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Laura Wolz

Publications and source records attributed to Laura Wolz.

At least 37 records · Page 2Linked to original sources

CRAFTS for HI cosmology: I. data processing pipeline and validation tests

We present the calibration procedures and validation of source measurement with the data of the Commensal Radio Astronomy FAST Survey (CRAFTS) for \HI intensity mapping by the Five-hundred-meter Aperture Spherical Radio Telescope (FAST). Using 70-hour drift-scan observation with the L-band (1.05-1.45GHz) 19-beam receiver, we obtain the data covering $270\,\rm deg^2$ sky area. We employ both the pulsar backend and the spectrum backend to calibrate the spectral time-ordered-data (TOD) before projecting them onto HEALPix maps. We produce calibrated TOD with frequency resolution of 30kHz and time resolution of 1s and the map data-cube with frequency resolution of 30kHz and spatial resolution of $2.95\,\rm arcmin^2$. We examine the pointing errors, noise overflow, RFI contamination and their effect on the data quality. The resulting noise level is $\sim$ 5.7mJy for the calibrated TOD and 1.6mJy for the map, consistent with the theoretical predictions within 5\% at RFI-free channels. We also validate the data by Principal Components Analysis (PCA) and find the residual map looks thermal noise dominated after removing 30 modes. We identify 447 isolated bright continuum sources in our data matching the NRAO-VLA Sky Survey (NVSS) catalog, with relative flux error of 8.3\% for TOD and 6.6\% for the map-level. We also measure the \HI emission of 90 galaxies with redshift $z<0.07$ and compare with \HI-MaNGA spectra, yielding an overall relative \HI integral flux error of 16.7\%. These results provide an important first step in assessing the feasibility of conducting cosmological \HI detection with CRAFTS.

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HI Intensity Mapping with the MIGHTEE Survey: First Results of the HI Power Spectrum

We present the first results of the HI intensity mapping power spectrum analysis with the MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) survey. We use data covering $\sim$4 square degrees in the COSMOS field using a frequency range 962.5 MHz to 1008.42 MHz, equivalent to HI emission in $0.4<z<0.48$. The data consists of 15 pointings with a total of 94.2 hours on-source. We verify the suitability of the MIGHTEE data for HI intensity mapping by testing for residual systematics across frequency, baselines and pointings. We also vary the window used for HI signal measurements and find no significant improvement using stringent Fourier mode cuts. Averaging in the power spectrum domain, i.e. using incoherent averaging, we calculate the first upper limits from MIGHTEE on the HI power spectrum at scales 0.5 Mpc$^{-1} \lesssim k \lesssim$ 10 Mpc$^{-1}$. We obtain the best 1$σ$ upper limit of 28.6 mK$^{2}$Mpc${^3}$ on $k\sim$2 Mpc$^{-1}$. Our results are consistent with the power spectrum detected with observations in the DEEP2 field with MeerKAT. The data we use here constitutes a small fraction of the MIGHTEE survey and demonstrates that combined analysis of the full MIGHTEE survey can potentially detect the HI power spectrum at $z\lesssim0.5$ in the range 0.1 Mpc$^{-1} \lesssim k \lesssim$ 10 Mpc$^{-1}$ or quasi-linear scales.

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Emission-line Stacking of 21cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data

We present a novel analysis of observational systematics through the emission-line stacking of the MeerKLASS L-band deep-field intensity maps, following the detection in arXiv:2407.21626. A stacking signal is obtained by stacking the 21cm intensity map cubelets around the galaxy positions from the GAMA survey at $0.39\lesssim z \lesssim0.46$. An extensive simulation framework is built to study the viability of the stacking detection, the covariance estimation, and the model inference, which are then applied to the data. The statistical significance of the detection is $8.66σ$ when averaged into an angular map, and $7.45σ$ when averaged into a spectrum. The stacked spectrum exhibits an oscillating component of systematics, and we provide evidence that these systematics are a convolutional effect on the map data. The oscillation frequency matches the diffraction from the secondary reflector into the primary beam of the MeerKAT telescope. Bayesian inference can be used to constrain the systematics and the average HI emission of the galaxies. The fitting of the parameters gives a constraint on the systematics frequency $ν_{\rm sys}\,[{\rm MHz}] = 17.90^{+6.53}_{-4.27}$. The posterior of the systematics amplitude reaches the wide prior and gives $A_{\rm sys}=0.50^{+0.33}_{-0.33}$. A tentative measurement of the average HI mass of the sources is achieved at $\log_{10}[\langle M_{HI}\rangle/M_\odot ]=9.84^{+0.48}_{-0.59}$, which is an underestimation limited by the narrow redshift bin, the strong degeneracy with the systematics, and the low-density galaxy sample. These shortfalls will be resolved for future MeerKLASS data to enable accurate measurements of the HI density through stacking of intensity maps.

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MeerKLASS L-band deep-field intensity maps: entering the HI dominated regime

We present results from MeerKAT single-dish HI intensity maps, the final observations to be performed in L-band in the MeerKAT Large Area Synoptic Survey (MeerKLASS) campaign. The observations represent the deepest single-dish HI intensity maps to date, produced from 41 repeated scans over $236\,{\rm deg}^2$, providing 62 hours of observational data for each of the 64 dishes before flagging. By introducing an iterative self-calibration process, the estimated thermal noise of the reconstructed maps is limited to ${\sim}\,1.21\,$mK ($1.2\,\times$ the theoretical noise level). This thermal noise will be sub-dominant relative to the HI fluctuations on large scales ($k\,{\lesssim}\,0.15\,h\,\text{Mpc}^{-1}$), which demands upgrades to power spectrum analysis techniques, particularly for covariance estimation. In this work, we present the improved MeerKLASS analysis pipeline, validating it on both a suite of mock simulations and a small sample of overlapping spectroscopic galaxies from the Galaxy And Mass Assembly (GAMA) survey. Despite only overlapping with ${\sim}\,25\%$ of the MeerKLASS deep field, and a conservative approach to covariance estimation, we still obtain a ${>}\,4\,σ$ detection of the cross-power spectrum between the intensity maps and the 2269 galaxies at the narrow redshift range $0.39\,{<}\,z\,{<}\,0.46$. We briefly discuss the HI auto-power spectrum from this data, the detection of which will be the focus of follow-up work. For the first time with MeerKAT single-dish intensity maps, we also present evidence of HI emission from stacking the maps onto the positions of the GAMA galaxies.

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Modeling the Nonlinear Power Spectrum in Low-redshift HI Intensity Mapping

We present a simulation-based framework to forecast the HI power spectrum on non-linear scales ($k\gtrsim 1\ {\rm Mpc^{-1}}$), as measured by interferometer arrays like MeerKAT in the low-redshift ($z\leq 1.0$) universe. Building on a galaxy-based HI mock catalog, we meticulously consider various factors, including the emission line profiles of HI discs and some observational settings, and explore their impacts on the HI power spectrum. While it is relatively insensitive to the profile shape of HI emission line at these scales, we identify a strong correlation with the profile width, that is, the Full Width at Half Maxima (FWHM, also known as $W_{\rm 50}$ in observations) in this work. By modeling the width function of $W_{50}$ as a function of $v_{\rm max}$, we assign each HI source a emission line profile and find that the resulting HI power spectrum is comparatively close to results from particles in the IllustrisTNG hydrodynamical simulation. After implementing $k$-space cuts matching the MeerKAT data, our prediction replicates the trend of the measurements obtained by MeerKAT at $z\approx 0.44$, though with a significantly lower amplitude. Utilizing a Monte Carlo Markov Chain sampling method, we constrain the parameter $A_{W_{\rm 50}}$ in the $W_{\rm 50}$ models and $Ω_{\rm HI}$ with the MeerKAT measurements and find that a strong degeneracy exists between these two parameters.

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Radio Frequency Interference from Radio Navigation Satellite Systems: simulations and comparison to MeerKAT single-dish data

Radio Frequency Interference (RFI) is emitted from various sources, terrestrial or orbital, and create a nuisance for ground-based 21cm experiments. In particular, single-dish 21cm intensity mapping experiments will be highly susceptible to contamination from these sources due to its wide primary beam and sensitivity. This work aims to simulate the contamination effects emitted from orbital sources in the Radio Navigational Satellite System within the 1100-1350 MHz frequency. This simulation can be split into two parts: (I) satellite positioning, emission power, and beam response on the telescope and (II) fitting of the satellite signal to data in order to improve the original model. We use previously observed single dish MeerKAT L-band data which needs to be specially calibrated to include data contaminated by satellite-based RFI. We find that due to non-linearity effects, it becomes non-trivial to fit the satellite power. However, when masking regions where this non-linearity is problematic, we can recreate the satellite contamination with high accuracy around its peak frequencies. The simulation can predict satellite movements and signal for past and future observations, which can help in RFI avoidance and testing novel cleaning methods. The predicted signal from simulations sits below the noise in the target cosmology window for the L-band (970 - 1015 MHz) making it difficult to confirm any out-of-band emission from satellites. However, a power spectrum analysis shows that such signal can still contaminate the 21cm power spectrum at these frequencies. In our simulations, this contamination overwhelms the auto-power spectrum but still allows for a clean detection of the signal in cross-correlations with mild foreground cleaning. Whether such contamination does exist one will require further characterization of the satellite signals far away from their peak frequencies.

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Accurate Fourier-space statistics for line intensity mapping: Cartesian grid sampling without aliased power

Estimators for $n$-point clustering statistics in Fourier-space demand that modern surveys of large-scale structure be transformed to Cartesian coordinates to perform Fast Fourier Transforms (FFTs). In this work, we explore this transformation in the context of pixelised line intensity maps (LIM), highlighting potential biasing effects on power spectrum measurements. Current analyses often avoid a complete resampling of the data by approximating survey geometry as rectangular in Cartesian space, an increasingly inaccurate assumption for modern wide-sky surveys. Our simulations of a $20\,{\times}\,20\,\text{deg}^2$ 21cm LIM survey at $0.34\,{<}\,z\,{<}\,0.54$ show this assumption biases power spectrum measurements by ${>}\,20\%$ across all scales. We therefore present a more robust framework for regridding the voxel intensities onto a 3D FFT field by coordinate transforming large numbers of Monte-Carlo sampling particles. Whilst this unbiases power spectrum measurements on large scales, smaller-scale discrepancies remain, caused by structure smoothing and aliasing from separations unresolved by the grid. To correct these effects, we introduce modelling techniques, higher-order particle assignments, and interlaced FFT grids to suppress the aliased power. Using a Piecewise Cubic Spline (PCS) particle assignment and an interlaced FFT field, we achieve sub-percent accuracy up to 80% of the Nyquist frequency for our 21cm LIM simulations. We find a more subtle hierarchical improvement in results for higher-order assignment schemes, relative to the gains made for galaxy surveys, which we attribute to the extra complexity in LIM from additional discretising steps. Python code accompanying this paper is available at github.com/stevecunnington/gridimp.

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Detecting the HI Power Spectrum in the Post-Reionization Universe with SKA-Low

We present a survey strategy to detect the neutral hydrogen (HI) power spectrum at $5<z<6$ using the SKA-Low radio telescope in presence of foregrounds and instrumental effects. We simulate observations of the inherently weak HI signal post-reionization with varying levels of noise and contamination with foreground amplitudes equivalent to residuals after sky model subtraction. We find that blind signal separation methods on imaged data are required in order to recover the HI signal at large cosmological scales. Comparing different methods of foreground cleaning, we find that Gaussian Process Regression (GPR) performs better than Principle Component Analysis (PCA), with the key difference being that GPR uses smooth kernels for the total data covariance. The integration time of one field needs to be larger than $\sim 250$ h to provide large enough signal-to-noise ratio (SNR) to accurately model the data covariance for foreground cleaning. Images within the primary beam field-of-view give measurements of the HI power spectrum at scales $k\sim 0.02\,{\rm Mpc^{-1}}-0.3\,{\rm Mpc^{-1} }$ with SNR $\sim 2-5$ in $Δ[{\rm log}( k/{\rm Mpc^{-1}})] = 0.25$ bins assuming an integration time of $600$ h. Systematic effects, which introduce small-scale fluctuations across frequency channels, need to be $\lesssim 5\times 10^{-5}$ to enable unbiased measurements outside the foreground wedge. Our results provide an important validation towards using the SKA-Low array for measuring the HI power spectrum in the post-reionization Universe.

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

Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish HI 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 HI 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 ${>}\,50\%$ negative bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-percent 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 auto-correlation power spectrum. We validate a method that utilises the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ${\pm}100\%$ bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing ${<}\,5\%$ bias in recovered values).

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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 hours of drift-scan observation carried out over seven nights in 2021, which covers $60\,{\rm deg}^2$ sky area. Our main findings are: (i) Our calibration strategy can successfully correct both the temporal and bandpass gain variation over the $4$-hour drift-scan observation. (ii) The continuum maps of the surveyed region are made with frequency resolution of $28$ kHz and pixel area of $2.95\,{\rm arcmin}^2$. The pixel noise levels of the continuum maps are slightly higher than the forecast assuming $T_{\rm sys}=20\,{\rm K}$, 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. (iii) The flux-weighted differential number count is consistent with the NRAO-VLA Sky Survey (NVSS) catalog down to the confusion limit $\sim7\,{\rm mJy}/{\rm beam}^{-1}$. (iv) The continuum flux measurements of the sources are consistent with that 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.

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Towards Optimal Foreground Mitigation Strategies for Interferometric HI Intensity Mapping in the Low-Redshift Universe

We conduct the first case study towards developing optimal foreground mitigation strategies for neutral hydrogen (HI) intensity mapping using radio interferometers at low redshifts. A pipeline for simulation, foreground mitigation and power spectrum estimation is built, which can be used for ongoing and future surveys using MeerKAT and Square Kilometre Array Observatory (SKAO). It simulates realistic sky signals to generate visibility data given instrument and observation specifications, which is subsequently used to perform foreground mitigation and power spectrum estimation. A quadratic estimator formalism is developed to estimate the temperature power spectrum in visibility space. Using MeerKAT telescope specifications for observations in the redshift range z~0.25-0.30 corresponding to the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey, we present a case study where we compare different approaches of foreground mitigation. We find that component separation in visibility space provides a more accurate estimation of HI clustering comparing to foreground avoidance, with the uncertainties being 30 per cent smaller. Power spectrum estimation from image is found to be less robust with larger bias and more information loss when compared to estimation in visibility. We conclude that for z~0.25-0.30, the MIGHTEE survey will be capable of measuring the HI power spectrum from k~0.5 Mpc$^{-1}$ to k~10 Mpc$^{-1}$ with high accuracy. We are the first to show that, at low redshift, component separation in visibility space suppresses foreground contamination at large line-of-sight scales, allowing measurement of HI power spectrum closer to the foreground wedge, crucial for data analysis towards future detections.

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HI intensity mapping with MeerKAT: power spectrum detection in cross-correlation with WiggleZ galaxies

We present a detection of correlated clustering between MeerKAT radio intensity maps and galaxies from the WiggleZ Dark Energy Survey. We find a $7.7σ$ detection of the cross-correlation power spectrum, the amplitude of which is proportional to the product of the HI density fraction ($Ω_{\rm HI}$), HI bias ($b_{\rm HI}$) and the cross-correlation coefficient ($r$). We therefore obtain the constraint $Ω_{\rm HI} b_{\rm HI} r\,{=}\,[0.86\,{\pm}\,0.10\,({\rm stat})\,{\pm}\,0.12\,({\rm sys})]\,{\times}\,10^{-3}$, at an effective scale of $k_{\rm eff}\,{\sim}\,0.13\,h\,{\rm Mpc}^{-1}$. The intensity maps were obtained from a pilot survey with the MeerKAT telescope, a 64-dish pathfinder array to the SKA Observatory (SKAO). The data were collected from 10.5 hours of observations using MeerKAT's L-band receivers over six nights covering the 11hr field of WiggleZ, in the frequency range $1015-973\,{\rm MHz}$ (0.400$\,{<}\,z\,{<}\,$0.459 in redshift). This detection is the first practical demonstration of the multi-dish auto-correlation intensity mapping technique for cosmology. This marks an important milestone in the roadmap for the cosmology science case with the full SKAO.

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HI constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps

We present the joint analysis of Neutral Hydrogen (HI) Intensity Mapping observations with three galaxy samples: the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples from the eBOSS survey, and the WiggleZ Dark Energy Survey sample. The HI intensity maps are Green Bank Telescope observations of the redshifted 21cm emission on 100deg2 covering the redshift range $0.6<z<1.0$. We process the data by separating and removing the foregrounds with FastICA, and construct a transfer function to correct for the effects of foreground removal on the HI signal. We cross-correlate the cleaned HI data with the galaxy samples and study the overall amplitude as well as the scale-dependence of the power spectrum. We also qualitatively compare our findings with the predictions by a semi-analytic galaxy evolution simulation. The cross-correlations constrain the quantity $Ω_{HI} b_{HI} r_{{HI},{opt}}$ at an effective scale $k_{eff}$, where $Ω_{HI}$ is the HI density fraction, $b_{HI}$ is the HI bias, and $r_{{HI},{opt}}$ the galaxy-hydrogen correlation coefficient, which is dependent on the HI content of the optical galaxy sample. At $k_{eff}=0.31 \, h/{Mpc}$ we find $Ω_{HI} b_{HI} r_{{HI},{Wig}} = [0.58 \pm 0.09 \, {(stat) \pm 0.05 \, {(sys)}}] \times 10^{-3}$ for GBT-WiggleZ, $Ω_{HI} b_{HI} r_{HI,{ELG}} = [0.40 \pm 0.09 \, {(stat) \pm 0.04 \, {(sys)}}] \times 10^{-3}$ for GBT-ELG, and $Ω_{HI} b_{HI} r_{{HI},{LRG}} = [0.35 \pm 0.08 \, {(stat) \pm 0.03 \, {(sys)}}] \times 10^{-3}$ for GBT-LRG, at $z\simeq 0.8$. We also report results at $k_{eff}=0.24 \, h/{Mpc}$ and $k_{eff}=0.48 \, h/{Mpc}$. With little information on HI parameters beyond our local Universe, these are amongst the most precise constraints on neutral hydrogen density fluctuations in an underexplored redshift range.

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SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge

Neutral Hydrogen Intensity Mapping (HI IM) surveys will be a powerful new probe of cosmology. However, strong astrophysical foregrounds contaminate the signal and their coupling with instrumental systematics further increases the data cleaning complexity. In this work, we simulate a realistic single-dish HI IM survey of a $5000$~deg$^2$ patch in the $950 - 1400$ MHz range, with both the MID telescope of the SKA Observatory (SKAO) and MeerKAT, its precursor. We include a state-of-the-art HI simulations and explore different foreground models and instrumental effects such as non-homogeneous thermal noise and beam side-lobes. We perform the first Blind Foreground Subtraction Challenge for HI IM on these synthetic data-cubes, aiming to characterise the performance of available foreground cleaning methods with no prior knowledge of the sky components and noise level. Nine foreground cleaning pipelines joined the Challenge, based on statistical source separation algorithms, blind polynomial fitting, and an astrophysical-informed parametric fit to foregrounds. We devise metrics to compare the pipeline performances quantitatively. In general, they can recover the input maps' 2-point statistics within 20 per cent in the range of scales least affected by the telescope beam. However, spurious artefacts appear in the cleaned maps due to interactions between the foreground structure and the beam side-lobes. We conclude that it is fundamental to develop accurate beam deconvolution algorithms and test data post-processing steps carefully before cleaning. This study was performed as part of SKAO preparatory work by the HI IM Focus Group of the SKA Cosmology Science Working Group.

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SkyPy: A package for modelling the Universe

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate.

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Extracting HI Astrophysics from Interferometric Intensity Mapping

We present a new halo model of neutral hydrogen (HI) calibrated to galaxy formation simulations at redshifts $z\sim0.1$ and $z\sim1.0$ that we employ to investigate the constraining power of interferometric HI intensity mapping on HI astrophysics. We demonstrate that constraints on the small-scale HI power spectrum can break the degeneracy between the HI density $Ω_{\rm HI}$ and the HI bias $b_{\rm HI}$. For $z\sim0.1$, we forecast that an accurate measurement of $Ω_{\rm HI}$ up to 6% level precision and the large-scale HI bias $b_{\rm HI}^0$ up to 1% level precision can be achieved using Square Kilometre Array (SKA) pathfinder data from MeerKAT and Australian SKA Pathfinder (ASKAP). We also propose a new description of the HI shot noise in the halo model framework in which a scatter of the relation between the HI mass of galaxies and their host halo mass is taken into account. Furthermore, given the number density of HI galaxies above a certain HI mass threshold, future surveys will also be able to constrain the HI mass function using only the HI shot noise. This will lead to constraints at the 10% level using the standard Schechter function. This technique will potentially provide a new way of measuring the HI Mass Function, independent from existing methods. We predict that the SKA will be able to further improve the low-redshift constraints by a factor of 3, as well as pioneering measurements of HI astrophysics at higher redshifts.

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Impact of Foregrounds on HI Intensity Mapping Cross-Correlations with Optical Surveys

The future of precision cosmology could benefit from cross-correlations between intensity maps of unresolved neutral hydrogen (HI) and more conventional optical galaxy surveys. A major challenge that needs to be overcome is removing the 21cm foreground emission that contaminates the cosmological HI signal. Using N-body simulations we simulate HI intensity maps and optical catalogues which share the same underlying cosmology. Adding simulated foreground contamination and using state-of-the-art reconstruction techniques we investigate the impacts that 21cm foregrounds and other systematics have on these cross-correlations. We find that the impact a FASTICA 21cm foreground clean has on the cross-correlations with spectroscopic optical surveys with well-constrained redshifts is minimal. However, problems arise when photometric surveys are considered: we find that a redshift uncertainty σ_z {\geq} 0.04 causes significant degradation in the cross power spectrum signal. We diagnose the main root of these problems, which relates to arbitrary amplitude changes along the line-of-sight in the intensity maps caused by the foreground clean and suggest solutions which should be applicable to real data. These solutions involve a reconstruction of the line-of-sight temperature means using the available overlapping optical data along with an artificial extension to the HI data through redshift to address edge effects. We then put these solutions through a further test in a mock experiment that uses a clustering-based redshift estimation technique to constrain the photometric redshifts of the optical sample. We find that with our suggested reconstruction, cross-correlations can be utilized to make an accurate prediction of the optical redshift distribution.

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Cosmology with Phase 1 of the Square Kilometre Array; Red Book 2018: Technical specifications and performance forecasts

We present a detailed overview of the cosmological surveys that will be carried out with Phase 1 of the Square Kilometre Array (SKA1), and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5,000 sqdeg; a wide and deep continuum galaxy and HI intensity mapping survey over 20,000 sqdeg from z = 0.35 - 3; and a deep, high-redshift HI intensity mapping survey over 100 sqdeg from z = 3 - 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to z ~ 3 with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to z = 6. These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical surveys like LSST and Euclid, leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys, and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.

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