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Register a new userOn Removing Interloper Contamination from Intensity Mapping Power Spectrum Measurements
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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.
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Intensity mapping (IM) with neutral hydrogen is a promising avenue to probe the large scale structure of the Universe. In this paper, we demonstrate that using the 64-dish MeerKAT radio telescope as a connected interferometer, it is possible to make a statistical detection of HI in the post-reionization Universe. With the MIGHTEE (MeerKAT International GHz Tiered Extragalactic Exploration) survey project observing in the L-band ($856 < u < 1712$ MHz, $z < 0.66$), we can achieve the required sensitivity to measure the HI IM power spectrum on quasi-linear scales, which will provide an important complementarity to the single-dish IM MeerKAT observations. We present a purpose-built simulation pipeline that emulates the MIGHTEE observations and forecast the constraints that can be achieved on the HI power spectrum at $z = 0.27$ for $k > 0.3$ $rm{Mpc}^{-1}$ using the foreground avoidance method. We present the power spectrum estimates with the current simulation on the COSMOS field that includes contributions from HI, noise and point source models constructed from the observed MIGHTEE data. The results from our textit{visibility} based pipeline are in qualitative agreement to the already available MIGHTEE data. This paper demonstrates that MeerKAT can achieve very high sensitivity to detect HI with the full MIGHTEE survey on quasi-linear scales (signal-to-noise ratio $> 7$ at $k=0.49$ $rm{Mpc}^{-1}$) which are instrumental in probing cosmological quantities such as the spectral index of fluctuation, constraints on warm dark matter, the quasi-linear redshift space distortions and the measurement of the HI content of the Universe up to $zsim 0.5$.
We model a 21 cm intensity mapping survey in the redshift range 0.01<z<1.5 designed to simulate the skies as seen by future radio telescopes such as the Square Kilometre Array (SKA), including instrumental noise and Galactic foregrounds. In our pipeline, we remove the introduced Galactic foregrounds with a fast independent component analysis (fastica) technique. We present the power spectrum of the large-scale matter distribution, C(l), before and after the application of this foreground removal method and calculate the resulting systematic errors. We attempt to reduce systematics in the foreground subtraction by optimally masking the maps to remove high foregrounds in the Galactic plane. Our simulations show a certain level of bias remains in the power spectrum at all scales l<400. At large-scales l<30 this bias is particularly significant. We measure the impact of these systematic effects in two different ways: firstly we fit cosmological parameters to the broadband shape of the power spectrum and secondly we extract the position of the Baryon Acoustic Oscillations (BAO). In the first analysis, we find that the systematics introduce an significant shift in the best fit cosmological parameters at the 2 to 3 sigma level which depends on the masking and noise levels. However, cosmic distances can be recovered in an unbiased way after foreground removal at all simulated redshifts by fitting the BAOs in the power spectrum. We conclude that further advances in foreground removal are needed in order to recover unbiased information from the broadband shape of the power spectrum, however, intensity mapping experiments will be a powerful tool for mapping cosmic distances across a wide redshift range.
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.
We assess the performance of the multipole expansion formalism in the case of single-dish HI intensity mapping, including instrumental and foreground removal effects. This formalism is used to provide MCMC forecasts for a range of HI and cosmological parameters, including redshift space distortions and the Alcock-Paczynski effect. We first determine the range of validity of our power spectrum modelling by fitting to simulation data, concentrating on the monopole, quadrupole, and hexadecapole contributions. We then show that foreground subtraction effects can lead to severe biases in the determination of cosmological parameters, in particular the parameters relating to the transverse BAO rescaling, the growth rate and the HI bias ($alpha_perp$, $overline{T}_text{HI} fsigma_8$, and $overline{T}_text{HI} b_text{HI} sigma_8$, respectively). We attempt to account for these biases by constructing a 2-parameter foreground modelling prescription, and find that our prescription leads to unbiased parameter estimation at the expense of increasing the estimated uncertainties on cosmological parameters. In addition, we confirm that instrumental and foreground removal effects significantly impact the theoretical covariance matrix, and cause the covariance between different multipoles to become non-negligible. Finally, we show the effect of including higher-order multipoles in our analysis, and how these can be used to investigate the presence of instrumental and systematic effects in HI intensity mapping data.
HI intensity mapping is a new observational technique to survey the large-scale structure of matter using the 21 cm emission line of atomic hydrogen (HI). In this work, we simulate BINGO (BAO from Integrated Neutral Gas Observations) and SKA (Square Kilometre Array) phase-1 dish array operating in auto-correlation mode. For the optimal case of BINGO with no foregrounds, the combination of the HI angular power spectra with Planck results allows $w$ to be measured with a precision of $4%$, while the combination of the BAO acoustic scale with Planck gives a precision of $7%$. We consider a number of potentially complicating effects, including foregrounds and redshift dependent bias, which increase the uncertainty on $w$ but not dramatically; in all cases the final uncertainty is found to be $Delta w < 8%$ for BINGO. For the combination of SKA-MID in auto-correlation mode with Planck, we find that, in ideal conditions, $w$ can be measured with a precision of $4%$ for the redshift range $0.35 < z < 3$ (i.e., for the bandwidth of $Delta u = [350, 1050]$ MHz) and $2%$ for $0 < z < 0.49$ (i.e., $Delta u = [950, 1421]$ MHz). Extending the model to include the sum of neutrino masses yields a $95%$ upper limit of $sum m_ u < 0.24$ eV for BINGO and $sum m_ u < 0.08$ eV for SKA phase 1, competitive with the current best constraints in the case of BINGO and significantly better than them in the case of SKA.
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