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PreprintCC BY 4.0arXiv

Through a glass, darkly: a combined framework for estimating fast radio burst host galaxy and population properties in an era of uncertain host identification

Abstract

The identification of fast radio burst (FRB) host galaxies, and subsequently their redshifts (z), has allowed the FRB dispersion measure (DM) to be used to probe the cosmological distribution of ionised gas, and study the properties of the FRB population itself. However, current methods cannot account for FRBs with uncertain host galaxy associations, leading to underutilisation of data, and potential biases towards nearby, bright hosts. In this work, we develop a methodology which can. We do so by combining three ingredients - the zDM code, for modelling the Macquart relation; PATH, for statistical host galaxy identification; and a set of models able to describe the intrinsic FRB host galaxy distribution - into a single formalism. We prove the fidelity of our formalism by using a synthetic set of FRB observations, with simulated hosts sampled from galaxy catalogues, and show that it reproduces intrinsic host galaxy properties even for FRB localisation uncertainties of 30", where a traditional PATH analysis produces no confidant host associations. When applied to a sample of FRBs localised by the Australian Square Kilometre Array Pathfinder, we confirm previous results showing that FRBs prefer host galaxies fainter than that predicted by star-formation, consistent with an exponential surface density scaling as 0.41+0.13−0.09 times the half-light radius. We encourage the application of this formalism to data-sets from other FRB-hunting instruments.

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BibTeX
@misc{james2026through,
  title = {{Through a glass, darkly: a combined framework for estimating fast radio burst host galaxy and population properties in an era of uncertain host identification}},
  author = {C. W. James and B. C. Andersen and L. Marnoch and J. L. Hoffmann and N. Loudas and J. X. Prochaska and S. D. Ryder and M. Woodland},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.04765},
  eprint = {2609.04765},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.04765},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Through a glass, darkly: a combined framework for estimating fast radio burst host galaxy and population properties in an era of uncertain host identification
AU  - C. W. James
AU  - B. C. Andersen
AU  - L. Marnoch
AU  - J. L. Hoffmann
AU  - N. Loudas
AU  - J. X. Prochaska
AU  - S. D. Ryder
AU  - M. Woodland
PY  - 2026
DA  - 2026/09/04
PB  - arXiv
DO  - 10.48550/arxiv.2609.04765
UR  - https://arxiv.org/abs/2609.04765
AB  - The identification of fast radio burst (FRB) host galaxies, and subsequently their redshifts (z), has allowed the FRB dispersion measure (DM) to be used to probe the cosmological distribution of ionised gas, and study the properties of the FRB population itself. However, current methods cannot account for FRBs with uncertain host galaxy associations, leading to underutilisation of data, and potential biases towards nearby, bright hosts. In this work, we develop a methodology which can. We do so by combining three ingredients - the zDM code, for modelling the Macquart relation; PATH, for statistical host galaxy identification; and a set of models able to describe the intrinsic FRB host galaxy distribution - into a single formalism. We prove the fidelity of our formalism by using a synthetic set of FRB observations, with simulated hosts sampled from galaxy catalogues, and show that it reproduces intrinsic host galaxy properties even for FRB localisation uncertainties of 30", where a traditional PATH analysis produces no confidant host associations. When applied to a sample of FRBs localised by the Australian Square Kilometre Array Pathfinder, we confirm previous results showing that FRBs prefer host galaxies fainter than that predicted by star-formation, consistent with an exponential surface density scaling as 0.41^+0.13_−0.09 times the half-light radius. We encourage the application of this formalism to data-sets from other FRB-hunting instruments.
ER  -