Intensity Mapping Surveys Research Articles

CII] line intensity mapping the epoch of reionization with the Prime-Cam on FYST. II. CO foreground masking based on an external catalog

The Fred Young Submillimeter Telescope (FYST) line intensity mapping (LIM) survey will measure the power spectrum (PS) of the singly ionized carbon 158 $ fine-structure line CII to trace the appearance of the first galaxies that emerged during and right after the epoch of reionization (EoR, $6<z<9$). We aim to quantify the contamination of the (post-)EoR CII LIM signal by foreground carbon monoxide (CO) line emission ($3 < J_ up < 12$) and assess the efficiency to retrieve this CII LIM signal by the targeted masking of bright CO emitters. Using the IllustrisTNG300 simulation, we produced mock CO intensity tomographies based on empirical star formation rate-to-CO luminosity relations. Combining these predictions with the CII PS predictions of the first paper of this series, we evaluated a masking technique where the interlopers are identified and masked using an external catalog whose properties are equivalent to those of a deep Euclid survey. Prior to masking, our CII PS forecast is an order of magnitude lower than the predicted CO contamination in the 225 GHz ( CII emitted at $z=6.8-8.3$) band of the FYST LIM survey, at the same level in its 280 GHz ( CII emitted at $z=5.3-6.3$) and 350 GHz ( CII emitted at $z=4.1-4.8$) bands, and an order of magnitude higher in its 410 GHz ( CII emitted at $z=3.4-3.9$) band. For our fiducial model, the optimal masking depth is reached when less than 10<!PCT!> of the survey volume is masked at 350 and 410 GHz but around 40<!PCT!> at 280 GHz and 60 <!PCT!> at 225 GHz. At these masking depths we anticipate a detection of the CII PS at 350 and 410 GHz, a tentative detection at 280 GHz, whereas at 225 GHz the CO signal still dominates our model. In the last case, alternative decontamination techniques will be needed.

Reconstructing the long-wavelength matter density fluctuation modes from the scalar-type clustering fossils

Revealing the large-scale structure from the 21cm intensity mapping surveys is only possible after the foreground cleaning. However, most current cleaning techniques relying on the smoothness of the foreground spectrum lead to a severe side effect of removing the large-scale structure signal along the line of sight. On the other hand, the clustering fossil, a coherent variation of the small-scale clustering over large scales, allows us to recover the long-wavelength density modes from the off-diagonal correlation between short-wavelength modes. In this paper, we revisit the reconstruction based on the short-wavelength matter density modes in real space and scrutinize the requirements for an unbiased and optimal clustering-fossil estimator. We show that (A) the estimator is unbiased only when using an accurate bispectrum model for the long-short-short mode coupling and (B) including the connected four-point correlation functions is essential for characterizing the noise power spectrum of the estimated long mode. For matter in real space, the clustering fossil estimator based upon the leading-order bispectrum yields an unbiased estimation of the long-wavelength (k ≲ 0.01 [h/Mpc]) modes with the cross-correlation coefficient of 0.7 at redshifts z = 0 to 3.

Testing the consistency of early and late cosmological parameters with BAO and CMB data

The recent local measurements of the Hubble constant H0, indicate a significant discrepancy of over 5σ compared to the value inferred from Planck observations of the cosmic microwave background (CMB). In this paper, we try to test the standard cosmological model ΛCDM by testing the consistency of early and late cosmological parameters in the same observed data. In practice, we simultaneously derive the early and late parameters using baryon acoustic oscillation (BAO) measurements, which provide both low and high-redshift information. CMB data are also included in the analysis as a “distance prior”, which tracks the same BAO feature and resolve parameter degeneracy. By using the parameter ωm=Ωmh2, we introduce ratio(ωm), defined as the ratio of ωm which are constrained from high and low-redshift measurements respectively, to quantify the consistency between early and late parameters. We obtained a value of ratio(ωm)=1.0069±0.0070, indicating there is no tension between early parameters and late parameters in the framework of ΛCDM model. As a result, our test does not expose the defects of the ΛCDM model. In addition, we forecast the future BAO measurements of ratio(ωm), using several galaxy redshift surveys and 21 cm intensity mapping surveys, and find that these measurements can significantly improve the precision of cosmological parameters.

Multi-tracing the primordial Universe with future surveys

The fluctuations generated by Inflation are nearly Gaussian in the simplest models, but may be non-Gaussian in more complex models, potentially leading to signatures in the late Universe. In particular, local-type primordial non-Gaussianity induces scale-dependent bias in tracers of the matter distribution. This non-Gaussian imprint in the tracer power spectrum survives at late times on ultra-large scales where nonlinearity is negligible. In order to combat the problem of growing cosmic variance on these scales, we use a multi-tracer analysis that combines different tracers to maximise any primordial signal. Previous work has investigated the combination of a spectroscopic galaxy survey with a 21 cm intensity mapping survey in single-dish mode. We extend this work by considering instead the case where the 21 cm intensity mapping survey is optimised for interferometer mode. As examples, we use two multi-tracer pairs of surveys: one at high redshift (1≤z≤2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1\\le z\\le 2$$\\end{document}) and one at very high redshift (2≤z≤5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\\le z\\le 5$$\\end{document}). The 21 cm surveys are idealised surveys based on HIRAX and PUMA. We implement foreground-avoidance filters and use detailed models of the interferometer thermal noise. The galaxy surveys are idealised surveys based on Euclid and MegaMapper. Via a simple Fisher forecast, we illustrate the potential of the multi-tracer. Our results show a ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document} 20–30% improvement in precision on local primordial non-Gaussianity from the multi-tracer. Furthermore, we investigate the effects on constraints of varying the parameter of non-Gaussian galaxy assembly bias and of varying the parameters of the intensity mapping foreground filters. We find that the non-Gaussian galaxy assembly bias parameter causes a greater change in the constraints on local primordial non-Gaussianity than the foreground filter parameters.

21 cm intensity mapping cross-correlation with galaxy surveys: Current and forecasted cosmological parameters estimation for the SKAO

ABSTRACT We present a comprehensive set of forecasts for the cross-correlation signal between 21 cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21 cm signal, DESI and Euclid for galaxy clustering. We build a likelihood which takes into account the effect of the beam for the radio observations, the Alcock–Paczynski effect, a simple parametrization of astrophysical nuisances, and fully exploit the tomographic power of such observations in the range z = 0.7–1.8 at linear and mildly non-linear scales (k < 0.25h Mpc−1). The forecasted constraints, obtained with Monte Carlo Markov Chains techniques in a Bayesian framework, in terms of the six base parameters of the standard ΛCDM model, are promising. The predicted signal-to-noise ratio for the cross-correlation can reach ∼50 for z ∼ 1 and k ∼ 0.1h Mpc−1. When the cross-correlation signal is combined with current Cosmic Microwave Background (CMB) data from Planck, the error bar on $\Omega _{\rm c}\, h^2$ and H0 is reduced by factors 3 and 6, respectively, compared to CMB only data, due to the measurement of matter clustering provided by the two observables. The cross-correlation signal has a constraining power that is comparable to the autocorrelation one and combining all the clustering measurements a sub-per cent error bar of 0.33 per cent on H0 can be achieved, which is about a factor 2 better than CMB only measurements. Finally, as a proof of concept, we test the full pipeline on the real data measured by the MeerKat collaboration (Cunnington et al. 2022) presenting some (weak) constraints on cosmological parameters.

Radio-optical synergies at high redshift to constrain primordial non-Gaussianity

We apply the multi-tracer technique to test the possibility of improved constraints on the amplitude of local primordial non-Gaussianity, f_NL, in the cosmic large-scale structure. A precise measurement of f_NL is difficult because the effects of non-Gaussianity mostly arise on the largest scales, which are heavily affected by the low statistical sampling commonly referred to as cosmic variance. The multi-tracer approach suppresses cosmic variance and we implement it by combining the information from next-generation galaxy surveys in the optical/near-infrared band and neutral hydrogen (Hi) intensity mapping surveys in the radio band. High-redshift surveys enhance the precision on f_NL, due to the larger available volume, and Hi intensity mapping surveys can naturally reach high redshifts. In order to extend the redshift coverage of a galaxy survey, we consider different emission-line galaxy populations, focusing on the Hα line at low redshift and on oxygen lines at higher redshift. By doing so, we cover a wide redshift range 1≲ z≲4. To assess the capability of our approach, we implement a synthetic-data analysis by means of Markov chain Monte Carlo sampling of the (cosmological+nuisance) parameter posterior, to evaluate the constraints on f_NL obtained in different survey configurations. We find significant improvements from the multi-tracer technique: the full data set leads to a precision of σ(f_NL)<1.

Cosmic Tidal Reconstruction in Redshift Space

Gravitational coupling between large- and small-scale density perturbations leads to anisotropic distortions to local small-scale matter fluctuations. Such local anisotropic distortions can be used to reconstruct large-scale matter distribution, known as tidal reconstruction. In this paper, we apply the tidal reconstruction methods to simulated galaxies in redshift space. We find that redshift-space distortions (RSDs) lead to anisotropic reconstruction results. While the reconstructed radial modes are more noisy mainly due to the small-scale velocity dispersion, the transverse modes are still reconstructed with high fidelity, and well correlated with the original large-scale density modes. The bias of the reconstructed field at large scales shows a simple angular dependence, which can be described by a form similar to that of the linear RSD. The noise power spectrum is nearly isotropic and scale independent on large scales. This makes the reconstructed tide fields an ideal tracer for cosmic variance cancellation and multi-tracer analysis and has profound implications for future 21 cm intensity mapping surveys.

Eliminating polarization leakage effect for neutral hydrogen intensity mapping with deep learning

ABSTRACT The neutral hydrogen (H i) intensity mapping (IM) survey is regarded as a promising approach for cosmic large-scale structure studies. A major issue for the H i IM survey is to remove the bright foreground contamination. A key to successfully removing the bright foreground is to well control or eliminate the instrumental effects. In this work, we consider the instrumental effects of polarization leakage and use the U-Net approach, a deep learning-based foreground removal technique, to eliminate the polarization leakage effect. The thermal noise is assumed to be a subdominant factor compared with the polarization leakage for future H i IM surveys and ignored in this analysis. In this method, the principal component analysis (PCA) foreground subtraction is used as a pre-processing step for the U-Net foreground subtraction. Our results show that the additional U-Net processing could either remove the foreground residual after the conservative PCA subtraction or compensate for the signal loss caused by the aggressive PCA pre-processing. Finally, we test the robustness of the U-Net foreground subtraction technique and show that it is still reliable in the case of existing constraint error on H i fluctuation amplitude.

FAST Drift Scan Survey for Hi Intensity Mapping: I. Preliminary Data Analysis

This work presents the initial results of the drift-scan observation for the neutral hydrogen (Hi) intensity mapping survey with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The data analyzed in this work were collected in night observations from 2019 through 2021. The primary findings are based on 28 hr of drift-scan observation carried out over 7 nights in 2021, which covers 60 deg2 sky area. Our main findings are, first, our calibration strategy can successfully correct both the temporal and bandpass gain variation over the 4 hr drift-scan observation. Second, the continuum maps of the surveyed region are made with frequency resolution of 28 kHz and pixel area of . The pixel noise levels of the continuum maps are slightly higher than the forecast assuming T sys = 20 K, which are 36.0 mK (for 10.0 s integration time) at the 1050–1150 MHz band, and 25.9 mK (for 16.7 s integration time) at the 1323–1450 MHz band, respectively. Third, the flux-weighted differential number count is consistent with the NRAO-VLA Sky Survey (NVSS) catalog down to the confusion limit ∼7 mJy beam−1. Finally, the continuum flux measurements of the sources are consistent with those found in the literature. The difference in the flux measurement of 81 isolated NVSS sources is about 6.3%. Our research offers a systematic analysis for the FAST Hi intensity mapping drift-scan survey and serves as a helpful resource for further cosmology and associated galaxies sciences with the FAST drift-scan survey.

Characteristic functions for cosmological cross-correlations

ABSTRACT We introduce a novel unbiased, cross-correlation estimator for the one-point statistics of cosmological random fields. One-point statistics are a useful tool for analysis of highly non-Gaussian density fields, while cross-correlations provide a powerful method for combining information from pairs of fields and separating them from noise and systematics. We derive a new Deconvolved Distribution Estimator that combines the useful properties of these two methods into one statistic. Using two example models of a toy Gaussian random field and a line intensity mapping survey, we demonstrate these properties quantitatively and show that the deconvolved distribution estimator can be used for inference. This new estimator can be applied to any pair of overlapping, non-Gaussian cosmological observations, including large-scale structure, the Sunyaev–Zeldovich effect, weak lensing, and many others.

CONCERTO: Extracting the power spectrum of the [CII] emission line

Context. CONCERTO is the first experiment to perform a [CII] line intensity mapping (LIM) survey on the COSMOS field to target z &gt; 5.2. Measuring the [CII] angular power spectrum allows us to study the role of dusty star-forming galaxies in the star formation history during the epochs of Reionization and post-Reionization. The main obstacle to this measurement is the contamination by bright foregrounds: the dust continuum emission and atomic and molecular lines from foreground galaxies at z ≲ 3. Aims. We evaluate our ability to retrieve the [CII] signal in mock observations of the sky using the Simulated Infrared Dusty Extragalactic Sky (SIDES), which covers the mid-infrared to millimetre range. We also measure the impact of field-to-field variance on the residual foreground contamination. Methods. We compared two methods for dealing with the dust continuum emission from galaxies (i.e. the cosmic infrared background fluctuations): the standard principal component analysis (PCA) and the asymmetric re-weighted penalized least-squares (arPLS) method. For line interlopers, the strategy relies on masking low-redshift galaxies using the instrumental beam profile and external catalogues. As we do not have observations of CO or deep-enough classical CO proxies (such as LIR), we relied on the COSMOS stellar mass catalogue, which we demonstrate to be a reliable CO proxy for masking. To measure the angular power spectrum of masked data, we adapted the P of K EstimatoR (POKER) from cosmic infrared background studies and discuss its use on LIM data. Results. The arPLS method achieves a reduction in the cosmic infrared background fluctuations to a sub-dominant level of the [CII] power at z ∼ 7, a factor of &gt; 70 below our fiducial [CII] model. When using the standard PCA, this factor is only 0.7 at this redshift. The masking lowers the power amplitude of line contamination down to 2 × 10−2 Jy2 sr−1. This residual level is dominated by faint undetected sources that are not clustered around the detected (and masked) sources. For our [CII] model, this results in a detection at z = 5.2 with a power ratio [CII]/(residual interlopers) = 62 ± 32 for a 22% area survey loss. However, at z = 7, [CII]/(residual interlopers) = 2.0 ± 1.4, due to the weak contrast between [CII] and the residual line contamination. Thanks to the large area covered by SIDES-Uchuu, we show that the power amplitude of line residuals varies by 12–15% for z = 5.2 − 7, which is less than the field-to-field variance affecting [CII] power spectra. Conclusions. We present an end-to-end simulation of the extragalactic foreground removal that we ran to detect the [CII] at high redshift via its angular power spectrum. We show that cosmic infrared background fluctuations are not a limiting foreground for [CII] LIM. On the contrary, the CO and [CI] line contamination severely limits our ability to accurately measure the [CII] angular power spectrum at z ≳ 7.

Boosting line intensity map signal-to-noise ratio with the Ly-α forest cross-correlation

ABSTRACT We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly-α forest measurements. Using large cosmological hydrodynamic simulations, we model the emission from the CO rotational transition in the CO Mapping Array Project LIM experiment at the 5-yr benchmark and the Ly-α forest absorption signal for extended Baryon Acoustic Oscillations (BOSS), Dark energy survey instrument (DESI), and Prime Focus multiplex Spectroscopy survey (PFS). We show that CO × Ly-α forest significantly enhances the detection signal-to-noise ratio (S/N) of CO, with up to $300{{\ \rm per\, cent}}$ improvement when correlated with the PFS Ly-α forest survey and a 50–75 per cent enhancement with the available eBOSS or the upcoming DESI observations. This is competitive with even CO × spectroscopic galaxy surveys. Furthermore, our study suggests that the clustering of CO emission is tightly constrained by CO × Ly-α forest due to the increased sensitivity and the simplicity of Ly-α absorption modelling. Foreground contamination or systematics are expected not to be shared between LIM and Ly-α forest observations, providing an unbiased inference. Ly-α forest will aid in detecting the first LIM signals. We also estimate that [C ii] × Ly-α forest measurements from Experiment for Cryogenic Large-Aperture Intensity Mapping and DESI/eBOSS should have a larger S/N than planned [C ii] × quasar observations by about an order of magnitude.

Cross-correlation Forecast of CSST Spectroscopic Galaxy and MeerKAT Neutral Hydrogen Intensity Mapping Surveys

Cross-correlating the data on neutral hydrogen (H i) 21 cm intensity mapping with galaxy surveys is an effective method to extract astrophysical and cosmological information. In this work, we investigate the cross-correlation of MeerKAT single-dish mode H i intensity mapping and China Space Station Telescope (CSST) spectroscopic galaxy surveys. We simulate a survey area of ∼300 deg2 of MeerKAT and CSST surveys at z = 0.5 using Multi-Dark N-body simulation. The PCA algorithm is applied to remove the foregrounds of H i intensity mapping, and signal compensation is considered to solve the signal loss problem in H i-galaxy cross power spectrum caused by the foreground removal process. We find that from CSST galaxy auto and MeerKAT-CSST cross power spectra, the constraint accuracy of the parameter product ΩH I b H I r H I,g can reach ∼1%, which is about one order of magnitude higher than the current results. After performing the full MeerKAT H i intensity mapping survey with 5000 deg2 survey area, the accuracy can be enhanced to <0.3%. This implies that the MeerKAT-CSST cross-correlation can be a powerful tool to probe the cosmic H i property and the evolution of galaxies and the Universe.

The foreground transfer function for H i intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications

ABSTRACT Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish H i intensity mapping surveys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for H i intensity mapping experiments. However, assessing whether this approach is viable for future intensity mapping surveys, where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to expose any limitations. We reveal that even when aggressive foreground cleaning is required, which causes ${\gt }\, 50~{{\ \rm per\ cent}}$ negative bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-per cent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an autocorrelation power spectrum. We validate a method that utilizes the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ${\pm }100~{{\ \rm per\ cent}}$ bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing ${\lt }\, 5~{{\ \rm per\ cent}}$ bias in recovered values).

Constraining primordial non-Gaussianity by combining next-generation galaxy and 21 cm intensity mapping surveys

Surveys of the matter distribution contain ‘fossil’ information on possible non-Gaussianity that is generated in the primordial Universe. This primordial signal survives only on the largest scales where cosmic variance is strongest. By combining different surveys in a multi-tracer approach, we can suppress the cosmic variance and significantly improve the precision on the level of primordial non-Gaussianity. We consider a combination of an optical galaxy survey, like the recently initiated DESI survey, together with a new and very different type of survey, a 21 cm intensity mapping survey, like the upcoming SKAO survey. A Fisher forecast of the precision on the local primordial non-Gaussianity parameter f_{textrm{NL}}, shows that this multi-tracer combination, together with non-overlap single-tracer information, can deliver precision comparable to that from the CMB. Taking account of the largest systematic, i.e. foreground contamination in intensity mapping, we find that sigma (f_{textrm{NL}}) sim 4.

Primordial non-Gaussianity and non-Gaussian covariance

In the pursuit of primordial non-Gaussianities, we hope to access smaller scales across larger comoving volumes. At low redshift, the search for primordial non-Gaussianities is hindered by gravitational collapse, to which we often associate a scale $k_{\rm NL}$. Beyond these scales, it will be hard to reconstruct the modes sensitive to the primordial distribution. When forecasting future constraints on the amplitude of primordial non-Gaussianity, $f_{\rm NL}$, off-diagonal components are usually neglected in the covariance because these are small compared to the diagonal. We show that the induced non-Gaussian off-diagonal components in the covariance degrade forecast constraints on primordial non-Gaussianity, even when all modes are well within what is usually considered the linear regime. As a testing ground, we examine the effects of these off-diagonal components on the constraining power of the matter bispectrum on $f_{\rm NL}$ as a function of $k_{\rm max}$ and redshift, confirming our results against N-body simulations out to redshift $z=10$. We then consider these effects on the hydrogen bispectrum as observed from a PUMA-like 21-cm intensity mapping survey at redshifts $2<z<6$ and show that not including off-diagonal covariance over-predicts the constraining power on $f_{\rm NL}$ by up to a factor of $5$. For future surveys targeting even higher redshifts, such as Cosmic Dawn and the Dark Ages, which are considered ultimate surveys for primordial non-Gaussianity, we predict that non-Gaussian covariance would severely limit prospects to constrain $f_{\rm NL}$ from the bispectrum.

Constraining cosmic inflation with observations: Prospects for 2030

ABSTRACT The ability to test and constrain theories of cosmic inflation will advance substantially over the next decade. Key data sources include cosmic microwave background (CMB) measurements and observations of the distribution of matter at low-redshift from optical, near-infrared, and 21-cm intensity surveys. A positive detection of a CMB B-mode consistent with a primordial stochastic gravitational wave background (SGWB) is widely viewed as a smoking gun for an inflationary phase. Still, a null result does not exclude inflation. However, in a significant class of inflationary scenarios, a low SGWB amplitude is correlated with a more significant running, αs, in the primordial density perturbations than is seen with the simplest inflationary potentials. With this motivation, we forecast the precision with which the spectral index ns and αs can be constrained by currently envisaged observations, including CMB (Simons Observatory, CMB-S4 and LiteBIRD), optical/near infra-red (DESI and SPHEREx), and 21-cm intensity mapping (Tianlai and CHIME) surveys. We identify optimal combinations of data sets for constraining the running and show that they may yield additional and informative constraints on the overall inflationary parameter space if the SGWB remains undetected.

A Simulation Experiment of a Pipeline Based on Machine Learning for Neutral Hydrogen Intensity Mapping Surveys

We present a simulation experiment of a pipeline based on machine learning algorithms for neutral hydrogen (H i) intensity mapping (IM) surveys with different telescopes. The simulation is conducted on H i signals, foreground emission, thermal noise from instruments, strong radio frequency interference (sRFI), and mild RFI (mRFI). We apply the Mini-Batch K-Means algorithm to identify sRFI, and Adam algorithm to remove foregrounds and mRFI. Results show that there exists a threshold of the sRFI amplitudes above which the performance of our pipeline enhances greatly. In removing foregrounds and mRFI, the performance of our pipeline is shown to have little dependence on the apertures of telescopes. In addition, the results show that there are thresholds of the signal amplitudes from which the performance of our pipeline begins to change rapidly. We consider all these thresholds as the edges of the signal amplitude ranges in which our pipeline can function well. Our work, for the first time, explores the feasibility of applying machine learning algorithms in the pipeline of IM surveys, especially for large surveys with the next-generation telescopes.

The Tianlai dish array low-z surveys forecasts

ABSTRACT We present the science case for surveys with the Tianlai dish array interferometer tuned to the [1300, 1400] MHz frequency range. Starting from a realistic generation of mock visibility data according to the survey strategy, we reconstruct maps of the sky and perform foreground subtraction. We estimate the level of residuals from imperfect subtraction, mostly due to mode mixing, i.e. distortions in the reconstructed 3D maps due to frequency-dependent instrument response. We show that a survey of the North Celestial Polar cap during a year of observations, covering an area of $150 \, \mathrm{deg^2}$, would reach a sensitivity of $1.5-2 \, \mathrm{mK}$ per $1 \, \mathrm{MHz} \times 0.25^2 \, \mathrm{deg^2 }$ voxel and be marginally impacted by mode mixing. Tianlai would be able to detect ∼10 nearby massive H i clumps as well as a very strong cross-correlation signal of 21 cm intensity maps with the North Celestial Cap Survey optical galaxies. We also studied the performance of a mid-latitude survey, covering $\sim 1500 \, \mathrm{deg^2}$ overlapping the SDSS footprint. Despite a higher noise level for the mid-latitude survey, as well as significant distortions due to mode mixing, Tianlai would be able to detect a highly significant cross-correlation between the 21 cm signal and the Sloan spectroscopic galaxy sample. Using the extragalactic signals measured from either or both of these surveys, and comparing them with simulations such as those presented here will make it possible to assess the impact of various instrumental imperfections on the Tianlai dish array performance. This would pave the way for future intensity mapping surveys with higher sensitivity.

Baryon acoustic oscillations from H i intensity mapping: The importance of cross-correlations in the monopole and quadrupole

ABSTRACT Cosmological parameter estimation in the post-reionization era via neutral hydrogen radio emission (H i) is among the key science goals of the forthcoming SKA Observatory (SKAO). This paper explores detection capability for baryon acoustic oscillations (BAO) with a suite of 100 simulations introducing the main limitations from foreground contamination and poor angular resolution caused by the radio telescope beam. Such broad single-dish beam representing a serious challenge for BAO detection with H i intensity mapping, we investigate a multipole expansion approach as a means for mitigating such limitations. We also showcase the gains made from cross-correlating the H i intensity mapping data with an overlapping spectroscopic galaxy survey, aiming to test potential synergies between the SKA project and other future cosmological experiments at optical/near-infrared wavelengths. For our ${\sim}\,4\, 000\,\mathrm{deg}^2$ data set at $z\, {=}\, 0.9$, replicating the essential features of an SKAO H i intensity mapping survey, we were able to achieve a ${\sim }\, 4.5\sigma$ detection of BAO features in auto-correlation despite the dominant beam effect. Cross-correlation with an overlapping galaxy survey can increase this to a ${\sim }\, 6\sigma$ detection. Furthermore, including the power spectrum quadrupole besides the monopole in a joint fit can approximately double the BAO detection significance. Despite not implementing a radial-only P(k∥) analysis in favour of the three-dimensional $P(\boldsymbol {k})$ and its multipoles, we were still able to obtain robust constraints on the radial Alcock–Paczynski parameter, whereas the perpendicular parameter remains unconstrained and prior dominated due to beam effects.