Constraining Reionization with Lyα Damping-Wing Absorption in Galaxy Spectra: A Machine Learning Model Based on Reionization Simulations
Recently, NIRSpec PRISM/CLEAR observations by JWST have begun providing rest-frame UV continuum measurements of galaxies at $z\gtrsim7$, revealing signatures of Ly$α$ damping-wing (DW) absorption by the intergalactic medium (IGM). We develop a methodology to constrain the global ionization fraction of the IGM $(Q_{\rm HII})$ using low-resolution spectra, employing the random forest classification (RFC) method. We construct mock spectra using the simulated galaxies and the IGM from the Cosmic Dawn II simulation and train RFC models to estimate $Q_{\rm HII}$ at the redshift of the source and to detect the presence of a damped Ly$α$ absorber (DLA). We find that individual galaxy spectra with spectral bins between 1220 and 1270 Å and with signal-to-noise ratios greater than 20 can place tight constraints on $Q_{\rm HII}$, provided the UV continuum is accurately modeled. This method is particularly effective for the early phase of reionization ($Q_{\rm HII}<50\%$), when the IGM opacity is high in the DW. As a demonstration, we apply our model to existing NIRSpec PRISM/CLEAR spectra, placing upper bounds of $Q_{\rm HII}=59.6\%$, $5.6\%$, and $18.5\%$ at $z=7.7,~9.4,$ and $10.6$, respectively, with $68\%$ confidence, though several modeling uncertainties remain to be discussed. These constraints favor late-starting reionization models, where $\gtrsim 80\%$ of the IGM is ionized after $z=8$. We conclude that high-SNR observations of carefully selected targets around $z\sim7-9$ can effectively constrain reionization models.