IRAS 17020+4544. Issue 3 (18th June 2020)

• Record Type: Journal Article
• Authors: Gonzalez, A G; Gallo, L C; Kosec, P; Fabian, A C; Alston, W N; Berton, M; Wilkins, D R
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 496:Issue 3(2020)
• Page Start: 3708
• Page End: 3724
• Publication Date: 2020-06-18
• Subjects: galaxies: active -- galaxies: individual: IRAS 17020+4544 -- galaxies: nuclei -- X-rays: galaxies; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/staa1735
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: We present results of temporal and spectral analyses on four XMM–Newton EPIC pn observations of IRAS 17020+4544, a narrow-line Seyfert 1 galaxy with evidence of a radio jet. Analysis of the light curves reveals that this radio-loud source does not behave like the bulk population of its radio-quiet counterparts. A trend of spectral hardening with increased flux is found. Variability is found to increase with energy, though it decreases as the spectrum hardens. The first 40 ks of the most recent observation behave uniquely among the epochs, exhibiting a softer spectral state than at any other time. Possible non-stationarity at low energies is found, with no such effect present at higher energies, suggesting at least two distinct spectral components. A reverberation signature is confirmed, with the lag-frequency, lag-energy, and covariance spectra changing significantly during the soft-state epoch. The temporal analysis suggests a variable power law in the presence of a reflection component, thus motivating such a fit for the 0.3−10 keV EPIC pn spectra from all epochs. We find an acceptable spectral fit using the timing-motivated parameters and report the detection of a broad Fe K emission line, requiring an additional model component beyond the reflection spectrum. We discuss links between this source and other narrow-line Seyfert 1 sources that show evidence of jet activity, finding similarities among this currently very limited sample of interesting objects.