arXiv subjects

Sultan Hassan

Publications and source records attributed to Sultan Hassan.

43 records · Page 3Linked to original sources

arXiv2020

Testing Galaxy Formation Simulations with Damped Lyman-$α$ Abundance and Metallicity Evolution

We examine the properties of damped Lyman-$α$ absorbers (DLAs) emerging from a single set of cosmological initial conditions in two state-of-the-art cosmological hydrodynamic simulations: {\sc Simba} and {\sc Technicolor Dawn}. The former includes star formation and black hole feedback treatments that yield a good match with low-redshift galaxy properties, while the latter uses multi-frequency radiative transfer to model an inhomogeneous ultraviolet background (UVB) self-consistently and is calibrated to match the Thomson scattering optical depth, UVB amplitude, and Ly-$α$ forest mean transmission at $z>5$. Both simulations are in reasonable agreement with the measured stellar mass and star formation rate functions at $z\geq 3$, and both reproduce the observed neutral hydrogen cosmological mass density, $Ω_{\rm HI}(z)$. However, the DLA abundance and metallicity distribution are sensitive to the galactic outflows' feedback and the UVB amplitude. Adopting a strong UVB and/or slow outflows under-produces the observed DLA abundance, but yields broad agreement with the observed DLA metallicity distribution. By contrast, faster outflows eject metals to larger distances, yielding more metal-rich DLAs whose observational selection may be more sensitive to dust bias. The DLA metallicity distribution in models adopting an ${\rm H}_2$-regulated star formation recipe includes a tail extending to $[M/H] \ll -3$, lower than any DLA observed to date, owing to curtailed star formation in low-metallicity galaxies. Our results show that DLA observations play an imporant role in constraining key physical ingredients in galaxy formation models, complementing traditional ensemble statistics such as the stellar mass and star formation rate functions.

astro-ph.GA↗

arXiv2020

ARTIST: Fast radiative transfer for large-scale simulations of the epoch of reionisation

We introduce the "Asymmetric Radiative Transfer In Shells Technique" (ARTIST), a new method for photon propagation on large scales that explicitly conserves photons, propagates photons at the speed of light, approximately accounts for photon directionality, and closely reproduces results of more detailed radiative transfer (RT) codes. Crucially, it is computationally fast enough to evolve the large cosmological volumes required to predict the 21cm power spectrum on scales that will be probed by future experiments targeting the Epoch of Reionisation (EoR). Most semi-numerical models aimed at predicting the EoR 21cm signal make use of an excursion set formalism (ESF) approach, which achieves computational viability by compromising on photon conservation, constraining ionised regions to be spherical by construction, and not accounting for light-travel time. By implementing our RT method within the semi-numerical code SimFast21, we show that ARTIST predicts a significantly different evolution for the EoR ionisation field compared to the code's native ESF. In particular, ARTIST predicts a more gradual evolution of the volume-averaged ionisation fraction, and up to an order-of-magnitude difference in the ionisation power, depending on the physical parameters assumed. Its application to large-scale EoR simulations will therefore allow more physically-motivated constraints to be obtained for key EoR parameters, such as the escape fraction.

astro-ph.CO↗

arXiv2018

Identifying Reionization Sources from 21cm Maps using Convolutional Neural Networks

Active Galactic Nuclei (AGN) and star-forming galaxies are leading candidates for being the luminous sources that reionized our Universe. Next-generation 21cm surveys are promising to break degeneracies between a broad range of reionization models, hence revealing the nature of the source population. While many current efforts are focused on a measurement of the 21cm power spectrum, some surveys will also image the 21cm field during reionization. This provides further information with which to determine the nature of reionizing sources. We create a Convolutional Neural Network (CNN) that is efficiently able to distinguish between 21cm maps that are produced by AGN versus galaxies scenarios with an accuracy of 92-100%, depending on redshift and neutral fraction range. An exception to this is when our Universe is highly ionized, since the source models give near-identical 21cm maps in that case. When adding thermal noise from typical 21cm experiments, the classification accuracy depends strongly on the effectiveness of foreground removal. Our results show that if foregrounds can be removed reasonably well, SKA, HERA and LOFAR should be able to discriminate between source models with greater accuracy at a fixed redshift. Only future SKA 21cm surveys are promising to break the degeneracies in the power spectral analysis.

astro-ph.CO↗

arXiv2018

Reionization Models Classifier using 21cm Map Deep Learning

Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to constrain the contribution of different reionizing sources populations to cosmic reionization. Using Convolutional Neural Networks, we present a simple network architecture that is sufficient to discriminate between Galaxy-dominated versus AGN-dominated models, even in the presence of simulated noise from different experiments such as the HERA and SKA.

astro-ph.CO↗

arXiv2017

Constraining the contribution of active galactic nuclei to reionisation

Recent results have suggested that active galactic nuclei (AGN) could provide enough photons to reionise the Universe. We assess the viability of this scenario using a semi-numerical framework for modeling reionisation, to which we add a quasar contribution by constructing a Quasar Halo Occupation Distribution (QHOD) based on Giallongo et al. observations. Assuming a constant QHOD, we find that an AGN-only model cannot simultaneously match observations of the optical depth $τ_e$, neutral fraction, and ionising emissivity. Such a model predicts $τ_e$ too low by $\sim 2σ$ relative to Planck constraints, and reionises the Universe at $z\lesssim 5$. Arbitrarily increasing the AGN emissivity to match these results yields a strong mismatch with the observed ionising emissivity at $z\sim 5$. If we instead assume a redshift-independent AGN luminosity function yielding an emissivity evolution like that assumed in Madau & Haardt model, then we can match $τ_e$ albeit with late reionisation, however such evolution is inconsistent with observations at $z\sim 4-6$ and poorly motivated physically. These results arise because AGN are more biased towards massive halos than typical reionising galaxies, resulting in stronger clustering and later formation times. AGN-dominated models produce larger ionising bubbles that are reflected in $\sim\times 2$ more 21cm power on all scales. A model with equal parts galaxies and AGN contribution is still (barely) consistent with observations, but could be distinguished using next-generation 21cm experiments HERA and SKA-low. We conclude that, even with recent claims of more faint AGN than previously thought, AGN are highly unlikely to dominate the ionising photon budget for reionisation.

astro-ph.CO↗

arXiv2017

Epoch of Reionisation 21cm Forecasting From MCMC-Constrained Semi-Numerical Models

The recent low value of Planck (2016) integrated optical depth to Thomson scattering suggests that the reionization occurred fairly suddenly, disfavoring extended reionization scenarios. This will have a significant impact on the 21cm power spectrum. Using a semi-numerical framework, we improve our model from Hassan et al. (2016) to include time-integrated ionisation and recombination effects, and find that this leads to more sudden reionisation. It also yields larger HII bubbles which leads to an order of magnitude more 21cm power on large scales, while suppressing the small scale ionization power. Local fluctuations in the neutral hydrogen density play the dominant role in boosting the 21cm power spectrum on large scales, while recombinations are subdominant. We use a Monte Carlo Markov Chain approach to constrain our model to observations of the star formation rate functions at z = 6,7,8 from Bouwens et al. (2015), the Planck (2016) optical depth measurements, and the Becker & Bolton (2013) ionising emissivity data at z~5. We then use this constrained model to perform 21cm forecasting for LOFAR, HERA, and SKA in order to determine how well such data can characterise the sources driving reionisation. We find that the 21cm power spectrum alone can somewhat constrain the halo mass dependence of ionising sources, the photon escape fraction and ionising amplitude, but combining the 21cm data with other current observations enables us to separately constrain all these parameters. Our framework illustrates how 21cm data can play a key role in understanding the sources and topology of reionisation as observations improve.

astro-ph.CO↗

arXiv2016

Simulating the 21-cm signal from reionisation including non-linear ionisations and inhomogeneous recombinations

We explore the impact of incorporating physically motivated ionisation and recombination rates on the history and topology of cosmic reionisation, by incorporating inputs from small-volume hydrodynamic simulations into a semi-numerical code, SimFast21, that evolves reionisation on large scales. We employ radiative hydrodynamic simulations to parameterize the ionisation rate Rion and recombination rate Rrec as functions of halo mass, overdensity and redshift. We find that Rion is super-linearly dependent on halo mass (Rion ~ Mh^1.41), in contrast to previous assumptions. We implement these scalings into SimFast21 to identify the ionized regions. We tune our models to be consistent with recent observations of the optical depth, ionizing emissivity, and neutral fraction by the end of reionisation. We require an average photon escape fraction fesc=0.04 within ~ 0.5 cMpc cells, independent of halo mass or redshift, to simultaneously match these data. We present predictions for the 21cm power spectrum, and show that it is converged with respect to simulation volume. We find that introducing superlinearly mass-dependent ionisations increases the duration of reionisation and boosts the small-scale 21cm power by ~ 2-3 at intermediate phases of reionisation. Introducing inhomogeneous recombinations reduces ionised bubble sizes and suppresses large-scale 21cm power by ~ 2-3. Moreover, gas clumping on sub-cell scales has a minimal effect on the 21cm power, indicating that robust predictions do not depend on the behaviour of kpc-scale structures. The superlinear ionisations significantly increase the median halo mass scale for ionising photon output to >10^10 Mo, giving greater hope for detecting most of ionising sources with next-generation facilities. These results highlight the importance of more accurately treating ionising sources and recombinations for modeling reionisation and its 21cm signal.

astro-ph.CO↗