arXiv subjects

Mario G. Santos

Publications and source records attributed to Mario G. Santos.

At least 37 records · Page 2Linked to original sources

arXiv2025

First Results from HERA Phase II

We report the first upper limits on the power spectrum of 21-cm fluctuations during the Epoch of Reionization and Cosmic Dawn from Phase II of the Hydrogen Epoch of Reionization Array (HERA) experiment. HERA Phase II constitutes several significant improvements in the signal chain compared to Phase I, most notably resulting in expanded frequency bandwidth, from 50-250 MHz. In these first upper limits, we investigate a small two-week subset of the available Phase II observations, with a focus on identifying new systematic characteristics of the instrument, and establishing an analysis pipeline to account for them. We report 2$σ$ upper limits in eight spectral bands, spanning $5.6 \leq z \leq 24.4$ that are consistent with thermal noise at the $2σ$ level for $k \gtrsim 0.6-0.9 h{\rm Mpc}^{-1}$ (band dependent). Our tightest limit during Cosmic Dawn ($z>12$) is $1.13\times 10^6 {\rm mK}^2$ at ($k=0.55 h{\rm Mpc}^{-1}, z=16.78$), and during the EoR ($5.5<z<12$) it is $1.78\times 10^3 {\rm mK}^2$ at ($k=0.70 h{\rm Mpc}^{-1}, z=7.05$). We find that mutual coupling has become our dominant systematic, leaking foreground power that strongly contaminates the low-$k$ modes, resulting in the loss of modes from $k=0.35-0.55$ compared to Phase I data.

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arXiv2025

MIGHTEE-HI: The HI mass-stellar mass relation of massive galaxies and the HI mass function at 0.25<z<0.5

The relationship between the already formed stellar mass in a galaxy and the gas reservoir of neutral atomic hydrogen, is a key element in our understanding of how gas is turned into stars in galaxy haloes. In this paper, we measure the $M_{\rm HI}-M_{\star}$ relation based on a stellar-mass selected sample at $0.25 < z < 0.5$ and the MIGHTEE-HI DR1 spectral data. Using a powerful Bayesian stacking technique, for the first time we are also able to measure the underlying bivariate distribution of HI mass and stellar mass of galaxies with $M_\star > 10^{9.5}$ M$_{\odot}$, finding that an asymmetric underlying HI distribution is strongly preferred by our complete samples. We define the concepts of the average of the logarithmic HI mass, $\langle\log_{10}(M_{\rm HI})\rangle$, and the logarithmic average of the HI mass, $\log_{10}(\langle M_{\rm HI}\rangle)$, and find that the difference between $\langle\log_{10}(M_{\rm HI})\rangle$ and $\log_{10}(\langle M_{\rm HI}\rangle)$ can be as large as $\sim$0.5 dex for the preferred asymmetric HI distribution. We observe shallow slopes in the underlying $M_{\rm HI}-M_{\star}$ scaling relations, suggesting the presence of an upper HI mass limit beyond which a galaxy can no longer retain further HI gas. From our bivariate distribution we also infer the HI mass function at this redshift and find tentative evidence for a decrease of 2-10 times in the co-moving space density of the most HI massive galaxies up to $z\sim 0.5$.

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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

Primary Beam Chromaticity in HIRAX: I. Characterization from Simulations and Power Spectrum Implications

The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) is an upcoming radio interferometric telescope designed to constrain dark energy through the 21cm intensity mapping of Baryon Acoustic Oscillations (BAO). Instrumental systematics must be controlled and carefully characterized to measure the 21cm power spectrum with fidelity and achieve high-precision constraints on the cosmological parameters. The chromaticity of the primary beam is one such complicated systematic, which can leak the power of spectrally smooth foregrounds beyond the ideal horizon limits due to the complex spatial and spectral structures of the sidelobes and the mainlobe. This paper studies the chromaticity of the HIRAX Stokes I primary beam and its effects on accurate measurements of the 21cm power spectrum. To investigate the effect of chromaticity in the 21cm power spectrum, we present a physically motivated beam modeling technique, which uses a flexible basis derived from traditional optics that can account for higher-order radial and azimuthal structures in the primary beam. We investigate the impact of imperfect knowledge of the mainlobe and sidelobes chromaticity in the power spectrum space by subtracting a simple foreground model in simulated snapshot visibilities to recover the H$\textsc{i}$ power spectrum. Additionally, we find that modeling up to the octupolar azimuthal order feature (fourth-order angular variation) in the primary beam is sufficient to reduce the leakage outside the wedge with minimal bias.

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arXiv2025

A demonstration of the effect of fringe-rate filtering in the Hydrogen Epoch of Reionization Array delay power spectrum pipeline

Radio interferometers targeting the 21cm brightness temperature fluctuations at high redshift are subject to systematic effects that operate over a range of different timescales. These can be isolated by designing appropriate Fourier filters that operate in fringe-rate (FR) space, the Fourier pair of local sidereal time (LST). Applications of FR filtering include separating effects that are correlated with the rotating sky vs. those relative to the ground, down-weighting emission in the primary beam sidelobes, and suppressing noise. FR filtering causes the noise contributions to the visibility data to become correlated in time however, making interpretation of subsequent averaging and error estimation steps more subtle. In this paper, we describe fringe rate filters that are implemented using discrete prolate spheroidal sequences, and designed for two different purposes -- beam sidelobe/horizon suppression (the `mainlobe' filter), and ground-locked systematics removal (the `notch' filter). We apply these to simulated data, and study how their properties affect visibilities and power spectra generated from the simulations. Included is an introduction to fringe-rate filtering and a demonstration of fringe-rate filters applied to simple situations to aid understanding.

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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

Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data

Observations with radio arrays that target the 21-cm signal originating from the early Universe suffer from a variety of systematic effects. An important class of these are reflections and spurious couplings between antennas. We apply a Hamiltonian Monte Carlo sampler to the modelling and mitigation of these systematics in simulated Hydrogen Epoch of Reionisation Array (HERA) data. This method allows us to form statistical uncertainty estimates for both our models and the recovered visibilities, which is an important ingredient in establishing robust upper limits on the Epoch of Reionisation (EoR) power spectrum. In cases where the noise is large compared to the EoR signal, this approach can constrain the systematics well enough to mitigate them down to the noise level for both systematics studied. Incoherently averaging the recovered power spectra can further reduce the noise and improve recovery. Where the noise level is lower than the EoR, our modelling can mitigate the majority of the reflections and coupling with there being only a minor level of residual systematics. Our approach performs similarly to existing filtering/fitting techniques used in the HERA pipeline, but with the added benefit of rigorously propagating uncertainties. In all cases it does not significantly attenuate the underlying signal.

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arXiv2025

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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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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arXiv2025

matvis: A matrix-based visibility simulator for fast forward modelling of many-element 21 cm arrays

Detection of the faint 21 cm line emission from the Cosmic Dawn and Epoch of Reionisation will require not only exquisite control over instrumental calibration and systematics to achieve the necessary dynamic range of observations but also validation of analysis techniques to demonstrate their statistical properties and signal loss characteristics. A key ingredient in achieving this is the ability to perform high-fidelity simulations of the kinds of data that are produced by the large, many-element, radio interferometric arrays that have been purpose-built for these studies. The large scale of these arrays presents a computational challenge, as one must simulate a detailed sky and instrumental model across many hundreds of frequency channels, thousands of time samples, and tens of thousands of baselines for arrays with hundreds of antennas. In this paper, we present a fast matrix-based method for simulating radio interferometric measurements (visibilities) at the necessary scale. We achieve this through judicious use of primary beam interpolation, fast approximations for coordinate transforms, and a vectorised outer product to expand per-antenna quantities to per-baseline visibilities, coupled with standard parallelisation techniques. We validate the results of this method, implemented in the publicly-available matvis code, against a high-precision reference simulator, and explore its computational scaling on a variety of problems.

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arXiv2024

Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment.

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arXiv2024

Deep extragalactic HI survey of the COSMOS field with FAST

We present a deep HI survey at L-band conducted with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) over the COSMOS field. This survey is strategically designed to overlap with the MIGHTEE COSMOS field, aiming to combine the sensitivity of the FAST and high-resolution of the MeerKAT. We observed the field with FAST for approximately 11 hours covering $\sim$2 square degrees, and reduced the raw data to HI spectral cubes over the frequency range 1310-1420 MHz. The FAST-HI data reach a median 3$σ$ column density of $N_{\rm HI}\sim2\times10^{17}$ cm$^{-2}$ over a 5 km s$^{-1}$ channel width, allowing for studies of the distribution of HI gas in various environments, such as in galaxies, the Circum-Galactic Medium (CGM) and Intergalactic Medium (IGM). We visually searched the spectral cubes for HI sources, and found a total of 80 HI detections, of which 56 have been cross-matched with the MIGHTEE-HI catalogue. With the cross-matched sources, we compare their HI masses and find that the total HI mass fraction in the IGM and CGM surrounding the galaxy pairs is statistically higher than the HI fraction surrounding the isolated galaxies by a difference of 13$\pm$4%, indicating that the CGM and IGM associated with interacting systems are richer in neutral hydrogen compared to those around isolated galaxies in the local Universe. We also describe several FAST-MeerKAT synergy projects, highlighting the full potential of exploiting both single-dish and interferometric observations to study the distribution and evolution of the diffuse HI gas.

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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

Hydrogen Epoch of Reionization Array (HERA) Phase II Deployment and Commissioning

This paper presents the design and deployment of the Hydrogen Epoch of Reionization Array (HERA) phase II system. HERA is designed as a staged experiment targeting 21 cm emission measurements of the Epoch of Reionization. First results from the phase I array are published as of early 2022, and deployment of the phase II system is nearing completion. We describe the design of the phase II system and discuss progress on commissioning and future upgrades. As HERA is a designated Square Kilometer Array (SKA) pathfinder instrument, we also show a number of "case studies" that investigate systematics seen while commissioning the phase II system, which may be of use in the design and operation of future arrays. Common pathologies are likely to manifest in similar ways across instruments, and many of these sources of contamination can be mitigated once the source is identified.

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arXiv2023

Mitigating the effect of 1/f noise on the detection of the HI intensity mapping power spectrum from single-dish measurements

We present and compare several methods to mitigate time-correlated (1/f) noise within the HI intensity mapping component of the MeerKAT Large Area Synoptic Survey (MeerKLASS). By simulating scan strategies, the HI signal, foreground emissions, white and correlated noise, we assess the ability of various data processing pipelines to recover the power spectrum of HI brightness temperature fluctuations. We use MeerKAT pilot data to assess the level of 1/f noise expected for the MeerKLASS survey and use these measurements to create realistic levels of time-correlated noise for our simulations. We find the time-correlated noise component within the pilot data to be between 10 and 20 times higher than the white noise level at the scale of k = 0.04 Mpc^-1. Having determined that the MeerKAT 1/f noise is partially correlated across all the frequency channels, we employ Singular Value Decomposition (SVD) as a technique to remove both the 1/f noise and Galactic foregrounds but find that over-cleaning results in the removal of HI power at large (angular and radial) scales; a power loss of 40 per cent is seen for a 3-mode SVD clean at the scale of k = 0.04 Mpc^-1. We compare the impact of map-making using weighting by the full noise covariance (i.e. including a 1/f component), as opposed to just a simple unweighted binning, finding that including the time-correlated noise information reduces the excess power added by 1/f noise by up to 30 per cent.

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arXiv2023

MIGHTEE-HI: The HI mass-stellar mass relation over the last billion years

We study the $M_{\rm HI}-M_{\star}$ relation over the last billion years using the MIGHTEE-HI sample. We first model the upper envelope of the $M_{\rm HI}-M_{\star}$ relation with a Bayesian technique applied to a total number of 249 HI-selected galaxies, without binning the datasets, while taking account of the intrinsic scatter. We fit the envelope with both linear and non-linear models, and find that the non-linear model is preferred over the linear one with a measured transition stellar mass of $\log_{10}(M_\star$/$M_{\odot})$ = $9.15\pm0.87$, beyond which the slope flattens. This finding supports the view that the lack of HI gas is ultimately responsible for the decreasing star formation rate observed in the massive main-sequence galaxies. For spirals alone, which are biased towards the massive galaxies in our sample, the slope beyond the transition mass is shallower than for the full sample, indicative of distinct gas processes ongoing for the spirals/high-mass galaxies from other types with lower stellar masses. We then create mock catalogues for the MIGHTEE-HI detections and non-detections with two main galaxy populations of late- and early-type galaxies to measure the underlying $M_{\rm HI}-M_{\star}$ relation. We find that the turnover in this relation persists whether considering the two galaxy populations as a whole or separately. We note that an underlying linear relation could mimic this turnover in the observed scaling relation, but a model with a turnover is strongly preferred. Measurements on the logarithmic average of HI masses against the stellar mass are provided as a benchmark for future studies.

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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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arXiv2023

Emulating radiation transport on cosmological scale using a denoising Unet

Semi-numerical simulations are the leading candidates for evolving reionization on cosmological scales. These semi-numerical models are efficient in generating large-scale maps of the 21cm signal, but they are too slow to enable inference at the field level. We present different strategies to train a U-Net to accelerate these simulations. We derive the ionization field directly from the initial density field without using the ionizing sources' location, and hence emulating the radiative transfer process. We find that the U-Net achieves higher accuracy in reconstructing the ionization field if the input includes either white noise or a noisy version of the ionization map beside the density field during training. Our model reconstructs the power spectrum over all scales perfectly well. This work represents a step towards generating large-scale ionization maps with a minimal cost and hence enabling rapid parameter inference at the field level.

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