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A New Emulated Monte Carlo Radiative Transfer Disk-Wind Model: X-Ray Accretion Disk-wind Emulator -- XRADE
- Publication Year :
- 2022
-
Abstract
- We present a new X-Ray Accretion Disk-wind Emulator (\textsc{xrade}) based on the 2.5D Monte Carlo radiative transfer code which provides a physically-motivated, self-consistent treatment of both absorption and emission from a disk-wind by computing the local ionization state and velocity field within the flow. \textsc{xrade} is then implemented through a process that combines X-ray tracing with supervised machine learning. We develop a novel emulation method consisting in training, validating, and testing the simulated disk-wind spectra into a purposely built artificial neural network. The trained emulator can generate a single synthetic spectrum for a particular parameter set in a fraction of a second, in contrast to the few hours required by a standard Monte Carlo radiative transfer pipeline. The emulator does not suffer from interpolation issues with multi-dimensional spaces that are typically faced by traditional X-ray fitting packages such as \textsc{xspec}. \textsc{xrade} will be suitable to a wide number of sources across the black-hole mass, ionizing luminosity, and accretion rate scales. As an example, we demonstrate the applicability of \textsc{xrade} to the physical interpretation of the X-ray spectra of the bright quasar PDS 456, which hosts the best-established accretion-disk wind observed to date. We anticipate that our emulation method will be an indispensable tool for the development of high-resolution theoretical models, with the necessary flexibility to be optimized for the next generation micro-calorimeters on board future missions, like \textit{XRISM/resolve} and \textit{Athena/X-IFU}. This tool can also be implemented across a wide variety of X-ray spectral models and beyond.<br />Comment: 20 pages, 17 figures, MNRAS accepted for publication
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2207.13731
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1093/mnras/stac2155