Evolution of the AGN UV luminosity function from redshift 7.5

Determinations of the UV luminosity function of AGN at high redshifts are important for constraining the AGN contribution to reionization and understanding the growth of supermassive black holes. Recent inferences of the luminosity function suffer from inconsistencies arising from inhomogeneous selection and analysis of AGN data. We address this problem by constructing a sample of more than 80,000 colour-selected AGN from redshift z=0 to 7.5. While this sample is composed of multiple data sets with spectroscopic redshifts and completeness estimates, we homogenise these data sets to identical cosmologies, intrinsic AGN spectra, and magnitude systems. Using this sample, we derive the AGN UV luminosity function from redshift z=0 to 7.5. The luminosity function has a double power law form at all redshifts. The break magnitude $M_*$ of the AGN luminosity function shows a steep brightening from $M_*\sim -24$ at z=0.7 to $M_*\sim -29$ at z=6. The faint-end slope $\beta$ significantly steepens from $-1.7$ at $z<2.2$ to $-2.4$ at $z\simeq 6$. In spite of this steepening, the contribution of AGN to the hydrogen photoionization rate at $z\sim 6$ is subdominant (< 3%), although it can be non-negligible (~10%) if these luminosity functions hold down to $M_{1450}=-18$. Under reasonable assumptions, AGN can reionize HeII by redshift z=2.9. At low redshifts (z<0.5), AGN can produce about half of the hydrogen photoionization rate inferred from the statistics of HI absorption lines in the IGM. Our global analysis of the luminosity function also reveals important systematic errors in the data, particularly at z=2.2--3.5, which need to be addressed and incorporated in the AGN selection function in future in order to improve our results. We make various fitting functions, luminosity function analysis codes, and homogenised AGN data publicly available.Comment: 30 pages, 15 figures; accepted in MNRAS; code, data, and various fits at https://github.com/gkulkarni/QL

Joint Bayesian Estimation of Quasar Continua and the Lyman-Alpha Forest Flux Probability Distribution Function

We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Ly$\alpha$ forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear Principal Component Analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation $\gamma-1$, while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method recovers the underlying quasar continua to a precision of $\simeq7\%$ and $\simeq10\%$ at $z=3$ and $z=5$, respectively. Given the number of principal component spectra, this is comparable to the underlying accuracy of the PCA model itself. Most importantly, we show that we can achieve a nearly unbiased estimate of the slope $\gamma-1$ of the IGM temperature-density relation with a precision of $\pm8.6\%$ at $z=3$, $\pm6.1\%$ at $z=5$, for an ensemble of ten mock high-resolution quasar spectra. Applying this method to real quasar spectra and comparing to a more realistic IGM model from hydrodynamical simulations would enable precise measurements of the thermal and cosmological parameters governing the IGM, albeit with somewhat larger uncertainties given the increased flexibility of the model.Comment: 21 pages (+ Appendix), accepted at Ap