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Philip Bull

Publications and source records attributed to Philip Bull.

At least 19 recordsLinked to original sources

Statistical Field Theory for Weak Gravitational Lensing

Standard weak-lensing calculations treat lensing as a linear remapping of the matter field along the line of sight. We instead formulate lensing as a stochastic field theory for the Sachs optical scalars, driven by random Ricci-focusing and Weyl-shearing fields. The resulting path integral generates a diagrammatic expansion for arbitrary $n$-point correlation functions of lensing observables, organised into linear response, nonlinear propagation, and driving-field cumulants. The conventional calculation emerges as the lowest-order, linear-propagation limit. Beyond it, nonlinear Sachs evolution couples to driving-field non-Gaussianity, mixing the matter cumulant hierarchy into the lensing hierarchy. A selection rule governs the couplings: an $n$-point observable receives a direct contribution from the $n$-point driving-field cumulant, and its leading hierarchy-mixing correction from the $(n+1)$-point cumulant via one nonlinear Sachs interaction, with higher cumulants entering only at higher order. The two-point function, for instance, is corrected by three-point cumulants of Ricci focusing and Weyl shearing, letting small-scale modes feed the lensing signal across scales and populating the $E$- and $B$-modes in comparable measure. Rather than a restrictive approximation scheme, the formalism is a paradigm shift: a unified framework naturally accommodating path corrections, higher-order matter statistics, stochasticity, and small-scale effects.

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

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

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Foreground Characterization and Mitigation in the Observations of the CD/EoR with the SKA

The Square Kilometre Array (SKA), with its unprecedented sensitivity, frequency coverage, and large collecting area, is poised to revolutionize our understanding of the Cosmic Dawn (CD) and Epoch of Reionization (EoR) epochs marking the formation of the first luminous sources and the subsequent reionization of the intergalactic medium (IGM). However, detecting the faint redshifted 21-cm signal from neutral hydrogen remains one of the foremost challenges in observational cosmology, as it is buried beneath bright foregrounds from Galactic synchrotron radiation, free-free emission, and extragalactic point sources that are 4-5 orders of magnitude stronger than the cosmological signal. In this chapter, we highlight the key components and characteristics of these foregrounds and review ongoing efforts to model, characterize, and mitigate them. We emphasize how the SKA-Low AA* configuration, through its optimized array design, wide field of view, and improved calibration accuracy, enhances our capacity to suppress foreground contamination and recover the cosmological signal. The SKA Observatory Foreground Challenge plays a pivotal role in this effort by bringing together the global EoR/CD community to develop, compare, and validate foreground removal pipelines using realistic simulated datasets. Building on the experience of existing pathfinders such as LOFAR, MWA, and HERA, these collaborative initiatives are helping refine statistical and machine learning-based approaches for signal recovery. Together, these advancements are laying the groundwork for the SKA to probe the thermal and ionization history of the early Universe with unprecedented precision.

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Cosmology with HI Intensity Mapping

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

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Cosmology from HI galaxy surveys with the SKA

The 21cm line from neutral hydrogen is expected to be a ubiquitous (albeit faint) tracer of galaxies in the late Universe. With SKAO-MID, large wide-field surveys of several million HI-containing galaxies will become feasible, resulting in catalogues of sufficient size to measure large-scale structure observables such as baryon acoustic oscillations and redshift-space distortions. While optical galaxy surveys over comparable areas are generally deeper, radio surveys of this kind have a number of other advantages, such as broader sampling of the halo mass function and the possibility of measuring luminosity distances via the Tully-Fisher relation. In this chapter, we provide predictions for the galaxy number counts versus redshift that will be achievable with a wide-field HI galaxy survey on SKAO-MID, along with corresponding forecasts for cosmological observables. Given the substantial uncertainty in the HI mass function with redshift, we bracket our predictions using a handful of different modelling methods.

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Cosmology with Intensity Mapping via Statistics Beyond the Power Spectrum in the SKAO Era

The cosmological distribution of neutral hydrogen (HI) during the post-reionization era is highly non-Gaussian due to the underlying non-linear structure formation, complex galaxy biasing, and potential primordial non-Gaussianity. One needs higher-order (beyond two-point) statistics to maximally extract the non-Gaussian information out of the 21-cm intensity maps. This chapter summarizes the potential of several higher-order statistics, including voxel intensity distribution, emission line stacking, probability density functions, $\ell_1$-norm, bispectrum, and various marked statistics. Additionally, image-based morphological descriptors, such as the Largest Cluster Statistic, local dimensions, and Minkowski functionals, etc., can potentially characterize the morphology and geometry of the cosmic web encoded in the 21-cm intensity maps. This chapter presents forecasts of the detectability of these higher-order statistics in the context of the future SKAO observations. These forecasts incorporate instrumental noise, observational effects, and, in some cases, foreground removal in their analyses. With its unprecedented sensitivity, the future SKAO 21-cm observations will enable us to measure these higher-order statistics more precisely, possibly helping to break degeneracies between astrophysical and cosmological parameters, and maximizing the science outcome from these surveys.

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Predicted number counts and clustering of Hi galaxies from future radio surveys

The 21cm emission line from neutral hydrogen (HI) contained within galaxies provides a way to make accurate spectroscopic redshift determinations at radio frequencies. Large arrays such as SKA-MID will have the sensitivity required to catalogue millions of HI galaxies. The expected number counts and clustering properties of the galaxies are still quite poorly understood however, leading to uncertainties in the predicted performance of cosmological surveys. We use three different simulated galaxy catalogues to predict the properties of the HI galaxy distribution, along with estimates of the error on these predictions due to modelling uncertainty. The simulations are S$^3$-SAX (semi-analytic models based on the Millennium dark matter-only simulation); GAEA (an updated semi-analytic model partially calibrated on hydrodynamical simulations); and IllustrisTNG (a hydrodynamical simulation). We present predictions for galaxy number counts as a function of sensitivity and redshift, and use these to forecast the cosmological performance of a proposed SKA-MID cosmological survey. The simulated predictions differ by a factor of $\sim 2$ in the number counts and around 10% in the bias at $z \sim 0.1$, yielding around 20% differences in forecast cosmological uncertainties. These differences become significantly larger at $z \gtrsim 0.4$. We also model a 'medium-deep' SKA HI galaxy survey at $z \lesssim 0.07$ by fitting a halo occupation distribution (HOD) model to angular correlation functions measured from multiple $20^\circ \times 20^\circ$ sub-fields of IllustrisTNG. This provides clustering predictions and uncertainty estimates that can be used in future forecasts.

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

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

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

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

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Cosmology with Tully-Fisher HI Galaxy Surveys

The SKA Observatory will enable measurements of the Tully-Fisher relation for statistical samples of HI selected galaxies out to unprecedented depths and redshifts thanks to its unique combined spatial and spectral sensitivity. This chapter explores the transformative potential of such surveys for cosmology, in particular in the field of peculiar velocity measurements. We briefly review the present observational landscape for Tully-Fisher HI galaxy surveys and existing peculiar velocity datasets, and compare them with predictions for SKAO Tully-Fisher HI galaxy surveys with AA* and AA4 configurations of the SKA-Mid array. We discuss the extended range of cosmology science cases covered and enabled by such surveys.

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Observational Frontiers in the post-EoR 21-cm Intensity Mapping: Lessons from the SKA Pathfinders

The 21-cm line from neutral hydrogen has long been recognised as a promising tracer of the large-scale structure of the Universe. The line is weak however, making individual galaxy detections quite inefficient, especially at higher redshifts. The technique of 21-cm intensity mapping has been pioneered over the last two decades to address this limitation. Instead of detecting individual galaxies, the brightness temperature field from the combined 21-cm emission of many unresolved galaxies is mapped as a function of angle and frequency, resulting in 3D tracer maps of the large-scale structure. In this chapter, we review the major pioneering efforts to develop this observable into a competitive cosmological tool, paying particular attention to the status of pathfinder observations that have paved the way for a large and highly sensitive 21-cm intensity mapping survey with the SKA-Mid telescope.

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Prospects for measuring the Doppler magnification dipole with LSST and DESI

We forecast the detectability of the Doppler magnification dipole with a joint analysis of galaxy spectroscopic redshifts and size measurements. The Doppler magnification arises from an apparent size variation caused by galaxies' peculiar velocities when mapping them from redshift space to real space. This phenomenon is the dominant contribution to the convergence at low redshifts ($\lesssim$ 0.5). A practical observational strategy is to cross-correlate a galaxy number count tracer, e.g. from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey, with the convergence field reconstructed from galaxy size measurements obtained by the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). To assess the achievable precision of galaxy size measurements, we simulate LSST Y1-quality galaxy images with \textsc{Galsim} and measure them with the \textsc{Galight} profile fitting package. Our investigations, based on galaxy populations from LSST's synthetic galaxy catalogue \textsc{cosmoDC2}, show that the variance due to intrinsic galaxy size variation dominates over size measurement errors as expected, but may be lower than previous studies have suggested. Under our analysis assumptions, the Doppler magnification dipole would be detectable with a signal-to-noise ratio $\geq 10$ in multiple redshift bins between $0.1 \leq z \leq 0.5$ with DESI spectroscopic redshifts and LSST imaging.

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Bayesian power spectrum estimation with modelling of systematic effects in delay-fringe rate space

Observing the Epoch of Reionisation using 21cm radio interferometry has proven to be a challenging task. Extraction of the extremely faint redshifted signal is complicated by the presence of bright foregrounds, radio frequency interference (RFI), and systematic artefacts. We discuss the challenge of accounting for systematic effects, particularly cable reflections, that appear in the visibility data obtained from 21cm interferometers. Cable reflections cause attenuated copies of the foreground signal to appear outside the 'foreground wedge' region in which foreground contamination is supposed to be localised. We build on the hydra-pspec Gibbs sampler to implement a model of the systematics as a multiplicative effect in delay-fringe rate space. We include this model in the inference of the joint posterior distribution, in addition to the 21cm signal, its power spectrum, and foregrounds. This allows the systematics contribution to be marginalised, rather than filtering it out and causing additional signal loss. We demonstrate the method on simulated visibility data for a single baseline, showing that the 21cm delay power spectrum can be recovered well regardless of the location of the systematics in delay-fringe rate space. Our implementation is suitable for modelling other multiplicative factors on the visibilities, e.g. residual gain errors.

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Disentangling the anisotropic radio sky: Fisher forecasts for 21cm arrays

The existence of a radio synchrotron background (RSB) excess is implied by a number of measurements, including excess emission seen by the ARCADE~2 and LWA experiments. Highly sensitive wideband radio arrays, of the kind used to measure the cosmic 21cm signal, provide a promising way to further constrain the RSB excess through its anisotropy, providing additional insight into its origin. We present a framework for evaluating the potential of 21cm arrays to disentangle different components of the diffuse radio sky based on the combination of their frequency spectrum and angular power spectrum (APS). The formalism is designed to calculate uncertainties due to the intrinsic cosmic variance alone or together with instrumental noise. In particular, we predict the potential for measuring the anisotropy of a broad generalised class of excess radio background models using the low-frequency HERA array as an example. We find that a HERA-like array can distinguish an RSB excess from other sky components based on its angular clustering and spectral dependence, even if these are quite similar to one or more of the other components -- but only in the case that the RSB excess is relatively bright.

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Meta-learning for cosmological emulation: Rapid adaptation to new lensing kernels

Theoretical computation of cosmological observables is an intensive process, restricting the speed at which cosmological data can be analysed and cosmological models constrained, and therefore limiting research access to those with high performance computing infrastructure. Whilst the use of machine learning to emulate these computations has been studied, most existing emulators are specialised and not suitable for emulating a wide range of observables with changing physical models. Here, we investigate the Model-Agnostic Meta-Learning algorithm (MAML) for training a cosmological emulator. MAML attempts to train a set of network parameters for rapid fine-tuning to new tasks within some distribution of tasks. Specifically, we consider a simple case where the galaxy sample changes, resulting in a different redshift distribution and lensing kernel. Using MAML, we train a cosmic-shear angular power spectrum emulator for rapid adaptation to new redshift distributions with only $O(100)$ fine-tuning samples, whilst not requiring any parametrisation of the redshift distributions. We compare the performance of the MAML emulator to two standard emulators, one pre-trained on a single redshift distribution and the other with no pre-training, both in terms of accuracy on test data, and the constraints produced when using the emulators for cosmological inference. We observe that within an MCMC analysis, the MAML emulator is able to better reproduce the fully-theoretical posterior, achieving a Battacharrya distance from the fully-theoretical posterior in the $S_8$ -- $Ω_m$ plane of 0.008, compared to 0.038 from the single-task pre-trained emulator and 0.243 for the emulator with no pre-training.

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Joint Bayesian calibration and map-making for intensity mapping experiments

Line-intensity mapping (LIM) is an emerging cosmological technique that traces large-scale structure through the integrated spectral-line emission of unresolved sources. Reconstructing unbiased sky maps requires careful joint treatment of instrumental calibration and map-making, a task made challenging by time-varying receiver gains, thermal drifts, and correlated $1/f$ noise intrinsic to single-dish radio telescopes. We present a Bayesian framework for joint calibration and map-making using Gibbs sampling, giving access to the full joint posterior of calibration and sky map parameters. Our data model is grounded in the radiometer equation, capturing the coupling between noise level and system temperature without assuming a fixed noise amplitude. Gain and system temperature are estimated via an iterative generalised least squares (GLS) scheme, while absolute flux calibration is achieved either with external calibrators or via known signal injections such as noise diodes. We further introduce a $1/f$ noise model that avoids spurious periodic correlations arising from the common assumption of a diagonally structured noise covariance in the frequency domain. The workflow is implemented in an efficient software package using the Levinson algorithm and a polynomial emulator to reduce computational cost. Demonstrated on simulations representative of MeerKLASS single-dish observations, the framework generalises to other single-dish surveys and to cross-correlation and interferometric data.

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Angular correlation functions of bright Lyman-break galaxies at $\mathbf{3 \lesssim z \lesssim 5}$

We investigate the clustering of Lyman-break galaxies at redshifts of 3 $\lesssim z \lesssim$ 5 within the COSMOS field by measuring the angular two-point correlation function. Our robust sample of $\sim$60,000 bright ($m_{\rm UV}\lesssim 27$) Lyman-break galaxies was selected based on spectral energy distribution fitting across 14 photometric bands spanning optical and near-infrared wavelengths. We constrained both the 1- and 2-halo terms at separations up to 300 arcsec, finding an excess in the correlation function at scales corresponding to $<20$ kpc, consistent with enhancement due to clumps in the same galaxy or interactions on this scale. We then performed Bayesian model fits on the correlation functions to infer the Halo Occupation Distribution parameters, star formation duty cycle, and galaxy bias in three redshift bins. We examined several cases where different combinations of parameters were varied, showing that our data can constrain the slope of the satellite occupation function, which previous studies have fixed. For an $M_{\rm{UV}}$-limited sub-sample, we found galaxy bias values of $b_g=3.18^{+0.14}_{-0.14}$ at $z\simeq3$, $b_g=3.58^{+0.27}_{-0.29}$ at $z\simeq4$, $b_g=4.27^{+0.25}_{-0.26}$ at $z\simeq5$. The duty cycle values are $0.62^{+0.25}_{-0.26}$, $0.40^{+0.34}_{-0.22}$, and $0.39^{+0.31}_{-0.20}$, respectively. These results suggest that, as the redshift increases, there is a slight decrease in the host halo masses and a shorter timescale for star formation in bright galaxies, at a fixed rest-frame UV luminosity threshold.

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RHINO: A large horn antenna for detecting the 21cm global signal

The sky-averaged brightness temperature of the 21cm line from neutral hydrogen provides a sensitive probe of the thermal state of the intergalactic medium, particularly before and during Cosmic Dawn and the Epoch of Reionisation. This `global signal' is faint, on the order of tens to hundreds of millikelvin, and spectrally relatively smooth, making it exceedingly difficult to disentangle from foreground radio emission and instrumental artefacts. In this paper, we introduce RHINO, an experiment based around a large horn antenna operating from 60-85 MHz. Horn antennas are highly characterisable and provide excellent shielding from their immediate environment, which are potentially decisive advantages when it comes to the beam measurement and modelling problems that are particularly challenging for this kind of experiment. The system also includes a novel continuous wave calibration source to control correlated gain fluctuations, allowing continuous monitoring of the overall gain level without needing to rapidly switch between the sky and a calibration source. Here, we describe the basic RHINO concept, including the antenna design, EM simulations, and receiver electronics. We use a basic simulation and analysis pipeline to study the impact of the limited bandwidth on recovery of physical 21cm global signal model parameters, and discuss a basic calibration scheme that incorporates the continuous wave signal. Finally, we report on the current state of a scaled-down prototype system under construction at Jodrell Bank Observatory.

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