Mock Galaxy Catalogues And Their Application To Future Galaxy Surveys

We present a method for constructing end-to-end mock galaxy catalogues using a semi-analytical model of galaxy formation, applied to the halo merger trees extracted from a cosmological N-body simulation. These mocks are lightcone catalogues, which incorporate the evolution of galaxy properties with cosmic time. Interpolation is used to determine the epoch at which a galaxy will appear in the past lightcone of the observer. We discuss several applications of mock catalogues. Firstly, we consider the effectiveness of the BzK colour selection technique. The mock catalogue predictions are in reasonable agreement with the observed number counts of BzK galaxies. We predict that over 75 per cent of the model galaxies with K≤23, and redshift 1.4<z<2.5, are selected by the BzK technique. Interloper galaxies, outside the target redshift range, are predicted to dominate bright samples of BzK galaxies (i.e. with K≤21). Fainter K-band cuts are necessary to reduce the predicted interloper fraction. Secondly, we use a mock catalogue to calibrate a galaxy group-finding algorithm, via an objective method based upon the recovery of the distributions of several, easily measurable group properties. We find that it is extremely difficult to determine unique values for the linking lengths by minimising the χ^2 statistic for individual properties, and that it is necessary to combine χ^2 for more than one group property to reduce the parameter space. However, based upon our calibration, we conclude that the optimal linking lengths depend upon the multiplicity of the groups and the group property that one wishes to recover. For our final application, we use a lightcone catalogue to estimate the cosmology-independent angular correlation function, ω(θ), for samples of galaxies, selected in bins of apparent magnitude, in a thin redshift slice comparable to the size of photometric redshift errors. We compare our estimates of ω(θ) with the GALFORM predictions of the 3-dimensional real-space and redshift-space correlation functions. The amplitude of the real-space and redshift-space correlation functions display a trend with increasing luminosity. However, this trend is less clear in ω(θ) due to noisy estimates for the brightest two apparent magnitudes bins

Predicting H{\alpha} emission line galaxy counts for future galaxy redshift surveys

Knowledge of the number density of H$\alpha$ emitting galaxies is vital for assessing the scientific impact of the Euclid and WFIRST missions. In this work we present predictions from a galaxy formation model, Galacticus, for the cumulative number counts of H$\alpha$-emitting galaxies. We couple Galacticus to three different dust attenuation methods and examine the counts using each method. A $\chi^2$ minimisation approach is used to compare the model predictions to observed galaxy counts and calibrate the dust parameters. We find that weak dust attenuation is required for the Galacticus counts to be broadly consistent with the observations, though the optimum dust parameters return large values for $\chi^2$, suggesting that further calibration of Galacticus is necessary. The model predictions are also consistent with observed estimates for the optical depth and the H$\alpha$ luminosity function. Finally we present forecasts for the redshift distributions and number counts for two Euclid-like and one WFIRST-like survey. For a Euclid-like survey with redshift range $0.9\leqslant z\leqslant 1.8$ and H$\alpha+{\rm [NII]}$ blended flux limit of $2\times 10^{-16}{\rm erg}\,{\rm s}^{-1}\,{\rm cm}^{-2}$ we predict a number density between 3900--4800 galaxies per square degree. For a WFIRST-like survey with redshift range $1\leqslant z\leqslant 2$ and blended flux limit of $1\times 10^{-16}{\rm erg}\,{\rm s}^{-1}\,{\rm cm}^{-2}$ we predict a number density between 10400--15200 galaxies per square degree.Comment: 21 pages (including appendix), 12 figures, 6 tables. Accepted b

Halo detection via large-scale Bayesian inference

We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect halos of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HADES, and a Bayesian chain rule (the Blackwell-Rao Estimator), which we use to connect the inferred density field to the properties of dark matter halos. To demonstrate the capability of our approach we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful of detection of halos in the mock catalogue increases as a function of the signal-to-noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.Comment: 17 pages, 13 figures. Accepted for publication in MNRAS following moderate correction

Empirical Modeling of the Redshift Evolution of the [N II]/Hα Ratio for Galaxy Redshift Surveys

We present an empirical parameterization of the [N ii]/Hα flux ratio as a function of stellar mass and redshift valid at 0 43.0 for galaxies at redshifts z ~ 1.5. This has implications for the prediction of Hα emitters for Euclid and WFIRST. We also study the impact of blended Hα and [N ii] on the accuracy of measured spectroscopic redshifts

Halo detection via large-scale Bayesian inference

We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the Blackwell–Rao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information, we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful detection of haloes in the mock catalogue increases as a function of the signal to noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations. Key words: methods: numerical – methods: statistical – galaxies: haloes – galaxies: clusters

HST Grism-derived Forecasts for Future Galaxy Redshift Surveys

The mutually complementary Euclid and Roman galaxy redshift surveys will use Halpha- and [OIII]-selected emission line galaxies as tracers of the large scale structure at $0.9 \lesssim z \lesssim 1.9$ (Halpha) and $1.5 \lesssim z \lesssim 2.7$ ([OIII]). It is essential to have a reliable and sufficiently precise knowledge of the expected numbers of Halpha-emitting galaxies in the survey volume in order to optimize these redshift surveys for the study of dark energy. Additionally, these future samples of emission-line galaxies will, like all slitless spectroscopy surveys, be affected by a complex selection function that depends on galaxy size and luminosity, line equivalent width, and redshift errors arising from the misidentification of single emission-line galaxies. Focusing on the specifics of the Euclid survey, we combine two slitless spectroscopic WFC3-IR datasets -- 3D-HST+AGHAST and the WISP survey -- to construct a Euclid-like sample that covers an area of 0.56 deg$^2$ and includes 1277 emission line galaxies. We detect 1091 ($\sim$3270 deg$^{-2}$) Halpha+[NII]-emitting galaxies in the range $0.9\leq z \leq 1.6$ and 162 ($\sim$440 deg$^{-2}$) [OIII]$\lambda$5007-emitters over $1.5\leq z \leq 2.3$ with line fluxes $\geq 2 \times 10^{-16}$ erg s$^{-1}$ cm$^{-2}$. The median of the Halpha+[NII] equivalent width distribution is $\sim$250\r{A}, and the effective radii of the continuum and Halpha+[NII] emission are correlated with a median of $\sim$0.38" and significant scatter ($\sigma \sim$0.2"$-$0.35"). Finally, we explore the prevalence of redshift misidentification in future Euclid samples, finding potential contamination rates of $\sim$14-20% and $\sim$6% down to $2\times 10^{-16}$ and $6 \times 10^{-17}$ erg s$^{-1}$ cm$^{-2}$, respectively, though with increased wavelength coverage these percentages drop to nearly zero.Comment: Accepted for publication in ApJ. 27 pages, 17 figures, 3 table

HST Grism-derived Forecasts for Future Galaxy Redshift Surveys

The mutually complementary Euclid and Roman galaxy redshift surveys will use Hα- and [O III]-selected emission-line galaxies (ELGs) as tracers of the large-scale structure at 0.9 ≾ z ≾ 1.9 (Hα) and 1.5 ≾ z ≾ 2.7 ([O III]). It is essential to have a reliable and sufficiently precise knowledge of the expected numbers of Hα-emitting galaxies in the survey volume in order to optimize these redshift surveys for the study of dark energy. Additionally, these future samples of ELGs will, like all slitless spectroscopy surveys, be affected by a complex selection function that depends on galaxy size and luminosity, line equivalent width (EW), and redshift errors arising from the misidentification of single ELGs. Focusing on the specifics of the Euclid survey, we combine two slitless spectroscopic WFC3-IR data sets—3D-HST+AGHAST and the WFC3 Infrared Spectroscopic Parallel survey—to construct a Euclid-like sample that covers an area of 0.56 deg² and includes 1277 ELGs. We detect 1091 (~3270 deg⁻²) Hα+[N II]-emitting galaxies in the range 0.9 ≤ z ≤ 1.6 and 162 (~440 deg⁻²) [O III] λ5007 emitters over 1.5 ≤ z ≤ 2.3 with line fluxes ≥2 × 10⁻¹⁶ erg s⁻¹ cm⁻². The median of the Hα+[N II] EW distribution is ~250 Å, and the effective radii of the continuum and Hα+[N II] emission are correlated with a median of ~0.”38 and significant scatter (σ ~ 0.”2–0.”35). Finally, we explore the prevalence of redshift misidentification in future Euclid samples, finding potential contamination rates of ~14%–20% and ~6% down to 2 × 10⁻¹⁶ erg s⁻¹ cm−2 and 6 × 10⁻¹⁷ erg s⁻¹ cm⁻², respectively, although with increased wavelength coverage these percentages drop to nearly zero

Galaxy And Mass Assembly (GAMA) : the large-scale structure of galaxies and comparison to mock universes

MA acknowledges funding from the University of St Andrews and the International Centre for Radio Astronomy Research. ASGR is supported by funding from a UWA Fellowship. PN acknowledges the support of the Royal Society through the award of a University Research Fellowship and the European Research Council, through receipt of a Starting Grant (DEGAS-259586). MJIB acknowledges the financial support of the Australian Research Council Future Fellowship 100100280. TMR acknowledges support from a European Research Council Starting Grant (DEGAS-259586).From a volume-limited sample of 45 542 galaxies and 6000 groups with z ≤ 0.213, we use an adapted minimal spanning tree algorithm to identify and classify large-scale structures within the Galaxy And Mass Assembly (GAMA) survey. Using galaxy groups, we identify 643 filaments across the three equatorial GAMA fields that span up to 200 h−1 Mpc in length, each with an average of eight groups within them. By analysing galaxies not belonging to groups, we identify a secondary population of smaller coherent structures composed entirely of galaxies, dubbed ‘tendrils’ that appear to link filaments together, or penetrate into voids, generally measuring around 10 h−1 Mpc in length and containing on average six galaxies. Finally, we are also able to identify a population of isolated void galaxies. By running this algorithm on GAMA mock galaxy catalogues, we compare the characteristics of large-scale structure between observed and mock data, finding that mock filaments reproduce observed ones extremely well. This provides a probe of higher order distribution statistics not captured by the popularly used two-point correlation function.Peer reviewe

Empirical Modeling of the Redshift Evolution of the [N II]/Hα Ratio for Galaxy Redshift Surveys

We present an empirical parameterization of the [N ii]/Hα flux ratio as a function of stellar mass and redshift valid at 0 43.0 for galaxies at redshifts z ~ 1.5. This has implications for the prediction of Hα emitters for Euclid and WFIRST. We also study the impact of blended Hα and [N ii] on the accuracy of measured spectroscopic redshifts