Prof. Matt Jarvis

Abstract:

Tighter constraints on measurements of primordial non-Gaussianity (PNG) will allow the differentiation of inflationary scenarios. The cosmic microwave background bispectrum – the standard method of measuring the local non-Gaussianity – is limited by cosmic variance. Therefore, it is sensible to investigate measurements of non-Gaussianity using the large-scale structure. This can be done by investigating the effects of non-Gaussianity on the power spectrum on large scales. In this study, we forecast the constraints on the local PNG parameter fNL that can be obtained with future radio surveys. We utilize the multitracer method that reduces the effect of cosmic variance and takes advantage of the multiple radio galaxy populations that are differently biased tracers of the same underlying dark matter distribution. Improvements on previous work include the use of observational bias and halo mass estimates, updated simulations, and realistic photometric redshift expectations, thus producing more realistic forecasts. Combinations of Square Kilometre Array simulations and radio observations were used as well as different redshift ranges and redshift bin sizes. It was found that in the most realistic case the 1σ error on fNL falls within the range 4.07–6.58, rivalling the tightest constraints currently available.

Abstract:

<jats:title>ABSTRACT</jats:title> <jats:p>Accurate methods for reverberation mapping using photometry are highly sought after since they are inherently less resource intensive than spectroscopic techniques. However, the effectiveness of photometric reverberation mapping for estimating black hole masses is sparsely investigated at redshifts higher than z ≈ 0.04. Furthermore, photometric methods frequently assume a damped random walk (DRW) model, which may not be universally applicable. We perform photometric reverberation mapping using the javelin photometric DRW model for the QSO SDSS-J144645.44+625304.0 at z = 0.351 and estimate the Hβ lag of $65^{+6}_{-1}$ d and black hole mass of $10^{8.22^{+0.13}_{-0.15}}\, \mathrm{M_{\odot }}$. An analysis of the reliability of photometric reverberation mapping, conducted using many thousands of simulated CARMA process light curves, shows that we can recover the input lag to within 6 per cent on average given our target’s observed signal-to-noise of &amp;gt;20 and average cadence of 14 d (even when DRW is not applicable). Furthermore, we use our suite of simulated light curves to deconvolve aliases and artefacts from our QSO’s posterior probability distribution, increasing the signal-to-noise on the lag by a factor of ∼2.2. We exceed the signal-to-noise of the Sloan Digital Sky Survey Reverberation Mapping Project (SDSS-RM) campaign with a quarter of the observing time per object, resulting in a ∼200 per cent increase in signal-to-noise efficiency over SDSS-RM.</jats:p>

Abstract:

The multi-tracer technique employs a ratio of densities of two differently biased galaxy samples that trace the same underlying matter density field, and was proposed to alleviate the cosmic variance problem. Here we propose a novel application of this approach, applying it to two different tracers one of which is the 21-cm signal of neutral hydrogen from the epochs of reionization and comic dawn. The second tracer is assumed to be a sample of high-redshift galaxies, but the approach can be generalized and applied to other high-redshift tracers. We show that the anisotropy of the ratio of the two density fields can be used to measure the sky-averaged 21-cm signal, probe the spectral energy distribution of radiative sources that drive this signal, and extract large-scale properties of the second tracer, e.g., the galaxy bias. Using simulated 21-cm maps and mock galaxy samples, we find that the method works well for an idealized galaxy survey. However, in the case of a more realistic galaxy survey which only probes highly biased luminous galaxies, the inevitable Poisson noise makes the reconstruction far more challenging. This difficulty can be mitigated with the greater sensitivity of future telescopes along with larger survey volumes.

Abstract:

We present a Bayesian stacking technique to directly measure the H i mass function (HIMF) and its evolution with redshift using galaxies formally below the nominal detection threshold. We generate galaxy samples over several sky areas given an assumed HIMF described by a Schechter function and simulate the H i emission lines with different levels of background noise to test the technique. We use Multinest to constrain the parameters of the HIMF in a broad redshift bin, demonstrating that the HIMF can be accurately reconstructed, using the simulated spectral cube far below the H i mass limit determined by the 5σ flux-density limit, i.e. down to MHI = 107.5 M⊙ over the redshift range 0 < z < 0.55 for this particular simulation, with a noise level similar to that expected for the MIGHTEE survey. We also find that the constraints on the parameters of the Schechter function, φ⋆, M⋆ and α can be reliably fit, becoming tighter as the background noise decreases as expected, although the constraints on the redshift evolution are not significantly affected. All the parameters become better constrained as the survey area increases. In summary, we provide an optimal method for estimating the H i mass at cosmological distances that allows us to constrain the H i mass function below the detection threshold in forthcoming H i surveys. This study is a first step towards the measurement of the HIMF at high (z > 0.1) redshifts.

Abstract:

Hydrodynamical cosmological simulations have recently made great advances in reproducing galaxy mass assembly over cosmic time - as often quantified from the comparison of their predicted stellar mass functions to observed stellar mass functions from data. In this paper we compare the clustering of galaxies from the hydrodynamical cosmological simulated lightcone Horizon-AGN, to clustering measurements from the VIDEO survey observations. Using mocks built from a VIDEO-like photometry, we first explore the bias introduced into clustering measurements by using stellar masses and redshifts derived from SED-fitting, rather than the intrinsic values. The propagation of redshift and mass statistical and systematic uncertainties in the clustering measurements causes us to underestimate the clustering amplitude. We find then that clustering and halo occupation distribution (HOD) modelling results are qualitatively similar in Horizon-AGN and VIDEO. However at low stellar masses Horizon-AGN underestimates the observed clustering by up to a factor of ~3, reflecting the known excess stellar mass to halo mass ratio for Horizon-AGN low mass haloes, already discussed in previous works. This reinforces the need for stronger regulation of star formation in low mass haloes in the simulation. Finally, the comparison of the stellar mass to halo mass ratio in the simulated catalogue, inferred from angular clustering, to that directly measured from the simulation, validates HOD modelling of clustering as a probe of the galaxy-halo connection.