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Register a new userSpherical Harmonic Analyses of Intensity Mapping Power Spectra
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Intensity mapping is a promising technique for surveying the large scale structure of our Universe from $z=0$ to $z sim 150$, using the brightness temperature field of spectral lines to directly observe previously unexplored portions of out cosmic timeline. Examples of targeted lines include the $21,textrm{cm}$ hyperfine transition of neutral hydrogen, rotational lines of carbon monoxide, and fine structure lines of singly ionized carbon. Recent efforts have focused on detections of the power spectrum of spatial fluctuations, but have been hindered by systematics such as foreground contamination. This has motivated the decomposition of data into Fourier modes perpendicular and parallel to the line-of-sight, which has been shown to be a particularly powerful way to diagnose systematics. However, such a method is well-defined only in the limit of a narrow-field, flat-sky approximation. This limits the sensitivity of intensity mapping experiments, as it means that wide surveys must be separately analyzed as a patchwork of smaller fields. In this paper, we develop a framework for analyzing intensity mapping data in a spherical Fourier-Bessel basis, which incorporates curved sky effects without difficulty. We use our framework to generalize a number of techniques in intensity mapping data analysis from the flat sky to the curved sky. These include visibility-based estimators for the power spectrum, treatments of interloper lines, and the foreground wedge signature of spectrally smooth foregrounds.
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We introduce DAYENU, a linear, spectral filter for HI intensity mapping that achieves the desirable foreground mitigation and error minimization properties of inverse co-variance weighting with minimal modeling of the underlying data. Beyond 21 cm power-spectrum estimation, our filter is suitable for any analysis where high dynamic-range removal of spectrally smooth foregrounds in irregularly (or regularly) sampled data is required, something required by many other intensity mapping techniques. Our filtering matrix is diagonalized by Discrete Prolate Spheroidal Sequences which are an optimal basis to model band-limited foregrounds in 21 cm intensity mapping experiments in the sense that they maximally concentrate power within a finite region of Fourier space. We show that DAYENU enables the access of large-scale line-of-sight modes that are inaccessible to tapered DFT estimators. Since these modes have the largest SNRs, DAYENU significantly increases the sensitivity of 21 cm analyses over tapered Fourier transforms. Slight modifications allow us to use DAYENU as a linear replacement for iterative delay CLEANing (DAYENUREST). We refer readers to the Code section at the end of this paper for links to examples and code.
We discuss the detectability of large-scale HI intensity fluctuations using the FAST telescope. We present forecasts for the accuracy of measuring the Baryonic Acoustic Oscillations and constraining the properties of dark energy. The FAST $19$-beam L-band receivers ($1.05$--$1.45$ GHz) can provide constraints on the matter power spectrum and dark energy equation of state parameters ($w_{0},w_{a}$) that are comparable to the BINGO and CHIME experiments. For one year of integration time we find that the optimal survey area is $6000,{rm deg}^2$. However, observing with larger frequency coverage at higher redshift ($0.95$--$1.35$ GHz) improves the projected errorbars on the HI power spectrum by more than $2~sigma$ confidence level. The combined constraints from FAST, CHIME, BINGO and Planck CMB observations can provide reliable, stringent constraints on the dark energy equation of state.
HI intensity mapping is an emerging tool to probe dark energy. Observations of the redshifted HI signal will be contaminated by instrumental noise, atmospheric and Galactic foregrounds. The latter is expected to be four orders of magnitude brighter than the HI emission we wish to detect. We present a simulation of single-dish observations including an instrumental noise model with 1/f and white noise, and sky emission with a diffuse Galactic foreground and HI emission. We consider two foreground cleaning methods: spectral parametric fitting and principal component analysis. For a smooth frequency spectrum of the foreground and instrumental effects, we find that the parametric fitting method provides residuals that are still contaminated by foreground and 1/f noise, but the principal component analysis can remove this contamination down to the thermal noise level. This method is robust for a range of different models of foreground and noise, and so constitutes a promising way to recover the HI signal from the data. However, it induces a leakage of the cosmological signal into the subtracted foreground of around 5%. The efficiency of the component separation methods depends heavily on the smoothness of the frequency spectrum of the foreground and the 1/f noise. We find that as, long as the spectral variations over the band are slow compared to the channel width, the foreground cleaning method still works.
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 $zsim 0.5$.
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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