Issue |
A&A
Volume 683, March 2024
|
|
---|---|---|
Article Number | A71 | |
Number of page(s) | 19 | |
Section | Cosmology (including clusters of galaxies) | |
DOI | https://doi.org/10.1051/0004-6361/202347139 | |
Published online | 08 March 2024 |
The dispersion measure contributions of the cosmic web
1
Max-Planck-Institute für Radioastronomie, Auf dem Hügel 69, 53121 Bonn, Germany
e-mail: cwalker@mpifr-bonn.mpg.de; lspitler@mpifr-bonn.mpg.de
2
Department of Physics, Stellenbosch University, Matieland 7602, South Africa
e-mail: mayinzhe@sun.ac.za
3
Xinjiang Astronomical Observatory, Chinese Academy of Sciences, Urumqi 830011, PR China
4
Instituto de Astrofisica, Facultad de Ciencias Exactas, Universidad Andres Bello, Fernandez Concha 700, Santiago, Chile
5
Physics and Astronomy Department Galileo Galilei, University of Padova, Vicolo dell’Osservatorio 3, 35122 Padova, Italy
6
INFN – Padova, Via Marzolo 8, 35131 Padova, Italy
7
TAPIR, California Institute of Technology, Pasadena, CA 91125, USA
Received:
9
June
2023
Accepted:
14
September
2023
Context. The large-scale distribution of baryons, commonly referred to as the cosmic web, is sensitive to gravitational collapse, mergers, and galactic feedback processes, and its large-scale structure (LSS) can be classified as halos, filaments, and voids. Fast radio bursts (FRBs) are extragalactic transient radio sources that undergo dispersion along their propagation paths. These systems provide insight into ionised matter along their sightlines by virtue of their dispersion measures (DMs), and have been investigated as probes of the LSS baryon fraction, the diffuse baryon distribution, and of cosmological parameters. Such efforts are highly complementary to the study of intergalactic medium (IGM) through X-ray observations, the Sunyaev-Zeldovich effect, and galaxy populations.
Aims. We use the cosmological simulation IllustrisTNG to study FRB DMs accumulated while traversing different types of LSS.
Methods. We combined methods for deriving electron density, classifying LSS, and tracing FRB sightlines through TNG300-1. We identified halos, filaments, voids, and collapsed structures along randomly selected sightlines, and calculated their DM contributions.
Results. We present a comprehensive analysis of the redshift-evolving cosmological DM components of the cosmic web. We find that the filamentary contribution to DM dominates, increasing from ∼71% to ∼80% on average for FRBs originating at z = 0.1 versus z = 5, while the halo contribution falls, and the void contribution remains consistent to within ∼1%. The majority of DM variance between sightlines originates from halo and filamentary environments, potentially making void-only sightlines more precise probes of cosmological parameters. We find that, on average, an FRB originating at z = 1 will intersect ∼1.8 foreground collapsed structures of any mass, with this value increasing to ∼12.4 structures for an FRB originating at z = 5. The measured impact parameters between our sightlines and TNG structures of any mass appear consistent with those reported for likely galaxy-intersecting FRBs. However, we measure lower average accumulated DMs from these structures than the ∼90 pc cm−3 DM excesses reported for these literature FRBs, indicating that some of this DM may arise from beyond the structures themselves.
Key words: methods: statistical / galaxies: halos / intergalactic medium / large-scale structure of Universe
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe to Open model.
Open access funding provided by Max Planck Society.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.