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Eloy de Lera Acedo

Publications and source records attributed to Eloy de Lera Acedo.

At least 55 records · Page 3Linked to original sources

The effects of the antenna power pattern uncertainty within a global 21 cm experiment

Experimental 21 cm cosmology aims to detect the formation of the first stars during the cosmic dawn and the subsequent epoch of reionization by utilizing the 21 cm hydrogen line transition. While several experiments have published results that begin to constrain the shape of this signal, a definitive detection has yet to be achieved. In this paper, we investigate the influence of uncertain antenna-sky interactions on the possibility of detecting the signal. This paper aims to define the level of accuracy to which a simulated antenna beam pattern is required to agree with the actual observing beam pattern of the antenna to allow for a confident detection of the global 21 cm signal. By utilising singular value decomposition, we construct a set of antenna power patterns that incorporate minor, physically motivated variations. We take the absolute mean averaged difference between the original beam and the perturbed beam averaged over frequency ($ΔD$) to quantifying this difference, identifying the correlation between $ΔD$ and antenna temperature. To analyse the impact of $ΔD$ on making a confident detection, we utilize the REACH Bayesian analysis pipeline and compare the Bayesian evidence $\log \mathcal{Z}$ and root-mean-square error for antenna beams of different $ΔD$ values. Our calculations suggest that achieving an agreement between the original and perturbed antenna power pattern with $ΔD$ better than -35 dB is necessary for confident detection of the global 21 cm signal. Furthermore, we discuss potential methods to achieve the required high level of accuracy within a global 21~cm experiment.

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Global 21 cm Signal Recovery Under Changing Environmental Conditions

The redshifted 21 cm line of cosmic atomic hydrogen is one of the most auspicious tools in deciphering the early Universe. Recovering this signal remains an ongoing problem for cosmologists in the field, with the signal being hidden behind foregrounds approximately five orders of magnitude brighter than itself. A traditional forward modelling data analysis pipeline using Bayesian data analysis and a physically motivated foreground model to find this signal shows great promise in the case of unchanging environmental conditions. However we demonstrate in this paper that in the presence of a soil with changing dielectric properties under the antenna over time, or a changing soil temperature in the far field of our observation these traditional methods struggle. In this paper we detail a tool using Masked Auto-regressive Flows that improves upon previous physically motivated foreground models when one is trying to recover this signal in the presence of changing environmental conditions. We demonstrate that with these changing parameters our tool consistently recovers the signal with a much greater Bayesian evidence than the traditional data analysis pipeline, decreasing the root mean square error in the recovery of the injected signal by up to 45 %.

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Understanding spectral artefacts in SKA-LOW 21-cm cosmology experiments: the impact of cable reflections

The Cosmic Dawn was marked by the formation of the first stars, and preceded the Epoch of Reionization (EoR), when the Universe underwent a fundamental transformation caused by the radiation from these first stars and galaxies. Interferometric 21-cm experiments aim to probe redshifted neutral hydrogen signals from these periods, constraining the conditions of the early Universe. The SKA-Low instrument of the Square Kilometre Array (SKA) is envisaged to be the largest and most sensitive radio telescope at metre and centimetre wavelengths. The latest Aperture Array Verification Systems feature 7-m coaxial transmission lines connecting the low noise amplifiers to optical transmitters at the front of the analogue-receiving chain. An impedance mismatch between these components results in a partially reflected electromagnetic signal, introducing chromatic aberrations into the instrument bandpass. This causes power from the foreground signals to appear at higher delays, potentially contaminating the 'EoR window', a region in which the 21-cm signal should be detectable. We present an end-to-end simulation pipeline for SKA-Low using a composite sky model combining radio foregrounds from the Galactic and Extragalactic All-Sky MWA (GLEAM) Survey, Haslam $408\,$MHz, and a 1.5-cGpc 21-cm brightness temperature cube generated with the 21cmSPACE simulator. We derive a model for the scattering parameters of a coaxial transmission line in terms of its specifications and bulk material properties. Assuming identical cables of length $\leq 15.0\,$m with impedance mismatch $\leq 10\, Ω$, the reflection is confined below the EoR window. However, we demonstrate that even a 0.1 per cent length tolerance introduces contamination with an absolute fractional difference of $\sim 10$ per cent across all accessible k-modes.

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A Broadband Multipole Method for Accelerated Mutual Coupling Analysis of Large Irregular Arrays Including Rotated Antennas

We present a numerical method for the analysis of mutual coupling effects in large, dense and irregular arrays with identical antennas. Building on the Method of Moments (MoM), our technique employs a Macro Basis Function (MBF) approach for rapid direct inversion of the MoM impedance matrix. To expedite the reduced matrix filling, we propose an extension of the Steepest-Descent Multipole expansion which remains numerically stable and efficient across a wide bandwidth. This broadband multipole-based approach is well suited to quasi-planar problems and requires only the pre-computation of each MBF's complex patterns, resulting in low antenna-dependent pre-processing costs. The method also supports arrays with arbitrarily rotated antennas at low additional cost. A simulation of all embedded element patterns of irregular arrays of 256 complex log-periodic antennas completes in just 10 minutes per frequency point on a current laptop, with an additional minute per new layout.

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High-dimensional inference of radio interferometer beam patterns I: Parametric model of the HERA beams

Accurate modelling of the primary beam is an important but difficult task in radio astronomy. For high dynamic range problems such as 21cm intensity mapping, small modelling errors in the sidelobes and spectral structure of the beams can translate into significant systematic errors. Realistic beams exhibit complex spatial and spectral structure, presenting a major challenge for beam measurement and calibration methods. In this paper series, we present a Bayesian framework to infer per-element beam patterns from the interferometric visibilities for large arrays with complex beam structure, assuming a particular (but potentially uncertain) sky model and calibration solution. In this first paper, we develop a compact basis for the beam so that the Bayesian computation is tractable with high-dimensional sampling methods. We use the Hydrogen Epoch of Reionization Array (HERA) as an example, verifying that the basis is capable of describing its single-element E-field beam (i.e. without considering array effects like mutual coupling) with a relatively small number of coefficients. We find that 32 coefficients per feed, incident polarization, and frequency, are sufficient to give percent-level and $\sim$10\% errors in the mainlobe and sidelobes respectively for the current HERA Vivaldi feeds, improving to $\sim 0.1\%$ and $\sim 1\%$ for 128 coefficients.

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Direct Optimal Mapping Image Power Spectrum and its Window Functions

The key to detecting neutral hydrogen during the epoch of reionization (EoR) is to separate the cosmological signal from the dominating foreground radiation. We developed direct optimal mapping (DOM) to map interferometric visibilities; it contains only linear operations, with full knowledge of point spread functions from visibilities to images. Here, we demonstrate a fast Fourier transform-based image power spectrum and its window functions computed from the DOM images. We use noiseless simulation, based on the Hydrogen Epoch of Reionization Array Phase I configuration, to study the image power spectrum properties. The window functions show $<10^{-11}$ of the integrated power leaks from the foreground-dominated region into the EoR window; the 2D and 1D power spectra also verify the separation between the foregrounds and the EoR.

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Calibration Error in 21-centimeter Global Spectrum Experiments

The redshifted 21 cm line signal is a powerful probe of the cosmic dawn and the epoch of reionization. The global spectrum can potentially be detected with a single antenna and spectrometer. However, this measurement requires an extremely accurate calibration of the instrument to facilitate the separation of the 21 cm signal from the much brighter foregrounds and possible variations in the instrument response. Understanding how the measurement errors propagate in a realistic instrument system and affect system calibration is the focus of this work. We simulate a 21 cm global spectrum observation based on the noise wave calibration scheme. We focus on how measurement errors in reflection coefficients affect the noise temperature and how typical errors impact the recovery of the 21 cm signal, especially in the frequency domain. Results show that for our example set up, a typical vector network analyzer (VNA) measurement error in the magnitude of the reflection coefficients of the antenna, receiver, and open cable, which are 0.001, 0.001, and 0.002 (linear), respectively, would result in a 200 mK deviation on the detected signal, and a typical measurement error of 0.48 degree, 0.78 degree, or 0.15 degree in the respective phases would cause a 40 mK deviation. The VNA measurement error can greatly affect the result of a 21 cm global spectrum experiment using this calibration technique, and such a feature could be mistaken for or be combined with the 21 cm signal

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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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Marginal Post Processing of Bayesian Inference Products with Normalizing Flows and Kernel Density Estimators

Bayesian analysis has become an indispensable tool across many different cosmological fields including the study of gravitational waves, the Cosmic Microwave Background and the 21-cm signal from the Cosmic Dawn among other phenomena. The method provides a way to fit complex models to data describing key cosmological and astrophysical signals and a whole host of contaminating signals and instrumental effects modelled with `nuisance parameters'. In this paper, we summarise a method that uses Masked Autoregressive Flows and Kernel Density Estimators to learn marginal posterior densities corresponding to core science parameters. We find that the marginal or 'nuisance-free' posteriors and the associated likelihoods have an abundance of applications including; the calculation of previously intractable marginal Kullback-Leibler divergences and marginal Bayesian Model Dimensionalities, likelihood emulation and prior emulation. We demonstrate each application using toy examples, examples from the field of 21-cm cosmology and samples from the Dark Energy Survey. We discuss how marginal summary statistics like the Kullback-Leibler divergences and Bayesian Model Dimensionalities can be used to examine the constraining power of different experiments and how we can perform efficient joint analysis by taking advantage of marginal prior and likelihood emulators. We package our multipurpose code up in the pip-installable code margarine for use in the wider scientific community.

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Joint analysis constraints on the physics of the first galaxies with low frequency radio astronomy data

The first billion years of cosmic history remains largely unobserved. We demonstrate, using a novel machine learning technique, how combining upper limits on the spatial fluctuations in the 21-cm signal with observations of the sky-averaged 21-cm signal from neutral hydrogen can improve our understanding of this epoch. By jointly analysing data from SARAS3 (redshift $z\approx15-25$) and limits from HERA ($z\approx8$ and $10$), we show that such a synergetic analysis provides tighter constraints on the astrophysics of galaxies 200 million years after the Big Bang than can be achieved with the individual data sets. Although our constraints are weak, this is the first time data from a sky-averaged 21-cm experiment and power spectrum experiment have been analysed together. In synergy, the two experiments leave only $64.9^{+0.3}_{-0.1}$% of the explored broad theoretical parameter space to be consistent with the joint data set, in comparison to $92.3^{+0.3}_{-0.1}$% for SARAS3 and $79.0^{+0.5}_{-0.2}$% for HERA alone. We use the joint analysis to constrain star formation efficiency, minimum halo mass for star formation, X-ray luminosity of early emitters and the radio luminosity of early galaxies. The joint analysis disfavours at 68% confidence a combination of galaxies with X-ray emission that is $\lesssim 33$ and radio emission that is $\gtrsim 32$ times as efficient as present day galaxies. We disfavour at $95$% confidence scenarios in which power spectra are $\geq126$ mK$^{2}$ at $z=25$ and the sky-averaged signals are $\leq-277$ mK.

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FlexKnot as a Generalised Model of the Sky-averaged 21-cm Signal at z ~ 6-30 in the Presence of Systematics

Global 21-cm experiments are built to study the evolution of the Universe between the cosmic dawn and the epoch of reionisation. FlexKnot is a function parameterised by freely moving knots stringed together by splines. Adopting the FlexKnot function as the signal model has the potential to separate the global 21-cm signal from the foregrounds and systematics while being capable of recovering the crucial features given by theoretical predictions. In this paper, we implement the FlexKnot method by integrating twice over a function of freely moving knots interpolated linearly. The function is also constrained at the lower frequencies corresponding to the dark ages by theoretical values. The FlexKnot model is tested in the framework of the realistic data analysis pipeline of the REACH global signal experiment using simulated antenna temperature data. We demonstrate that the FlexKnot model performs better than existing signal models, e.g. the Gaussian signal model, at reconstructing the shape of the true signals present in the simulated REACH data, especially for injected signals with complex structures. The capabilities of the FlexKnot signal model is also tested by introducing various systematics and simulated global signals of different types. These tests show that four to five knots are sufficient to recover the general shape of most realistic injected signals, with or without sinusoidal systematics. We show that true signals whose absorption trough of amplitude between 120 to 450 mK can be well recovered with systematics up to about 50 mK.

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A Bayesian Method to Mitigate the Effects of Unmodelled Time-Varying Systematics for 21-cm Cosmology Experiments

Radio observations of the neutral hydrogen signal from the Cosmic Dawn and Epoch of Reionisation have helped to provide constraints on the properties of the first stars and galaxies. Since this global 21-cm cosmological signal from the Cosmic Dawn is effectively constant on observing timescales and since effects resulting from systematics will vary with time, the effects of these systematics can be mitigated without the need for a model of the systematic. We present a method to account for unmodelled time-varying systematics in 21-cm radio cosmology experiments using a squared-exponential Gaussian process kernel to account for correlations between time bins in a fully Bayesian way. We find by varying the model parameters of a simulated systematic that the Gaussian process method improves our ability to recover the signal parameters by widening the posterior in the presence of a systematic and reducing the bias in the mean fit parameters. When varying the amplitude of a model sinusoidal systematic between 0.25 and 2.00 times the 21-cm signal amplitude and the period between 0.5 and 4.0 times the signal width, we find on average a 5% improvement in the root mean squared error of the fitted signal. We can use the fitted Gaussian process hyperparameters to identify the presence of a systematic in the data, demonstrating the method's utility as a diagnostic tool. Furthermore, we can use Gaussian process regression to calculate a mean fit to the residuals over time, providing a basis for producing a model of the time-varying systematic.

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The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology II: Mitigation of Foreground Systematics for HERA

One key challenge in detecting 21 cm cosmological signal at z > 6 is to separate the cosmological signal from foreground emission. This can be studied in a power spectrum space where the foreground is confined to low delay modes whereas the cosmological signal can spread out to high delay modes. When there is a calibration error, however, chromaticity of gain errors propagates to the power spectrum estimate and contaminates the modes for cosmological detection. The Hydrogen Epoch of Reionization Array (HERA) employs a high-precision calibration scheme using redundancy in measurements. In this study, we focus on the gain errors induced by nonredundancies arising from feed offset relative to the HERA's 14 meter parabolic dish element, and investigate how to mitigate the chromatic gain errors using three different methods: restricting baseline lengths for calibration, smoothing the antenna gains, and applying a temporal filter prior to calibration. With 2 cm/2 degree perturbations for translation/tilting motions, a level achievable under normal HERA operating conditions, the combination of the baseline cut and temporal filtering indicates that the spurious gain feature due to nonredundancies is significantly reduced, and the power spectrum recovers the clean foreground-free region. We found that the mitigation technique works even for large feed motions but in order to keep a stable calibration process, the feed positions need to be constrained to 2 cm for translation motions and 2 degree for tilting offset relative to the dish's vertex.

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Modelling a Hot Horizon in Global 21 cm Experimental Foregrounds

The 21 cm signal from cosmic hydrogen is one of the most propitious probes of the early Universe. The detection of this signal would reveal key information about the first stars, the nature of dark matter, and early structure formation. We explore the impact of an emissive and reflective, or `hot', horizon on the recovery of this signal for global 21 cm experiments. It is demonstrated that using physically motivated foreground models to recover the sky-averaged 21 cm signal one must accurately describe the horizon around the radiometer. We show that not accounting for the horizon will lead to a signal recovery with residuals an order of magnitude larger than the injected signal, with a log Bayesian evidence of almost 1600 lower than when one does account for the horizon. It is shown that signal recovery is sensitive to incorrect values of soil temperature and reflection coefficient in describing the horizon, with even a 10% error in reflectance causing twofold increases in the RMSE of a given fit. We also show these parameters may be fitted using Bayesian inference to mitigate for these issues without overfitting and mischaracterising a non-detection. We further demonstrate that signal recovery is sensitive to errors in measurements of the horizon projection onto the sky, but fitting for soil temperature and reflection coefficients with priors that extend beyond physical expectation can resolve these problems. We show that using an expanded prior range can reliably recover the signal even when the height of the horizon is mismeasured by up to 20%, decreasing the RMSE from the model that does not perform this fitting by a factor of 9.

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Sky-averaged 21-cm signal extraction using multiple antennas with an SVD framework: the REACH case

In a sky-averaged 21-cm signal experiment, the uncertainty on the extracted signal depends mainly on the covariance between the foreground and 21-cm signal models. In this paper, we construct these models using the modes of variation obtained from the Singular Value Decomposition of a set of simulated foreground and 21-cm signals. We present a strategy to reduce this overlap between the 21-cm and foreground modes by simultaneously fitting the spectra from multiple different antennas, which can be used in combination with the method of utilizing the time dependence of foregrounds while fitting multiple drift scan spectra. To demonstrate this idea, we consider two different foreground models (i) a simple foreground model, where we assume a constant spectral index over the sky, and (ii) a more realistic foreground model, with a spatial variation of the spectral index. For the simple foreground model, with just a single antenna design, we are able to extract the signal with good accuracy if we simultaneously fit the data from multiple time slices. The 21-cm signal extraction is further improved when we simultaneously fit the data from different antennas as well. This improvement becomes more pronounced while using the more realistic mock observations generated from the detailed foreground model. We find that even if we fit multiple time slices, the recovered signal is biased and inaccurate for a single antenna. However, simultaneously fitting the data from different antennas reduces the bias and the uncertainty by a factor of 2-3 on the extracted 21-cm signal.

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On the use of temporal filtering for mitigating galactic synchrotron calibration bias in 21 cm reionization observations

Precision antenna calibration is required for mitigating the impact of foreground contamination in 21 cm cosmological radio surveys. One widely studied source of error is the effect of missing point sources in the calibration sky model; however, poorly understood diffuse galactic emission also creates a calibration bias that can complicate the clean separation of foregrounds from the 21 cm signal. In this work, we present a technique for suppressing this bias with temporal filtering of radio interferometric visibilities observed in a drift-scan mode. We demonstrate this technique on mock simulations of the Hydrogen Epoch of Reionization Array (HERA) experiment. Inspecting the recovered calibration solutions, we find that our technique reduces spurious errors by over an order of magnitude. This improved accuracy approaches the required accuracy needed to make a fiducial detection of the 21 cm signal with HERA, but is dependent on a number of external factors that we discuss. We also explore different types of temporal filtering techniques and discuss their relative performance and tradeoffs.

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Characterization Of Inpaint Residuals In Interferometric Measurements of the Epoch Of Reionization

Radio Frequency Interference (RFI) is one of the systematic challenges preventing 21cm interferometric instruments from detecting the Epoch of Reionization. To mitigate the effects of RFI on data analysis pipelines, numerous inpaint techniques have been developed to restore RFI corrupted data. We examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that capable of inpainting RFI corrupted data in interferometric instruments. We train our network on simulated data and show that our network is capable at inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modeling are best suited for inpainting over narrowband RFI. We also show that with our fiducial parameters Discrete Prolate Spheroidal Sequences (DPSS) and CLEAN provide the best performance for intermittent ``narrowband'' RFI while Gaussian Progress Regression (GPR) and Least Squares Spectral Analysis (LSSA) provide the best performance for larger RFI gaps. However we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We find these results to be consistent in both simulated and real visibilities. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that in the future, as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities of HERA data.

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Search for the Epoch of Reionisation with HERA: Upper Limits on the Closure Phase Delay Power Spectrum

Radio interferometers aiming to measure the power spectrum of the redshifted 21 cm line during the Epoch of Reionisation (EoR) need to achieve an unprecedented dynamic range to separate the weak signal from overwhelming foreground emissions. Calibration inaccuracies can compromise the sensitivity of these measurements to the effect that a detection of the EoR is precluded. An alternative to standard analysis techniques makes use of the closure phase, which allows one to bypass antenna-based direction-independent calibration. Similarly to standard approaches, we use a delay spectrum technique to search for the EoR signal. Using 94 nights of data observed with Phase I of the Hydrogen Epoch of Reionization Array (HERA), we place approximate constraints on the 21 cm power spectrum at $z=7.7$. We find at 95% confidence that the 21 cm EoR brightness temperature is $\le$(372)$^2$ "pseudo" mK$^2$ at 1.14 "pseudo" $h$ Mpc$^{-1}$, where the "pseudo" emphasises that these limits are to be interpreted as approximations to the actual distance scales and brightness temperatures. Using a fiducial EoR model, we demonstrate the feasibility of detecting the EoR with the full array. Compared to standard methods, the closure phase processing is relatively simple, thereby providing an important independent check on results derived using visibility intensities, or related.

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