arXiv subjects

Philip Bull

Publications and source records attributed to Philip Bull.

At least 55 records · Page 3Linked to original sources

arXiv2024

Modes of the Dark Ages 21cm field accessible to a lunar radio interferometer

At redshifts beyond $z \gtrsim 30$, the 21cm line from neutral hydrogen is expected to be essentially the only viable probe of the 3D matter distribution. The lunar far-side is an extremely appealing site for future radio arrays that target this signal, as it is protected from terrestrial radio frequency interference, and has no ionosphere to attenuate and absorb radio emission at low frequencies (tens of MHz and below). We forecast the sensitivity of low-frequency lunar radio arrays to the bispectrum of the 21cm brightness temperature field, which can in turn be used to probe primordial non-Gaussianity generated by particular early universe models. We account for the loss of particular regions of Fourier space due to instrumental limitations and systematic effects, and predict the sensitivity of different representative array designs to local-type non-Gaussianity in the bispectrum, parametrised by $f_{\rm NL}$. Under the most optimistic assumption of sample variance-limited observations, we find that $σ(f_{\rm NL}) \lesssim 0.01$ could be achieved for several broad redshift bins at $z \gtrsim 30$ if foregrounds can be removed effectively. These values degrade to between $σ(f_{\rm NL}) \sim 0.03$ and $0.7$ for $z=30$ to $z=170$ respectively when a large foreground wedge region is excluded.

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arXiv2024

Sensitivity of Bayesian 21 cm power spectrum estimation to foreground model errors

Power spectrum estimators are an important tool in efforts to detect the 21 cm brightness temperature fluctuations from neutral hydrogen at early times. An initial detection will likely be statistical in nature, meaning that it will not be possible to make a coherent map of the brightness temperature fluctuations; instead, only their variance will be measured against a background of noise and residual systematic effects. Optimal Quadratic Estimator (OQE)-based methods often apply an inverse covariance weighting to the data. However, inaccurate covariance modelling can lead to reduced sensitivity and, in some cases, severe signal loss. We recently proposed a Bayesian method to jointly estimate the 21 cm fluctuations, their power spectrum, and foreground emission. Instead of requiring a fixed a priori estimate of the covariance, we estimate the covariance as part of the inference. Choices of parametrization, particularly of the foregrounds, are subject to model errors and could lead to biases and other ill effects if not properly controlled. In this paper, we investigate the effects of inaccurate foreground models on 21 cm power spectrum recovery. Using simulated visibilities, we find that, even in the most extreme scenarios tested, our approach is capable of recovering 21 cm delay power spectrum estimates consistent with a known input signal for delays $\gtrsim300$ ns ($\sim$88\% of the available Fourier modes). This is true even when using foreground models derived from modified foreground catalogs containing spatial and spectral perturbations at the quoted level of uncertainty on our foreground catalogs.

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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

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

Statistical recovery of 21cm visibilities and their power spectra with Gaussian constrained realisations and Gibbs sampling

Radio interferometers designed to probe the 21cm signal from Cosmic Dawn and the Epoch of Reionisation must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21cm signal from foreground emission and other effects. For instance, the instrument's chromatic response modulates the otherwise spectrally smooth foregrounds, making them difficult to model, while a significant fraction of the data must be excised due to the presence of radio frequency interference (RFI), leaving gaps in the data. Errors in modelling the (modulated and gappy) foregrounds can easily generate spurious contamination of what should otherwise be 21cm signal-dominated modes. Various approaches have been developed to mitigate these issues by (e.g.) using non-parametric reconstruction of the foregrounds, in-painting the gaps, and weighting the data to reduce the level of contamination. We present a Bayesian statistical method that combines these approaches, using the coupled techniques of Gaussian constrained realisations (GCR) and Gibbs sampling. This provides a way of drawing samples from the joint posterior distribution of the 21cm signal modes and their power spectrum in the presence of gappy data and an uncertain foreground model in a computationally scalable manner. The data are weighted by an inverse covariance matrix that is estimated as part of the inference, along with a foreground model that can then be marginalised over. We demonstrate the application of this technique on a simulated HERA-like delay spectrum analysis, comparing three different approaches for accounting for the foreground components.

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arXiv2023

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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arXiv2023

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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arXiv2023

Improved Constraints on the 21 cm EoR Power Spectrum and the X-Ray Heating of the IGM with HERA Phase I Observations

We report the most sensitive upper limits to date on the 21 cm epoch of reionization power spectrum using 94 nights of observing with Phase I of the Hydrogen Epoch of Reionization Array (HERA). Using similar analysis techniques as in previously reported limits (HERA Collaboration 2022a), we find at 95% confidence that $Δ^2(k = 0.34$ $h$ Mpc$^{-1}$) $\leq 457$ mK$^2$ at $z = 7.9$ and that $Δ^2 (k = 0.36$ $h$ Mpc$^{-1}) \leq 3,496$ mK$^2$ at $z = 10.4$, an improvement by a factor of 2.1 and 2.6 respectively. These limits are mostly consistent with thermal noise over a wide range of $k$ after our data quality cuts, despite performing a relatively conservative analysis designed to minimize signal loss. Our results are validated with both statistical tests on the data and end-to-end pipeline simulations. We also report updated constraints on the astrophysics of reionization and the cosmic dawn. Using multiple independent modeling and inference techniques previously employed by HERA Collaboration (2022b), we find that the intergalactic medium must have been heated above the adiabatic cooling limit at least as early as $z = 10.4$, ruling out a broad set of so-called "cold reionization" scenarios. If this heating is due to high-mass X-ray binaries during the cosmic dawn, as is generally believed, our result's 99% credible interval excludes the local relationship between soft X-ray luminosity and star formation and thus requires heating driven by evolved low-metallicity stars.

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arXiv2023

Impact of instrument and data characteristics in the interferometric reconstruction of the 21 cm power spectrum

Combining the visibilities measured by an interferometer to form a cosmological power spectrum is a complicated process. In a delay-based analysis, the mapping between instrumental and cosmological space is not a one-to-one relation. Instead, neighbouring modes contribute to the power measured at one point, with their respective contributions encoded in the window functions. To better understand the power measured by an interferometer, we assess the impact of instrument characteristics and analysis choices on these window functions. Focusing on the Hydrogen Epoch of Reionization Array (HERA) as a case study, we find that long-baseline observations correspond to enhanced low-k tails of the window functions, which facilitate foreground leakage, whilst an informed choice of bandwidth and frequency taper can reduce said tails. With simple test cases and realistic simulations, we show that, apart from tracing mode mixing, the window functions help accurately reconstruct the power spectrum estimator of simulated visibilities. The window functions depend strongly on the beam chromaticity, and less on its spatial structure - a Gaussian approximation, ignoring side lobes, is sufficient. Finally, we investigate the potential of asymmetric window functions, down-weighting the contribution of low-k power to avoid foreground leakage. The window functions presented here correspond to the latest HERA upper limits for the full Phase I data. They allow an accurate reconstruction of the power spectrum measured by the instrument and will be used in future analyses to confront theoretical models and data directly in cylindrical space.

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arXiv2022

Bayesian jackknife tests with a small number of subsets: Application to HERA 21cm power spectrum upper limits

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open source code, CHIBORG, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from the Hydrogen Epoch of Reionization Array (HERA) to assess whether different sub-seasons of observing can justifiably be combined to produce a deeper 21cm power spectrum upper limit. We find that, with a handful of exceptions, the HERA data in question are statistically consistent and this decision is justified. We conclude by pointing out the wide applicability of this test, including to CMB experiments and the $H_0$ tension.

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arXiv2022

Direct Optimal Mapping for 21cm Cosmology: A Demonstration with the Hydrogen Epoch of Reionization Array

Motivated by the desire for wide-field images with well-defined statistical properties for 21cm cosmology, we implement an optimal mapping pipeline that computes a maximum likelihood estimator for the sky using the interferometric measurement equation. We demonstrate this direct optimal mapping with data from the Hydrogen Epoch of Reionization (HERA) Phase I observations. After validating the pipeline with simulated data, we develop a maximum likelihood figure-of-merit for comparing four sky models at 166MHz with a bandwidth of 100kHz. The HERA data agree with the GLEAM catalogs to <10%. After subtracting the GLEAM point sources, the HERA data discriminate between the different continuum sky models, providing most support for the model of Byrne et al. 2021. We report the computation cost for mapping the HERA Phase I data and project the computation for the HERA 320-antenna data; both are feasible with a modern server. The algorithm is broadly applicable to other interferometers and is valid for wide-field and non-coplanar arrays.

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arXiv2022

HI intensity mapping with MeerKAT: power spectrum detection in cross-correlation with WiggleZ galaxies

We present a detection of correlated clustering between MeerKAT radio intensity maps and galaxies from the WiggleZ Dark Energy Survey. We find a $7.7σ$ detection of the cross-correlation power spectrum, the amplitude of which is proportional to the product of the HI density fraction ($Ω_{\rm HI}$), HI bias ($b_{\rm HI}$) and the cross-correlation coefficient ($r$). We therefore obtain the constraint $Ω_{\rm HI} b_{\rm HI} r\,{=}\,[0.86\,{\pm}\,0.10\,({\rm stat})\,{\pm}\,0.12\,({\rm sys})]\,{\times}\,10^{-3}$, at an effective scale of $k_{\rm eff}\,{\sim}\,0.13\,h\,{\rm Mpc}^{-1}$. The intensity maps were obtained from a pilot survey with the MeerKAT telescope, a 64-dish pathfinder array to the SKA Observatory (SKAO). The data were collected from 10.5 hours of observations using MeerKAT's L-band receivers over six nights covering the 11hr field of WiggleZ, in the frequency range $1015-973\,{\rm MHz}$ (0.400$\,{<}\,z\,{<}\,$0.459 in redshift). This detection is the first practical demonstration of the multi-dish auto-correlation intensity mapping technique for cosmology. This marks an important milestone in the roadmap for the cosmology science case with the full SKAO.

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arXiv2022

Characterizing line-of-sight variability of polarized dust emission with future CMB experiments

Galactic dust emission is often accounted for in cosmic microwave background (CMB) analyses by fitting a simple two-parameter modified blackbody (MBB) model in each pixel, which nominally accounts for the temperature and opacity of the dust. While this may be a good approximation for individual dust clouds, typically a number of such clouds are found along each line of sight and within each angular pixel, resulting in a superposition of their spectra. In this paper, we study the effects of this superposition on pixel-based foreground fitting strategies by modelling the spectral energy distribution (SED) in each pixel as the integral of individual MBB spectra over various physically-motivated statistical distributions of dust cloud properties. We show that fitting these SEDs with the simple two-parameter MBB model generally results in unbiased estimates of the CMB Stokes Q and U amplitudes in each pixel, unless there are significant changes in both the dust SED and polarization angle along the line of sight, in which case significant ($ > 10σ$) biases are observed in an illustrative model. We also find that the best-fit values of the dust temperature, $T_d$, and spectral index, $β_d$, are significantly biased away from the mean/median of the corresponding statistical distributions when the distributions are broad, suggesting that MBB model fits can give an unrepresentative picture of the physical properties of the dust at microwave wavelengths if not interpreted carefully. Using a Fisher matrix analysis, we also determine the experimental sensitivity required to recover the parameters of the $T_d$ and $β_d$ distributions themselves by fitting a probabilistic MBB model, finding that only the parameters of broad distributions can be measured by SED fitting on a single line of sight.

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arXiv2022

Automated Detection of Antenna Malfunctions in Large-N Interferometers: A Case Study with the Hydrogen Epoch of Reionization Array

We present a framework for identifying and flagging malfunctioning antennas in large radio interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study. Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets.

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arXiv2022

Measurements of the diffuse Galactic synchrotron spectral index and curvature from MeerKLASS pilot data

21cm intensity mapping experiments are bringing an influx of high spectral resolution observational data in the $\sim100$ MHz $- 1$ GHz regime. We use pilot $971-1075$ MHz data from MeerKAT in single-dish mode, recently used to test the calibration and data reduction scheme of the upcoming MeerKLASS survey, to probe the spectral index of diffuse synchrotron emission below 1 GHz within $145^{\circ} < α< 180^{\circ}$, $-1^{\circ} < δ< 8^{\circ}$. Through comparisons with data from the OVRO Long Wavelength Array and the Maipu and MU surveys, we find an average spectral index of $-2.75 < β< -2.71$ between 45 and 1055 MHz. By fitting for spectral curvature with a spectral index of the form $β+ c \, {\rm{ln}}(ν/ 73~{\rm MHz})$, we measure $β= -2.55 \pm 0.13$ and $c = -0.12 \pm 0.05$ within our target field. Our results are in good agreement (within $1σ$) with existing measurements from experiments such as ARCADE2 and EDGES. These results show the calibration accuracy of current data and demonstrate that MeerKLASS will also be capable of achieving a secondary science goal of probing the interstellar medium.

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arXiv2021

Spin-based removal of instrumental systematics in 21cm intensity mapping surveys

Upcoming cosmological intensity mapping surveys will open new windows on the Universe, but they must first overcome a number of significant systematic effects, including polarization leakage. We present a formalism that uses scan strategy information to model the effect of different instrumental systematics on the recovered cosmological intensity signal for `single-dish' (autocorrelation) surveys. This modelling classifies different systematics according to their spin symmetry, making it particularly relevant for dealing with polarization leakage. We show how to use this formalism to calculate the expected contamination from different systematics as a function of the scanning strategy. Most importantly, we show how systematics can be disentangled from the intensity signal based on their spin properties via map-making. We illustrate this, using a set of toy models, for some simple instrumental systematics, demonstrating the ability to significantly reduce the contamination to the observed intensity signal. Crucially, unlike existing foreground removal techniques, this approach works for signals that are non-smooth in frequency, e.g. polarized foregrounds. These map-making approaches are simple to apply and represent an orthogonal and complementary approach to existing techniques for removing systematics from upcoming 21cm intensity mapping surveys.

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arXiv2021

Cleaning foregrounds from single-dish 21cm intensity maps with Kernel Principal Component Analysis

The high dynamic range between contaminating foreground emission and the fluctuating 21cm brightness temperature field is one of the most problematic characteristics of 21cm intensity mapping data. While these components would ordinarily have distinctive frequency spectra, making it relatively easy to separate them, instrumental effects and calibration errors further complicate matters by modulating and mixing them together. A popular class of foreground cleaning method are unsupervised techniques related to Principal Component Analysis (PCA), which exploit the different shapes and amplitudes of each component's contribution to the covariance of the data in order to segregate the signals. These methods have been shown to be effective at removing foregrounds, while also unavoidably filtering out some of the 21cm signal too. In this paper we examine, for the first time in the context of 21cm intensity mapping, a generalised method called Kernel PCA, which instead operates on the covariance of non-linear transformations of the data. This allows more flexible functional bases to be constructed, in principle allowing a cleaner separation between foregrounds and the 21cm signal to be found. We show that Kernel PCA is effective when applied to simulated single-dish (autocorrelation) 21cm data under a variety of assumptions about foregrounds models, instrumental effects etc. It presents a different set of behaviours to PCA, e.g. in terms of sensitivity to the data resolution and smoothing scale, outperforming it on intermediate to large scales in most scenarios.

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