Percent-level timing of reionisation: Self-consistent, implicit-likelihood inference from XQR-30+ Lyα forest data

Abstract The Lyman alpha (Ly $\alpha$ ) forest in the spectra of $z\gt5$ quasars provides a powerful probe of the late stages of the epoch of reionisation (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Ly $\alpha$ opacity. Here we introduce a Bayesian analysis framework that forward-models large-scale lightcones of intergalactic medium (IGM) properties and accounts for unresolved sub-structure in the Ly $\alpha$ opacity by calibrating to higher-resolution hydrodynamic simulations. Our models directly connect physically intuitive galaxy properties with the corresponding IGM evolution, without having to tune ‘effective’ parameters or calibrate out the mean transmission. The forest data, in combination with UV luminosity functions and the CMB optical depth, are able to constrain global IGM properties at percent level precision in our fiducial model. Unlike many other works, we recover the forest observations without invoking a rapid drop in the ionising emissivity from $z\sim7$ to 5.5, which we attribute to our sub-grid model for recombinations. In this fiducial model, reionisation ends at $z=5.44\pm0.02$ and the EoR mid-point is at $z=7.7\pm0.1$ . The ionising escape fraction increases towards faint galaxies, showing a mild redshift evolution at fixed UV magnitude, $M_\textrm{UV}$ . Half of the ionising photons are provided by galaxies fainter than $M_\textrm{UV} \sim -12$ , well below direct detection limits of optical/NIR instruments including $\textit{ JWST}$ . We also show results from an alternative galaxy model that does not allow for a redshift evolution in the ionising escape fraction. Despite being decisively disfavoured by the Bayesian evidence, the posterior of this model is in qualitative agreement with that from our fiducial model. We caution, however, that our conclusions regarding the early stages of the EoR and which sources reionised the Universe are more model-dependent.

Authors

Institutions

Publication Details

Journal
Publications of the Astronomical Society of Australia
Published
2025-01-01
DOI
https://doi.org/10.1017/pasa.2025.35
Citations
18
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
14.51

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Percent-level timing of reionisation: Self-consistent, implicit-likelihood inference from XQR-30+ Lyα forest data

Prakash Gaikwad, Fabian Walter, M. Bischetti, Sindhu Satyavolu et al.
18 citations
Publications of the Astronomical Society of Australia
Protein Structure and Dynamics
14.51
article

Percent-level timing of reionisation: Self-consistent, implicit-likelihood inference from XQR-30+ Lyα forest data

Prakash Gaikwad, Fabian Walter, M. Bischetti, Sindhu Satyavolu, Martin G. Haehnelt, Emma Ryan‐Weber, Frederick B. Davies, David Prelogović, Yongda Zhu, Samuel Lai, Sarah E. I. Bosman, Andrei Mesinger, Yuxiang Qin, V. D’Odorico, George D. Becker, Laura C. Keating
article en
18 citations

Abstract

Abstract The Lyman alpha (Ly $\alpha$ ) forest in the spectra of $z\gt5$ quasars provides a powerful probe of the late stages of the epoch of reionisation (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Ly $\alpha$ opacity. Here we introduce a Bayesian analysis framework that forward-models large-scale lightcones of intergalactic medium (IGM) properties and accounts for unresolved sub-structure in the Ly $\alpha$ opacity by calibrating to higher-resolution hydrodynamic simulations. Our models directly connect physically intuitive galaxy properties with the corresponding IGM evolution, without having to tune ‘effective’ parameters or calibrate out the mean transmission. The forest data, in combination with UV luminosity functions and the CMB optical depth, are able to constrain global IGM properties at percent level precision in our fiducial model. Unlike many other works, we recover the forest observations without invoking a rapid drop in the ionising emissivity from $z\sim7$ to 5.5, which we attribute to our sub-grid model for recombinations. In this fiducial model, reionisation ends at $z=5.44\pm0.02$ and the EoR mid-point is at $z=7.7\pm0.1$ . The ionising escape fraction increases towards faint galaxies, showing a mild redshift evolution at fixed UV magnitude, $M_\textrm{UV}$ . Half of the ionising photons are provided by galaxies fainter than $M_\textrm{UV} \sim -12$ , well below direct detection limits of optical/NIR instruments including $\textit{ JWST}$ . We also show results from an alternative galaxy model that does not allow for a redshift evolution in the ionising escape fraction. Despite being decisively disfavoured by the Bayesian evidence, the posterior of this model is in qualitative agreement with that from our fiducial model. We caution, however, that our conclusions regarding the early stages of the EoR and which sources reionised the Universe are more model-dependent.

Publications of the Astronomical Society of AustraliaVol. 42
University of California, Riverside (US), Australian National University (AU), Tata Institute of Fundamental Research (IN), Commonwealth Scientific and Industrial Research Organisation (AU), University of Arizona (US), Scuola Internazionale Superiore di Studi Avanzati (IT), University of Trieste (IT), Scuola Normale Superiore (IT), Institute for High Energy Physics (ES), Heidelberg University (DE), National Radio Astronomy Observatory (US), Trieste Astronomical Observatory (IT), Health Sciences and Nutrition (AU), Max Planck Institute for Astronomy (DE), Institute of Astronomy (RU), Swinburne University of Technology (AU), University of Edinburgh (GB)
Science and Technology Facilities Council, National Cancer Institute
Openalex Percentile: Top 1%
Protein Structure and Dynamics
14.51
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.