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University of Cambridge > Talks.cam > Institute of Astronomy Seminars > Understanding wind-mode feedback in the X-ray brightest AGN
Understanding wind-mode feedback in the X-ray brightest AGNAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Dr Giovanni Rosotti. A crucial missing piece in our understanding of AGN feedback is the physics of accretion-driven black hole winds. These fast, highly ionized, energetic winds, which can dramatically impact their host galaxies, imprint their physical states in absorption features seen in the X-ray band. In order to robustly map the ionization, velocity and density structure of these powerful outflows, as well as their duty cycles, high signal-to-noise, high spectral resolution data are required, spanning multiple epochs; and where such data are available, their modelling can present many challenges. In this talk I will introduce an improved approach to modelling deep X-ray spectra for nearby AGN , wherein the ionizing spectrum and absorption by winds are treated self-consistently within an MCMC analysis. This provides substantial improvements in our ability to explore parameter space and to recover the covariance between the emission and absorption parameters. For the first time, we are able to perform robust model selection, allowing us to establish how many wind components are required by the data. By way of example, we apply our approach to a new, deep observation of the Seyfert-1 galaxy NGC 4051 (700 ks of Chandra HETG ), where we successfully map multiple absorbing components moving at ~few 1000 km/s, and, with the use of archival data, track their temporal evolution. Future work will extend the analysis to a population study of the physical structure and duty cycles of disk winds in local AGN , and serve as a pathfinder for future high spectral resolution X-ray missions, including XRISM , Arcus, and ATHENA . This talk is part of the Institute of Astronomy Seminars series. This talk is included in these lists:
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