Re-acceleration Model for Radio Relics with Spectral Curvature
Hyesung Kang (1), Dongsu Ryu (2,3) ((1) Department of Earth, Sciences, Pusan National University, Korea, (2) Department of Physics, UNIST,, Korea, (3) Korea Astronomy, Space Science Institute, Korea)

TL;DR
This paper proposes a re-acceleration model for radio relics involving shock waves passing through fossil electron clouds, explaining observed spectral steepening and matching radio observations with specific shock parameters.
Contribution
It introduces a model where shock re-acceleration in finite fossil electron clouds explains spectral curvature, extending previous DSA models to account for steep spectra.
Findings
The model fits the Sausage relic's radio spectrum and brightness profile.
Shock speed and Mach number are constrained to match observations.
Steep spectra can be explained by fossil electron re-acceleration and cloud configuration.
Abstract
Most of the observed features of radio {\it gischt} relics such as spectral steepening across the relic width and power-law-like integrated spectrum can be adequately explained by diffusive shock acceleration (DSA) model, in which relativistic electrons are (re-)accelerated at shock waves induced in the intracluster medium. However, the steep spectral curvature in the integrated spectrum above GHz detected in some radio relics such as the Sausage relic in cluster CIZA J2242.8+5301 may not be interpreted by simple radiative cooling of postshock electrons. In order to understand such steepening, we here consider a model in which a spherical shock sweeps through and then exits out of a finite-size cloud with fossil relativistic electrons. The ensuing integrated radio spectrum is expected to steepen much more than predicted for aging postshock electrons, since the re-acceleration…
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.
