QUBIC: The Q & U Bolometric Interferometer for Cosmology
Journal of Low Temperature Physics Springer Science and Business Media LLC 199:1-2 (2020) 482-490
Reionization history constraints from neural network based predictions of high-redshift quasar continua
Monthly Notices of the Royal Astronomical Society Oxford University Press 493:3 (2020) 4256-4275
Abstract:
Observations of the early Universe suggest that reionization was complete by z ∼ 6, however, the exact history of this process is still unknown. One method for measuring the evolution of the neutral fraction throughout this epoch is via observing the Lyα damping wings of high-redshift quasars. In order to constrain the neutral fraction from quasar observations, one needs an accurate model of the quasar spectrum around Lyα, after the spectrum has been processed by its host galaxy but before it is altered by absorption and damping in the intervening IGM. In this paper, we present a novel machine learning approach, using artificial neural networks, to reconstruct quasar continua around Lyα. Our QSANNDRA algorithm improves the error in this reconstruction compared to the state-of-the-art PCA-based model in the literature by 14.2% on average, and provides an improvement of 6.1% on average when compared to an extension thereof. In comparison with the extended PCA model, QSANNDRA further achieves an improvement of 22.1% and 16.8% when evaluated on low-redshift quasars most similar to the two high-redshift quasars under consideration, ULAS J1120+0641 at z = 7.0851 and ULAS J1342+0928 at z = 7.5413, respectively. Using our more accurate reconstructions of these two z > 7 quasars, we estimate the neutral fraction of the IGM using a homogeneous reionization model and find x¯H1=0.25+0.05−0.05 at z = 7.0851 and x¯H1=0.60+0.11−0.11 at z = 7.5413. Our results are consistent with the literature and favour a rapid end to reionization.
Beyond the Runge-Kutta-Wentzel-Kramers-Brillouin method
Phys. Rev. D 101, 043517 (2020)
Abstract:
We explore higher-dimensional generalizations of the Runge-Kutta-Wentzel-Kramers-Brillouin method for integrating coupled systems of first-order ordinary differential equations with highly oscillatory solutions. Such methods could improve the performance and adaptability of the codes which are used to compute numerical solutions to the Einstein-Boltzmann equations. We test Magnus expansion-based methods on the Einstein-Boltzmann equations for a simple universe model dominated by photons with a small amount of cold dark matter. The Magnus expansion methods achieve an increase in run speed of about 50% compared to a standard Runge-Kutta integration method. A comparison of approximate solutions derived from the Magnus expansion and the Wentzel-Kramers-Brillouin (WKB) method implies the two are distinct mathematical approaches. Simple Magnus expansion solutions show inferior long range accuracy compared to WKB. However we also demonstrate how one can improve on the standard Magnus approach to obtain a new "Jordan-Magnus" method. This has a WKB-like performance on simple two-dimensional systems, although its higher-dimensional generalization remains elusive.
The Obelisk simulation: galaxies contribute more than AGN to HI reionization of protoclusters
(2020)