arXiv subjects

David Parkinson

Publications and source records attributed to David Parkinson.

At least 55 records · Page 3Linked to original sources

arXiv2020

Developing a unified pipeline for large-scale structure data analysis with angular power spectra -- II. A case study for magnification bias and radio continuum surveys

Following on our purpose of developing a unified pipeline for large-scale structure data analysis with angular (i.e. harmonic-space) power spectra, we now include the weak lensing effect of magnification bias on galaxy clustering in a publicly available, modular parameter estimation code. We thus forecast constraints on the parameters of the concordance cosmological model, dark energy, and modified gravity theories from galaxy clustering tomographic angular power spectra. We find that a correct modelling of magnification is crucial in order not to bias the estimation of cosmological parameters, especially in the case of deep galaxy surveys. Our case study adopts specifications of the Evolutionary Map of the Universe (EMU), which is a full-sky, deep radio-continuum survey, and is expected to probe the Universe up to redshift $z\sim6$. We assume the Limber approximation, and include magnification bias on top of density fluctuations and redshift-space distortions. By restricting our analysis to the regime where the Limber approximation holds true, we significantly minimise the computational time needed, compared to that of the exact calculation. We also show that there is a trend for more biased parameter estimates from neglecting magnification when the redshift bins are very wide. We conclude that this result implies a strong dependence on the lensing contribution, which is an integrated effect and becomes dominant when wide redshift bins are considered. Finally, we note that instead of being considered a contaminant, magnification bias encodes important cosmological information, and its inclusion leads to an alleviation of the degeneracy between the galaxy bias and the amplitude normalisation of the matter fluctuations.

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arXiv2020

Testing gravity using galaxy-galaxy lensing and clustering amplitudes in KiDS-1000, BOSS and 2dFLenS

The physics of gravity on cosmological scales affects both the rate of assembly of large-scale structure, and the gravitational lensing of background light through this cosmic web. By comparing the amplitude of these different observational signatures, we can construct tests that can distinguish general relativity from its potential modifications. We used the latest weak gravitational lensing dataset from the Kilo-Degree Survey, KiDS-1000, in conjunction with overlapping galaxy spectroscopic redshift surveys BOSS and 2dFLenS, to perform the most precise existing amplitude-ratio test. We measured the associated E_G statistic with 15-20% errors, in five dz = 0.1 tomographic redshift bins in the range 0.2 < z < 0.7, on projected scales up to 100 Mpc/h. The scale-independence and redshift-dependence of these measurements are consistent with the theoretical expectation of general relativity in a Universe with matter density Omega_m = 0.27 +/- 0.04. We demonstrate that our results are robust against different analysis choices, including schemes for correcting the effects of source photometric redshift errors, and compare the performance of angular and projected galaxy-galaxy lensing statistics.

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arXiv2020

HIR4: cosmology from a simulated neutral hydrogen full sky using Horizon Run 4

The distribution of cosmological neutral hydrogen will provide a new window into the large-scale structure of the Universe with the next generation of radio telescopes and surveys. The observation of this material, through 21cm line emission, will be confused by foreground emission in the same frequencies. Even after these foregrounds are removed, the reconstructed map may not exactly match the original cosmological signal, which will introduce systematic errors and offset into the measured correlations. In this paper, we simulate future surveys of neutral hydrogen using the Horizon Run 4 (HR4) cosmological N-body simulation. We generate HI intensity maps from the HR4 halo catalogue, and combine with foreground radio emission maps from the Global Sky Model, to create accurate simulations over the entire sky. We simulate the HI sky for the frequency range 700-800 MHz, matching the sensitivity of the Tianlai pathfinder. We test the accuracy of the fastICA, PCA and log-polynomial fitting foreground removal methods to recover the input cosmological angular power spectrum and measure the parameters. We show the effect of survey noise levels and beam sizes on the recovered the cosmological constraints. We find that while the reconstruction removes power from the cosmological 21cm distribution on large-scales, we can correct for this and recover the input parameters in the noise-free case. However, the effect of noise and beam size of the Tianlai pathfinder prevents accurate recovery of the cosmological parameters when using only intensity mapping information.

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arXiv2020

Discovery of a Radio Relic in the Massive Merging Cluster SPT-CL 2023-5535 from the ASKAP-EMU PILOT SURVEY

The ASKAP-EMU survey is a deep wide-field radio continuum survey designed to cover the entire southern sky and a significant fraction of the northern sky up to $+30^{\circ}$. Here, we report a discovery of a radio relic in the merging cluster SPT-CL 2023-5535 at z=0.23 from the ASKAP-EMU pilot 300 sq. deg survey (800-1088 MHz). The deep high-resolution data reveal a $\sim2$ Mpc-scale radio halo elongated in the east-west direction, coincident with the intracluster gas. The radio relic is located at the western edge of this radio halo stretched $\sim0.5$ Mpc in the north-south orientation. The integrated spectral index of the radio relic within the narrow bandwidth is $α^{\scriptstyle \rm 1088~MHz}_{\scriptstyle \rm 800~MHz}=-0.76 \pm 0.06$. Our weak-lensing analysis shows that the system is massive ($M_{200}=1.04\pm0.36\times 10^{15} M_{\odot}$) and composed of at least three subclusters. We suggest a scenario, wherein the radio features arise from the collision between the eastern and middle subclusters. Our discovery illustrates the effectiveness of the ASKAP-EMU survey in detecting diffuse emissions in galaxy clusters and when completed, the survey will greatly increase the number of merging cluster detections with diffuse radio emissions.

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arXiv2020

Impact of bias and redshift-space modelling for the halo power spectrum: Testing the effective field theory of large-scale structure

We study the impact of different bias and redshift-space models on the halo power spectrum, quantifying their effect by comparing the fit to a subset of realizations taken from the WizCOLA suite. These provide simulated power spectrum measurements between $k_{\rm min}$ = 0.03 h/Mpc and $k_{\rm max}$ = 0.29 h/Mpc, constructed using the comoving Lagrangian acceleration method. For the bias prescription we include (i) simple linear bias; (ii) the McDonald & Roy model and (iii) its coevolution variant introduced by Saito et al.; and (iv) a very general model including all terms up to one-loop and corrections from advection. For the redshift-space modelling we include the Kaiser formula with exponential damping and the power spectrum provided by (i) tree-level perturbation theory and (ii) the Halofit prescription; (iii) one-loop perturbation theory, also with exponential damping; and (iv) an effective field theory description, also at one-loop, with damping represented by the EFT subtractions. We quantify the improvement from each layer of modelling by measuring the typical improvement in chi-square when fitting to a member of the simulation suite. We attempt to detect overfitting by testing for compatibility between the best-fit power spectrum per realization and the best-fit over the entire WizCOLA suite. For both bias and the redshift-space map we find that increasingly permissive models yield improvements in chi-square but with diminishing returns. The most permissive models show modest evidence for overfitting. Accounting for model complexity using the Bayesian Information Criterion, we argue that standard perturbation theory up to one-loop, or a related model such as that of Taruya, Nishimichi & Saito, coupled to the coevolution bias model, is likely to provide a good compromise for near-future galaxy surveys operating with comparable $k_{\rm max}$.

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arXiv2020

Testing the violation of the equivalence principle in the electromagnetic sector and its consequences in $f(T)$ gravity

A violation of the distance-duality relation is directly linked with a temporal variation of the electromagnetic fine-structure constant. We consider a number of well-studied $f(T)$ gravity models and we revise the theoretical prediction of their corresponding induced violation of the distance-duality relationship. We further extract constraints on the involved model parameters through fine-structure constant variation data, alongside with supernovae data, and Hubble parameter measurements. Moreover, we constrain the evolution of the effective $f(T)$ gravitational constant. Finally, we compare with revised constraints on the phenomenological parametrisations of the violation of the equivalence principle in the electromagnetic sector.

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arXiv2019

DASH: Deep Learning for the Automated Spectral Classification of Supernovae and their Hosts

We present DASH (Deep Automated Supernova and Host classifier), a novel software package that automates the classification of the type, age, redshift, and host galaxy of supernova spectra. DASH makes use of a new approach that does not rely on iterative template matching techniques like all previous software, but instead classifies based on the learned features of each supernova's type and age. It has achieved this by employing a deep convolutional neural network to train a matching algorithm. This approach has enabled DASH to be orders of magnitude faster than previous tools, being able to accurately classify hundreds or thousands of objects within seconds. We have tested its performance on four years of data from the Australian Dark Energy Survey (OzDES). The deep learning models were developed using TensorFlow, and were trained using over 4000 supernova spectra taken from the CfA Supernova Program and the Berkeley SN Ia Program as used in SNID (Supernova Identification software, Blondin & Tonry 2007). Unlike template matching methods, the trained models are independent of the number of spectra in the training data, which allows for DASH's unprecedented speed. We have developed both a graphical interface for easy visual classification and analysis of supernovae, and a Python library for the autonomous and quick classification of several supernova spectra. The speed, accuracy, user-friendliness, and versatility of DASH presents an advancement to existing spectral classification tools. We have made the code publicly available on GitHub and PyPI (pip install astrodash) to allow for further contributions and development. The package documentation is available at https://astrodash.readthedocs.io.

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arXiv2019

Identifying complex sources in large astronomical data using a coarse-grained complexity measure

The volume of data that will be produced by the next generation of astrophysical instruments represents a significant opportunity for making unplanned and unexpected discoveries. Conversely, finding unexpected objects or phenomena within such large volumes of data presents a challenge that may best be solved using computational and statistical approaches. We present the application of a coarse-grained complexity measure for identifying interesting observations in large astronomical data sets. This measure, which has been termed apparent complexity, has been shown to model human intuition and perceptions of complexity. Apparent complexity is computationally efficient to derive and can be used to segment and identify interesting observations in very large data sets based on their morphological complexity. We show, using data from the Australia Telescope Large Area Survey, that apparent complexity can be combined with clustering methods to provide an automated process for distinguishing between images of galaxies which have been classified as having simple and complex morphologies. The approach generalizes well when applied to new data after being calibrated on a smaller data set, where it performs better than tested classification methods using pixel data. This generalizability positions apparent complexity as a suitable machine-learning feature for identifying complex observations with unanticipated features.

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arXiv2019

Research and Development for HI Intensity Mapping

Development of the hardware, data analysis, and simulation techniques for large compact radio arrays dedicated to mapping the 21 cm line of neutral hydrogen gas has proven to be more difficult than imagined twenty years ago when such telescopes were first proposed. Despite tremendous technical and methodological advances, there are several outstanding questions on how to optimally calibrate and analyze such data. On the positive side, it has become clear that the outstanding issues are purely technical in nature and can be solved with sufficient development activity. Such activity will enable science across redshifts, from early galaxy evolution in the pre-reionization era to dark energy evolution at low redshift.

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arXiv2019

Probing $Λ$CDM cosmology with the Evolutionary Map of the Universe survey

The Evolutionary Map of the Universe (EMU) is an all-sky survey in radio-continuum which uses the Australian SKA Pathfinder (ASKAP). Using galaxy angular power spectrum and the integrated Sachs-Wolfe effect, we study the potential of EMU to constrain models beyond $Λ$CDM (i.e., local primordial non-Gaussianity, dynamical dark energy, spatial curvature and deviations from general relativity), for different design sensitivities. We also include a multi-tracer analysis, distinguishing between star-forming galaxies and galaxies with an active galactic nucleus, to further improve EMU's potential. We find that EMU could measure the dark energy equation of state parameters around 35\% more precisely than existing constraints, and that the constraints on $f_{\rm NL}$ and modified gravity parameters will improve up to a factor $\sim2$ with respect to Planck and redshift space distortions measurements. With this work we demonstrate the promising potential of EMU to contribute to our understanding of the Universe.

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arXiv2018

Cosmology with Phase 1 of the Square Kilometre Array; Red Book 2018: Technical specifications and performance forecasts

We present a detailed overview of the cosmological surveys that will be carried out with Phase 1 of the Square Kilometre Array (SKA1), and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5,000 sqdeg; a wide and deep continuum galaxy and HI intensity mapping survey over 20,000 sqdeg from z = 0.35 - 3; and a deep, high-redshift HI intensity mapping survey over 100 sqdeg from z = 3 - 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to z ~ 3 with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to z = 6. These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical surveys like LSST and Euclid, leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys, and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.

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arXiv2017

KiDS-450 + 2dFLenS: Cosmological parameter constraints from weak gravitational lensing tomography and overlapping redshift-space galaxy clustering

We perform a combined analysis of cosmic shear tomography, galaxy-galaxy lensing tomography, and redshift-space multipole power spectra (monopole and quadrupole) using 450 deg$^2$ of imaging data by the Kilo Degree Survey (KiDS) overlapping with two spectroscopic surveys: the 2-degree Field Lensing Survey (2dFLenS) and the Baryon Oscillation Spectroscopic Survey (BOSS). We restrict the galaxy-galaxy lensing and multipole power spectrum measurements to the overlapping regions with KiDS, and self-consistently compute the full covariance between the different observables using a large suite of $N$-body simulations. We methodically analyze different combinations of the observables, finding that galaxy-galaxy lensing measurements are particularly useful in improving the constraint on the intrinsic alignment amplitude (by 30%, positive at $3.5σ$ in the fiducial data analysis), while the multipole power spectra are useful in tightening the constraints along the lensing degeneracy direction (e.g. factor of two stronger matter density constraint in the fiducial analysis). The fully combined constraint on $S_8 \equiv σ_8 \sqrt{Ω_{\rm m}/0.3} = 0.742 \pm 0.035$, which is an improvement by 20% compared to KiDS alone, corresponds to a $2.6σ$ discordance with Planck, and is not significantly affected by fitting to a more conservative set of scales. Given the tightening of the parameter space, we are unable to resolve the discordance with an extended cosmology that is simultaneously favored in a model selection sense, including the sum of neutrino masses, curvature, evolving dark energy, and modified gravity. The complementarity of our observables allows for constraints on modified gravity degrees of freedom that are not simultaneously bounded with either probe alone, and up to a factor of three improvement in the $S_8$ constraint in the extended cosmology compared to KiDS alone.

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arXiv2017

Beyond the growth rate of cosmic structure: Testing modified gravity models with an extra degree of freedom

In 'modified' gravity the observed acceleration of the universe is explained by changing the gravitational force law or the number of degrees of freedom in the gravitational sector. Both possibilities can be tested by measurements of cosmological structure formation. In this paper we elaborate the details of such tests using the Galileon model as a case study. We pay attention to the possibility that each new degree of freedom may have stochastically independent initial conditions, generating different types of potential well in the early universe and breaking complete correlation between density and velocity power spectra. This 'stochastic bias' can confuse schemes to parametrize the predictions of modified gravity models, such as the use of the growth parameter f alone. Using data from the WiggleZ Dark Energy Survey we show that it will be possible to obtain constraints using information about the cosmological-scale force law embedded in the multipole power spectra of redshift-space distortions. As an example, we obtain an upper limit on the strength of the conformal coupling to matter in the cubic Galileon model, giving |1/M| < 200 / Mp. This allows the fifth-force to be stronger than gravity, but is consistent with zero coupling.

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arXiv2016

The 2-degree Field Lensing Survey: photometric redshifts from a large new training sample to r<19.5

We present a new training set for estimating empirical photometric redshifts of galaxies, which was created as part of the 2dFLenS project. This training set is located in a 700 sq deg area of the KiDS South field and is randomly selected and nearly complete at r<19.5. We investigate the photometric redshift performance obtained with ugriz photometry from VST-ATLAS and W1/W2 from WISE, based on several empirical and template methods. The best redshift errors are obtained with kernel-density estimation, as are the lowest biases, which are consistent with zero within statistical noise. The 68th percentiles of the redshift scatter for magnitude-limited samples at r<(15.5, 17.5, 19.5) are (0.014, 0.017, 0.028). In this magnitude range, there are no known ambiguities in the colour-redshift map, consistent with a small rate of redshift outliers. In the fainter regime, the KDE method produces p(z) estimates per galaxy that represent unbiased and accurate redshift frequency expectations. The p(z) sum over any subsample is consistent with the true redshift frequency plus Poisson noise. Further improvements in redshift precision at r<20 would mostly be expected from filter sets with narrower passbands to increase the sensitivity of colours to small changes in redshift.

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arXiv2016

Measuring the 2D Baryon Acoustic Oscillation signal of galaxies in WiggleZ: Cosmological constraints

We present results from the 2D anisotropic Baryon Acoustic Oscillation (BAO) signal present in the final dataset from the WiggleZ Dark Energy Survey. We analyse the WiggleZ data in two ways: firstly using the full shape of the 2D correlation function and secondly focussing only on the position of the BAO peak in the reconstructed data set. When fitting for the full shape of the 2D correlation function we use a multipole expansion to compare with theory. When we use the reconstructed data we marginalise over the shape and just measure the position of the BAO peak, analysing the data in wedges separating the signal along the line of sight from that parallel to the line of sight. We verify our method with mock data and find the results to be free of bias or systematic offsets. We also redo the pre-reconstruction angle averaged (1D) WiggleZ BAO analysis with an improved covariance and present an updated result. The final results are presented in the form of $Ω_c h^2$, $H(z)$, and $D_A(z)$ for three redshift bins with effective redshifts $z = 0.44$, $0.60$, and $0.73$. Within these bins and methodologies, we recover constraints between 5% and 22% error. Our cosmological constraints are consistent with Flat $Λ$CDM cosmology and agree with results from the Baryon Oscillation Spectroscopic Survey (BOSS).

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arXiv2016

2dFLenS and KiDS: Determining source redshift distributions with cross-correlations

We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum variance weighted quadratic function of the data: a quadratic estimator. This extends and modifies the methodology presented by McQuinn & White (2013). The derived source redshift distribution is degenerate with the source galaxy bias, which must be constrained via additional assumptions. We apply this estimator to constrain source galaxy redshift distributions in the Kilo-Degree imaging survey through cross-correlation with the spectroscopic 2-degree Field Lensing Survey, presenting results first as a binned step-wise distribution in the range z < 0.8, and then building a continuous distribution using a Gaussian process model. We demonstrate the robustness of our methodology using mock catalogues constructed from N-body simulations, and comparisons with other techniques for inferring the redshift distribution.

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arXiv2016

CFHTLenS revisited: assessing concordance with Planck including astrophysical systematics

We investigate the impact of astrophysical systematics on cosmic shear cosmological parameter constraints from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), and the concordance with cosmic microwave background measurements by Planck. We present updated CFHTLenS cosmic shear tomography measurements extended to degree scales using a covariance calibrated by a new suite of N-body simulations. We analyze these measurements with a new model fitting pipeline, accounting for key systematic uncertainties arising from intrinsic galaxy alignments, baryonic effects in the nonlinear matter power spectrum, and photometric redshift uncertainties. We examine the impact of the systematic degrees of freedom on the cosmological parameter constraints, both independently and jointly. When the systematic uncertainties are considered independently, the intrinsic alignment amplitude is the only degree of freedom that is substantially preferred by the data. When the systematic uncertainties are considered jointly, there is no consistently strong preference in favor of the more complex models. We quantify the level of concordance between the CFHTLenS and Planck datasets by employing two distinct data concordance tests, grounded in Bayesian evidence and information theory. We find that the two data concordance tests largely agree with one another, and that the level of concordance between the CFHTLenS and Planck datasets is sensitive to the exact details of the systematic uncertainties included in our analysis, ranging from decisive discordance to substantial concordance as the treatment of the systematic uncertainties becomes more conservative. The least conservative scenario is the one most favored by the cosmic shear data, but it is also the one that shows the greatest degree of discordance with Planck. The data and analysis code are public at https://github.com/sjoudaki/cfhtlens_revisited

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arXiv2016

Characterising Dark Energy through supernovae

Type Ia supernovae are a powerful cosmological probe, that gave the first strong evidence that the expansion of the universe is accelerating. Here we provide an overview of how supernovae can go further to reveal information about what is causing the acceleration, be it dark energy or some modification to our laws of gravity. We first summarise the many different approaches used to explain or test the acceleration, including parametric models (like the standard model, LambdaCDM), non-parametric models, dark fluid models such as quintessence, and extensions to standard gravity. We also show how supernova data can be used beyond the Hubble diagram, to give information on gravitational lensing and peculiar velocities that can be used to distinguish between models that predict the same expansion history. Finally, we review the methods of statistical inference that are commonly used, making a point of separating parameter estimation from model selection.

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