Connecting galaxy formation and galaxy clustering

We study the environmental dependence of the formation history of dark matter haloes in a large dark matter simulation, the Millennium Run. Adopting a sensitive test of this dependence —— the marked correlation function —— reveals highly significant evidence that haloes of a given mass form earlier in denser regions. We explore the effect further using a new variant of this statistic, and confirm our results using some simpler tests made possible by the size and resolution of the simulation. We go on to study the effect of this environmental dependence on the galaxy population generated by a recent semi-analytic model run in the Millennium Run. We show that environmentally dependent halo formation imparts a small but cleanly detected change to the correlation function and void probability function of galaxies. We can model this change by applying a modulation based on local density to the halo occupation distribution of galaxies. We also note that having the correct placement scheme for galaxies within haloes is at least as important as correctly accounting for environmental effects. Two more dark matter simulations are run, and their outputs are appropriately relabelled and rescaled to represent different cosmologies. We generate consistent semi- analytic galaxy populations in these simulations, using two versions of each of three variants of our semi-analytic model. We compare the predictions for the galaxy clustering from these models to the projected two-point correlation function of the SDSS, obtaining a constraint on the amplitude of the fluctuations in the mass, σ(_8) = 0.96 士 0.05. We find that environmental effects do not significantly affect this estimate, but discuss other possible effects which might. We remark on how this result compares to other recent determinations of σ(_8)

Constraints on sigma(8) from galaxy clustering in N-body simulations and semi-analytic models

We generate mock galaxy catalogues for a grid of different cosmologies, using rescaled N-body simulations in tandem with a semi-analytic model run using consistent parameters. Because we predict the galaxy bias, rather than fitting it as a nuisance parameter, we obtain an almost pure constraint on sigma(8) by comparing the projected two-point correlation function we obtain to that from the Sloan Digital Sky Survey (SDSS). A systematic error arises because different semi-analytic modelling assumptions allow us to fit the r-band luminosity function equally well. Combining our estimate of the error from this source with the statistical error, we find sigma(8) = 0.97 +/- 0.06. We obtain consistent results if we use galaxy samples with a different magnitude threshold, or if we select galaxies by b(J)-band rather than r-band luminosity and compare to data from the 2dF Galaxy Redshift Survey (2dFGRS). Our estimate for sigma(8) is higher than that obtained for other analyses of galaxy data alone, and we attempt to find the source of this difference. We note that in any case, galaxy clustering data provide a very stringent constraint on galaxy formation models.</p

Effects Of The Ionosphere On Ground-Based Detection Of The Global 21 CM Signal From The Cosmic Dawn And The Dark Ages

Detection of the global HI 21 cm signal from Cosmic Dawn and Epoch of Reionization is the key science driver for several ongoing ground-based and future ground/space-based experiments. The crucial spectral features in the global 21 cm signal (turning points) occur at low radio frequencies <100 MHz. In addition to the human-generated RFI, Earth's ionosphere drastically corrupts low-frequency radio observations from the ground. In this paper, we examine the effects of time-varying ionospheric refraction, absorption and thermal emission at these low radio frequencies and their combined effect on any ground-based global 21 cm experiment. It should be noted that this is the first study of the effect of a dynamic ionosphere on global 21 cm experiments. The fluctuations in the ionosphere are influenced by solar activity with flicker noise characteristics. The same characteristics are reflected in the ionospheric corruption to any radio signal passing through the ionosphere. As a result, any ground based observations of the faint global 21 cm signal are corrupted by flicker noise (or "$1/f$" noise, where "$f$" is the dynamical frequency) which scales as $\nu^{-2}$ (where $\nu$ is the frequency of observation) in the presence of a bright galactic foreground ($\propto \nu^{-s}$, where $s$ is radio spectral index). Hence, the calibration of the ionosphere for any such experiment is critical. Any attempt to calibrate the ionospheric effects will be subject to the inaccuracies in the current ionospheric measurements using GPS ionospheric measurements, riometer measurements, ionospheric soundings, etc. Even considering an optimistic improvement in the accuracy of GPS-TEC (Total Electron Content) measurements, we conclude that the detection of the global 21 cm signal below 100 MHz is best done from above the Earth's atmosphere in orbit of the Moon.Comment: 15 pages, 11 figures. Submitted to The Astrophysical Journal. This is an updated version after addressing the comments from the refere

Cosmic Dawn and Epoch of Reionization Foreground Removal with the SKA

The exceptional sensitivity of the SKA will allow observations of the Cosmic Dawn and Epoch of Reionization (CD/EoR) in unprecedented detail, both spectrally and spatially. This wealth of information is buried under Galactic and extragalactic foregrounds, which must be removed accurately and precisely in order to reveal the cosmological signal. This problem has been addressed already for the previous generation of radio telescopes, but the application to SKA is different in many aspects. In this chapter we summarise the contributions to the field of foreground removal in the context of high redshift and high sensitivity 21-cm measurements. We use a state-of-the-art simulation of the SKA Phase 1 observations complete with cosmological signal, foregrounds and frequency-dependent instrumental effects to test both parametric and non-parametric foreground removal methods. We compare the recovered cosmological signal using several different statistics and explore one of the most exciting possibilities with the SKA --- imaging of the ionized bubbles. We find that with current methods it is possible to remove the foregrounds with great accuracy and to get impressive power spectra and images of the cosmological signal. The frequency-dependent PSF of the instrument complicates this recovery, so we resort to splitting the observation bandwidth into smaller segments, each of a common resolution. If the foregrounds are allowed a random variation from the smooth power law along the line of sight, methods exploiting the smoothness of foregrounds or a parametrization of their behaviour are challenged much more than non-parametric ones. However, we show that correction techniques can be implemented to restore the performances of parametric approaches, as long as the first-order approximation of a power law stands.Comment: Accepted for publication in the SKA Science Book 'Advancing Astrophysics with the Square Kilometre Array', to appear in 201

Fast Large-Scale Reionization Simulations

We present an efficient method to generate large simulations of the Epoch of Reionization (EoR) without the need for a full 3-dimensional radiative transfer code. Large dark-matter-only simulations are post-processed to produce maps of the redshifted 21cm emission from neutral hydrogen. Dark matter haloes are embedded with sources of radiation whose properties are either based on semi-analytical prescriptions or derived from hydrodynamical simulations. These sources could either be stars or power-law sources with varying spectral indices. Assuming spherical symmetry, ionized bubbles are created around these sources, whose radial ionized fraction and temperature profiles are derived from a catalogue of 1-D radiative transfer experiments. In case of overlap of these spheres, photons are conserved by redistributing them around the connected ionized regions corresponding to the spheres. The efficiency with which these maps are created allows us to span the large parameter space typically encountered in reionization simulations. We compare our results with other, more accurate, 3-D radiative transfer simulations and find excellent agreement for the redshifts and the spatial scales of interest to upcoming 21cm experiments. We generate a contiguous observational cube spanning redshift 6 to 12 and use these simulations to study the differences in the reionization histories between stars and quasars. Finally, the signal is convolved with the LOFAR beam response and its effects are analyzed and quantified. Statistics performed on this mock data set shed light on possible observational strategies for LOFAR.Comment: 18 pages, 21 figures, submitted to MNRAS For high-resolution images follow "http://www.astro.rug.nl/~thomas/eormap.pdf

Constraining the epoch of reionization with the variance statistic: simulations of the LOFAR case

Several experiments are underway to detect the cosmic redshifted 21-cm signal from neutral hydrogen from the Epoch of Reionization (EoR). Due to their very low signal-to-noise ratio, these observations aim for a statistical detection of the signal by measuring its power spectrum. We investigate the extraction of the variance of the signal as a first step towards detecting and constraining the global history of the EoR. Signal variance is the integral of the signal's power spectrum, and it is expected to be measured with a high significance. We demonstrate this through results from a simulation and parameter estimation pipeline developed for the Low Frequency Array (LOFAR)-EoR experiment. We show that LOFAR should be able to detect the EoR in 600 hours of integration using the variance statistic. Additionally, the redshift ($z_r$) and duration ($\Delta z$) of reionization can be constrained assuming a parametrization. We use an EoR simulation of $z_r = 7.68$ and $\Delta z = 0.43$ to test the pipeline. We are able to detect the simulated signal with a significance of 4 standard deviations and extract the EoR parameters as $z_r = 7.72^{+0.37}_{-0.18}$ and $\Delta z = 0.53^{+0.12}_{-0.23}$ in 600 hours, assuming that systematic errors can be adequately controlled. We further show that the significance of detection and constraints on EoR parameters can be improved by measuring the cross-variance of the signal by cross-correlating consecutive redshift bins.Comment: 13 pages, 14 figures, Accepted for publication in MNRA