Paula S. Soares

Bio: Paula S. Soares is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Intensity mapping & Multipole expansion. The author has an hindex of 4, co-authored 6 publications receiving 41 citations.

H I intensity mapping with MeerKAT: calibration pipeline for multidish autocorrelation observations

Abstract: While most purpose-built 21cm intensity mapping experiments are close-packed interferometer arrays, general-purpose dish arrays should also be capable of measuring the cosmological 21cm signal. This can be achieved most efficiently if the array is used as a collection of scanning autocorrelation dishes rather than as an interferometer. As a first step towards demonstrating the feasibility of this observing strategy, we show that we are able to successfully calibrate dual-polarisation autocorrelation data from 64 MeerKAT dishes in the L-band (856-1712 MHz, 4096 channels), with 10.5 hours of data retained from six nights of observing. We describe our calibration pipeline, which is based on multi-level RFI flagging, periodic noise diode injection to stabilise gain drifts and an absolute calibration based on a multi-component sky model. We show that it is sufficiently accurate to recover maps of diffuse celestial emission and point sources over a 10 deg x 30 deg patch of the sky overlapping with the WiggleZ 11hr field. The reconstructed maps have a good level of consistency between per-dish maps and external datasets, with the estimated thermal noise limited to 1.4 x the theoretical noise level (~ 2 mK). The residual maps have rms amplitudes below 0.1 K, corresponding to <1% of the model temperature. The reconstructed Galactic HI intensity map shows excellent agreement with the Effelsberg-Bonn HI Survey, and the flux of the radio galaxy 4C+03.18 is recovered to within 3.6%, which demonstrates that the autocorrelation can be successfully calibrated to give the zero-spacing flux and potentially help in the imaging of MeerKAT interferometric data. Our results provide a positive indication towards the feasibility of using MeerKAT and the future SKA to measure the HI intensity mapping signal and probe cosmology on degree scales and above.

Gaussian Process Regression for foreground removal in HI intensity mapping experiments

Abstract: We apply for the first time Gaussian Process Regression (GPR) as a foreground removal technique in the context of single-dish, low redshift HI intensity mapping, and present an open-source python toolkit for doing so. We use MeerKAT and SKA1-MID-like simulations of 21cm foregrounds (including polarisation leakage), HI cosmological signal and instrumental noise. We find that it is possible to use GPR as a foreground removal technique in this context, and that it is better suited in some cases to recover the HI power spectrum than Principal Component Analysis (PCA), especially on small scales. GPR is especially good at recovering the radial power spectrum, outperforming PCA when considering the full bandwidth of our data. Both methods are worse at recovering the transverse power spectrum, since they rely on frequency-only covariance information. When halving our data along frequency, we find that GPR performs better in the low frequency range, where foregrounds are brighter. It performs worse than PCA when frequency channels are missing, to emulate RFI flagging. We conclude that GPR is an excellent foreground removal option for the case of single-dish, low redshift HI intensity mapping. Our python toolkit gpr4im and the data used in this analysis are publicly available on GitHub. The GitHub symbol in the caption of each figure links to a jupyter notebook showing how the figure was produced.

H i intensity mapping with MeerKAT: Power spectrum detection in cross-correlation with WiggleZ galaxies

Abstract: 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 ${\rm H}\, \small {\rm I}$ density fraction ($\Omega _{{\rm H}\, \small {\rm I}}$), ${\rm H}\, \small {\rm I}$ bias ($b_{{\rm H}\, \small {\rm I}}$) and the cross-correlation coefficient (r). We therefore obtain the constraint $\Omega _{{\rm H}\, \small {\rm I}}b_{{\rm H}\, \small {\rm I}}r\, {=}\, [0.86\, {\pm }\, 0.10\, ({\rm stat})\, {\pm }\, 0.12\, ({\rm sys})]\, {\times }\, 10^{-3}$, at an effective scale of keff ∼ 0.13 h 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 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.

Multipole expansion for H I intensity mapping experiments: simulations and modelling

Abstract: We present a framework and an open-source python toolkit to analyse the 2-point statistics of 3D fluctuations in the context of HI intensity maps using the multipole expansion formalism. We include simulations of the cosmological HI signal using N-body and log-normal methods, foregrounds and their removal, as well as instrumental effects. Using these simulations and analytical modelling, we investigate the impact of foreground cleaning and the instrumental beam on the power spectrum multipoles as well as on the Fourier space clustering wedges. We find that both the instrumental beam and the foreground removal can produce a quadrupole (and a hexadecapole) signal, and demonstrate the importance of controlling and accurately modelling these effects for precision radio cosmology. We conclude that these effects can be modelled with reasonable accuracy using our multipole expansion technique. We also perform an MCMC analysis to showcase the effect of foreground cleaning on the estimation of the HI abundance and bias parameters. The accompanying python toolkit is available at this https URL, and includes an interactive suite of examples to aid new users.

Power spectrum multipole expansion for H i intensity mapping experiments: unbiased parameter estimation

Abstract: We assess the performance of the multipole expansion formalism in the case of single-dish H i intensity mapping, including instrumental and foreground removal effects. This formalism is used to provide Markov chain Monte Carlo forecasts for a range of H i and cosmological parameters, including redshift space distortions and the Alcock–Paczynski effect. We first determine the range of validity of our power spectrum modelling by fitting to simulation data, concentrating on the monopole, quadrupole, and hexadecapole contributions. We then show that foreground subtraction effects can lead to severe biases in the determination of cosmological parameters, in particular the parameters relating to the transverse Baryon Acoustic Oscillations (BAO) rescaling, the growth rate, and the H i bias (α⊥, $\\overline{T}_\\rm{H{\\small I}}f\\sigma _8$, and $\\overline{T}_{\\mathrm {H}\\,{\\small I}}b_{\\mathrm {H}\\,{\\small I}}\\sigma _8$, respectively). We attempt to account for these biases by constructing a two-parameter foreground modelling prescription, and find that our prescription leads to unbiased parameter estimation at the expense of increasing the estimated uncertainties on cosmological parameters. In addition, we confirm that instrumental and foreground removal effects significantly impact the theoretical covariance matrix, and cause the covariance between different multipoles to become non-negligible. Finally, we show the effect of including higher order multipoles in our analysis, and how these can be used to investigate the presence of instrumental and systematic effects in H i intensity mapping data.

The American statistician

Abstract: Statistical Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1, 124, 254, 297 History Corner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20, 179 Teacher’s Corner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 173, 263, 335 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40, 147, 211, 366 Statistical Computing and Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Statistical Computing and Software Reviews . . . . . . . . . . . . . . . . . . . . . . . . 75, 187 Reviews of Books and Teaching Materials . . . . . . . . . . . . . . . . . 92, 189, 281, 401 Brief Reviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100, 195, 292, 404 Letters to the Editor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102, 197, 294, 406 Special Section: Statistical Training and Curricular Revision . . . . . . . . . . . . . 105 Errata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 Special Section: Opportunities and Challenges for the Discipline . . . . . . . . . 201 Software Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Baryon Acoustic Oscillation Intensity Mapping of Dark Energy

Abstract: The expansion of the universe appears to be accelerating, and the mysterious anti-gravity agent of this acceleration has been called ``dark energy''. To measure the dynamics of dark energy, Baryon Acoustic Oscillations (BAO) can be used. Previous discussions of the BAO dark energy test have focused on direct measurements of redshifts of as many as $10^9$ individual galaxies, by observing the 21cm line or by detecting optical emission. Here we show how the study of acoustic oscillation in the 21 cm brightness can be accomplished by economical three dimensional intensity mapping. If our estimates gain acceptance they may be the starting point for a new class of dark energy experiments dedicated to large angular scale mapping of the radio sky, shedding light on dark energy.

Unveiling the Universe with emerging cosmological probes

Abstract: Abstract The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave Background, Supernovae Type Ia, Baryon Acoustic Oscillations) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most importantly, to increase the accuracy and robustness of our results. This review is meant to provide a state-of-art benchmark of the latest advances in emerging “beyond-standard” cosmological probes. We present how several different methods can become a key resource for observational cosmology. In particular, we review cosmic chronometers, quasars, gamma-ray bursts, standard sirens, lensing time-delay with galaxies and clusters, cosmic voids, neutral hydrogen intensity mapping, surface brightness fluctuations, stellar ages of the oldest objects, secular redshift drift, and clustering of standard candles. The review describes the method, systematics, and results of each probe in a homogeneous way, giving the reader a clear picture of the available innovative methods that have been introduced in recent years and how to apply them. The review also discusses the potential synergies and complementarities between the various probes, exploring how they will contribute to the future of modern cosmology.

Recovery of 21-cm intensity maps with sparse component separation

Abstract: 21-cm intensity mapping has emerged as a promising technique to map the large-scale structure of the Universe. However, the presence of foregrounds with amplitudes orders of magnitude larger than the cosmological signal constitutes a critical challenge. Here, we test the sparsity-based algorithm generalized morphological component analysis (GMCA) as a blind component separation technique for this class of experiments. We test the GMCA performance against realistic full-sky mock temperature maps that include, besides astrophysical foregrounds, also a fraction of the polarized part of the signal leaked into the unpolarized one, a very troublesome foreground to subtract, usually referred to as polarization leakage. To our knowledge, this is the first time the removal of such component is performed with no prior assumption. We assess the success of the cleaning by comparing the true and recovered power spectra, in the angular and radial directions. In the best scenario looked at, GMCA is able to recover the input angular (radial) power spectrum with an average bias of |${\sim} 5{{\ \rm per\ cent}}$| for l > 25 (⁠|$20\!-\!30 {{\ \rm per\ cent}}$| for |$k_{\parallel } \gtrsim 0.02 \, h^{-1}$| Mpc), in the presence of polarization leakage. Our results are robust also when up to |$40{{\ \rm per\ cent}}$| of channels are missing, mimicking a radio-frequency interference (RFI) flagging of the data. Having quantified the notable effect of polarization leakage on our results, in perspective we advocate the use of more realistic simulations when testing 21-cm intensity mapping capabilities.