arXiv subjects

Marta Spinelli

Publications and source records attributed to Marta Spinelli.

At least 37 records · Page 2Linked to original sources

arXiv2026

Beyond power spectrum to unveil systematics on HI intensity maps

HI intensity mapping is a promising technique to probe large-scale structure, traditionally analyzed via two-point statistics such as the angular power spectrum. This technique has proven very powerful but may miss key non-Gaussian information present in the signal. We extend the starlet l1-norm, a multi-scale higher-order statistic previously applied to weak lensing maps, to the brightness temperature fluctuations of the HI density field. The HI signal is highly non-Gaussian at late times (z < 1) due to nonlinear structure growth, motivating the use of advanced summary statistics. We simulated full-sky HI lognormal brightness temperature maps using CAMB and GLASS, generating 10,000 realizations with associated cosmological parameters. We extracted both the starlet l1-norm and angular power spectrum from these maps. Using the JaxILI framework, we performed neural density estimation for implicit likelihood inference. The analysis considered simulated maps incorporating realistic noise and telescope beam, capturing the impact of observational effects on parameter inference. In this work, we focus on the redshift range 0.4 < z < 0.45, chosen to match the interval already targeted by existing MeerKLASS observations. The starlet l1-norm significantly outperforms the angular power spectrum in constraining cosmological parameters, achieving almost a 3x improvement in the figure of merit relative to the angular power spectrum by capturing non-Gaussian features missed by two-point statistics. Moreover, our results suggest that the starlet l1-norm is robust to several of the systematic effects included in our simulations. Our findings highlight the potential of multi-scale higher-order statistics such as the starlet l1-norm to enhance cosmological inference from future HI intensity mapping surveys.

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arXiv2026

Optimisation of calibration sources for global 21-cm experiments: the REACH case

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the early Universe. However, its detection remains a major challenge owing to its low strength compared to the bright foregrounds and the requirement of precise calibration of the instrument to prevent systematics that could hinder a detection or lead to false inferences. REACH (Radio Experiment for the Analysis of Cosmic Hydrogen) is a radiometer experiment designed to detect this sky-averaged signal in the frequency range of 50--130~MHz. Using a wide-beam antenna, REACH calibration relies on internal reference sources, covering a broad range of temperatures and reflection coefficients. The choice of type and number of calibrators used significantly influences the quality of the calibration. This work investigates these effects and introduces a novel method for selecting an optimal set of calibration sources. With an optimised set, we aim to reduce calibration time, thereby increasing sky integration time while preserving calibration accuracy. We explore two optimisation strategies: one applied across the full receiver band and another performed on a frequency-by-frequency basis. Finally, we demonstrate that, with a total calibration time comparable to the conventional full-calibrator set, an optimised set with fewer calibrators achieves approximately a $15~\%$ reduction in calibrated temperature noise and improved absolute calibration of the instrument. This has implications for better calibration strategies in similar radiometer experiments.

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arXiv2026

Painting a full radio sky -- Empirical mock catalogues with multiple source populations for future radio surveys

Upcoming radio surveys will probe the sky with unprecedented depth and sky coverage, enabling a broad range of cosmological and astrophysical applications, as well as powerful synergies with experiments at other wavelengths. The preparation and scientific exploitation of these surveys require realistic mock catalogues that capture the complexity of the radio sky and the interplay of its emitting components. We present a modular and extensible algorithm for generating empirical simulations over the full radio sky, i.e. a solid angle of $4π$ steradians ($f_{\rm sky}=1$), down to redshift $z=5$, comprising both radio continuum and line emission. The framework combines a simulated dark-matter light-cone with empirically sampled galaxy populations and a probabilistic galaxy-halo assignment scheme, producing self-consistent mock catalogues including multiple radio populations on the same light-cone. We release two public catalogues: a shallow catalogue, fully constrained by existing observational data and limited to flux thresholds of $S_\text{1.4 GHz}^\text{lim} \sim 8\times10^{-5}\ \text{Jy}$ at $1.4\ \text{GHz}$ and $S_\text{21}^\text{lim} \sim 2\ \text{Jy}\cdot\text{Hz}$ for the HI 21 cm line; and a deep catalogue extending the calibrated empirical model to better sensitivities, broadly matching future SKAO surveys, with flux limits of $S_\text{1.4 GHz}^\text{lim} \sim 4\times10^{-5}\ \text{Jy}$ and $S_\text{21}^\text{lim} \sim 0.3\ \text{Jy}\cdot\text{Hz}$. The catalogues include radio continuum active galactic nuclei and star-forming galaxies, together with HI-emitting galaxies, for a total of more than 260 million sources in the shallow catalogue and more than 1 billion in the deep catalogue. We validate the simulations by analysing their statistical properties: the mocks reproduce the targeted clustering and population statistics while retaining minimal physical assumptions.

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arXiv2026

Circuit Modeling for In Situ 21 cm Radiometer Calibration

Recent experiments in cosmology, particularly those aimed at detecting the faint, redshifted, global 21 cm hydrogen line (depth < ~200 mK, z > 7.5), have imposed stringent new requirements on radiometer calibration. In this work, we present a framework for circuit modeling and parameter inference to strengthen these calibration pipelines. This new approach enables in situ characterization of otherwise immeasurable systematics using physically motivated models. A combination of frequentist and Bayesian techniques are employed in a pipeline that supports iterative modeling, robust parameter estimation, and detailed uncertainty quantification. The framework is applied to the REACH telescope, where the precise correction of variations in the radio signal paths arising from component aging or environmental effects is critical. Circuit models of REACH's calibration sources are developed, with the goal of predicting source temperature corrections that are conventionally obtained from laboratory measurements. By fitting the models to measured data using a convolutional cost function, a strong agreement with RMS residuals no worse than -37 dB is obtained. However, Bayesian inference reveals that the resulting temperature corrections can have uncertainties on the order of 1 to 2 K, caused by reflection coefficient degeneracies, measurement noise, and errors in the models. To combat this, posteriors obtained from laboratory measurements are employed as updated priors, reducing correction uncertainties down to 75 mK. Ultimately, the framework provides a means of dynamically accounting for drift in system non-idealities over time, addressing the increasing precision demands of global 21 cm radio astronomy.

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arXiv2026

Simulations of the 21cm emission line for upcoming large-scale HI galaxy surveys

Upcoming galaxy surveys with the SKA Observatory will detect neutral hydrogen (HI) across unprecedented volumes, and their scientific return will crucially depend on predictive models for HI observables. In this work, we present a framework to simulate the neutral hydrogen 21cm emission line in such large-scale HI galaxy surveys. This framework is developed as a modular layer that builds on semi-analytical models. In particular we use as bases the Galaxy Evolution and Assembly (GAEA) and L-Galaxies semi-analytical models, coupled to merger trees from the Millennium Simulation suite. We validate our framework against local Universe observations, demonstrating consistency with velocity functions, and generalised Tully-Fisher relations. Predictions based on GAEA and L-Galaxies exhibit mutual consistency despite the distinct underlying physical prescriptions. We construct mock galaxy catalogues that incorporate forward-modelled selection functions, inclination effects, and redshift broadening, reproducing the statistical distributions of HI-selected galaxies in the ALFALFA survey. Finally, we present redshift distribution forecasts for future SKA Observatory HI galaxy surveys. This framework offers a flexible tool for interpreting upcoming large-scale radio surveys and studying HI line observables as cosmological probes.

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arXiv2026

Revealing cosmological fluctuations in 21cm intensity maps with MeerKLASS: from maps to power spectra

Mapping the integrated 21cm emission line from dark matter-tracing neutral hydrogen gas is the primary science goal for MeerKLASS (MeerKAT's Large Area Synoptic Survey). Prior to the arrival of MeerKAT, this intensity mapping technique had only been tested on a couple of pre-existing single-dish radio telescopes with a handful of observational hours with which to make early pioneering detections. The 64-dish MeerKAT array, precursor to the Square Kilometre Array Observatory (SKAO), can scan the sky in auto-correlation mode and perform intensity mapping across large sky areas, presenting the exciting potential for a wide-sky (${\gtrsim}\,10{,}000\,{\rm deg}^2$) spectroscopic survey across redshift $0.4\,{<}\,z\,{<}\,1.45$. Validating the auto-correlation (or single-dish) mode of observation for a multi-dish array and developing the analysis pipeline with which to make unbiased measurements has presented major challenges to this endeavour. In this work, we overview the advances in the field that have facilitated a robust analysis framework for single-dish intensity mapping, and review some results that showcase its success using early MeerKLASS surveys. We demonstrate our control of foreground cleaning, signal loss and map regridding to deliver detections of cosmological clustering within the intensity maps through cross-correlation power spectrum measurements with overlapping galaxy surveys. Finally, we discuss the prospects for future MeerKLASS observations and forecast its potential, making our code publicly available: https://github.com/meerklass/MeerFish.

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arXiv2025

Foreground removal in HI 21 cm intensity mapping under frequency-dependent beam distortions

Neutral hydrogen (HI) intensity mapping with single-dish experiments is a powerful approach for probing cosmology in the post-reionization epoch. However, the presence of bright foregrounds over four orders of magnitude stronger than the HI signal makes its extraction highly challenging. While all methods perform well when assuming a Gaussian beam degraded to the worst resolution, most of them degrade significantly in the presence of a more realistic beam model. In this work, we investigate the performance of SDecGMCA. This method extends DecGMCA to spherical data, combining sparse component separation with beam deconvolution. Our goal is to evaluate this method in comparison with established foreground removal techniques, assessing its ability to recover the cosmological HI signal from single-dish intensity mapping observations under varying beam conditions. We use simulated HI signal and foregrounds, covering the frequency ranges relevant to MeerKAT and SKA-Mid. The foreground removal techniques tested fall into two main categories: model-fitting methods (polynomial and parametric) and blind source separation methods (PCA, ICA, GMCA, and SDecGMCA). Their effectiveness is evaluated based on the recovery of the HI angular and frequency power spectra under progressively more realistic beam conditions. While all methods perform adequately under a uniform degraded beam, SDecGMCA remains robust when frequency-dependent beam distortions are introduced. In the oscillating beam case, SDecGMCA suppresses the spurious spectral peak at $k_ν\sim 0.3$ and achieves $\lesssim 5\%$ accuracy at intermediate angular scales ($10 < \ell < 200$), outperforming other methods. Beam inversion, however, remains intrinsically unstable beyond $\ell \sim 200$, setting a practical limit on the method.

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arXiv2025

Hydrogen intensity mapping with MeerKAT: Preserving cosmological signal by optimising contaminant separation

Removing contaminants is a delicate, yet crucial step in neutral hydrogen (HI) intensity mapping and often considered the technique's greatest challenge. Here, we address this challenge by analysing HI intensity maps of about $100$ deg$^2$ at redshift $z\approx0.4$ collected by the MeerKAT radio telescope, an SKA Observatory (SKAO) precursor, with a combined 10.5-hour observation. Using unsupervised statistical methods, we removed the contaminating foreground emission and systematically tested, step-by-step, some common pre-processing choices to facilitate the cleaning process. We also introduced and tested a novel multiscale approach: the data were redundantly decomposed into subsets referring to different spatial scales (large and small), where the cleaning procedure was performed independently. We confirm the detection of the HI cosmological signal in cross-correlation with an ancillary galactic data set, without the need to correct for signal loss. In the best set-up we achieved, we were able to constrain the HI distribution through the combination of its cosmic abundance ($Ω_{HI}$) and linear clustering bias ($b_{HI}$) up to a cross-correlation coefficient ($r$). We measured $Ω_{HI}b_{HI}r = [0.93 \pm 0.17]\,\times\,10^{-3}$ with a $\approx6σ$ confidence, which is independent of scale cuts at both edges of the probed scale range ($0.04 \lesssim k \lesssim 0.3 \,h$ Mpc$^{-1}$), corroborating its robustness. Our new pipeline has successfully found an optimal compromise in separating contaminants without incurring a catastrophic signal loss. This development instills an added degree of confidence in the outstanding science we can deliver with MeerKAT on the path towards HI intensity mapping surveys with the full SKAO.

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arXiv2025

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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arXiv2025

Weighing neutrinos with 21cm Intensity Mapping at the SKAO

We explore the constraining power of future 21cm intensity mapping (IM) observations at the SKAO, focusing primarily on the sum of neutrino masses, $Σm_ν$. We forecast observations of the 21cm IM auto-power spectrum as well as the 21cm IM and galaxy surveys cross-correlation power spectrum. We construct different synthetic data sets of observations for the 21cm IM observables. For galaxy clustering, we consider two stage-IV surveys to mimic a DESI-like and Euclid-like cross-correlation signal. We study the impact of assuming three different fiducial values for the sum of neutrino masses, i.e. $Σm_ν= 0.06, 0.1, 0.4$ eV, in the synthetic data sets. To investigate the constraining power of the forecasted 21cm observations, we build a likelihood code. We find that the 21cm auto-power spectrum alone could provide an upper limit on the sum of neutrino masses of $Σm_ν< 0.287$ eV, at $95\%$ confidence level, for the case of the lowest fiducial value of $Σm_ν$. This result is comparable to the upper limits provided by cosmic microwave background (CMB) observations alone. When combining the 21cm auto-power spectrum synthetic data set with Planck 2018 CMB measurements, we find a tighter upper limit of $Σm_ν< 0.105$ eV, which improves on the constraints from Planck alone. We obtain a similar result with 21cm and galaxy clustering cross-correlation power spectrum, whose detection is more easily achieved as they are less affected by systematic effects. Combining with Planck 2018 data, we find the upper limits of $Σm_ν< 0.116$ eV and $Σm_ν< 0.117$ eV for the 21cm signal in cross-correlation with the DESI-like and Euclid-like surveys, respectively. These constraints are comparable to those obtained by combining Planck data with the 21cm auto-power spectrum synthetic data sets, thus supporting the case for 21cm cross-correlation detections.

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arXiv2025

Karabo: A versatile SKA Observation Simulation Framework

Karabo is a versatile Python-based software framework simplifying research with radio astronomy data. It bundles existing software packages into a coherent whole to improve the ease of use of its components. Karabo includes useful abstractions, like strategies to scale and parallelize typical workloads or science-specific Python modules. The framework includes functionality to access datasets and mock observations to study the Square Kilometer Array (SKA) instruments and their expected accuracy. SKA will address problems in a wide range of fields of astronomy. We demonstrate the application of Karabo to some of the SKA science cases from HI intensity mapping, mock radio surveys, radio source detection, the epoch of re-ionisation and heliophysics. We discuss the capabilities and challenges of simulating large radio datasets in the context of SKA.

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arXiv2025

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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arXiv2024

Bayesian data analysis for sky-averaged 21-cm experiments with contamination from linearly polarised foreground

The precise measurement of the sky-averaged HI absorption signal between 50 and 200 MHz is the primary goal of global 21-cm cosmology. This measurement has the potential to unravel the underlying physics of cosmic structure formation and evolution during the Cosmic Dawn. It is, however, hindered by various non-smooth, frequency-dependent effects, whose structures resemble those of the signal. One such effect is the leakage of polarised foregrounds into the measured intensity signal: polarised foreground emission undergoes Faraday rotation as it passes through the magnetic fields of the interstellar medium, imprinting a chromatic structure in the relevant frequency range which complicates the extraction of the cosmological HI absorption feature. We investigate the effect of polarised Galactic foregrounds on extracting the global 21-cm signal from simulated data using REACH's data analysis pipeline; the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) is an experiment designed to detect the sky-averaged 21-cm HI signal from the early Universe using physically informed models. Using the REACH pipeline, we successfully recover an injected global 21-cm signal with an amplitude of approximately 0.16 K, centred between 80 and 120 MHz, achieving a low root-mean-square error (less than 30\% of the injected signal strength) in all the tested cases. This includes scenarios with simulated polarised Galactic diffuse emissions and polarised point source emissions, provided the overall polarisation fraction is below $\sim 3\%$. The linear mixing of contamination, caused by the superposition of multiple patches with varying strengths of Faraday rotation, produces patterns that are more distinct from the global signal. This distinction makes global signal recovery easier compared to contamination resulting from a single, slow oscillation pattern.

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arXiv2024

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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arXiv2024

21cm Intensity Mapping cross-correlation with galaxy surveys: current and forecasted cosmological parameters estimation for the SKAO

We present a comprehensive set of forecasts for the cross-correlation signal between 21cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21cm 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 parameterization 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 ($k<0.25 h/$Mpc). The forecasted constraints, obtained with Monte Carlo Markov Chains techniques in a Bayesian framework, in terms of the six base parameters of the standard $Λ$CDM model, are promising. The predicted signal-to-noise ratio for the cross-correlation can reach $\sim 50$ for $z\sim 1$ and $k\sim 0.1 h/$ Mpc. When the cross-correlation signal is combined with current Cosmic Microwave Background (CMB) data from Planck, the error bar on $Ω_{\rm c}\,h^2$ and $H_0$ is reduced by a factor 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 auto-correlation one and combining all the clustering measurements a sub-percent error bar of 0.33% on $H_0$ can be achieved, which is about a factor 2 better than CMB only measurement. 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.

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arXiv2023

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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arXiv2022

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.

astro-ph.CO↗

arXiv2022

Multipole expansion for 21cm Intensity Mapping power spectrum: forecasted cosmological parameters estimation for the SKA Observatory

The measurement of the large scale distribution of neutral hydrogen in the late Universe, obtained with radio telescopes through the hydrogen 21cm line emission, has the potential to become a key cosmological probe in the upcoming years. We explore the constraining power of 21cm intensity mapping observations on the full set of cosmological parameters that describe the $Λ$CDM model. We assume a single-dish survey for the SKA Observatory and simulate the 21cm linear power spectrum monopole and quadrupole within six redshift bins in the range $z=0.25-3$. Forecasted constraints are computed numerically through Markov Chain Monte Carlo techniques. We extend the sampler \texttt{CosmoMC} by implementing the likelihood function for the 21cm power spectrum multipoles. We assess the constraining power of the mock data set alone and combined with Planck 2018 CMB observations. We include a discussion on the impact of extending measurements to non-linear scales in our analysis. We find that 21cm multipoles observations alone are enough to obtain constraints on the cosmological parameters comparable with other probes. Combining the 21cm data set with CMB observations results in significantly reduced errors on all the cosmological parameters. The strongest effect is on $Ω_ch^2$ and $H_0$, for which the error is reduced by almost a factor four. The percentage errors we estimate are $σ_{Ω_ch^2} = 0.25\%$ and $σ_{H_0} = 0.16\%$, to be compared with the Planck only results $σ_{Ω_ch^2} = 0.99\%$ and $σ_{H_0} = 0.79\%$. We conclude that 21cm SKAO observations will provide a competitive cosmological probe, complementary to CMB and, thus, pivotal for gaining statistical significance on the cosmological parameters constraints, allowing a stress test for the current cosmological model.

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