Statistical features of multiple Compton scattering in a strong magnetic field
Alexander A. Mushtukov, Ivan D. Markozov, Valery F. Suleimanov,, Dmitrij I. Nagirner, Alexander D. Kaminker, Alexander. Y. Potekhin, Simon, Portegies Zwart

TL;DR
This study uses Monte Carlo simulations to analyze how strong magnetic fields influence Compton scattering of polarized X-ray radiation, revealing detailed effects on photon energy distribution and momentum transfer in neutron star environments.
Contribution
It provides new insights into the statistical features of magnetic Compton scattering, including energy redistribution and momentum transfer, considering polarization, electron temperature, and bulk velocity effects.
Findings
Photons near the cyclotron energy tend to have energies close to the cyclotron energy with small dispersion.
Photon redistribution within the Doppler core differs from complete redistribution.
Electron gas temperature and bulk velocity significantly affect momentum transfer efficiency.
Abstract
Compton scattering is a key process shaping spectra formation and accretion flow dynamics in accreting strongly magnetized neutron stars. A strong magnetic field affects the scattering cross section and makes it dependent on photon energy, momentum, and polarization state. Using Monte Carlo simulations, we investigate statistical features of Compton scattering of polarized X-ray radiation in a strong magnetic field. Our analysis is focused on photon gas behaviour well inside the scattering region. We take into account the resonant scattering at the fundamental cyclotron frequency, thermal distribution of electrons at the ground Landau level, and bulk velocity of the electron gas. We show that (i) the photons scattered around the cyclotron energy by the electron gas at rest tend to acquire the final energy close to the cyclotron one with a very small dispersion measure; (ii) the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
