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Steven Cunnington

Publications and source records attributed to Steven Cunnington.

At least 19 recordsLinked to original sources

Beyond {\Lambda}CDM with the SKA Observatory -- II: Unveiling the Secrets of the Early Universe

The origins of the universe remain one of the biggest mysteries in modern cosmology. While the Planck satellite has provided a wealth of information about the early universe, there is still much to be discovered. The Square Kilometre Array Observatory (SKAO) offers a unique opportunity to probe the universe's infancy, going beyond the current limitations of our knowledge. By measuring the power spectrum of biased tracers of the dark matter distribution on the largest cosmological scales and exploring beyond 2-point statistics, SKAO will enable us to refine our understanding of the primordial universe, including the shape of the inflationary power spectrum and the presence of primordial non-Gaussianity. In this chapter we will review recent works looking at the potential of SKAO's surveys, and how synergies with other surveys can revolutionize our understanding of the origins of the cosmos.

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Cosmology with HI Intensity Mapping

The redshifted spectral emission from neutral hydrogen (HI) at rest wavelength 21 cm can be used as a tracer of large-scale structure and its evolution. Within the HI intensity mapping method, sufficient signal-to-noise is achieved by integrating the line emission within large voxels over a wide sky area and line of sight depth which allows access to the largest scales of the matter distribution. The resulting tomographic maps usually feature low angular and high redshift resolution. The SKAO will be able to conduct HI intensity mapping experiments observing up to 20,000 square degrees over a wide range of redshifts. For SKA-Mid, we will employ the array in a fast-scanning single-dish mode using Band 1 and 2 to access 0<z<3, mapping an enormous volume with fast survey speed, allowing for the possibility of a commensal survey producing high angular resolution maps via the on-the-fly imaging of the visibilities. For SKA-Low, we will focus on deep observations to detect the HI signal in a frequency band matching 3<z<6. In this chapter, we will give an overview of HI intensity mapping with the SKAO, including an outline of planned surveys, a discussion of observational challenges, and methodology for power spectrum methodology and forecasts. We present predictions on the constraining power on LambdaCDM cosmology from HI intensity mapping data via power spectrum, and other observables such as bi-spectrum and HI stacking. We also demonstrate the synergy power of HI intensity mapping with other cosmological surveys.

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meer21cm: an Analysis Pipeline and Comprehensive Toolkit for HI Intensity Mapping

We present meer21cm, a comprehensive python package for cosmological data analysis of single-dish HI intensity mapping surveys. This package is simple to use, with a modularised code structure designed for interactive usage. meer21cm is designed for data analysis, with particular focus on the UHF-band observation of MeerKAT Large Area Synoptic Survey (MeerKLASS). We explicitly impose meer21cm to be survey-oriented, ensuring consistent modelling of observational effects in the clustering power spectrum with the survey specifications and data analysis choices. meer21cm covers a large range of data analysis procedures post calibration, including data read-in, foreground cleaning, power spectrum estimation, mock simulation, transfer function corrections and parameter inference. It handles both meer21cm intensity maps and overlapping galaxy catalogues, allowing for multi-tracer and cross-correlation analysis between MeerKLASS and optical galaxy surveys. Tested with a simulated survey of ten $750\,$deg$^2$ sky patches in the redshift sub-band $0.6\,{<}\,z\,{<}\,0.8$, the meer21cm pipeline achieves per-cent accuracy in the power spectrum estimation for $k \in [0.02, 0.2]\,{h{\rm Mpc}^{-1}}$, with deviations $\lesssim 0.5\sigma$ between the mock and the model power spectra, where $\sigma$ is the signal variance. The meer21cm package is publicly available and easy to install, with a comprehensive documentation website at https://meer21cm.readthedocs.io

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Methodological Frontiers in 21-cm Intensity Mapping: the Treatment of Systematics and Foreground Contamination

The distribution of neutral hydrogen (HI) in the post-reionization universe traces the cosmic large-scale structure and therefore serves as a powerful cosmological probe. An efficient way to measure its distribution over wide sky areas and redshift ranges is through single-dish intensity mapping, which exploits the autocorrelation signal of each dish in a telescope array while scanning the same sky patch. Thanks to its broad frequency coverage and technical capabilities, SKA-Mid will enable measurements of the integrated 21 cm emission from HI up to redshift $z\sim3$, making single-dish intensity mapping a key observable for probing dark matter and dark energy. Isolating the faint 21 cm cosmological signal without introducing biases is, however, challenging. The 21 cm signal is several orders of magnitude weaker than the astrophysical foregrounds, and its analysis is further affected by instrumental systematics. Overcoming these difficulties requires detailed modelling together with continuous improvements and innovations in data-analysis techniques. Over the past decade, the international community has developed and tested new methods to address current observational challenges and prepare for forthcoming SKA-Mid observations. This chapter reviews recent advances in map-making and component-separation techniques, with particular emphasis on telescope-specific systematics such as beam response and correlated noise. We focus on results obtained in controlled simulation environments, providing a valuable framework for assessing the strengths and limitations of different approaches. Developing robust algorithms capable of accurately handling instrumental effects and sky-model uncertainties is a crucial step toward fully exploiting the cosmological potential of HI intensity-mapping surveys in the SKA Observatory era.

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Single-dish HI Intensity Mapping with the SKAO: Precursor Progress with MeerKAT's Large Area Synoptic Survey (MeerKLASS)

Using the SKAO to map the intensity of neutral hydrogen's 21cm emission line will be a golden opportunity to constrain models of cosmology. To access the largest cosmological scales, wide-sky surveys should ideally reach thousands of square degrees, requiring SKA-Mid's dishes to scan the sky in auto-correlation mode, so-called single-dish observations. In this chapter, we overview the latest results from MeerKAT's Large Area Synoptic Survey (MeerKLASS), which has been pioneering this single-dish observing strategy, and motivating its continuation with the SKA-Mid AA4 deployment. MeerKLASS, operating on the same Karoo site where the SKA-Mid is being built, has now achieved multiple cosmological detections from single-dish observations, including high-significance cross-correlations with optical galaxy surveys and continually improving measurements of the HI auto-power spectrum. These results demonstrate that stable calibration, effective foreground mitigation, and statistical recovery of cosmological signal are all achievable with a large multi-dish telescope in total-power mode. The success of MeerKLASS therefore validates the observational strategies required for SKA-Mid and marks a key milestone in demonstrating the viability of single-dish HI intensity mapping for cosmology. Looking ahead, SKA-Mid's increased sensitivity and Band 1 coverage (350-1050 MHz) will allow the same methodology to probe redshifts up to $z\,{\sim}\,3$, mapping volumes several orders of magnitude larger than currently accessible. The techniques refined with MeerKLASS thus form the operational and scientific foundation for a large portion of the SKAO's cosmology programme.

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HI Simulations for Cosmology with the SKA Observatory

We present a comparative overview of state-of-the-art methods for modelling the distribution of neutral hydrogen (HI) in the post-reionization Universe, developed in preparation for upcoming SKAO cosmological surveys. Our aim is to assess how different physical and empirical assumptions reflect into predictions for key observables such as the cosmic HI density, the HI mass function, and the HI-halo mass relation. We consider both: (i) semi-analytical approaches that self-consistently evolve baryonic components within dark matter merger trees through physically motivated prescriptions and (ii) empirical schemes tailored to different observables and based on fast approximations designed for large ensemble studies. By comparing the predictions from the different methods considered, we find overall consistency in integrated quantities such as $\Omega_{\mathrm{HI}}$, yet systematic differences in the detailed shape and scatter of the HI--halo mass relation and its redshift evolution. Semi-analytical models offer physically grounded predictions but depend on assumed prescriptions, while empirical methods provide flexibility and computational efficiency at the expense of robustness in extrapolated regions of the parameter space. The increasing number of HI measurements from SKA precursors and pathfinders (including surveys with MeerKAT, ASKAP, and FAST) will provide critical observational constraints to refine and calibrate current simulation methodologies. In turn, increasingly realistic HI simulations play a key role in interpreting these data, guiding survey design and analysis strategies, in preparation for the advent of SKAO data.

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Cosmology from Synergies Between SKAO Surveys and Gravitational Wave Observations

Both radio surveys and gravitational wave observations have the potential to probe unprecedented volumes in the Universe with systematics independent of existing cosmological probes. This gives them the potential, especially in combination, to solve some of the outstanding issues in cosmology. Here we show how the use of radio observations as electromagnetic signals tracing large scale structures can be used to provide information on gravitational wave \textit{standard sirens}. By providing a way to link luminosity distance to redshift, this combination can constrain the expansion history of the Universe, and provide information on the Hubble constant ($H_0$). We describe the utility of SKA-Mid neutral hydrogen (\hi) intensity maps, \hi\ galaxy redshift surveys, and continuum galaxy surveys compared to and in conjunction with large contemporaneous optical surveys. Such radio tracers provide a unique, large volume and high redshift information for gravitational wave source, capable of probing effectively the expansion history of the Universe $H(z)$.

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Tracing Large-scale Structure with the MeerKLASS On-the-Fly Survey: Angular Clustering of Radio Sources at 816 MHz

We present the first measurement of the angular two-point correlation function \(w(\theta)\) of radio sources from the MeerKAT Large Area Synoptic Survey (MeerKLASS) UHF on-the-fly (OTF) continuum Data Release~1. DR1 provides interferometric Stokes-\(I\) imaging at a reference frequency of 816\,MHz over \(\sim 800~\mathrm{deg}^2\) within the DESI footprint. We detect a positive clustering signal over \(0.02^\circ \lesssim \theta \lesssim 10^\circ\). The measurement is stable to reasonable variations of the depth mask and flux threshold on intermediate and large scales. Modelling the intermediate-scale signal (\(0.112^\circ\le\theta\le 1.36^\circ\)) with a fixed-slope power law (\(\gamma=1.8\)) yields \(A(1^\circ)=(1.434\pm0.475)\times10^{-3}\), corresponding to \(\log_{10}A=-2.843^{+0.124}_{-0.175}\). We infer an effective large-scale bias by fitting \(\Lambda\)CDM projected-matter templates \(w_{\rm DM}(\theta)\) computed with \textsc{CAMB} and Limber projection, including an integral-constraint correction evaluated from random--random weights. Using two bracketing T-RECS redshift-distribution priors, we obtain \(b_{\rm eff}=1.998\pm0.350\) (AGN prior) and \(b_{\rm eff}=1.530\pm0.265\) (TOTAL prior), demonstrating that the dominant modelling uncertainty arises from \(N(z)\). As a derived summary we Limber-invert the power-law amplitude to obtain \(r_0=6.18\pm1.13\) and \(5.59\pm1.02~h^{-1}\mathrm{Mpc}\) for the AGN and TOTAL priors, respectively. These results establish MeerKLASS UHF DR1 as a new wide-area, intermediate-frequency dataset for radio-continuum clustering. As MeerKLASS expands and overlapping optical/IR spectroscopy provides improved redshift calibration, future releases will enable population-split clustering and bias evolution measurements with substantially reduced modelling uncertainty.

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Radio sirens: inferring $H_0$ with binary black holes and neutral hydrogen in the era of the Einstein Telescope and the SKA Observatory

A new synergy between gravitational waves (GWs) and the study of the large-scale structure of the Universe is now emerging. Along this line of research, we combine simulated observations of stellar-origin black hole mergers and neutral hydrogen 21 cm line intensity mapping to probe the expansion rate of the Universe through the distance-redshift relation. GW signals from binary black holes provide direct distance information, while neutral hydrogen intensity maps offer a tomographic view of the large-scale structure of the Universe. Using the 3-dimensional density fields of hydrogen as a redshift prior for GW events, we explore a novel dark-sirens-like approach, here termed radio sirens, to measure the late-time expansion history of the Universe. We study the performance of the next-generation GW observatories, such as the Einstein Telescope, to ensure enough statistics and access to high-redshift data. On the other hand, future spectroscopic intensity mapping surveys with the SKA-Mid telescope are expected to trace the underlying dark matter distribution at large scales up to redshift $z\sim 3$. This combined methodology allows us to constrain the Hubble constant to $\sim 8\%$ precision, using around 3,000 GW events with signal-to-noise ratios greater than 150. This corresponds to an improvement of around $90\%$ compared to not considering the information from the neutral hydrogen maps.

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Bayesian component separation and power spectrum estimation for 21 cm intensity mapping data cubes

Foreground removal remains an ongoing challenge in radio cosmology, and increasingly sensitive experiments necessitate more robust analysis techniques. In this work, we model simulated data from a single-dish intensity mapping experiment, and use the Gibbs sampling and Gaussian constrained realisation (GCR) techniques to draw samples from the posterior probability distribution of the model parameters. This allows for a separation of the foregrounds and 21 cm signal at the map level, as well as recovery of the 1-dimensional HI power spectrum to within statistical uncertainties. Despite the model consisting of over 2 million free parameters in the example presented here, these methods allow us to sample from the Bayesian posterior at a rate of $<30$ seconds per iteration. This framework is also resilient to frequency channel flagging (e.g. due to RFI excision), with the GCR steps effectively in-painting the missing data with statistically-consistent model realisations. The power spectrum is recovered accurately in the presence of strong foreground contamination and RFI flagging -- the estimate falling within $2\sigma$ of the true model in our example, similar to the commonly-used transfer function correction method. Statistical realisations of foreground and HI maps are also recovered, with associated uncertainties available from the full joint posterior distribution of all parameters.

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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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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 $8.66\sigma$ when averaged into an angular map, and $7.45\sigma$ 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 $\nu_{\rm sys}\,[{\rm MHz}] = 17.90^{+6.53}_{-4.27}$. 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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Cosmology with ESO-SKAO Synergies

We discuss the possible synergies for cosmology between SKAO and ESO facilities, focusing on the combinations SKA-Mid with the Multi-Object Spectrograph Telescope (4MOST) instrument built for ESO's Visible and Infrared Survey Telescope for Astronomy (VISTA), and SKA-Low with ESO's Extremely Large Telescope (ELT) multi-object spectrograph MOSAIC. Combining multiple tracers allows for tackling systematics and lifting parameter degeneracies. It will play a crucial role in the pursuit of precision cosmology.

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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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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 ($\Omega_{HI}$) and linear clustering bias ($b_{HI}$) up to a cross-correlation coefficient ($r$). We measured $\Omega_{HI}b_{HI}r = [0.93 \pm 0.17]\,\times\,10^{-3}$ with a $\approx6\sigma$ 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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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 ${>}\,4\,\sigma$ 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 $\Omega_{\rm HI}$ 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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