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Robert G. Mann

Publications and source records attributed to Robert G. Mann.

At least 19 recordsLinked to original sources

Linking enhanced star formation and quenching to faint tidal features in galaxies

Galaxy mergers and interactions have long been suggested as a significant driver of galaxy evolution. However, the exact extent to which mergers enhance star formation and AGN activity has been challenging to establish observationally. In previous work, we visually classified a sample of galaxies with various types of faint tidal features in DECaLS images. In this paper, we cross-correlate this sample with SDSS-derived data to investigate how the presence and specific nature of these features correlates with intense star formation and AGN activity. Averaged over all tidal classes, we find that our 688 tidal feature galaxies are 6.6$\pm$0.9 times more likely to be in a starburst phase and 19.6$\pm$5.0 times more likely to have rapidly quenched (post-starbursts) than a sample of 4073 controls matched in both stellar mass and redshift. Examining differences between tidal classes, galaxies with \textit{arm} features were $\sim$1.3-4.0 times more likely to be starbursting than the other categories, while those with \textit{shell} features were $\sim$2.3-5.3 times more likely to be in a quiescent state. In a similar analysis, we identify which galaxies show evidence of AGN activity (from a sample of $\sim$2100) and find no significant difference between those with or without tidal features. Overall, our results reinforce the notion that mergers play an important role in driving star formation and rapid quenching in galaxies, and provide some of the first empirical evidence that the strength of this effect has a dependence on the detailed nature of the interaction, as traced by the tidal feature morphology.

astro-ph.GA

Galaxy Zoo Evo: 1 million human-annotated images of galaxies

We introduce Galaxy Zoo Evo, a labeled dataset for building and evaluating foundation models on images of galaxies. GZ Evo includes 104M crowdsourced labels for 823k images from four telescopes. Each image is labeled with a series of fine-grained questions and answers (e.g. "featured galaxy, two spiral arms, tightly wound, merging with another galaxy"). These detailed labels are useful for pretraining or finetuning. We also include four smaller sets of labels (167k galaxies in total) for downstream tasks of specific interest to astronomers, including finding strong lenses and describing galaxies from the new space telescope Euclid. We hope GZ Evo will serve as a real-world benchmark for computer vision topics such as domain adaption (from terrestrial to astronomical, or between telescopes) or learning under uncertainty from crowdsourced labels. We also hope it will support a new generation of foundation models for astronomy; such models will be critical to future astronomers seeking to better understand our universe.

astro-ph.IM

Uncovering Tidal Treasures: Automated Classification of Faint Tidal Features in DECaLS Data

Tidal features are a key observable prediction of the hierarchical model of galaxy formation and contain a wealth of information about the properties and history of a galaxy. Modern wide-field surveys such as LSST and Euclid will revolutionise the study of tidal features. However, the volume of data will prohibit visual inspection to identify features, thereby motivating a need to develop automated detection methods. This paper presents a visual classification of $\sim2,000$ galaxies from the DECaLS survey into different tidal feature categories: arms, streams, shells, and diffuse. We trained a Convolutional Neural Network (CNN) to reproduce the assigned visual classifications using these labels. Evaluated on a testing set where galaxies with tidal features were outnumbered $\sim1:10$, our network performed very well and retrieved a median $98.7\pm0.3$, $99.1\pm0.5$, $97.0\pm0.8$, and $99.4^{+0.2}_{-0.6}$ per cent of the actual instances of arm, stream, shell, and diffuse features respectively for just 20 per cent contamination. A modified version that identified galaxies with any feature against those without achieved scores of $0.981^{+0.001}_{-0.003}$, $0.834^{+0.014}_{-0.026}$, $0.974^{+0.008}_{-0.004}$, and $0.900^{+0.073}_{-0.015}$ for the accuracy, precision, recall, and F1 metrics, respectively. We used a Gradient-weighted Class Activation Mapping analysis to highlight important regions on images for a given classification to verify the network was classifying the galaxies correctly. This is the first demonstration of using CNNs to classify tidal features into sub-categories, and it will pave the way for the identification of different categories of tidal features in the vast samples of galaxies that forthcoming wide-field surveys will deliver.

astro-ph.GA

Scaling Laws for Galaxy Images

We present the first systematic investigation of supervised scaling laws outside of an ImageNet-like context - on images of galaxies. We use 840k galaxy images and over 100M annotations by Galaxy Zoo volunteers, comparable in scale to Imagenet-1K. We find that adding annotated galaxy images provides a power law improvement in performance across all architectures and all tasks, while adding trainable parameters is effective only for some (typically more subjectively challenging) tasks. We then compare the downstream performance of finetuned models pretrained on either ImageNet-12k alone vs. additionally pretrained on our galaxy images. We achieve an average relative error rate reduction of 31% across 5 downstream tasks of scientific interest. Our finetuned models are more label-efficient and, unlike their ImageNet-12k-pretrained equivalents, often achieve linear transfer performance equal to that of end-to-end finetuning. We find relatively modest additional downstream benefits from scaling model size, implying that scaling alone is not sufficient to address our domain gap, and suggest that practitioners with qualitatively different images might benefit more from in-domain adaption followed by targeted downstream labelling.

cs.CV

The Growth of Intracluster Light in XCS-HSC Galaxy Clusters from $0.1 < z < 0.5$

We estimate the Intracluster Light (ICL) component within a sample of 18 clusters detected in XMM Cluster Survey (XCS) data using deep ($\sim$ 26.8 mag) Hyper Suprime Cam Subaru Strategic Program DR1 (HSC-SSP DR1) $i$-band data. We apply a rest-frame $μ_{B} = 25 \ \mathrm{mag/arcsec^{2}}$ isophotal threshold to our clusters, below which we define light as the ICL within an aperture of $R_{X,500}$ (X-ray estimate of $R_{500}$) centered on the Brightest Cluster Galaxy (BCG). After applying careful masking and corrections for flux losses from background subtraction, we recover $\sim$20% of the ICL flux, approximately four times our estimate of the typical background at the same isophotal level ($\sim$ 5%). We find that the ICL makes up about $\sim$ 24% of the total cluster stellar mass on average ($\sim$ 41% including the flux contained in the BCG within 50 kpc); this value is well-matched with other observational studies and semi-analytic/numerical simulations, but is significantly smaller than results from recent hydrodynamical simulations (even when measured in an observationally consistent way). We find no evidence for any links between the amount of ICL flux with cluster mass, but find a growth rate of $2-4$ for the ICL between $0.1 < z < 0.5$. We conclude that the ICL is the dominant evolutionary component of stellar mass in clusters from $z \sim 1$. Our work highlights the need for a consistent approach when measuring ICL alongside the need for deeper imaging, in order to unambiguously measure the ICL across as broad a redshift range as possible (e.g. 10-year stacked imaging from the Vera C. Rubin Observatory).

astro-ph.GA

Environmental dependence of X-ray and optical properties of galaxy clusters

Galaxy clusters are widely used to constrain cosmological parameters through their properties, such as masses, luminosity and temperature distributions. One should take into account all kind of biases that could affect these analyses in order to obtain reliable constraints. In this work, we study the difference in the properties of clusters residing in different large scale environments, defined by their position within or outside of voids, and the density of their surrounding space. We use both observational and simulation cluster and void catalogues, i.e. XCS and redMaPPer clusters, BOSS voids, and Magneticum simulations. We devise two different environmental proxies for the clusters and study their redshift, richness, mass, X-ray luminosity and temperature distributions as well as some properties of their galaxy populations. We use the Kolmogorov-Smirnov two-sample test to discover that richer and more massive clusters are more prevalent in overdense regions and outside of voids. We also find that clusters of matched richness and mass in overdense regions and outside voids tend to have higher X-ray luminosities and temperatures. These differences could have important implications for precision cosmology with clusters of galaxies, since cluster mass calibrations can vary with environment.

astro-ph.CO

KiDS+VIKING-450: A new combined optical & near-IR dataset for cosmology and astrophysics

We present the curation and verification of a new combined optical and near infrared dataset for cosmology and astrophysics, derived from the combination of $ugri$-band imaging from the Kilo Degree Survey (KiDS) and $ZY\!J\!H\!K_{\rm s}$-band imaging from the VISTA Kilo degree Infrared Galaxy (VIKING) survey. This dataset is unrivaled in cosmological imaging surveys due to its combination of area ($458$ deg$^2$ before masking), depth ($r\le25$), and wavelength coverage ($ugriZY\!J\!H\!K_{\rm s}$). The combination of survey depth, area, and (most importantly) wavelength coverage allows significant reductions in systematic uncertainties (i.e. reductions of between 10 and 60\% in bias, outlier rate, and scatter) in photometric-to-spectroscopic redshift comparisons, compared to the optical-only case at photo-$z$ above $0.7$. The complementarity between our optical and NIR surveys means that over $80\%$ of our sources, across all photo-$z$, have significant detections (i.e. not upper limits) in our $8$ reddest bands. We derive photometry, photo-$z$, and stellar masses for all sources in the survey, and verify these data products against existing spectroscopic galaxy samples. We demonstrate the fidelity of our higher-level data products by constructing the survey stellar mass functions in 8 volume-complete redshift bins. We find that these photometrically derived mass functions provide excellent agreement with previous mass evolution studies derived using spectroscopic surveys. The primary data products presented in this paper are publicly available at http://kids.strw.leidenuniv.nl/.

astro-ph.CO

Correlations between X-ray properties and Black Hole Mass in AGN: towards a new method to estimate black hole mass from short exposure X-ray observations

Several investigations of the X-ray variability of active galactic nuclei (AGN) using the normalised excess variance (${σ^2_{\rm NXS}}$) parameter have shown that variability has a strong anti-correlation with black hole mass ($M_{\rm BH}$) and X-ray luminosity ($L_{\rm X}$). In this study we confirm these previous correlations and find no evidence of a redshift evolution. Using observations from XMM-Newton, we determine the ${σ^2_{\rm NXS}}$ and $L_{\rm X}$ for a sample of 1091 AGN drawn from the XMM-Newton Cluster Survey (XCS) - making this the largest study of X-ray spectral properties of AGNs. We created light-curves in three time-scales; 10 ks, 20 ks and 40 ks and used these to derive scaling relations between ${σ^2_{\rm NXS}}$, $L_{\rm X}$ (2.0-10 keV range) and literature estimates of $M_{\rm BH}$ from reverberation mapping. We confirm the anti-correlation between $M_{\rm BH}$ and ${σ^2_{\rm NXS}}$ and find a positive correlation between $M_{\rm BH}$ and $L_{\rm X}$. The use of ${σ^2_{\rm NXS}}$ is practical only for pointed observations where the observation time is tens of kiloseconds. For much shorter observations one cannot accurately quantify variability to estimate $M_{\rm BH}$. Here we describe a method to derive $L_{\rm X}$ from short duration observations and used these results as an estimate for $M_{\rm BH}$. We find that it is possible to estimate $L_{\rm X}$ from observations of just a few hundred seconds and that when correlated with $M_{\rm BH}$, the relation is statistically similar to the relation of $M_{\rm BH}$-$L_{\rm X}$ derived from a spectroscopic analysis of full XMM observations. This method may be particularly useful to the eROSITA mission, an all-sky survey, which will detect $>$10$^{6}$ AGN.

astro-ph.GA

Identification of Low Surface Brightness Tidal Features in Galaxies Using Convolutional Neural Networks

Faint tidal features around galaxies record their merger and interaction histories over cosmic time. Due to their low surface brightnesses and complex morphologies, existing automated methods struggle to detect such features and most work to date has heavily relied on visual inspection. This presents a major obstacle to quantitative study of tidal debris features in large statistical samples, and hence the ability to be able to use these features to advance understanding of the galaxy population as a whole. This paper uses convolutional neural networks (CNNs) with dropout and augmentation to identify galaxies in the CFHTLS-Wide Survey that have faint tidal features. Evaluating the performance of the CNNs against previously-published expert visual classifications, we find that our method achieves high (76%) completeness and low (20%) contamination, and also performs considerably better than other automated methods recently applied in the literature. We argue that CNNs offer a promising approach to effective automatic identification of low surface brightness tidal debris features in and around galaxies. When applied to forthcoming deep wide-field imaging surveys (e.g. LSST, Euclid), CNNs have the potential to provide a several order-of-magnitude increase in the sample size of morphologically-perturbed galaxies and thereby facilitate a much-anticipated revolution in terms of quantitative low surface brightness science.

astro-ph.GA

The ${\it XMM}$ Cluster Survey: joint modelling of the $L_{\rm X}-T$ scaling relation for clusters and groups of galaxies

We characterize the X-ray luminosity--temperature ($L_{\rm X}-T$) relation using a sample of 353 clusters and groups of galaxies with temperatures in excess of 1 keV, spanning the redshift range $0.1 < z < 0.6$, the largest ever assembled for this purpose. All systems are part of the ${\it XMM-Newton}$ Cluster Survey (XCS), and have also been independently identified in Sloan Digital Sky Survey (SDSS) data using the redMaPPer algorithm. We allow for redshift evolution of the normalisation and intrinsic scatter of the $L_{\rm X}-T$ relation, as well as, for the first time, the possibility of a temperature-dependent change-point in the exponent of such relation. However, we do not find strong statistical support for deviations from the usual modelling of the $L_{\rm X}-T$ relation as a single power-law, where the normalisation evolves self-similarly and the scatter remains constant with time. Nevertheless, assuming {\it a priori} the existence of the type of deviations considered, then faster evolution than the self-similar expectation for the normalisation of the $L_{\rm X}-T$ relation is favoured, as well as a decrease with redshift in the scatter about the $L_{\rm X}-T$ relation. Further, the preferred location for a change-point is then close to 2 keV, possibly marking the transition between the group and cluster regimes. Our results also indicate an increase in the power-law exponent of the $L_{\rm X}-T$ relation when moving from the group to the cluster regime, and faster evolution in the former with respect to the later, driving the temperature-dependent change-point towards higher values with redshift.

astro-ph.CO

The XMM Cluster Survey: The Halo Occupation Number of BOSS galaxies in X-ray clusters

We present a direct measurement of the mean halo occupation distribution (HOD) of galaxies taken from the eleventh data release (DR11) of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS). The HOD of BOSS low-redshift (LOWZ: $0.2 < z < 0.4$) and Constant-Mass (CMASS: $0.43 <z <0.7$) galaxies is inferred via their association with the dark-matter halos of 174 X-ray-selected galaxy clusters drawn from the XMM Cluster Survey (XCS). Halo masses are determined for each galaxy cluster based on X-ray temperature measurements, and range between ${\rm log_{10}} (M_{180}/M_{\odot}) = 13-15$. Our directly measured HODs are consistent with the HOD-model fits inferred via the galaxy-clustering analyses of Parejko et al. for the BOSS LOWZ sample and White et al. for the BOSS CMASS sample. Under the simplifying assumption that the other parameters that describe the HOD hold the values measured by these authors, we have determined a best-fit alpha-index of 0.91$\pm$0.08 and $1.27^{+0.03}_{-0.04}$ for the CMASS and LOWZ HOD, respectively. These alpha-index values are consistent with those measured by White et al. and Parejko et al. In summary, our study provides independent support for the HOD models assumed during the development of the BOSS mock-galaxy catalogues that have subsequently been used to derive BOSS cosmological constraints.

astro-ph.CO

The XMM Cluster Survey: evolution of the velocity dispersion -- temperature relation over half a Hubble time

We measure the evolution of the velocity dispersion--temperature ($σ_{\rm v}$--$T_{\rm X}$) relation up to $z = 1$ using a sample of 38 galaxy clusters drawn from the \textit{XMM} Cluster Survey. This work improves upon previous studies by the use of a homogeneous cluster sample and in terms of the number of high redshift clusters included. We present here new redshift and velocity dispersion measurements for 12 $z > 0.5$ clusters observed with the GMOS instruments on the Gemini telescopes. Using an orthogonal regression method, we find that the slope of the relation is steeper than that expected if clusters were self-similar, and that the evolution of the normalisation is slightly negative, but not significantly different from zero ($σ_{\rm v} \propto T^{0.86 \pm 0.14} E(z)^{-0.37 \pm 0.33}$). We verify our results by applying our methods to cosmological hydrodynamical simulations. The lack of evolution seen in our data is consistent with simulations that include both feedback and radiative cooling.

astro-ph.CO

The XMM Cluster Survey: Testing chameleon gravity using the profiles of clusters

The chameleon gravity model postulates the existence of a scalar field that couples with matter to mediate a fifth force. If it exists, this fifth force would influence the hot X-ray emitting gas filling the potential wells of galaxy clusters. However, it would not influence the clusters' weak lensing signal. Therefore, by comparing X-ray and weak lensing profiles, one can place upper limits on the strength of a fifth force. This technique has been attempted before using a single, nearby cluster (Coma, $z=0.02$). Here we apply the technique to the stacked profiles of 58 clusters at higher redshifts ($0.1<z<1.2$), including 12 new to the literature, using X-ray data from the XMM Cluster Survey (XCS) and weak lensing data from the Canada France Hawaii Telescope Lensing Survey (CFHTLenS). Using a multi-parameter MCMC analysis, we constrain the two chameleon gravity parameters ($β$ and $ϕ_{\infty}$). Our fits are consistent with general relativity, not requiring a fifth force. In the special case of $f(R)$ gravity (where $β= \sqrt{1/6}$), we set an upper limit on the background field amplitude today of $|f_{\rm{R0}}| < 6 \times 10^{-5}$ (95% CL). This is one of the strongest constraints to date on $|f_{\rm{R0}}|$ on cosmological scales. We hope to improve this constraint in future by extending the study to hundreds of clusters using data from the Dark Energy Survey.

astro-ph.CO

The Past, Present and Future of Astronomical Data Formats

The future of astronomy is inextricably entwined with the care and feeding of astronomical data products. Community standards such as FITS and NDF have been instrumental in the success of numerous astronomy projects. Their very success challenges us to entertain pragmatic strategies to adapt and evolve the standards to meet the aggressive data-handling requirements of facilities now being designed and built. We discuss characteristics that have made standards successful in the past, as well as desirable features for the future, and an open discussion follows.

astro-ph.IM

Renewal Strings for Cleaning Astronomical Databases

Large astronomical databases obtained from sky surveys such as the SuperCOSMOS Sky Surveys (SSS) invariably suffer from a small number of spurious records coming from artefactual effects of the telescope, satellites and junk objects in orbit around earth and physical defects on the photographic plate or CCD. Though relatively small in number these spurious records present a significant problem in many situations where they can become a large proportion of the records potentially of interest to a given astronomer. In this paper we focus on the four most common causes of unwanted records in the SSS: satellite or aeroplane tracks, scratches fibres and other linear phenomena introduced to the plate, circular halos around bright stars due to internal reflections within the telescope and diffraction spikes near to bright stars. Accurate and robust techniques are needed for locating and flagging such spurious objects. We have developed renewal strings, a probabilistic technique combining the Hough transform, renewal processes and hidden Markov models which have proven highly effective in this context. The methods are applied to the SSS data to develop a dataset of spurious object detections, along with confidence measures, which can allow this unwanted data to be removed from consideration. These methods are general and can be adapted to any future astronomical survey data.

cs.AI

The VISTA Science Archive

We describe the VISTA Science Archive (VSA) and its first public release of data from five of the six VISTA Public Surveys. The VSA exists to support the VISTA Surveys through their lifecycle: the VISTA Public Survey consortia can use it during their quality control assessment of survey data products before submission to the ESO Science Archive Facility (ESO SAF); it supports their exploitation of survey data prior to its publication through the ESO SAF; and, subsequently, it provides the wider community with survey science exploitation tools that complement the data product repository functionality of the ESO SAF. This paper has been written in conjunction with the first public release of public survey data through the VSA and is designed to help its users understand the data products available and how the functionality of the VSA supports their varied science goals. We describe the design of the database and outline the database-driven curation processes that take data from nightly pipeline-processed and calibrated FITS files to create science-ready survey datasets. Much of this design, and the codebase implementing it, derives from our earlier WFCAM Science Archive (WSA), so this paper concentrates on the VISTA-specific aspects and on improvements made to the system in the light of experience gained in operating the WSA.

astro-ph.IM

The XMM Cluster Survey: Evidence for energy injection at high redshift from evolution of the X-ray luminosity-temperature relation

We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with spectroscopic redshifts drawn from the XMM Cluster Survey first data release (XCS-DR1). This is the first study spanning this redshift range using a single, large, homogeneous cluster sample. Using an orthogonal regression technique, we find no evidence for evolution in the slope or intrinsic scatter of the relation since z~1.5, finding both to be consistent with previous measurements at z~0.1. However, the normalisation is seen to evolve negatively with respect to the self-similar expectation: we find E(z)^{-1} L_X = 10^{44.67 +/- 0.09} (T/5)^{3.04 +/- 0.16} (1+z)^{-1.5 +/- 0.5}, which is within 2 sigma of the zero evolution case. We see milder, but still negative, evolution with respect to self-similar when using a bisector regression technique. We compare our results to numerical simulations, where we fit simulated cluster samples using the same methods used on the XCS data. Our data favour models in which the majority of the excess entropy required to explain the slope of the L_X-T relation is injected at high redshift. Simulations in which AGN feedback is implemented using prescriptions from current semi-analytic galaxy formation models predict positive evolution of the normalisation, and differ from our data at more than 5 sigma. This suggests that more efficient feedback at high redshift may be needed in these models.

astro-ph.CO

The XMM Cluster Survey: Optical analysis methodology and the first data release

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we present the first data release from the XMM Cluster Survey (XCS-DR1). This consists of 503 optically confirmed, serendipitously detected, X-ray clusters. Of these clusters, 255 are new to the literature and 356 are new X-ray discoveries. We present 464 clusters with a redshift estimate (0.06 < z < 1.46), including 261 clusters with spectroscopic redshifts. In addition, we have measured X-ray temperatures (Tx) for 402 clusters (0.4 < Tx < 14.7 keV). We highlight seven interesting subsamples of XCS-DR1 clusters: (i) 10 clusters at high redshift (z > 1.0, including a new spectroscopically-confirmed cluster at z = 1.01); (ii) 67 clusters with high Tx (> 5 keV); (iii) 131 clusters/groups with low Tx (< 2 keV); (iv) 27 clusters with measured Tx values in the SDSS `Stripe 82' co-add region; (v) 78 clusters with measured Tx values in the Dark Energy Survey region; (vi) 40 clusters detected with sufficient counts to permit mass measurements (under the assumption of hydrostatic equilibrium); (vii) 105 clusters that can be used for applications such as the derivation of cosmological parameters and the measurement of cluster scaling relations. The X-ray analysis methodology used to construct and analyse the XCS-DR1 cluster sample has been presented in a companion paper, Lloyd-Davies et al. (2010).

astro-ph.CO