Scaling Relation between Sunyaev-Zel'dovich Effect and X-ray Luminosity and Scale-Free Evolution of Cosmic Baryon Field
Qiang Yuan (1,2), Hao-Yi Wan (1), Tong-Jie Zhang (1,3,4), Ji-Ren Liu, (4), Long-Long Feng (5,6), Li-Zhi Fang (4),((1) Department of Astronomy,, Beijing Normal University, (2) Key Laboratory of Particle Astrophysics,, Institute of High Energy Physics, Chinese Academy of Sciences

TL;DR
This paper demonstrates that the relation between the Sunyaev-Zel'dovich effect and X-ray luminosity is scale-invariant across different cosmic structures, supporting a self-similar evolution model of cosmic baryon fields.
Contribution
It provides observational and simulation evidence for the scale invariance of the $y(r)$-$L_x(r)$ relation, confirming predictions of the self-similar hierarchical scenario of nonlinear cosmic evolution.
Findings
The $y(r)$-$L_x(r)$ relation coefficients are scale-invariant.
The relation applies to both collapsed and non-collapsed regions at scales larger than dissipation.
Implications for non-gravitational heating scales are discussed.
Abstract
It has been revealed recently that, in the scale free range, i.e. from the scale of the onset of nonlinear evolution to the scale of dissipation, the velocity and mass density fields of cosmic baryon fluid are extremely well described by the self-similar log-Poisson hierarchy. As a consequence of this evolution, the relations among various physical quantities of cosmic baryon fluid should be scale invariant, if the physical quantities are measured in cells on scales larger than the dissipation scale, regardless the baryon fluid is in virialized dark halo, or in pre-virialized state. We examine this property with the relation between the Compton parameter of the thermal Sunyaev-Zel'dovich effect, , and X-ray luminosity, , where being the scale of regions in which and are measured. According to the self-similar hierarchical scenario of nonlinear…
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.
