Inferring the ionizing photon contributions of high-redshift galaxies to reionization with JWST NIRCam photometry
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 537:3 (2025) staf126
Abstract:
JWST observations are providing unprecedented constraints on the history of reionization owing to the ability to detect faint galaxies at z ≫ 6. Modelling this history requires understanding both the ionizing photon production rate (ξion) and the fraction of those photons that escape into the intergalactic medium (fesc). Observational estimates of these quantities generally rely on spectroscopy for which large samples with well-defined selection functions remain limited. To overcome this challenge, we present and release a novel implicit likelihood inference pipeline, PHOTONIOn, trained on mock photometry to predict the escaped ionizing luminosity of individual galaxies (N ion) based on photometric magnitudes and redshifts. We show that PHOTONIOn is able to reliably infer N ion from photometry. This is in contrast to traditional spectral energy distribution-fitting approaches which rely on fesc prescriptions that often overpredict N ion for Lyman Continuum (LyC)-dim galaxies, even when given access to spectroscopic data. We have deployed PHOTONIOn on a sample of 4559 high-redshift galaxies from the JWST Advanced Deep Extragalactic Survey (JADES), finding gentle redshift evolutions of log10(N ion) = (0.08 ± 0.01)z + (51.60 ± 0.06) and log10(fescξion) = (0.07 ± 0.01)z + (24.12 ± 0.07). Late-time values for the ionizing photon production rate density are consistent with both theoretical models and observations. Finally, we measure the evolution of the intergalactic medium ionized fraction to find that observed populations of star-forming galaxies are capable of driving reionization in this field to completion by z ∼ 5.3 without the need for active galactic nucleus or other exotic sources, consistent with other studies of the same field. The 20 per cent of UV-brightest galaxies (MUV < −18.5) reionize roughly 35 per cent of the survey volume, demonstrating that UV faint LyC emitters are crucial for reionization.The Prevalence of Star-forming Clumps as a Function of Environmental Overdensity in Local Galaxies
The Astrophysical Journal American Astronomical Society 979:2 (2025) 118
Abstract:
At the peak of cosmic star formation (1 ≲ z ≲ 2), the majority of star-forming galaxies hosted compact, star-forming clumps, which were responsible for a large fraction of cosmic star formation. By comparison, ≲5% of local star-forming galaxies host comparable clumps. In this work, we investigate the link between the environmental conditions surrounding local (z < 0.04) galaxies and the prevalence of clumps in these galaxies. To obtain our clump sample, we use a Faster R-CNN object detection network trained on the catalog of clump labels provided by the Galaxy Zoo: Clump Scout project, then apply this network to detect clumps in approximately 240,000 Sloan Digital Sky Survey galaxies (originally selected for Galaxy Zoo 2). The resulting sample of 41,445 u-band bright clumps in 34,246 galaxies is the largest sample of clumps yet assembled. We then select a volume-limited sample of 9964 galaxies and estimate the density of their local environment using the distance to their projected fifth nearest neighbor. We find a robust correlation between environment and the clumpy fraction (f clumpy) for star-forming galaxies (specific star formation rate, sSFR > 10−2 Gyr−1) but find little to no relationship when controlling for galaxies’ sSFR or color. Further, f clumpy increases significantly with sSFR in local galaxies, particularly above sSFR > 10−1 Gyr−1. We posit that a galaxy’s gas fraction primarily controls the formation and lifetime of its clumps, and that environmental interactions play a smaller role.Fast Projected Bispectra: the filter-square approach
The Open Journal of Astrophysics Maynooth University 8 (2025)
Abstract:
<jats:p>The study of third-order statistics in large-scale structure analyses has been hampered by the increased complexity of bispectrum estimators (compared to power spectra), the large dimensionality of the data vector, and the difficulty in estimating its covariance matrix. In this paper we present the filtered-squared bispectrum (FSB), an estimator of the projected bispectrum effectively consisting of the cross-correlation between the square of a field filtered on a range of scales and the original field. Within this formalism, we are able to recycle much of the infrastructure built around power spectrum measurement to construct an estimator that is both fast and robust against mode-coupling effects caused by incomplete sky observations. Furthermore, we demonstrate that the existing techniques for the estimation of analytical power spectrum covariances can be used within this formalism to calculate the bispectrum covariance at very high accuracy, naturally accounting for the most relevant Gaussian and non-Gaussian contributions in a model-independent manner.</jats:p>Fast projected bispectra: the filter-square approach
Open Journal of Astrophysics Maynooth Academic Publishing 8 (2025)
Abstract:
The study of third-order statistics in large-scale structure analyses has been hampered by the increased complexity of bispectrum estimators (compared to power spectra), the large dimensionality of the data vector, and the difficulty in estimating its covariance matrix. In this paper we present the filtered-squared bispectrum (FSB), an estimator of the projected bispectrum effectively consisting of the cross-correlation between the square of a field filtered on a range of scales and the original field. Within this formalism, we are able to recycle much of the infrastructure built around power spectrum measurement to construct an estimator that is both fast and robust against mode-coupling effects caused by incomplete sky observations. Furthermore, we demonstrate that the existing techniques for the estimation of analytical power spectrum covariances can be used within this formalism to calculate the bispectrum covariance at very high accuracy, naturally accounting for the most relevant Gaussian and non-Gaussian contributions in a model-independent manner.
Predicting Interstellar Object Chemodynamics with Gaia
Astronomical Journal American Astronomical Society 169:2 (2025) 78