{"paper":{"title":"A New Emulated Monte Carlo Radiative Transfer Disk-Wind Model: X-Ray Accretion Disk-wind Emulator -- XRADE","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.GA","astro-ph.IM"],"primary_cat":"astro-ph.HE","authors_text":"D. Barret, E. Kammoun, E. Nardini, G. A. Matzeu, J. N. Reeves, J. P\\'erez Cabrera, M. Brusa, M. Dadina, M. Giustini, M. Lieu, M. L. Parker, M. T. Costa, P. G. Boorman, R. Middei, S. A. Sim, S. Marchesi, V. Braito","submitted_at":"2022-07-27T18:13:42Z","abstract_excerpt":"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 tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.13731","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.13731/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}