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Register a new userCorrecting correlation functions for redshift-dependent interloper contamination
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The construction of catalogues of a particular type of galaxy can be complicated by interlopers contaminating the sample. In spectroscopic galaxy surveys this can be due to the misclassification of an emission line; for example in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) low redshift [OII] emitters may make up a few percent of the observed Ly${alpha}$ emitter (LAE) sample. The presence of contaminants affects the measured correlation functions and power spectra. Previous attempts to deal with this using the cross-correlation function have assumed sources at a fixed redshift, or not modelled evolution within the adopted redshift bins. However, in spectroscopic surveys like HETDEX, where the contamination fraction is likely to be redshift dependent, the observed clustering of misclassified sources will appear to evolve strongly due to projection effects, even if their true clustering does not. We present a practical method for accounting for the presence of contaminants with redshift-dependent contamination fractions and projected clustering. We show using mock catalogues that our method, unlike existing approaches, yields unbiased clustering measurements from the upcoming HETDEX survey in scenarios with redshift-dependent contamination fractions within the redshift bins used. We show our method returns auto-correlation functions with systematic biases much smaller than the statistical noise for samples with at least as high as 7 per cent contamination. We also present and test a method for fitting for the redshift-dependent interloper fraction using the LAE-[OII] galaxy cross-correlation function, which gives less biased results than assuming a single interloper fraction for the whole sample.
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Line intensity mapping experiments seek to trace large scale structure by measuring the spatial fluctuations in the combined emission, in some convenient spectral line, from individually unresolved galaxies. An important systematic concern for these surveys is line confusion from foreground or background galaxies emitting in other lines that happen to lie at the same observed frequency as the target emission line of interest. We develop an approach to separate this interloper emission at the power spectrum level. If one adopts the redshift of the target emission line in mapping from observed frequency and angle on the sky to co-moving units, the interloper emission is mapped to the wrong co-moving coordinates. Since the mapping is different in the line of sight and transverse directions, the interloper contribution to the power spectrum becomes anisotropic, especially if the interloper and target emission are at widely separated redshifts. This distortion is analogous to the Alcock-Paczynski test, but here the warping arises from assuming the wrong redshift rather than an incorrect cosmological model. We apply this to the case of a hypothetical [CII] emission survey at z~7 and find that the distinctive interloper anisotropy can, in principle, be used to separate strong foreground CO emission fluctuations. In our models, however, a significantly more sensitive instrument than currently planned is required, although there are large uncertainties in forecasting the high redshift [CII] emission signal. With upcoming surveys, it may nevertheless be useful to apply this approach after first masking pixels suspected of containing strong interloper contamination.
Laporte et al. (2011) reported a very high redshift galaxy candidate: a lensed J-band dropout (A2667-J1). J1 has a photometric redshift of z=9.6-12, the probability density function for which permits no low or intermediate z solution. We here report new spectroscopic observations of this galaxy with VLT/XShooter, which show clear [OIII]5007AA, Ly-alpha, H-alpha, and H-beta emission and place the galaxy firmly at z=2.082. The oxygen lines contribute only ~25% to the H-band flux, and do not significantly affect the dropout selection of J1. After correcting the broadband fluxes for line emission, we identify two roughly equally plausible natures for A2667-J1: either it is young heavily reddened starburst, or a maximally old system with a very pronounced 4000AA break, upon which a minor secondary burst of star formation is superimposed. Fits show that to make a 3 sigma detection of this object in the B-band (V-band), imaging of depth AB=30.2 (29.5) would be required - despite the relatively bright NIR magnitude, we would need optical data of equivalent depth to the Hubble Ultra Deep Field to rule out the mid-z solution on purely photometric grounds. Assuming that this stellar population can be scaled to the NIR magnitudes of recent HST/WFC3 IR-selected galaxies, we conclude that infeasibly deep optical data AB~32 would be required for the same level of security. There is a population of galaxies at z~2 with continuum colours alone that mimic those of our z=7-12 candidates.
We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation redshift methods, this approach does not require a reference sample with known redshifts. By measuring the projected cross- and auto- correlations of different galaxy sub-samples, e.g., as chosen by simple cells in color-magnitude space, we are able to estimate the galaxy-dark matter bias model parameters, and the shape of the redshift distributions of each sub-sample. This method fully marginalises over a flexible parameterisation of the redshift distribution and galaxy-dark matter bias parameters of sub-samples of galaxies, and thus provides a general Bayesian framework to incorporate redshift uncertainty into the cosmological analysis in a data-driven, consistent, and reproducible manner. This result is improved by an order of magnitude by including cross-correlations with the CMB and with galaxy-galaxy lensing. We showcase how this method could be applied to real galaxies. By using idealised data vectors, in which all galaxy-dark matter model parameters and redshift distributions are known, this method is demonstrated to recover unbiased estimates on important quantities, such as the offset $Delta_z$ between the mean of the true and estimated redshift distribution and the 68% and 95% and 99.5% widths of the redshift distribution to an accuracy required by current and future surveys.
The cross-correlation study of the unresolved $gamma$-ray background (UGRB) with galaxy clusters has a potential to reveal the nature of the UGRB. In this paper, we perform a cross-correlation analysis between $gamma$-ray data by the Fermi Large Area Telescope (Fermi-LAT) and a galaxy cluster catalogue from the Subaru Hyper Suprime-Cam (HSC) survey. The Subaru HSC cluster catalogue provides a wide and homogeneous large-scale structure distribution out to the high redshift at $z=1.1$, which has not been accessible in previous cross-correlation studies. We conduct the cross-correlation analysis not only for clusters in the all redshift range ($0.1 < z < 1.1$) of the survey, but also for subsamples of clusters divided into redshift bins, the low redshift bin ($0.1 < z < 0.6$) and the high redshift bin ($0.6 < z < 1.1$), to utilize the wide redshift coverage of the cluster catalogue. We find the evidence of the cross-correlation signals with the significance of 2.0-2.3$sigma$ for all redshift and low-redshift cluster samples. On the other hand, for high-redshift clusters, we find the signal with weaker significance level (1.6-1.9$sigma$). We also compare the observed cross-correlation functions with predictions of a theoretical model in which the UGRB originates from $gamma$-ray emitters such as blazars, star-forming galaxies and radio galaxies. We find that the detected signal is consistent with the model prediction.
Redshift-space distortions (RSD) in galaxy redshift surveys generally break both the isotropy and homogeneity of galaxy distribution. While the former aspect is particularly highlighted as a probe of growth of structure induced by gravity, the latter aspect, often quoted as wide-angle RSD but ignored in most of the cases, will become important and critical to account for as increasing the statistical precision in next-generation surveys. However, the impact of wide-angle RSD has been mostly studied using linear perturbation theory. In this paper, employing the Zeldovich approximation, i.e., first-order Lagrangian perturbation theory for gravitational evolution of matter fluctuations, we present a quasi-linear treatment of wide-angle RSD, and compute the cross-correlation function. The present formalism consistently reproduces linear theory results, and can be easily extended to incorporate relativistic corrections (e.g., gravitational redshift).
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