REVIEW 2 cited by
Photon-conserving Comptonization in simulations of accretion disks around black holes
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Photon-conserving Comptonization in simulations of accretion disks around black holes
read the original abstract
We introduce a new method for treating Comptonization in computational fluid dynamics. By construction, this method conserves the number of photons. Whereas the traditional "blackbody Comptonization" approach assumes that the radiation is locally a perfect blackbody and therefore uses a single parameter, the radiation temperature, to describe the radiation, the new "photon-conserving Comptonization" approach treats the photon gas as a Bose-Einstein fluid and keeps track of both the radiation temperature and the photon number density. We have implemented photon-conserving Comptonization in the general relativistic radiation magnetohydrodynamical code KORAL and we describe its impact on simulations of mildly super-critical black hole accretion disks. We find that blackbody Comptonization underestimates the gas and radiation temperature by up to a factor of two compared to photon-conserving Comptonization. This discrepancy could be serious when computing spectra. The photon-conserving simulation indicates that the spectral color correction factor of the escaping radiation in the funnel region of the disk could be as large as 5.
Forward citations
Cited by 2 Pith papers
-
Little Red Dots as Hidden Neutrino Sources
Little Red Dots can contribute ~30% of the diffuse neutrino background at TeV-sub-PeV energies through photomeson production in black hole envelopes, with modified flavor ratios at higher energies.
-
Identifying Observational Signatures of Flux Eruption Events in Supermassive Black Hole Accretion Flows with Machine Learning
Machine learning on simulated images identifies that flux eruption events cause more diffuse, polarized, lower-flux millimeter emission with decreased Q-U loop rotation rate, achieving ~80% accuracy with random forest...
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.