Inferring the Ionizing Photon Contributions of High-Redshift Galaxies to Reionization with JWST NIRCam Photometry
Nicholas Choustikov, Richard Stiskalek, Aayush Saxena, Harley Katz,, Julien Devriendt, Adrianne Slyz

TL;DR
This paper introduces PHOTONIOn, a new photometry-based inference pipeline that reliably estimates the ionizing photon output of high-redshift galaxies, shedding light on their role in cosmic reionization.
Contribution
The paper presents PHOTONIOn, an implicit likelihood inference method trained on mock data, which accurately predicts ionizing luminosity from photometry, outperforming traditional SED-fitting approaches.
Findings
PHOTONIOn reliably infers ionizing photon rates from photometry.
High-redshift galaxies can reionize the universe by z~5.3 without exotic sources.
UV-faint galaxies significantly contribute to reionization.
Abstract
JWST is providing constraints on the history of reionization owing to its ability to detect faint galaxies at . Modeling this history requires understanding both the ionizing photon production rate () and the fraction of those photons that escape into the intergalactic medium (). Observational estimates of these quantities generally rely on spectroscopy for which large samples with well-defined selection functions are limited. To overcome this challenge, we present and release an implicit likelihood inference pipeline, PHOTONIOn, trained on mock photometry to predict the escaped ionizing luminosity of individual galaxies () based on photometric magnitudes and redshifts. We show that PHOTONIOn is able to reliably infer from photometry. This is in contrast to traditional SED-fitting approaches which rely on $f_{\rm…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Gamma-ray bursts and supernovae · Astronomical Observations and Instrumentation
