Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space

Abstract Fast radio bursts (FRBs), millisecond-duration radio transient events, possess the potential to serve as excellent cosmological probes. The FRB redshift distribution contains information about the FRB sources, providing key constraints on the types of engines. However, it is quite challenging to obtain the FRB redshifts due to the poor localization and the faintness of the host galaxies. This reality severely restricts the application prospects and study of the physical origins of FRBs. We propose that the clustering of observed FRBs can be an effective approach to address this issue without needing to accurately model dispersion measure (DM) contributions from the host galaxy and the immediate environment of the source. Using the clustering of 5 × 10 7 simulated FRBs from future observations with sensitivity similar to the second phase of the Square Kilometre Array, we show that in extragalactic DM space, the redshift distributions can be accurately reconstructed, and the mean redshift for FRBs between 384.8 and 1450.3 pc cm −3 can be constrained to ∼0.001 ± 0.003(1 + z ). The results demonstrate the potential of FRB clustering to constrain redshift distributions and provide valuable insights into FRB source models and cosmological applications.

Authors

Publication Details

Journal
The Astrophysical Journal
Published
2025-03-24
DOI
https://doi.org/10.3847/1538-4357/adbbda
Citations
3
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
3.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space

Hui Peng, Yu Yu
3 citations
The Astrophysical Journal
Pulsars and Gravitational Waves Research
3.46
article

Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space

Hui Peng, Yu Yu
article en
3 citations

Abstract

Abstract Fast radio bursts (FRBs), millisecond-duration radio transient events, possess the potential to serve as excellent cosmological probes. The FRB redshift distribution contains information about the FRB sources, providing key constraints on the types of engines. However, it is quite challenging to obtain the FRB redshifts due to the poor localization and the faintness of the host galaxies. This reality severely restricts the application prospects and study of the physical origins of FRBs. We propose that the clustering of observed FRBs can be an effective approach to address this issue without needing to accurately model dispersion measure (DM) contributions from the host galaxy and the immediate environment of the source. Using the clustering of 5 × 10 7 simulated FRBs from future observations with sensitivity similar to the second phase of the Square Kilometre Array, we show that in extragalactic DM space, the redshift distributions can be accurately reconstructed, and the mean redshift for FRBs between 384.8 and 1450.3 pc cm −3 can be constrained to ∼0.001 ± 0.003(1 + z ). The results demonstrate the potential of FRB clustering to constrain redshift distributions and provide valuable insights into FRB source models and cosmological applications.

The Astrophysical JournalVol. 982(2)
Openalex Percentile: Top 8%
Pulsars and Gravitational Waves Research
3.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space — Hui Peng, Yu Yu · The Astrophysical Journal (2025) | TGRS Research Map | TGRS